Overview

Dataset statistics

Number of variables54
Number of observations497
Missing cells3673
Missing cells (%)13.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory209.8 KiB
Average record size in memory432.3 B

Variable types

DateTime1
Categorical38
Numeric3
Text11
Unsupported1

Alerts

limpio_contexto is highly imbalanced (50.8%)Imbalance
limpio_municipio is highly imbalanced (51.0%)Imbalance
limpio_tipo_casa is highly imbalanced (58.8%)Imbalance
limpio_instancia is highly imbalanced (65.1%)Imbalance
limpio_agua_beber is highly imbalanced (61.8%)Imbalance
limpio_freq_pago is highly imbalanced (53.5%)Imbalance
limpio_entidad_pago is highly imbalanced (55.8%)Imbalance
limpio_percepcion_seguridad_rio_cercano is highly imbalanced (54.0%)Imbalance
limpio_tipo_baño is highly imbalanced (73.7%)Imbalance
limpio_conoce_responsable_saneamiento is highly imbalanced (54.3%)Imbalance
limpio_responsable_saneamiento is highly imbalanced (84.9%)Imbalance
limpio_destino_agua_servida is highly imbalanced (67.0%)Imbalance
limpio_sabe_uso_dinero_tarifa_saneamiento is highly imbalanced (63.0%)Imbalance
limpio_dias_sin_serv has 48 (9.7%) missing valuesMissing
limpio_razon_NA_checar has 52 (10.5%) missing valuesMissing
limpio_obtencion_agua has 72 (14.5%) missing valuesMissing
limpio_almacenamiento has 29 (5.8%) missing valuesMissing
limpio_acarreo has 182 (36.6%) missing valuesMissing
limpio_nombre_fuente has 126 (25.4%) missing valuesMissing
limpio_instancia has 180 (36.2%) missing valuesMissing
limpio_usos has 21 (4.2%) missing valuesMissing
limpio_negativa_visita has 202 (40.6%) missing valuesMissing
limpio_afimartiva_visita has 323 (65.0%) missing valuesMissing
limpio_nombre_rio_cercano has 125 (25.2%) missing valuesMissing
limpio_seguridad_baño has 461 (92.8%) missing valuesMissing
limpio_responsable_saneamiento has 213 (42.9%) missing valuesMissing
limpio_vertido_aguas_grises has 442 (88.9%) missing valuesMissing
limpio_destino_drenaje has 114 (22.9%) missing valuesMissing
limpio_percep_calidad_servicio has 68 (13.7%) missing valuesMissing
limpio_percep_costo_saneamiento has 89 (17.9%) missing valuesMissing
limpio_sabe_uso_dinero_tarifa_saneamiento has 89 (17.9%) missing valuesMissing
limpio_iniciativas_conocidas has 162 (32.6%) missing valuesMissing
limpio_conocimiento_iniciativa has 123 (24.7%) missing valuesMissing
limpio_conocimiento_iniciativas_saneamiento has 219 (44.1%) missing valuesMissing
limpio_observaciones has 284 (57.1%) missing valuesMissing
limpio_gasto_agua is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-01-31 19:58:05.471288
Analysis finished2024-01-31 19:58:12.209578
Duration6.74 seconds
Software versionydata-profiling vv4.6.4
Download configurationconfig.json

Variables

Distinct496
Distinct (%)100.0%
Missing1
Missing (%)0.2%
Memory size4.0 KiB
Minimum2022-10-25 09:59:13.806000
Maximum2023-05-21 12:53:42.392000
2024-01-31T13:58:12.428228image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-31T13:58:12.827557image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

limpio_genero
Categorical

Distinct2
Distinct (%)0.4%
Missing4
Missing (%)0.8%
Memory size4.0 KiB
Femenino
300 
Masculino
193 

Length

Max length9
Median length8
Mean length8.39148073
Min length8

Characters and Unicode

Total characters4137
Distinct characters12
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowFemenino
2nd rowMasculino
3rd rowFemenino
4th rowFemenino
5th rowFemenino

Common Values

ValueCountFrequency (%)
Femenino 300
60.4%
Masculino 193
38.8%
(Missing) 4
 
0.8%

Length

2024-01-31T13:58:13.211771image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-31T13:58:13.545509image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
femenino 300
60.9%
masculino 193
39.1%

Most occurring characters

ValueCountFrequency (%)
n 793
19.2%
e 600
14.5%
i 493
11.9%
o 493
11.9%
F 300
 
7.3%
m 300
 
7.3%
M 193
 
4.7%
a 193
 
4.7%
s 193
 
4.7%
c 193
 
4.7%
Other values (2) 386
9.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 3644
88.1%
Uppercase Letter 493
 
11.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n 793
21.8%
e 600
16.5%
i 493
13.5%
o 493
13.5%
m 300
 
8.2%
a 193
 
5.3%
s 193
 
5.3%
c 193
 
5.3%
u 193
 
5.3%
l 193
 
5.3%
Uppercase Letter
ValueCountFrequency (%)
F 300
60.9%
M 193
39.1%

Most occurring scripts

ValueCountFrequency (%)
Latin 4137
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
n 793
19.2%
e 600
14.5%
i 493
11.9%
o 493
11.9%
F 300
 
7.3%
m 300
 
7.3%
M 193
 
4.7%
a 193
 
4.7%
s 193
 
4.7%
c 193
 
4.7%
Other values (2) 386
9.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4137
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n 793
19.2%
e 600
14.5%
i 493
11.9%
o 493
11.9%
F 300
 
7.3%
m 300
 
7.3%
M 193
 
4.7%
a 193
 
4.7%
s 193
 
4.7%
c 193
 
4.7%
Other values (2) 386
9.3%

limpio_edad
Real number (ℝ)

Distinct69
Distinct (%)13.9%
Missing2
Missing (%)0.4%
Infinite0
Infinite (%)0.0%
Mean39.42424242
Minimum10
Maximum85
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.0 KiB
2024-01-31T13:58:13.915881image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Quantile statistics

Minimum10
5-th percentile16.7
Q129
median38
Q349
95-th percentile66
Maximum85
Range75
Interquartile range (IQR)20

Descriptive statistics

Standard deviation14.9244324
Coefficient of variation (CV)0.3785597764
Kurtosis-0.31342846
Mean39.42424242
Median Absolute Deviation (MAD)10
Skewness0.3999858521
Sum19515
Variance222.7386824
MonotonicityNot monotonic
2024-01-31T13:58:14.324738image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
32 20
 
4.0%
39 18
 
3.6%
43 18
 
3.6%
34 16
 
3.2%
33 16
 
3.2%
36 16
 
3.2%
17 15
 
3.0%
40 15
 
3.0%
42 14
 
2.8%
16 13
 
2.6%
Other values (59) 334
67.2%
ValueCountFrequency (%)
10 1
 
0.2%
11 1
 
0.2%
12 1
 
0.2%
13 1
 
0.2%
15 8
1.6%
ValueCountFrequency (%)
85 1
0.2%
81 1
0.2%
80 1
0.2%
79 1
0.2%
78 1
0.2%
Distinct6
Distinct (%)1.2%
Missing1
Missing (%)0.2%
Memory size4.0 KiB
Universidad
211 
Posgrado
192 
Preparatoria
79 
Secundaria
 
9
Primaria
 
4

Length

Max length12
Median length11
Mean length9.95766129
Min length8

Characters and Unicode

Total characters4939
Distinct characters19
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)0.2%

Sample

1st rowUniversidad
2nd rowUniversidad
3rd rowUniversidad
4th rowPosgrado
5th rowPosgrado

Common Values

ValueCountFrequency (%)
Universidad 211
42.5%
Posgrado 192
38.6%
Preparatoria 79
 
15.9%
Secundaria 9
 
1.8%
Primaria 4
 
0.8%
Sin estudios 1
 
0.2%
(Missing) 1
 
0.2%

Length

2024-01-31T13:58:14.741736image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-31T13:58:15.075262image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
universidad 211
42.5%
posgrado 192
38.6%
preparatoria 79
 
15.9%
secundaria 9
 
1.8%
primaria 4
 
0.8%
sin 1
 
0.2%
estudios 1
 
0.2%

Most occurring characters

ValueCountFrequency (%)
a 666
13.5%
r 657
13.3%
d 624
12.6%
i 520
10.5%
o 464
9.4%
s 405
8.2%
e 300
6.1%
P 275
5.6%
n 221
 
4.5%
U 211
 
4.3%
Other values (9) 596
12.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 4442
89.9%
Uppercase Letter 496
 
10.0%
Space Separator 1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 666
15.0%
r 657
14.8%
d 624
14.0%
i 520
11.7%
o 464
10.4%
s 405
9.1%
e 300
6.8%
n 221
 
5.0%
v 211
 
4.8%
g 192
 
4.3%
Other values (5) 182
 
4.1%
Uppercase Letter
ValueCountFrequency (%)
P 275
55.4%
U 211
42.5%
S 10
 
2.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 4938
> 99.9%
Common 1
 
< 0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 666
13.5%
r 657
13.3%
d 624
12.6%
i 520
10.5%
o 464
9.4%
s 405
8.2%
e 300
6.1%
P 275
5.6%
n 221
 
4.5%
U 211
 
4.3%
Other values (8) 595
12.0%
Common
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4939
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 666
13.5%
r 657
13.3%
d 624
12.6%
i 520
10.5%
o 464
9.4%
s 405
8.2%
e 300
6.1%
P 275
5.6%
n 221
 
4.5%
U 211
 
4.3%
Other values (9) 596
12.1%
Distinct8
Distinct (%)1.6%
Missing1
Missing (%)0.2%
Memory size4.0 KiB
Sí, asalariado/a-recibe un sueldo fijo
242 
No, estudiante de tiempo completo
94 
Sí, negocio propio formal
48 
Sí, negocio propio informal
27 
No, actualmente desempleado
25 
Other values (3)
60 

Length

Max length40
Median length38
Mean length32.76209677
Min length14

Characters and Unicode

Total characters16250
Distinct characters26
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo, actualmente desempleado
2nd rowSí, negocio propio formal
3rd rowSí, asalariado/a-recibe un sueldo fijo
4th rowSí, asalariado/a-recibe un sueldo fijo
5th rowSí, asalariado/a-recibe un sueldo fijo

Common Values

ValueCountFrequency (%)
Sí, asalariado/a-recibe un sueldo fijo 242
48.7%
No, estudiante de tiempo completo 94
 
18.9%
Sí, negocio propio formal 48
 
9.7%
Sí, negocio propio informal 27
 
5.4%
No, actualmente desempleado 25
 
5.0%
Sí, por comisiones 23
 
4.6%
No, jubilado/a 21
 
4.2%
No, labores del hogar de tiempo completo 16
 
3.2%
(Missing) 1
 
0.2%

Length

2024-01-31T13:58:15.418836image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-31T13:58:15.791769image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
340
14.9%
asalariado/a-recibe 242
10.6%
un 242
10.6%
sueldo 242
10.6%
fijo 242
10.6%
no 156
 
6.8%
de 110
 
4.8%
tiempo 110
 
4.8%
completo 110
 
4.8%
estudiante 94
 
4.1%
Other values (12) 390
17.1%

Most occurring characters

ValueCountFrequency (%)
1782
 
11.0%
o 1734
 
10.7%
a 1528
 
9.4%
e 1499
 
9.2%
i 1174
 
7.2%
d 775
 
4.8%
l 772
 
4.8%
r 689
 
4.2%
s 665
 
4.1%
u 624
 
3.8%
Other values (16) 5008
30.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 12971
79.8%
Space Separator 1782
 
11.0%
Other Punctuation 759
 
4.7%
Uppercase Letter 496
 
3.1%
Dash Punctuation 242
 
1.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 1734
13.4%
a 1528
11.8%
e 1499
11.6%
i 1174
 
9.1%
d 775
 
6.0%
l 772
 
6.0%
r 689
 
5.3%
s 665
 
5.1%
u 624
 
4.8%
n 486
 
3.7%
Other values (10) 3025
23.3%
Other Punctuation
ValueCountFrequency (%)
, 496
65.3%
/ 263
34.7%
Uppercase Letter
ValueCountFrequency (%)
S 340
68.5%
N 156
31.5%
Space Separator
ValueCountFrequency (%)
1782
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 242
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 13467
82.9%
Common 2783
 
17.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 1734
12.9%
a 1528
11.3%
e 1499
11.1%
i 1174
 
8.7%
d 775
 
5.8%
l 772
 
5.7%
r 689
 
5.1%
s 665
 
4.9%
u 624
 
4.6%
n 486
 
3.6%
Other values (12) 3521
26.1%
Common
ValueCountFrequency (%)
1782
64.0%
, 496
 
17.8%
/ 263
 
9.5%
- 242
 
8.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 15910
97.9%
None 340
 
2.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1782
 
11.2%
o 1734
 
10.9%
a 1528
 
9.6%
e 1499
 
9.4%
i 1174
 
7.4%
d 775
 
4.9%
l 772
 
4.9%
r 689
 
4.3%
s 665
 
4.2%
u 624
 
3.9%
Other values (15) 4668
29.3%
None
ValueCountFrequency (%)
í 340
100.0%

limpio_cp
Real number (ℝ)

Distinct139
Distinct (%)28.1%
Missing2
Missing (%)0.4%
Infinite0
Infinite (%)0.0%
Mean90022.62222
Minimum22130
Maximum98155
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.0 KiB
2024-01-31T13:58:16.278811image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Quantile statistics

Minimum22130
5-th percentile91000
Q191070
median91172
Q391380
95-th percentile91636.3
Maximum98155
Range76025
Interquartile range (IQR)310

Descriptive statistics

Standard deviation8152.799598
Coefficient of variation (CV)0.09056389824
Kurtosis47.48572835
Mean90022.62222
Median Absolute Deviation (MAD)128
Skewness-6.835159102
Sum44561198
Variance66468141.29
MonotonicityNot monotonic
2024-01-31T13:58:16.534073image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
91500 35
 
7.0%
91300 35
 
7.0%
91000 31
 
6.2%
91190 26
 
5.2%
91070 15
 
3.0%
91637 14
 
2.8%
91100 11
 
2.2%
91240 11
 
2.2%
91380 10
 
2.0%
91130 10
 
2.0%
Other values (129) 297
59.8%
ValueCountFrequency (%)
22130 1
0.2%
23344 1
0.2%
24566 1
0.2%
29130 1
0.2%
29150 1
0.2%
ValueCountFrequency (%)
98155 1
0.2%
94180 1
0.2%
93700 1
0.2%
93655 1
0.2%
92820 1
0.2%

limpio_contexto
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.6%
Missing1
Missing (%)0.2%
Memory size4.0 KiB
Urbano
412 
Rural
67 
Suburbano
 
17

Length

Max length9
Median length6
Mean length5.967741935
Min length5

Characters and Unicode

Total characters2960
Distinct characters10
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowRural
2nd rowUrbano
3rd rowUrbano
4th rowUrbano
5th rowUrbano

Common Values

ValueCountFrequency (%)
Urbano 412
82.9%
Rural 67
 
13.5%
Suburbano 17
 
3.4%
(Missing) 1
 
0.2%

Length

2024-01-31T13:58:16.752223image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-31T13:58:16.905431image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
urbano 412
83.1%
rural 67
 
13.5%
suburbano 17
 
3.4%

Most occurring characters

ValueCountFrequency (%)
r 496
16.8%
a 496
16.8%
b 446
15.1%
n 429
14.5%
o 429
14.5%
U 412
13.9%
u 101
 
3.4%
R 67
 
2.3%
l 67
 
2.3%
S 17
 
0.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 2464
83.2%
Uppercase Letter 496
 
16.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
r 496
20.1%
a 496
20.1%
b 446
18.1%
n 429
17.4%
o 429
17.4%
u 101
 
4.1%
l 67
 
2.7%
Uppercase Letter
ValueCountFrequency (%)
U 412
83.1%
R 67
 
13.5%
S 17
 
3.4%

Most occurring scripts

ValueCountFrequency (%)
Latin 2960
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
r 496
16.8%
a 496
16.8%
b 446
15.1%
n 429
14.5%
o 429
14.5%
U 412
13.9%
u 101
 
3.4%
R 67
 
2.3%
l 67
 
2.3%
S 17
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2960
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
r 496
16.8%
a 496
16.8%
b 446
15.1%
n 429
14.5%
o 429
14.5%
U 412
13.9%
u 101
 
3.4%
R 67
 
2.3%
l 67
 
2.3%
S 17
 
0.6%

limpio_municipio
Categorical

IMBALANCE 

Distinct24
Distinct (%)4.9%
Missing3
Missing (%)0.6%
Memory size4.0 KiB
Xalapa
280 
Coatepec
82 
Banderilla
44 
Emiliano Zapata
 
20
Xico
 
16
Other values (19)
52 

Length

Max length18
Median length6
Mean length7.473684211
Min length4

Characters and Unicode

Total characters3692
Distinct characters41
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique13 ?
Unique (%)2.6%

Sample

1st rowAcajete
2nd rowXalapa
3rd rowXalapa
4th rowXalapa
5th rowCoatepec

Common Values

ValueCountFrequency (%)
Xalapa 280
56.3%
Coatepec 82
 
16.5%
Banderilla 44
 
8.9%
Emiliano Zapata 20
 
4.0%
Xico 16
 
3.2%
Tlalnelhuayocan 16
 
3.2%
Jilotepec 10
 
2.0%
Teocelo 6
 
1.2%
Acajete 3
 
0.6%
Cosautlán 2
 
0.4%
Other values (14) 15
 
3.0%
(Missing) 3
 
0.6%

Length

2024-01-31T13:58:17.085615image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
xalapa 280
54.2%
coatepec 82
 
15.9%
banderilla 44
 
8.5%
emiliano 20
 
3.9%
zapata 20
 
3.9%
xico 16
 
3.1%
tlalnelhuayocan 16
 
3.1%
jilotepec 10
 
1.9%
teocelo 6
 
1.2%
acajete 3
 
0.6%
Other values (18) 20
 
3.9%

Most occurring characters

ValueCountFrequency (%)
a 1165
31.6%
l 465
 
12.6%
p 397
 
10.8%
X 296
 
8.0%
e 268
 
7.3%
o 169
 
4.6%
c 141
 
3.8%
t 125
 
3.4%
i 115
 
3.1%
n 106
 
2.9%
Other values (31) 445
 
12.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 3154
85.4%
Uppercase Letter 515
 
13.9%
Space Separator 23
 
0.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 1165
36.9%
l 465
 
14.7%
p 397
 
12.6%
e 268
 
8.5%
o 169
 
5.4%
c 141
 
4.5%
t 125
 
4.0%
i 115
 
3.6%
n 106
 
3.4%
r 49
 
1.6%
Other values (16) 154
 
4.9%
Uppercase Letter
ValueCountFrequency (%)
X 296
57.5%
C 84
 
16.3%
B 45
 
8.7%
T 26
 
5.0%
E 21
 
4.1%
Z 20
 
3.9%
J 10
 
1.9%
A 4
 
0.8%
N 3
 
0.6%
V 2
 
0.4%
Other values (4) 4
 
0.8%
Space Separator
ValueCountFrequency (%)
23
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 3669
99.4%
Common 23
 
0.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 1165
31.8%
l 465
 
12.7%
p 397
 
10.8%
X 296
 
8.1%
e 268
 
7.3%
o 169
 
4.6%
c 141
 
3.8%
t 125
 
3.4%
i 115
 
3.1%
n 106
 
2.9%
Other values (30) 422
 
11.5%
Common
ValueCountFrequency (%)
23
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3683
99.8%
None 9
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 1165
31.6%
l 465
 
12.6%
p 397
 
10.8%
X 296
 
8.0%
e 268
 
7.3%
o 169
 
4.6%
c 141
 
3.8%
t 125
 
3.4%
i 115
 
3.1%
n 106
 
2.9%
Other values (27) 436
 
11.8%
None
ValueCountFrequency (%)
á 4
44.4%
ó 2
22.2%
í 2
22.2%
é 1
 
11.1%
Distinct200
Distinct (%)40.5%
Missing3
Missing (%)0.6%
Memory size4.0 KiB
2024-01-31T13:58:17.579953image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Length

Max length32
Median length25
Mean length11.77125506
Min length4

Characters and Unicode

Total characters5815
Distinct characters63
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique114 ?
Unique (%)23.1%

Sample

1st rowCentro
2nd rowTamborel
3rd rowRevolución
4th rowRafael Hernández Ochoa
5th rowFraccionamiento San José
ValueCountFrequency (%)
centro 64
 
7.2%
de 54
 
6.0%
la 22
 
2.5%
júarez 21
 
2.4%
benito 21
 
2.4%
xalapa 20
 
2.2%
san 20
 
2.2%
ánimas 18
 
2.0%
las 16
 
1.8%
zapata 15
 
1.7%
Other values (239) 622
69.7%
2024-01-31T13:58:18.476156image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 750
12.9%
e 524
 
9.0%
o 462
 
7.9%
r 408
 
7.0%
401
 
6.9%
n 352
 
6.1%
i 324
 
5.6%
l 254
 
4.4%
t 244
 
4.2%
s 223
 
3.8%
Other values (53) 1873
32.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 4568
78.6%
Uppercase Letter 806
 
13.9%
Space Separator 401
 
6.9%
Decimal Number 32
 
0.6%
Other Punctuation 8
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 750
16.4%
e 524
11.5%
o 462
10.1%
r 408
8.9%
n 352
7.7%
i 324
 
7.1%
l 254
 
5.6%
t 244
 
5.3%
s 223
 
4.9%
d 184
 
4.0%
Other values (20) 843
18.5%
Uppercase Letter
ValueCountFrequency (%)
C 134
16.6%
M 90
 
11.2%
L 67
 
8.3%
B 55
 
6.8%
J 46
 
5.7%
S 40
 
5.0%
P 39
 
4.8%
E 38
 
4.7%
R 36
 
4.5%
F 33
 
4.1%
Other values (15) 228
28.3%
Decimal Number
ValueCountFrequency (%)
0 14
43.8%
2 11
34.4%
6 3
 
9.4%
3 2
 
6.2%
1 2
 
6.2%
Other Punctuation
ValueCountFrequency (%)
. 4
50.0%
, 4
50.0%
Space Separator
ValueCountFrequency (%)
401
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 5374
92.4%
Common 441
 
7.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 750
14.0%
e 524
 
9.8%
o 462
 
8.6%
r 408
 
7.6%
n 352
 
6.6%
i 324
 
6.0%
l 254
 
4.7%
t 244
 
4.5%
s 223
 
4.1%
d 184
 
3.4%
Other values (45) 1649
30.7%
Common
ValueCountFrequency (%)
401
90.9%
0 14
 
3.2%
2 11
 
2.5%
. 4
 
0.9%
, 4
 
0.9%
6 3
 
0.7%
3 2
 
0.5%
1 2
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5698
98.0%
None 117
 
2.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 750
13.2%
e 524
 
9.2%
o 462
 
8.1%
r 408
 
7.2%
401
 
7.0%
n 352
 
6.2%
i 324
 
5.7%
l 254
 
4.5%
t 244
 
4.3%
s 223
 
3.9%
Other values (45) 1756
30.8%
None
ValueCountFrequency (%)
á 23
19.7%
Á 21
17.9%
ú 21
17.9%
ó 15
12.8%
é 14
12.0%
í 12
10.3%
ñ 9
 
7.7%
É 2
 
1.7%

limpio_habitantes
Real number (ℝ)

Distinct14
Distinct (%)2.8%
Missing2
Missing (%)0.4%
Infinite0
Infinite (%)0.0%
Mean3.75959596
Minimum0
Maximum123
Zeros1
Zeros (%)0.2%
Negative0
Negative (%)0.0%
Memory size4.0 KiB
2024-01-31T13:58:18.836222image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q12
median3
Q34
95-th percentile6
Maximum123
Range123
Interquartile range (IQR)2

Descriptive statistics

Standard deviation6.811872215
Coefficient of variation (CV)1.811862841
Kurtosis239.626969
Mean3.75959596
Median Absolute Deviation (MAD)1
Skewness14.89011253
Sum1861
Variance46.40160308
MonotonicityNot monotonic
2024-01-31T13:58:19.151191image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
2 127
25.6%
4 116
23.3%
3 109
21.9%
5 57
11.5%
1 45
 
9.1%
6 17
 
3.4%
7 8
 
1.6%
8 6
 
1.2%
9 4
 
0.8%
11 2
 
0.4%
Other values (4) 4
 
0.8%
(Missing) 2
 
0.4%
ValueCountFrequency (%)
0 1
 
0.2%
1 45
 
9.1%
2 127
25.6%
3 109
21.9%
4 116
23.3%
ValueCountFrequency (%)
123 1
 
0.2%
89 1
 
0.2%
11 2
0.4%
10 1
 
0.2%
9 4
0.8%

limpio_tipo_casa
Categorical

IMBALANCE 

Distinct16
Distinct (%)3.2%
Missing1
Missing (%)0.2%
Memory size4.0 KiB
Casa única en el terreno
342 
Casa que comparte terreno con otra (s)
73 
Vivienda en vecindad o cuartería
 
28
Vivienda Colectiva
 
15
Departamento
 
13
Other values (11)
 
25

Length

Max length38
Median length24
Mean length25.50403226
Min length7

Characters and Unicode

Total characters12650
Distinct characters38
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique8 ?
Unique (%)1.6%

Sample

1st rowCasa única en el terreno
2nd rowCasa única en el terreno
3rd rowCasa única en el terreno
4th rowCasa que comparte terreno con otra (s)
5th rowCasa única en el terreno

Common Values

ValueCountFrequency (%)
Casa única en el terreno 342
68.8%
Casa que comparte terreno con otra (s) 73
 
14.7%
Vivienda en vecindad o cuartería 28
 
5.6%
Vivienda Colectiva 15
 
3.0%
Departamento 13
 
2.6%
Casa Duplex 13
 
2.6%
Condominio 2
 
0.4%
Casa rentada 2
 
0.4%
Local no construido para habitación 1
 
0.2%
Casa habitación de interés social 1
 
0.2%
Other values (6) 6
 
1.2%

Length

2024-01-31T13:58:19.476267image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
casa 432
17.6%
terreno 415
16.9%
en 370
15.1%
única 342
13.9%
el 342
13.9%
que 73
 
3.0%
comparte 73
 
3.0%
con 73
 
3.0%
otra 73
 
3.0%
s 73
 
3.0%
Other values (25) 190
7.7%

Most occurring characters

ValueCountFrequency (%)
1960
15.5%
e 1848
14.6%
a 1544
12.2%
n 1300
10.3%
r 1054
8.3%
o 707
 
5.6%
t 639
 
5.1%
c 568
 
4.5%
s 508
 
4.0%
i 499
 
3.9%
Other values (28) 2023
16.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 10017
79.2%
Space Separator 1960
 
15.5%
Uppercase Letter 527
 
4.2%
Open Punctuation 73
 
0.6%
Close Punctuation 73
 
0.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 1848
18.4%
a 1544
15.4%
n 1300
13.0%
r 1054
10.5%
o 707
 
7.1%
t 639
 
6.4%
c 568
 
5.7%
s 508
 
5.1%
i 499
 
5.0%
l 376
 
3.8%
Other values (15) 974
9.7%
Uppercase Letter
ValueCountFrequency (%)
C 449
85.2%
V 44
 
8.3%
D 26
 
4.9%
F 2
 
0.4%
L 1
 
0.2%
E 1
 
0.2%
M 1
 
0.2%
U 1
 
0.2%
P 1
 
0.2%
R 1
 
0.2%
Space Separator
ValueCountFrequency (%)
1960
100.0%
Open Punctuation
ValueCountFrequency (%)
( 73
100.0%
Close Punctuation
ValueCountFrequency (%)
) 73
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 10544
83.4%
Common 2106
 
16.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 1848
17.5%
a 1544
14.6%
n 1300
12.3%
r 1054
10.0%
o 707
 
6.7%
t 639
 
6.1%
c 568
 
5.4%
s 508
 
4.8%
i 499
 
4.7%
C 449
 
4.3%
Other values (25) 1428
13.5%
Common
ValueCountFrequency (%)
1960
93.1%
( 73
 
3.5%
) 73
 
3.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 12277
97.1%
None 373
 
2.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1960
16.0%
e 1848
15.1%
a 1544
12.6%
n 1300
10.6%
r 1054
8.6%
o 707
 
5.8%
t 639
 
5.2%
c 568
 
4.6%
s 508
 
4.1%
i 499
 
4.1%
Other values (24) 1650
13.4%
None
ValueCountFrequency (%)
ú 342
91.7%
í 28
 
7.5%
ó 2
 
0.5%
é 1
 
0.3%
Distinct2
Distinct (%)0.4%
Missing1
Missing (%)0.2%
Memory size4.0 KiB
330 
No
166 

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters992
Distinct characters4
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd row
3rd row
4th rowNo
5th row

Common Values

ValueCountFrequency (%)
330
66.4%
No 166
33.4%
(Missing) 1
 
0.2%

Length

2024-01-31T13:58:19.654422image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-31T13:58:19.970464image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
330
66.5%
no 166
33.5%

Most occurring characters

ValueCountFrequency (%)
S 330
33.3%
í 330
33.3%
N 166
16.7%
o 166
16.7%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 496
50.0%
Lowercase Letter 496
50.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
S 330
66.5%
N 166
33.5%
Lowercase Letter
ValueCountFrequency (%)
í 330
66.5%
o 166
33.5%

Most occurring scripts

ValueCountFrequency (%)
Latin 992
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
S 330
33.3%
í 330
33.3%
N 166
16.7%
o 166
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 662
66.7%
None 330
33.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
S 330
49.8%
N 166
25.1%
o 166
25.1%
None
ValueCountFrequency (%)
í 330
100.0%
Distinct81
Distinct (%)16.3%
Missing1
Missing (%)0.2%
Memory size4.0 KiB
2024-01-31T13:58:20.215808image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Length

Max length99
Median length77
Mean length17.67943548
Min length4

Characters and Unicode

Total characters8769
Distinct characters30
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique47 ?
Unique (%)9.5%

Sample

1st rowMarzo, Abril, Mayo
2nd rowNingún mes
3rd rowNingún mes
4th rowJulio
5th rowNingún mes
ValueCountFrequency (%)
mayo 240
17.4%
abril 188
13.6%
junio 167
12.1%
ningún 153
11.1%
mes 153
11.1%
julio 122
8.8%
marzo 100
7.2%
agosto 85
 
6.1%
septiembre 49
 
3.5%
octubre 34
 
2.5%
Other values (4) 92
 
6.7%
2024-01-31T13:58:21.034627image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
887
 
10.1%
o 872
 
9.9%
i 741
 
8.5%
, 734
 
8.4%
e 497
 
5.7%
n 494
 
5.6%
r 491
 
5.6%
b 342
 
3.9%
M 340
 
3.9%
a 340
 
3.9%
Other values (20) 3031
34.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 5918
67.5%
Uppercase Letter 1230
 
14.0%
Space Separator 887
 
10.1%
Other Punctuation 734
 
8.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 872
14.7%
i 741
12.5%
e 497
 
8.4%
n 494
 
8.3%
r 491
 
8.3%
b 342
 
5.8%
a 340
 
5.7%
u 323
 
5.5%
l 310
 
5.2%
m 245
 
4.1%
Other values (9) 1263
21.3%
Uppercase Letter
ValueCountFrequency (%)
M 340
27.6%
J 289
23.5%
A 273
22.2%
N 177
14.4%
S 49
 
4.0%
O 34
 
2.8%
F 28
 
2.3%
E 21
 
1.7%
D 19
 
1.5%
Space Separator
ValueCountFrequency (%)
887
100.0%
Other Punctuation
ValueCountFrequency (%)
, 734
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 7148
81.5%
Common 1621
 
18.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 872
 
12.2%
i 741
 
10.4%
e 497
 
7.0%
n 494
 
6.9%
r 491
 
6.9%
b 342
 
4.8%
M 340
 
4.8%
a 340
 
4.8%
u 323
 
4.5%
l 310
 
4.3%
Other values (18) 2398
33.5%
Common
ValueCountFrequency (%)
887
54.7%
, 734
45.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 8616
98.3%
None 153
 
1.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
887
 
10.3%
o 872
 
10.1%
i 741
 
8.6%
, 734
 
8.5%
e 497
 
5.8%
n 494
 
5.7%
r 491
 
5.7%
b 342
 
4.0%
M 340
 
3.9%
a 340
 
3.9%
Other values (19) 2878
33.4%
None
ValueCountFrequency (%)
ú 153
100.0%

limpio_dias_sin_serv
Categorical

MISSING 

Distinct7
Distinct (%)1.6%
Missing48
Missing (%)9.7%
Memory size4.0 KiB
No falta
228 
1 a 3
126 
4 a 6
39 
7 a 9
24 
Superior a 15 días
 
17
Other values (2)
 
15

Length

Max length18
Median length8
Mean length7.082405345
Min length5

Characters and Unicode

Total characters3180
Distinct characters25
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row4 a 6
2nd rowNo falta
3rd rowNo falta
4th row4 a 6
5th rowNo falta

Common Values

ValueCountFrequency (%)
No falta 228
45.9%
1 a 3 126
25.4%
4 a 6 39
 
7.8%
7 a 9 24
 
4.8%
Superior a 15 días 17
 
3.4%
10 a 12 8
 
1.6%
13 a 15 7
 
1.4%
(Missing) 48
 
9.7%

Length

2024-01-31T13:58:21.437792image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-31T13:58:21.833346image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
no 228
20.1%
falta 228
20.1%
a 221
19.5%
1 126
11.1%
3 126
11.1%
4 39
 
3.4%
6 39
 
3.4%
7 24
 
2.1%
9 24
 
2.1%
15 24
 
2.1%
Other values (5) 57
 
5.0%

Most occurring characters

ValueCountFrequency (%)
a 694
21.8%
687
21.6%
o 245
 
7.7%
N 228
 
7.2%
f 228
 
7.2%
l 228
 
7.2%
t 228
 
7.2%
1 173
 
5.4%
3 133
 
4.2%
4 39
 
1.2%
Other values (15) 297
9.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1776
55.8%
Space Separator 687
 
21.6%
Decimal Number 472
 
14.8%
Uppercase Letter 245
 
7.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 694
39.1%
o 245
 
13.8%
f 228
 
12.8%
l 228
 
12.8%
t 228
 
12.8%
r 34
 
1.9%
u 17
 
1.0%
p 17
 
1.0%
e 17
 
1.0%
i 17
 
1.0%
Other values (3) 51
 
2.9%
Decimal Number
ValueCountFrequency (%)
1 173
36.7%
3 133
28.2%
4 39
 
8.3%
6 39
 
8.3%
5 24
 
5.1%
9 24
 
5.1%
7 24
 
5.1%
0 8
 
1.7%
2 8
 
1.7%
Uppercase Letter
ValueCountFrequency (%)
N 228
93.1%
S 17
 
6.9%
Space Separator
ValueCountFrequency (%)
687
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 2021
63.6%
Common 1159
36.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 694
34.3%
o 245
 
12.1%
N 228
 
11.3%
f 228
 
11.3%
l 228
 
11.3%
t 228
 
11.3%
r 34
 
1.7%
u 17
 
0.8%
p 17
 
0.8%
e 17
 
0.8%
Other values (5) 85
 
4.2%
Common
ValueCountFrequency (%)
687
59.3%
1 173
 
14.9%
3 133
 
11.5%
4 39
 
3.4%
6 39
 
3.4%
5 24
 
2.1%
9 24
 
2.1%
7 24
 
2.1%
0 8
 
0.7%
2 8
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3163
99.5%
None 17
 
0.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 694
21.9%
687
21.7%
o 245
 
7.7%
N 228
 
7.2%
f 228
 
7.2%
l 228
 
7.2%
t 228
 
7.2%
1 173
 
5.5%
3 133
 
4.2%
4 39
 
1.2%
Other values (14) 280
8.9%
None
ValueCountFrequency (%)
í 17
100.0%

limpio_razon_NA_checar
Categorical

MISSING 

Distinct20
Distinct (%)4.5%
Missing52
Missing (%)10.5%
Memory size4.0 KiB
No aplica
153 
Por Tandeos
139 
Desconozco
29 
Por Reparación
26 
Desabasto
23 
Other values (15)
75 

Length

Max length34
Median length30
Mean length11.3011236
Min length9

Characters and Unicode

Total characters5029
Distinct characters32
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)1.3%

Sample

1st rowNo aplica
2nd rowNo aplica
3rd rowPor Reparación
4th rowNo aplica
5th rowNo aplica

Common Values

ValueCountFrequency (%)
No aplica 153
30.8%
Por Tandeos 139
28.0%
Desconozco 29
 
5.8%
Por Reparación 26
 
5.2%
Desabasto 23
 
4.6%
Corte de agua 21
 
4.2%
Por Mantenimiento 14
 
2.8%
Falta de presión 13
 
2.6%
Por mal uso 6
 
1.2%
Temporada de lluvia 5
 
1.0%
Other values (10) 16
 
3.2%
(Missing) 52
 
10.5%

Length

2024-01-31T13:58:22.302586image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
por 192
21.4%
no 153
17.0%
aplica 153
17.0%
tandeos 139
15.5%
de 45
 
5.0%
reparación 31
 
3.4%
desconozco 29
 
3.2%
desabasto 23
 
2.6%
corte 22
 
2.4%
agua 21
 
2.3%
Other values (20) 91
10.1%

Most occurring characters

ValueCountFrequency (%)
a 692
13.8%
o 660
13.1%
454
 
9.0%
e 358
 
7.1%
r 281
 
5.6%
n 275
 
5.5%
c 253
 
5.0%
s 249
 
5.0%
i 245
 
4.9%
p 204
 
4.1%
Other values (22) 1358
27.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 3915
77.8%
Uppercase Letter 651
 
12.9%
Space Separator 454
 
9.0%
Other Punctuation 9
 
0.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 692
17.7%
o 660
16.9%
e 358
9.1%
r 281
7.2%
n 275
 
7.0%
c 253
 
6.5%
s 249
 
6.4%
i 245
 
6.3%
p 204
 
5.2%
d 195
 
5.0%
Other values (11) 503
12.8%
Uppercase Letter
ValueCountFrequency (%)
P 200
30.7%
N 153
23.5%
T 152
23.3%
D 55
 
8.4%
R 33
 
5.1%
C 22
 
3.4%
M 17
 
2.6%
F 16
 
2.5%
A 3
 
0.5%
Space Separator
ValueCountFrequency (%)
454
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 4566
90.8%
Common 463
 
9.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 692
15.2%
o 660
14.5%
e 358
 
7.8%
r 281
 
6.2%
n 275
 
6.0%
c 253
 
5.5%
s 249
 
5.5%
i 245
 
5.4%
p 204
 
4.5%
P 200
 
4.4%
Other values (20) 1149
25.2%
Common
ValueCountFrequency (%)
454
98.1%
/ 9
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4976
98.9%
None 53
 
1.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 692
13.9%
o 660
13.3%
454
 
9.1%
e 358
 
7.2%
r 281
 
5.6%
n 275
 
5.5%
c 253
 
5.1%
s 249
 
5.0%
i 245
 
4.9%
p 204
 
4.1%
Other values (19) 1305
26.2%
None
ValueCountFrequency (%)
ó 48
90.6%
í 3
 
5.7%
é 2
 
3.8%

limpio_obtencion_agua
Categorical

MISSING 

Distinct27
Distinct (%)6.4%
Missing72
Missing (%)14.5%
Memory size4.0 KiB
De ningún lado
94 
Pipa
70 
Almacenamiento
47 
Cisterna
39 
Garrafón
38 
Other values (22)
137 

Length

Max length30
Median length24
Mean length9.409411765
Min length4

Characters and Unicode

Total characters3999
Distinct characters37
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique11 ?
Unique (%)2.6%

Sample

1st rowDe ningún lado
2nd rowDe ningún lado
3rd rowPipa
4th rowTinaco
5th rowCisterna

Common Values

ValueCountFrequency (%)
De ningún lado 94
18.9%
Pipa 70
14.1%
Almacenamiento 47
9.5%
Cisterna 39
7.8%
Garrafón 38
7.6%
Lluvia 30
 
6.0%
Vecinos 30
 
6.0%
Tinaco 26
 
5.2%
Pozo 11
 
2.2%
Nacimiento/Río 10
 
2.0%
Other values (17) 30
 
6.0%
(Missing) 72
14.5%

Length

2024-01-31T13:58:22.730341image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
de 94
14.8%
ningún 94
14.8%
lado 94
14.8%
pipa 76
12.0%
almacenamiento 52
8.2%
garrafón 42
6.6%
cisterna 39
6.2%
lluvia 38
6.0%
vecinos 34
 
5.4%
tinaco 27
 
4.3%
Other values (8) 43
6.8%

Most occurring characters

ValueCountFrequency (%)
n 551
13.8%
a 491
12.3%
i 400
 
10.0%
e 300
 
7.5%
o 253
 
6.3%
208
 
5.2%
l 197
 
4.9%
c 129
 
3.2%
r 123
 
3.1%
m 122
 
3.1%
Other values (27) 1225
30.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 3314
82.9%
Uppercase Letter 451
 
11.3%
Space Separator 208
 
5.2%
Other Punctuation 26
 
0.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n 551
16.6%
a 491
14.8%
i 400
12.1%
e 300
9.1%
o 253
7.6%
l 197
 
5.9%
c 129
 
3.9%
r 123
 
3.7%
m 122
 
3.7%
t 116
 
3.5%
Other values (12) 632
19.1%
Uppercase Letter
ValueCountFrequency (%)
P 94
20.8%
D 94
20.8%
A 52
11.5%
G 42
9.3%
C 40
8.9%
L 38
8.4%
V 34
 
7.5%
T 29
 
6.4%
N 11
 
2.4%
R 11
 
2.4%
Other values (2) 6
 
1.3%
Other Punctuation
ValueCountFrequency (%)
, 15
57.7%
/ 11
42.3%
Space Separator
ValueCountFrequency (%)
208
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 3765
94.1%
Common 234
 
5.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
n 551
14.6%
a 491
13.0%
i 400
 
10.6%
e 300
 
8.0%
o 253
 
6.7%
l 197
 
5.2%
c 129
 
3.4%
r 123
 
3.3%
m 122
 
3.2%
t 116
 
3.1%
Other values (24) 1083
28.8%
Common
ValueCountFrequency (%)
208
88.9%
, 15
 
6.4%
/ 11
 
4.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3852
96.3%
None 147
 
3.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n 551
14.3%
a 491
12.7%
i 400
 
10.4%
e 300
 
7.8%
o 253
 
6.6%
208
 
5.4%
l 197
 
5.1%
c 129
 
3.3%
r 123
 
3.2%
m 122
 
3.2%
Other values (24) 1078
28.0%
None
ValueCountFrequency (%)
ú 94
63.9%
ó 42
28.6%
í 11
 
7.5%

limpio_almacenamiento
Categorical

MISSING 

Distinct29
Distinct (%)6.2%
Missing29
Missing (%)5.8%
Memory size4.0 KiB
Tinaco
135 
Cisterna
110 
Cubetas
67 
Tambo
45 
Ninguno
22 
Other values (24)
89 

Length

Max length24
Median length23
Mean length8.049145299
Min length5

Characters and Unicode

Total characters3767
Distinct characters20
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique10 ?
Unique (%)2.1%

Sample

1st rowCubetas, Tinaco, Pileta
2nd rowTinaco
3rd rowTinaco
4th rowTambo
5th rowCisterna

Common Values

ValueCountFrequency (%)
Tinaco 135
27.2%
Cisterna 110
22.1%
Cubetas 67
13.5%
Tambo 45
 
9.1%
Ninguno 22
 
4.4%
Pileta 14
 
2.8%
Cisterna, Tinaco 13
 
2.6%
Tambo, Cubetas 9
 
1.8%
Tinaco, Cubetas 7
 
1.4%
Tinaco, Cisterna 7
 
1.4%
Other values (19) 39
 
7.8%
(Missing) 29
 
5.8%

Length

2024-01-31T13:58:23.053075image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
tinaco 183
33.4%
cisterna 139
25.4%
cubetas 97
17.7%
tambo 78
14.2%
pileta 29
 
5.3%
ninguno 22
 
4.0%

Most occurring characters

ValueCountFrequency (%)
a 526
14.0%
i 373
9.9%
n 366
9.7%
o 283
 
7.5%
t 265
 
7.0%
e 265
 
7.0%
T 261
 
6.9%
C 236
 
6.3%
s 236
 
6.3%
c 183
 
4.9%
Other values (10) 773
20.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 3059
81.2%
Uppercase Letter 548
 
14.5%
Other Punctuation 80
 
2.1%
Space Separator 80
 
2.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 526
17.2%
i 373
12.2%
n 366
12.0%
o 283
9.3%
t 265
8.7%
e 265
8.7%
s 236
7.7%
c 183
 
6.0%
b 175
 
5.7%
r 139
 
4.5%
Other values (4) 248
8.1%
Uppercase Letter
ValueCountFrequency (%)
T 261
47.6%
C 236
43.1%
P 29
 
5.3%
N 22
 
4.0%
Other Punctuation
ValueCountFrequency (%)
, 80
100.0%
Space Separator
ValueCountFrequency (%)
80
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 3607
95.8%
Common 160
 
4.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 526
14.6%
i 373
10.3%
n 366
10.1%
o 283
7.8%
t 265
7.3%
e 265
7.3%
T 261
7.2%
C 236
 
6.5%
s 236
 
6.5%
c 183
 
5.1%
Other values (8) 613
17.0%
Common
ValueCountFrequency (%)
, 80
50.0%
80
50.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3767
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 526
14.0%
i 373
9.9%
n 366
9.7%
o 283
 
7.5%
t 265
 
7.0%
e 265
 
7.0%
T 261
 
6.9%
C 236
 
6.3%
s 236
 
6.3%
c 183
 
4.9%
Other values (10) 773
20.5%

limpio_acarreo
Text

MISSING 

Distinct107
Distinct (%)34.0%
Missing182
Missing (%)36.6%
Memory size4.0 KiB
2024-01-31T13:58:23.485433image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Length

Max length57
Median length56
Mean length13.33968254
Min length7

Characters and Unicode

Total characters4202
Distinct characters30
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique69 ?
Unique (%)21.9%

Sample

1st rowFemenino, 54 / Femenino, 24
2nd rowNo aplica
3rd rowNo aplica
4th rowNo aplica
5th rowNo aplica
ValueCountFrequency (%)
masculino 172
23.9%
no 97
13.5%
aplica 97
13.5%
femenino 72
10.0%
44
 
6.1%
ninguno 28
 
3.9%
36 9
 
1.2%
30 8
 
1.1%
47 8
 
1.1%
38 8
 
1.1%
Other values (56) 178
24.7%
2024-01-31T13:58:24.224071image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
406
 
9.7%
n 375
 
8.9%
o 372
 
8.9%
i 370
 
8.8%
a 367
 
8.7%
c 271
 
6.4%
l 269
 
6.4%
, 210
 
5.0%
u 200
 
4.8%
s 173
 
4.1%
Other values (20) 1189
28.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 2743
65.3%
Decimal Number 417
 
9.9%
Space Separator 406
 
9.7%
Uppercase Letter 371
 
8.8%
Other Punctuation 265
 
6.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n 375
13.7%
o 372
13.6%
i 370
13.5%
a 367
13.4%
c 271
9.9%
l 269
9.8%
u 200
7.3%
s 173
6.3%
e 147
 
5.4%
p 97
 
3.5%
Other values (3) 102
 
3.7%
Decimal Number
ValueCountFrequency (%)
3 79
18.9%
4 78
18.7%
5 57
13.7%
2 50
12.0%
0 35
8.4%
6 32
7.7%
7 26
 
6.2%
1 23
 
5.5%
8 22
 
5.3%
9 15
 
3.6%
Uppercase Letter
ValueCountFrequency (%)
M 172
46.4%
N 125
33.7%
F 73
19.7%
D 1
 
0.3%
Other Punctuation
ValueCountFrequency (%)
, 210
79.2%
/ 55
 
20.8%
Space Separator
ValueCountFrequency (%)
406
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 3114
74.1%
Common 1088
 
25.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
n 375
12.0%
o 372
11.9%
i 370
11.9%
a 367
11.8%
c 271
8.7%
l 269
8.6%
u 200
6.4%
s 173
5.6%
M 172
5.5%
e 147
 
4.7%
Other values (7) 398
12.8%
Common
ValueCountFrequency (%)
406
37.3%
, 210
19.3%
3 79
 
7.3%
4 78
 
7.2%
5 57
 
5.2%
/ 55
 
5.1%
2 50
 
4.6%
0 35
 
3.2%
6 32
 
2.9%
7 26
 
2.4%
Other values (3) 60
 
5.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4202
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
406
 
9.7%
n 375
 
8.9%
o 372
 
8.9%
i 370
 
8.8%
a 367
 
8.7%
c 271
 
6.4%
l 269
 
6.4%
, 210
 
5.0%
u 200
 
4.8%
s 173
 
4.1%
Other values (20) 1189
28.3%
Distinct13
Distinct (%)2.6%
Missing4
Missing (%)0.8%
Memory size4.0 KiB
Desconozco
163 
Río
112 
Manantial
65 
Presa
55 
Fuente Municipal
50 
Other values (8)
48 

Length

Max length16
Median length13
Mean length7.9168357
Min length3

Characters and Unicode

Total characters3903
Distinct characters28
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)1.0%

Sample

1st rowRío
2nd rowDesconozco
3rd rowRío
4th rowPresa
5th rowDesconozco

Common Values

ValueCountFrequency (%)
Desconozco 163
32.8%
Río 112
22.5%
Manantial 65
 
13.1%
Presa 55
 
11.1%
Fuente Municipal 50
 
10.1%
Lluvia 21
 
4.2%
Pozo 20
 
4.0%
Río/Lluvia 2
 
0.4%
Pipa 1
 
0.2%
Nacimiento 1
 
0.2%
Other values (3) 3
 
0.6%
(Missing) 4
 
0.8%

Length

2024-01-31T13:58:24.650449image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
desconozco 163
30.0%
río 112
20.6%
manantial 65
 
12.0%
presa 55
 
10.1%
fuente 50
 
9.2%
municipal 50
 
9.2%
lluvia 21
 
3.9%
pozo 20
 
3.7%
río/lluvia 2
 
0.4%
pipa 1
 
0.2%
Other values (4) 4
 
0.7%

Most occurring characters

ValueCountFrequency (%)
o 645
16.5%
n 399
10.2%
c 377
9.7%
a 334
 
8.6%
e 319
 
8.2%
s 218
 
5.6%
i 194
 
5.0%
z 183
 
4.7%
D 163
 
4.2%
l 141
 
3.6%
Other values (18) 930
23.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 3302
84.6%
Uppercase Letter 547
 
14.0%
Space Separator 50
 
1.3%
Other Punctuation 4
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 645
19.5%
n 399
12.1%
c 377
11.4%
a 334
10.1%
e 319
9.7%
s 218
 
6.6%
i 194
 
5.9%
z 183
 
5.5%
l 141
 
4.3%
u 124
 
3.8%
Other values (8) 368
11.1%
Uppercase Letter
ValueCountFrequency (%)
D 163
29.8%
M 117
21.4%
R 115
21.0%
P 76
13.9%
F 50
 
9.1%
L 24
 
4.4%
N 1
 
0.2%
G 1
 
0.2%
Space Separator
ValueCountFrequency (%)
50
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 3849
98.6%
Common 54
 
1.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 645
16.8%
n 399
10.4%
c 377
9.8%
a 334
 
8.7%
e 319
 
8.3%
s 218
 
5.7%
i 194
 
5.0%
z 183
 
4.8%
D 163
 
4.2%
l 141
 
3.7%
Other values (16) 876
22.8%
Common
ValueCountFrequency (%)
50
92.6%
/ 4
 
7.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3787
97.0%
None 116
 
3.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o 645
17.0%
n 399
10.5%
c 377
10.0%
a 334
8.8%
e 319
 
8.4%
s 218
 
5.8%
i 194
 
5.1%
z 183
 
4.8%
D 163
 
4.3%
l 141
 
3.7%
Other values (16) 814
21.5%
None
ValueCountFrequency (%)
í 115
99.1%
ó 1
 
0.9%

limpio_nombre_fuente
Text

MISSING 

Distinct73
Distinct (%)19.7%
Missing126
Missing (%)25.4%
Memory size4.0 KiB
2024-01-31T13:58:25.114992image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Length

Max length43
Median length40
Mean length10.60916442
Min length4

Characters and Unicode

Total characters3936
Distinct characters54
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique51 ?
Unique (%)13.7%

Sample

1st rowPixquiac
2nd rowSedeño
3rd rowDesconozco
4th rowRío Pixquiac
5th rowHuitzilapan
ValueCountFrequency (%)
desconozco 166
35.4%
pixquiac 49
 
10.4%
de 25
 
5.3%
sedeño 23
 
4.9%
huitzilapan 22
 
4.7%
agua 13
 
2.8%
ojo 9
 
1.9%
el 8
 
1.7%
manantial 6
 
1.3%
huitzilapan/pixquiac 6
 
1.3%
Other values (93) 142
30.3%
2024-01-31T13:58:26.098577image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
o 608
15.4%
c 430
10.9%
a 312
 
7.9%
e 291
 
7.4%
i 268
 
6.8%
n 266
 
6.8%
z 212
 
5.4%
s 187
 
4.8%
D 168
 
4.3%
u 143
 
3.6%
Other values (44) 1051
26.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 3329
84.6%
Uppercase Letter 479
 
12.2%
Space Separator 98
 
2.5%
Other Punctuation 27
 
0.7%
Decimal Number 3
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 608
18.3%
c 430
12.9%
a 312
9.4%
e 291
8.7%
i 268
8.1%
n 266
8.0%
z 212
 
6.4%
s 187
 
5.6%
u 143
 
4.3%
l 116
 
3.5%
Other values (19) 496
14.9%
Uppercase Letter
ValueCountFrequency (%)
D 168
35.1%
P 90
18.8%
S 41
 
8.6%
H 40
 
8.4%
C 33
 
6.9%
A 26
 
5.4%
M 20
 
4.2%
O 12
 
2.5%
L 11
 
2.3%
E 8
 
1.7%
Other values (10) 30
 
6.3%
Other Punctuation
ValueCountFrequency (%)
/ 26
96.3%
. 1
 
3.7%
Decimal Number
ValueCountFrequency (%)
0 2
66.7%
4 1
33.3%
Space Separator
ValueCountFrequency (%)
98
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 3808
96.7%
Common 128
 
3.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 608
16.0%
c 430
11.3%
a 312
 
8.2%
e 291
 
7.6%
i 268
 
7.0%
n 266
 
7.0%
z 212
 
5.6%
s 187
 
4.9%
D 168
 
4.4%
u 143
 
3.8%
Other values (39) 923
24.2%
Common
ValueCountFrequency (%)
98
76.6%
/ 26
 
20.3%
0 2
 
1.6%
4 1
 
0.8%
. 1
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3892
98.9%
None 44
 
1.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o 608
15.6%
c 430
11.0%
a 312
 
8.0%
e 291
 
7.5%
i 268
 
6.9%
n 266
 
6.8%
z 212
 
5.4%
s 187
 
4.8%
D 168
 
4.3%
u 143
 
3.7%
Other values (39) 1007
25.9%
None
ValueCountFrequency (%)
ñ 26
59.1%
á 8
 
18.2%
í 6
 
13.6%
ó 3
 
6.8%
ú 1
 
2.3%

limpio_instancia
Categorical

IMBALANCE  MISSING 

Distinct13
Distinct (%)4.1%
Missing180
Missing (%)36.2%
Memory size4.0 KiB
CMAS
255 
Comité local
 
15
CAEV
 
12
Desconozco
 
9
Ninguno
 
8
Other values (8)
 
18

Length

Max length20
Median length4
Mean length4.864353312
Min length4

Characters and Unicode

Total characters1542
Distinct characters33
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)1.9%

Sample

1st rowDesconozco
2nd rowCMAS
3rd rowCMAS
4th rowCMAS
5th rowCMAS

Common Values

ValueCountFrequency (%)
CMAS 255
51.3%
Comité local 15
 
3.0%
CAEV 12
 
2.4%
Desconozco 9
 
1.8%
Ninguno 8
 
1.6%
CMAP 8
 
1.6%
Gestión Propia 4
 
0.8%
SAPAM 1
 
0.2%
Comité Local 1
 
0.2%
Organización vecinal 1
 
0.2%
Other values (3) 3
 
0.6%
(Missing) 180
36.2%

Length

2024-01-31T13:58:26.517947image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
cmas 255
75.2%
comité 16
 
4.7%
local 16
 
4.7%
caev 12
 
3.5%
desconozco 9
 
2.7%
ninguno 8
 
2.4%
cmap 8
 
2.4%
gestión 4
 
1.2%
propia 4
 
1.2%
sapam 1
 
0.3%
Other values (6) 6
 
1.8%

Most occurring characters

ValueCountFrequency (%)
C 293
19.0%
A 280
18.2%
M 264
17.1%
S 258
16.7%
o 71
 
4.6%
i 36
 
2.3%
c 36
 
2.3%
l 33
 
2.1%
n 32
 
2.1%
a 24
 
1.6%
Other values (23) 215
13.9%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 1163
75.4%
Lowercase Letter 355
 
23.0%
Space Separator 22
 
1.4%
Other Punctuation 2
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 71
20.0%
i 36
10.1%
c 36
10.1%
l 33
9.3%
n 32
9.0%
a 24
 
6.8%
t 20
 
5.6%
m 16
 
4.5%
é 16
 
4.5%
e 14
 
3.9%
Other values (8) 57
16.1%
Uppercase Letter
ValueCountFrequency (%)
C 293
25.2%
A 280
24.1%
M 264
22.7%
S 258
22.2%
P 14
 
1.2%
E 14
 
1.2%
V 12
 
1.0%
D 9
 
0.8%
N 9
 
0.8%
G 4
 
0.3%
Other values (3) 6
 
0.5%
Space Separator
ValueCountFrequency (%)
22
100.0%
Other Punctuation
ValueCountFrequency (%)
. 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1518
98.4%
Common 24
 
1.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
C 293
19.3%
A 280
18.4%
M 264
17.4%
S 258
17.0%
o 71
 
4.7%
i 36
 
2.4%
c 36
 
2.4%
l 33
 
2.2%
n 32
 
2.1%
a 24
 
1.6%
Other values (21) 191
12.6%
Common
ValueCountFrequency (%)
22
91.7%
. 2
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1521
98.6%
None 21
 
1.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
C 293
19.3%
A 280
18.4%
M 264
17.4%
S 258
17.0%
o 71
 
4.7%
i 36
 
2.4%
c 36
 
2.4%
l 33
 
2.2%
n 32
 
2.1%
a 24
 
1.6%
Other values (21) 194
12.8%
None
ValueCountFrequency (%)
é 16
76.2%
ó 5
 
23.8%

limpio_gasto_agua
Unsupported

REJECTED  UNSUPPORTED 

Missing3
Missing (%)0.6%
Memory size4.0 KiB

limpio_usos
Text

MISSING 

Distinct272
Distinct (%)57.1%
Missing21
Missing (%)4.2%
Memory size4.0 KiB
2024-01-31T13:58:27.029246image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Length

Max length79
Median length57
Mean length35.73739496
Min length4

Characters and Unicode

Total characters17011
Distinct characters29
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique199 ?
Unique (%)41.8%

Sample

1st rowLavar trastes/Limpieza de vivienda/Baño
2nd rowLimpieza de vivienda/Lavar ropa
3rd rowTodas
4th rowBaño/Lavar trastes/Lavar ropa
5th rowBaño/Lavar trastes/Lavar ropa
ValueCountFrequency (%)
de 231
 
14.8%
trastes/lavar 181
 
11.6%
lavar 162
 
10.4%
vivienda 106
 
6.8%
ropa 84
 
5.4%
plantas 46
 
3.0%
limpieza 46
 
3.0%
ropa/limpieza 45
 
2.9%
ducha/lavar 37
 
2.4%
trastes 31
 
2.0%
Other values (171) 589
37.8%
2024-01-31T13:58:28.040057image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 3059
18.0%
r 1391
 
8.2%
/ 1157
 
6.8%
e 1154
 
6.8%
1083
 
6.4%
i 1062
 
6.2%
v 1015
 
6.0%
L 790
 
4.6%
o 724
 
4.3%
s 673
 
4.0%
Other values (19) 4903
28.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 13139
77.2%
Uppercase Letter 1632
 
9.6%
Other Punctuation 1157
 
6.8%
Space Separator 1083
 
6.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 3059
23.3%
r 1391
10.6%
e 1154
 
8.8%
i 1062
 
8.1%
v 1015
 
7.7%
o 724
 
5.5%
s 673
 
5.1%
t 655
 
5.0%
p 560
 
4.3%
d 464
 
3.5%
Other values (10) 2382
18.1%
Uppercase Letter
ValueCountFrequency (%)
L 790
48.4%
B 319
19.5%
D 288
 
17.6%
C 154
 
9.4%
R 61
 
3.7%
M 16
 
1.0%
T 4
 
0.2%
Other Punctuation
ValueCountFrequency (%)
/ 1157
100.0%
Space Separator
ValueCountFrequency (%)
1083
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 14771
86.8%
Common 2240
 
13.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 3059
20.7%
r 1391
 
9.4%
e 1154
 
7.8%
i 1062
 
7.2%
v 1015
 
6.9%
L 790
 
5.3%
o 724
 
4.9%
s 673
 
4.6%
t 655
 
4.4%
p 560
 
3.8%
Other values (17) 3688
25.0%
Common
ValueCountFrequency (%)
/ 1157
51.7%
1083
48.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 16752
98.5%
None 259
 
1.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 3059
18.3%
r 1391
 
8.3%
/ 1157
 
6.9%
e 1154
 
6.9%
1083
 
6.5%
i 1062
 
6.3%
v 1015
 
6.1%
L 790
 
4.7%
o 724
 
4.3%
s 673
 
4.0%
Other values (18) 4644
27.7%
None
ValueCountFrequency (%)
ñ 259
100.0%
Distinct5
Distinct (%)1.0%
Missing1
Missing (%)0.2%
Memory size4.0 KiB
Buena
292 
Regular
108 
Excelente
77 
Mala
 
16
Inaceptable
 
3

Length

Max length11
Median length5
Mean length6.060483871
Min length4

Characters and Unicode

Total characters3006
Distinct characters17
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowRegular
2nd rowExcelente
3rd rowBuena
4th rowBuena
5th rowExcelente

Common Values

ValueCountFrequency (%)
Buena 292
58.8%
Regular 108
 
21.7%
Excelente 77
 
15.5%
Mala 16
 
3.2%
Inaceptable 3
 
0.6%
(Missing) 1
 
0.2%

Length

2024-01-31T13:58:28.566640image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-31T13:58:28.970846image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
buena 292
58.9%
regular 108
 
21.8%
excelente 77
 
15.5%
mala 16
 
3.2%
inaceptable 3
 
0.6%

Most occurring characters

ValueCountFrequency (%)
e 637
21.2%
a 438
14.6%
u 400
13.3%
n 372
12.4%
B 292
9.7%
l 204
 
6.8%
r 108
 
3.6%
g 108
 
3.6%
R 108
 
3.6%
c 80
 
2.7%
Other values (7) 259
8.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 2510
83.5%
Uppercase Letter 496
 
16.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 637
25.4%
a 438
17.5%
u 400
15.9%
n 372
14.8%
l 204
 
8.1%
r 108
 
4.3%
g 108
 
4.3%
c 80
 
3.2%
t 80
 
3.2%
x 77
 
3.1%
Other values (2) 6
 
0.2%
Uppercase Letter
ValueCountFrequency (%)
B 292
58.9%
R 108
 
21.8%
E 77
 
15.5%
M 16
 
3.2%
I 3
 
0.6%

Most occurring scripts

ValueCountFrequency (%)
Latin 3006
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 637
21.2%
a 438
14.6%
u 400
13.3%
n 372
12.4%
B 292
9.7%
l 204
 
6.8%
r 108
 
3.6%
g 108
 
3.6%
R 108
 
3.6%
c 80
 
2.7%
Other values (7) 259
8.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3006
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 637
21.2%
a 438
14.6%
u 400
13.3%
n 372
12.4%
B 292
9.7%
l 204
 
6.8%
r 108
 
3.6%
g 108
 
3.6%
R 108
 
3.6%
c 80
 
2.7%
Other values (7) 259
8.6%
Distinct2
Distinct (%)0.4%
Missing1
Missing (%)0.2%
Memory size4.0 KiB
No
419 
77 

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters992
Distinct characters4
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo

Common Values

ValueCountFrequency (%)
No 419
84.3%
77
 
15.5%
(Missing) 1
 
0.2%

Length

2024-01-31T13:58:29.227825image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-31T13:58:29.369898image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
no 419
84.5%
77
 
15.5%

Most occurring characters

ValueCountFrequency (%)
N 419
42.2%
o 419
42.2%
S 77
 
7.8%
í 77
 
7.8%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 496
50.0%
Lowercase Letter 496
50.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
N 419
84.5%
S 77
 
15.5%
Lowercase Letter
ValueCountFrequency (%)
o 419
84.5%
í 77
 
15.5%

Most occurring scripts

ValueCountFrequency (%)
Latin 992
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 419
42.2%
o 419
42.2%
S 77
 
7.8%
í 77
 
7.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 915
92.2%
None 77
 
7.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 419
45.8%
o 419
45.8%
S 77
 
8.4%
None
ValueCountFrequency (%)
í 77
100.0%

limpio_agua_beber
Categorical

IMBALANCE 

Distinct13
Distinct (%)2.6%
Missing1
Missing (%)0.2%
Memory size4.0 KiB
Garrafón/Embotellada
338 
De la llave con filtro
111 
Directa de la llave
 
21
Hervida
 
12
Del Manantial
 
3
Other values (8)
 
11

Length

Max length33
Median length20
Mean length20.06653226
Min length7

Characters and Unicode

Total characters9953
Distinct characters34
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)1.2%

Sample

1st rowGarrafón/Embotellada
2nd rowGarrafón/Embotellada
3rd rowGarrafón/Embotellada
4th rowGarrafón/Embotellada
5th rowDe la llave con filtro

Common Values

ValueCountFrequency (%)
Garrafón/Embotellada 338
68.0%
De la llave con filtro 111
 
22.3%
Directa de la llave 21
 
4.2%
Hervida 12
 
2.4%
Del Manantial 3
 
0.6%
Garrafón 3
 
0.6%
Cisterna de recolección 2
 
0.4%
Garrafón/Tratamiento al agua 1
 
0.2%
Plata coloidal/Serpentín de cobre 1
 
0.2%
Uso ozonificador 1
 
0.2%
Other values (3) 3
 
0.6%

Length

2024-01-31T13:58:29.574018image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
garrafón/embotellada 338
33.1%
de 137
13.4%
la 132
 
12.9%
llave 132
 
12.9%
con 111
 
10.9%
filtro 111
 
10.9%
directa 21
 
2.1%
hervida 12
 
1.2%
del 4
 
0.4%
manantial 3
 
0.3%
Other values (15) 20
 
2.0%

Most occurring characters

ValueCountFrequency (%)
a 1686
16.9%
l 1197
12.0%
r 839
 
8.4%
e 658
 
6.6%
o 573
 
5.8%
548
 
5.5%
t 482
 
4.8%
n 471
 
4.7%
f 455
 
4.6%
d 380
 
3.8%
Other values (24) 2664
26.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 8224
82.6%
Uppercase Letter 840
 
8.4%
Space Separator 548
 
5.5%
Other Punctuation 341
 
3.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 1686
20.5%
l 1197
14.6%
r 839
10.2%
e 658
 
8.0%
o 573
 
7.0%
t 482
 
5.9%
n 471
 
5.7%
f 455
 
5.5%
d 380
 
4.6%
ó 345
 
4.2%
Other values (11) 1138
13.8%
Uppercase Letter
ValueCountFrequency (%)
G 343
40.8%
E 338
40.2%
D 136
 
16.2%
H 13
 
1.5%
M 3
 
0.4%
C 2
 
0.2%
T 1
 
0.1%
P 1
 
0.1%
S 1
 
0.1%
U 1
 
0.1%
Space Separator
ValueCountFrequency (%)
548
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 341
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 9064
91.1%
Common 889
 
8.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 1686
18.6%
l 1197
13.2%
r 839
9.3%
e 658
 
7.3%
o 573
 
6.3%
t 482
 
5.3%
n 471
 
5.2%
f 455
 
5.0%
d 380
 
4.2%
ó 345
 
3.8%
Other values (22) 1978
21.8%
Common
ValueCountFrequency (%)
548
61.6%
/ 341
38.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 9607
96.5%
None 346
 
3.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 1686
17.5%
l 1197
12.5%
r 839
 
8.7%
e 658
 
6.8%
o 573
 
6.0%
548
 
5.7%
t 482
 
5.0%
n 471
 
4.9%
f 455
 
4.7%
d 380
 
4.0%
Other values (22) 2318
24.1%
None
ValueCountFrequency (%)
ó 345
99.7%
í 1
 
0.3%
Distinct5
Distinct (%)1.0%
Missing1
Missing (%)0.2%
Memory size4.0 KiB
Lo justo
273 
Mucho
101 
Poco
89 
Nada
 
27
No puedo pagarlo
 
6

Length

Max length16
Median length8
Mean length6.550403226
Min length4

Characters and Unicode

Total characters3249
Distinct characters19
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowLo justo
2nd rowNada
3rd rowPoco
4th rowLo justo
5th rowMucho

Common Values

ValueCountFrequency (%)
Lo justo 273
54.9%
Mucho 101
 
20.3%
Poco 89
 
17.9%
Nada 27
 
5.4%
No puedo pagarlo 6
 
1.2%
(Missing) 1
 
0.2%

Length

2024-01-31T13:58:29.750601image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-31T13:58:30.017144image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
lo 273
35.0%
justo 273
35.0%
mucho 101
 
12.9%
poco 89
 
11.4%
nada 27
 
3.5%
no 6
 
0.8%
puedo 6
 
0.8%
pagarlo 6
 
0.8%

Most occurring characters

ValueCountFrequency (%)
o 843
25.9%
u 380
11.7%
285
 
8.8%
L 273
 
8.4%
j 273
 
8.4%
s 273
 
8.4%
t 273
 
8.4%
c 190
 
5.8%
h 101
 
3.1%
M 101
 
3.1%
Other values (9) 257
 
7.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 2468
76.0%
Uppercase Letter 496
 
15.3%
Space Separator 285
 
8.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 843
34.2%
u 380
15.4%
j 273
 
11.1%
s 273
 
11.1%
t 273
 
11.1%
c 190
 
7.7%
h 101
 
4.1%
a 66
 
2.7%
d 33
 
1.3%
p 12
 
0.5%
Other values (4) 24
 
1.0%
Uppercase Letter
ValueCountFrequency (%)
L 273
55.0%
M 101
 
20.4%
P 89
 
17.9%
N 33
 
6.7%
Space Separator
ValueCountFrequency (%)
285
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 2964
91.2%
Common 285
 
8.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 843
28.4%
u 380
12.8%
L 273
 
9.2%
j 273
 
9.2%
s 273
 
9.2%
t 273
 
9.2%
c 190
 
6.4%
h 101
 
3.4%
M 101
 
3.4%
P 89
 
3.0%
Other values (8) 168
 
5.7%
Common
ValueCountFrequency (%)
285
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3249
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o 843
25.9%
u 380
11.7%
285
 
8.8%
L 273
 
8.4%
j 273
 
8.4%
s 273
 
8.4%
t 273
 
8.4%
c 190
 
5.8%
h 101
 
3.1%
M 101
 
3.1%
Other values (9) 257
 
7.9%

limpio_freq_pago
Categorical

IMBALANCE 

Distinct9
Distinct (%)1.8%
Missing1
Missing (%)0.2%
Memory size4.0 KiB
Mensual
253 
Anual
193 
No pago
40 
Bimestral
 
5
Desconozco
 
1
Other values (4)
 
4

Length

Max length33
Median length7
Mean length6.33266129
Min length5

Characters and Unicode

Total characters3141
Distinct characters31
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)1.0%

Sample

1st rowAnual
2nd rowMensual
3rd rowMensual
4th rowMensual
5th rowMensual

Common Values

ValueCountFrequency (%)
Mensual 253
50.9%
Anual 193
38.8%
No pago 40
 
8.0%
Bimestral 5
 
1.0%
Desconozco 1
 
0.2%
Semanal 1
 
0.2%
Semestral 1
 
0.2%
Pagos de conexión y acequibilidad 1
 
0.2%
Cooperación al comité 1
 
0.2%
(Missing) 1
 
0.2%

Length

2024-01-31T13:58:30.407155image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-31T13:58:30.750330image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
mensual 253
46.7%
anual 193
35.6%
no 40
 
7.4%
pago 40
 
7.4%
bimestral 5
 
0.9%
desconozco 1
 
0.2%
semanal 1
 
0.2%
semestral 1
 
0.2%
pagos 1
 
0.2%
de 1
 
0.2%
Other values (6) 6
 
1.1%

Most occurring characters

ValueCountFrequency (%)
a 499
15.9%
l 455
14.5%
n 451
14.4%
u 447
14.2%
e 266
8.5%
s 261
8.3%
M 253
8.1%
A 193
 
6.1%
o 88
 
2.8%
46
 
1.5%
Other values (21) 182
 
5.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 2599
82.7%
Uppercase Letter 496
 
15.8%
Space Separator 46
 
1.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 499
19.2%
l 455
17.5%
n 451
17.4%
u 447
17.2%
e 266
10.2%
s 261
10.0%
o 88
 
3.4%
p 41
 
1.6%
g 41
 
1.6%
i 11
 
0.4%
Other values (12) 39
 
1.5%
Uppercase Letter
ValueCountFrequency (%)
M 253
51.0%
A 193
38.9%
N 40
 
8.1%
B 5
 
1.0%
S 2
 
0.4%
D 1
 
0.2%
P 1
 
0.2%
C 1
 
0.2%
Space Separator
ValueCountFrequency (%)
46
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 3095
98.5%
Common 46
 
1.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 499
16.1%
l 455
14.7%
n 451
14.6%
u 447
14.4%
e 266
8.6%
s 261
8.4%
M 253
8.2%
A 193
 
6.2%
o 88
 
2.8%
p 41
 
1.3%
Other values (20) 141
 
4.6%
Common
ValueCountFrequency (%)
46
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3138
99.9%
None 3
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 499
15.9%
l 455
14.5%
n 451
14.4%
u 447
14.2%
e 266
8.5%
s 261
8.3%
M 253
8.1%
A 193
 
6.2%
o 88
 
2.8%
46
 
1.5%
Other values (19) 179
 
5.7%
None
ValueCountFrequency (%)
ó 2
66.7%
é 1
33.3%

limpio_entidad_pago
Categorical

IMBALANCE 

Distinct5
Distinct (%)1.0%
Missing3
Missing (%)0.6%
Memory size4.0 KiB
CMAS
398 
Está incluido en el pago de mi renta
 
37
Comité local
 
34
No pago
 
24
Desconozco
 
1

Length

Max length36
Median length4
Mean length7.105263158
Min length4

Characters and Unicode

Total characters3510
Distinct characters26
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)0.2%

Sample

1st rowCMAS
2nd rowCMAS
3rd rowCMAS
4th rowCMAS
5th rowCMAS

Common Values

ValueCountFrequency (%)
CMAS 398
80.1%
Está incluido en el pago de mi renta 37
 
7.4%
Comité local 34
 
6.8%
No pago 24
 
4.8%
Desconozco 1
 
0.2%
(Missing) 3
 
0.6%

Length

2024-01-31T13:58:30.999806image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-31T13:58:31.169854image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
cmas 398
49.1%
pago 61
 
7.5%
está 37
 
4.6%
incluido 37
 
4.6%
en 37
 
4.6%
el 37
 
4.6%
de 37
 
4.6%
mi 37
 
4.6%
renta 37
 
4.6%
comité 34
 
4.2%
Other values (3) 59
 
7.3%

Most occurring characters

ValueCountFrequency (%)
C 432
12.3%
A 398
11.3%
S 398
11.3%
M 398
11.3%
317
 
9.0%
o 193
 
5.5%
e 149
 
4.2%
i 145
 
4.1%
l 142
 
4.0%
a 132
 
3.8%
Other values (16) 806
23.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 1688
48.1%
Lowercase Letter 1505
42.9%
Space Separator 317
 
9.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 193
12.8%
e 149
9.9%
i 145
9.6%
l 142
9.4%
a 132
8.8%
n 112
 
7.4%
t 108
 
7.2%
d 74
 
4.9%
c 73
 
4.9%
m 71
 
4.7%
Other values (8) 306
20.3%
Uppercase Letter
ValueCountFrequency (%)
C 432
25.6%
A 398
23.6%
S 398
23.6%
M 398
23.6%
E 37
 
2.2%
N 24
 
1.4%
D 1
 
0.1%
Space Separator
ValueCountFrequency (%)
317
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 3193
91.0%
Common 317
 
9.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
C 432
13.5%
A 398
12.5%
S 398
12.5%
M 398
12.5%
o 193
 
6.0%
e 149
 
4.7%
i 145
 
4.5%
l 142
 
4.4%
a 132
 
4.1%
n 112
 
3.5%
Other values (15) 694
21.7%
Common
ValueCountFrequency (%)
317
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3439
98.0%
None 71
 
2.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
C 432
12.6%
A 398
11.6%
S 398
11.6%
M 398
11.6%
317
9.2%
o 193
 
5.6%
e 149
 
4.3%
i 145
 
4.2%
l 142
 
4.1%
a 132
 
3.8%
Other values (14) 735
21.4%
None
ValueCountFrequency (%)
á 37
52.1%
é 34
47.9%
Distinct2
Distinct (%)0.4%
Missing1
Missing (%)0.2%
Memory size4.0 KiB
No
312 
184 

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters992
Distinct characters4
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row
2nd row
3rd row
4th row
5th row

Common Values

ValueCountFrequency (%)
No 312
62.8%
184
37.0%
(Missing) 1
 
0.2%

Length

2024-01-31T13:58:31.473353image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-31T13:58:31.763414image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
no 312
62.9%
184
37.1%

Most occurring characters

ValueCountFrequency (%)
N 312
31.5%
o 312
31.5%
S 184
18.5%
í 184
18.5%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 496
50.0%
Lowercase Letter 496
50.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
N 312
62.9%
S 184
37.1%
Lowercase Letter
ValueCountFrequency (%)
o 312
62.9%
í 184
37.1%

Most occurring scripts

ValueCountFrequency (%)
Latin 992
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 312
31.5%
o 312
31.5%
S 184
18.5%
í 184
18.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 808
81.5%
None 184
 
18.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 312
38.6%
o 312
38.6%
S 184
22.8%
None
ValueCountFrequency (%)
í 184
100.0%

limpio_negativa_visita
Categorical

MISSING 

Distinct22
Distinct (%)7.5%
Missing202
Missing (%)40.6%
Memory size4.0 KiB
Desconozco cuál es
107 
No está cerca
47 
Por falta de tiempo
35 
Está contaminado
27 
No estoy interesado
20 
Other values (17)
59 

Length

Max length56
Median length42
Mean length16.9220339
Min length6

Characters and Unicode

Total characters4992
Distinct characters35
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique11 ?
Unique (%)3.7%

Sample

1st rowDesconozco cuál es
2nd rowDesconozco cuál es
3rd rowDesconozco cuál es
4th rowEstá en Propiedad Privada
5th rowNo está cerca

Common Values

ValueCountFrequency (%)
Desconozco cuál es 107
21.5%
No está cerca 47
 
9.5%
Por falta de tiempo 35
 
7.0%
Está contaminado 27
 
5.4%
No estoy interesado 20
 
4.0%
Falta de tiempo 15
 
3.0%
No lo había pensado 9
 
1.8%
Difícil acceso 9
 
1.8%
No hay 8
 
1.6%
Zona insegura 5
 
1.0%
Other values (12) 13
 
2.6%
(Missing) 202
40.6%

Length

2024-01-31T13:58:32.150234image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
es 108
12.1%
desconozco 107
12.0%
cuál 107
12.0%
no 86
9.6%
está 79
8.9%
de 52
 
5.8%
falta 50
 
5.6%
tiempo 50
 
5.6%
cerca 47
 
5.3%
por 35
 
3.9%
Other values (36) 171
19.2%

Most occurring characters

ValueCountFrequency (%)
o 643
12.9%
597
12.0%
e 515
10.3%
c 487
9.8%
s 373
 
7.5%
a 311
 
6.2%
t 260
 
5.2%
n 224
 
4.5%
á 190
 
3.8%
l 182
 
3.6%
Other values (25) 1210
24.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 4080
81.7%
Space Separator 597
 
12.0%
Uppercase Letter 309
 
6.2%
Other Punctuation 6
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 643
15.8%
e 515
12.6%
c 487
11.9%
s 373
9.1%
a 311
7.6%
t 260
 
6.4%
n 224
 
5.5%
á 190
 
4.7%
l 182
 
4.5%
i 141
 
3.5%
Other values (14) 754
18.5%
Uppercase Letter
ValueCountFrequency (%)
D 118
38.2%
N 86
27.8%
P 41
 
13.3%
E 36
 
11.7%
F 15
 
4.9%
Z 7
 
2.3%
S 3
 
1.0%
A 2
 
0.6%
Y 1
 
0.3%
Space Separator
ValueCountFrequency (%)
597
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 4389
87.9%
Common 603
 
12.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 643
14.7%
e 515
11.7%
c 487
11.1%
s 373
 
8.5%
a 311
 
7.1%
t 260
 
5.9%
n 224
 
5.1%
á 190
 
4.3%
l 182
 
4.1%
i 141
 
3.2%
Other values (23) 1063
24.2%
Common
ValueCountFrequency (%)
597
99.0%
/ 6
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4781
95.8%
None 211
 
4.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o 643
13.4%
597
12.5%
e 515
10.8%
c 487
10.2%
s 373
 
7.8%
a 311
 
6.5%
t 260
 
5.4%
n 224
 
4.7%
l 182
 
3.8%
i 141
 
2.9%
Other values (22) 1048
21.9%
None
ValueCountFrequency (%)
á 190
90.0%
í 20
 
9.5%
ú 1
 
0.5%
Distinct63
Distinct (%)36.2%
Missing323
Missing (%)65.0%
Memory size4.0 KiB
2024-01-31T13:58:32.543405image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Length

Max length41
Median length36
Mean length22.97126437
Min length5

Characters and Unicode

Total characters3997
Distinct characters40
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique38 ?
Unique (%)21.8%

Sample

1st rowRealizar limpieza
2nd rowActividad recreativa
3rd rowMonitorear su estado/Una vez al mes
4th rowActividad recreativa
5th rowActividad recreativa/Cada dos meses
ValueCountFrequency (%)
actividad 82
18.9%
recreativa 41
 
9.4%
traslado 18
 
4.1%
veces 18
 
4.1%
por 17
 
3.9%
semana 16
 
3.7%
monitorear 16
 
3.7%
su 16
 
3.7%
al 15
 
3.4%
cotidiano 13
 
3.0%
Other values (64) 183
42.1%
2024-01-31T13:58:34.043132image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 538
13.5%
e 455
11.4%
i 375
 
9.4%
t 299
 
7.5%
r 269
 
6.7%
261
 
6.5%
d 251
 
6.3%
c 222
 
5.6%
v 194
 
4.9%
n 179
 
4.5%
Other values (30) 954
23.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 3424
85.7%
Space Separator 261
 
6.5%
Uppercase Letter 243
 
6.1%
Other Punctuation 69
 
1.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 538
15.7%
e 455
13.3%
i 375
11.0%
t 299
8.7%
r 269
7.9%
d 251
7.3%
c 222
6.5%
v 194
 
5.7%
n 179
 
5.2%
o 172
 
5.0%
Other values (13) 470
13.7%
Uppercase Letter
ValueCountFrequency (%)
A 85
35.0%
M 36
14.8%
T 24
 
9.9%
D 24
 
9.9%
C 22
 
9.1%
F 11
 
4.5%
P 9
 
3.7%
S 8
 
3.3%
R 8
 
3.3%
U 7
 
2.9%
Other values (4) 9
 
3.7%
Other Punctuation
ValueCountFrequency (%)
/ 65
94.2%
, 4
 
5.8%
Space Separator
ValueCountFrequency (%)
261
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 3667
91.7%
Common 330
 
8.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 538
14.7%
e 455
12.4%
i 375
10.2%
t 299
8.2%
r 269
 
7.3%
d 251
 
6.8%
c 222
 
6.1%
v 194
 
5.3%
n 179
 
4.9%
o 172
 
4.7%
Other values (27) 713
19.4%
Common
ValueCountFrequency (%)
261
79.1%
/ 65
 
19.7%
, 4
 
1.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3970
99.3%
None 27
 
0.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 538
13.6%
e 455
11.5%
i 375
9.4%
t 299
 
7.5%
r 269
 
6.8%
261
 
6.6%
d 251
 
6.3%
c 222
 
5.6%
v 194
 
4.9%
n 179
 
4.5%
Other values (27) 927
23.4%
None
ValueCountFrequency (%)
ó 17
63.0%
ñ 9
33.3%
í 1
 
3.7%
Distinct16
Distinct (%)3.2%
Missing1
Missing (%)0.2%
Memory size4.0 KiB
Río
247 
No lo sé
119 
Arroyo
45 
Manantial
34 
Lago
26 
Other values (11)
25 

Length

Max length25
Median length15
Mean length5.316532258
Min length3

Characters and Unicode

Total characters2637
Distinct characters32
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique6 ?
Unique (%)1.2%

Sample

1st rowRío
2nd rowRío
3rd rowManantial
4th rowRío
5th rowRío

Common Values

ValueCountFrequency (%)
Río 247
49.7%
No lo sé 119
23.9%
Arroyo 45
 
9.1%
Manantial 34
 
6.8%
Lago 26
 
5.2%
Lago artificial 6
 
1.2%
Laguna 5
 
1.0%
Nacimiento 4
 
0.8%
Pozo 2
 
0.4%
Aguas negras 2
 
0.4%
Other values (6) 6
 
1.2%

Length

2024-01-31T13:58:34.543066image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
río 247
33.0%
lo 119
15.9%
119
15.9%
no 119
15.9%
arroyo 45
 
6.0%
manantial 34
 
4.5%
lago 33
 
4.4%
artificial 7
 
0.9%
laguna 6
 
0.8%
nacimiento 4
 
0.5%
Other values (10) 15
 
2.0%

Most occurring characters

ValueCountFrequency (%)
o 620
23.5%
252
9.6%
R 247
 
9.4%
í 247
 
9.4%
a 174
 
6.6%
l 160
 
6.1%
s 126
 
4.8%
N 123
 
4.7%
é 119
 
4.5%
r 104
 
3.9%
Other values (22) 465
17.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1887
71.6%
Uppercase Letter 497
 
18.8%
Space Separator 252
 
9.6%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 620
32.9%
í 247
 
13.1%
a 174
 
9.2%
l 160
 
8.5%
s 126
 
6.7%
é 119
 
6.3%
r 104
 
5.5%
n 81
 
4.3%
i 65
 
3.4%
t 47
 
2.5%
Other values (11) 144
 
7.6%
Uppercase Letter
ValueCountFrequency (%)
R 247
49.7%
N 123
24.7%
A 47
 
9.5%
L 39
 
7.8%
M 34
 
6.8%
P 3
 
0.6%
E 2
 
0.4%
C 1
 
0.2%
O 1
 
0.2%
Space Separator
ValueCountFrequency (%)
252
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 2384
90.4%
Common 253
 
9.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 620
26.0%
R 247
 
10.4%
í 247
 
10.4%
a 174
 
7.3%
l 160
 
6.7%
s 126
 
5.3%
N 123
 
5.2%
é 119
 
5.0%
r 104
 
4.4%
n 81
 
3.4%
Other values (20) 383
16.1%
Common
ValueCountFrequency (%)
252
99.6%
, 1
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2271
86.1%
None 366
 
13.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o 620
27.3%
252
11.1%
R 247
 
10.9%
a 174
 
7.7%
l 160
 
7.0%
s 126
 
5.5%
N 123
 
5.4%
r 104
 
4.6%
n 81
 
3.6%
i 65
 
2.9%
Other values (20) 319
14.0%
None
ValueCountFrequency (%)
í 247
67.5%
é 119
32.5%
Distinct102
Distinct (%)27.4%
Missing125
Missing (%)25.2%
Memory size4.0 KiB
2024-01-31T13:58:35.022848image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Length

Max length43
Median length37
Mean length9.846774194
Min length3

Characters and Unicode

Total characters3663
Distinct characters55
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique72 ?
Unique (%)19.4%

Sample

1st rowSedeño
2nd rowPixquiac
3rd rowManantial Lagunilla
4th rowSedeño
5th rowPixquiac
ValueCountFrequency (%)
desconozco 68
 
13.0%
pixquiac 66
 
12.6%
sedeño 57
 
10.9%
los 25
 
4.8%
lagos 24
 
4.6%
la 20
 
3.8%
de 14
 
2.7%
el 14
 
2.7%
del 10
 
1.9%
carneros 9
 
1.7%
Other values (123) 216
41.3%
2024-01-31T13:58:35.929063image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
o 474
 
12.9%
a 383
 
10.5%
e 289
 
7.9%
c 254
 
6.9%
i 226
 
6.2%
219
 
6.0%
s 182
 
5.0%
n 179
 
4.9%
d 108
 
2.9%
l 108
 
2.9%
Other values (45) 1241
33.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 2932
80.0%
Uppercase Letter 496
 
13.5%
Space Separator 219
 
6.0%
Other Punctuation 16
 
0.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 474
16.2%
a 383
13.1%
e 289
9.9%
c 254
8.7%
i 226
 
7.7%
s 182
 
6.2%
n 179
 
6.1%
d 108
 
3.7%
l 108
 
3.7%
u 107
 
3.6%
Other values (19) 622
21.2%
Uppercase Letter
ValueCountFrequency (%)
P 90
18.1%
L 88
17.7%
S 79
15.9%
D 68
13.7%
C 49
9.9%
M 20
 
4.0%
A 20
 
4.0%
E 19
 
3.8%
T 11
 
2.2%
Á 8
 
1.6%
Other values (13) 44
8.9%
Other Punctuation
ValueCountFrequency (%)
/ 15
93.8%
, 1
 
6.2%
Space Separator
ValueCountFrequency (%)
219
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 3428
93.6%
Common 235
 
6.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 474
13.8%
a 383
 
11.2%
e 289
 
8.4%
c 254
 
7.4%
i 226
 
6.6%
s 182
 
5.3%
n 179
 
5.2%
d 108
 
3.2%
l 108
 
3.2%
u 107
 
3.1%
Other values (42) 1118
32.6%
Common
ValueCountFrequency (%)
219
93.2%
/ 15
 
6.4%
, 1
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3583
97.8%
None 80
 
2.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o 474
13.2%
a 383
 
10.7%
e 289
 
8.1%
c 254
 
7.1%
i 226
 
6.3%
219
 
6.1%
s 182
 
5.1%
n 179
 
5.0%
d 108
 
3.0%
l 108
 
3.0%
Other values (38) 1161
32.4%
None
ValueCountFrequency (%)
ñ 62
77.5%
Á 8
 
10.0%
í 3
 
3.8%
á 3
 
3.8%
ó 2
 
2.5%
ü 1
 
1.2%
Í 1
 
1.2%
Distinct7
Distinct (%)1.4%
Missing1
Missing (%)0.2%
Memory size4.0 KiB
No
332 
Tal vez
114 
43 
No lo sé
 
4
Algunos
 
1
Other values (2)
 
2

Length

Max length15
Median length2
Mean length3.237903226
Min length2

Characters and Unicode

Total characters1606
Distinct characters22
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3 ?
Unique (%)0.6%

Sample

1st rowNo
2nd rowAlgunos
3rd rowNo
4th rowTal vez
5th rowNo

Common Values

ValueCountFrequency (%)
No 332
66.8%
Tal vez 114
 
22.9%
43
 
8.7%
No lo sé 4
 
0.8%
Algunos 1
 
0.2%
Sí, los urbanos 1
 
0.2%
Casi 1
 
0.2%
(Missing) 1
 
0.2%

Length

2024-01-31T13:58:36.336373image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-31T13:58:36.656676image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
no 336
54.2%
tal 114
 
18.4%
vez 114
 
18.4%
44
 
7.1%
lo 4
 
0.6%
4
 
0.6%
algunos 1
 
0.2%
los 1
 
0.2%
urbanos 1
 
0.2%
casi 1
 
0.2%

Most occurring characters

ValueCountFrequency (%)
o 343
21.4%
N 336
20.9%
124
 
7.7%
l 120
 
7.5%
a 116
 
7.2%
T 114
 
7.1%
v 114
 
7.1%
e 114
 
7.1%
z 114
 
7.1%
S 44
 
2.7%
Other values (12) 67
 
4.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 985
61.3%
Uppercase Letter 496
30.9%
Space Separator 124
 
7.7%
Other Punctuation 1
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 343
34.8%
l 120
 
12.2%
a 116
 
11.8%
v 114
 
11.6%
e 114
 
11.6%
z 114
 
11.6%
í 44
 
4.5%
s 8
 
0.8%
é 4
 
0.4%
u 2
 
0.2%
Other values (5) 6
 
0.6%
Uppercase Letter
ValueCountFrequency (%)
N 336
67.7%
T 114
 
23.0%
S 44
 
8.9%
A 1
 
0.2%
C 1
 
0.2%
Space Separator
ValueCountFrequency (%)
124
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1481
92.2%
Common 125
 
7.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 343
23.2%
N 336
22.7%
l 120
 
8.1%
a 116
 
7.8%
T 114
 
7.7%
v 114
 
7.7%
e 114
 
7.7%
z 114
 
7.7%
S 44
 
3.0%
í 44
 
3.0%
Other values (10) 22
 
1.5%
Common
ValueCountFrequency (%)
124
99.2%
, 1
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1558
97.0%
None 48
 
3.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o 343
22.0%
N 336
21.6%
124
 
8.0%
l 120
 
7.7%
a 116
 
7.4%
T 114
 
7.3%
v 114
 
7.3%
e 114
 
7.3%
z 114
 
7.3%
S 44
 
2.8%
Other values (10) 19
 
1.2%
None
ValueCountFrequency (%)
í 44
91.7%
é 4
 
8.3%

limpio_tipo_baño
Categorical

IMBALANCE 

Distinct11
Distinct (%)2.2%
Missing1
Missing (%)0.2%
Memory size4.0 KiB
Baño (taza) de agua integrado a la casa
427 
Baño seco incorporado a la casa
 
26
Baño (taza) de cubeta en interior
 
23
Baño seco en exterior
 
6
Baño (taza) de cubeta en exterior (caseta)
 
4
Other values (6)
 
10

Length

Max length71
Median length39
Mean length37.87096774
Min length10

Characters and Unicode

Total characters18784
Distinct characters29
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique4 ?
Unique (%)0.8%

Sample

1st rowBaño (taza) de agua integrado a la casa
2nd rowBaño (taza) de agua integrado a la casa
3rd rowBaño (taza) de agua integrado a la casa
4th rowBaño (taza) de agua integrado a la casa
5th rowBaño (taza) de agua integrado a la casa

Common Values

ValueCountFrequency (%)
Baño (taza) de agua integrado a la casa 427
85.9%
Baño seco incorporado a la casa 26
 
5.2%
Baño (taza) de cubeta en interior 23
 
4.6%
Baño seco en exterior 6
 
1.2%
Baño (taza) de cubeta en exterior (caseta) 4
 
0.8%
Desconozco 3
 
0.6%
Letrina en exterior 3
 
0.6%
Biodigestor, Pozo de absorción 1
 
0.2%
No tengo baño 1
 
0.2%
Baño (taza) de agua integrado a la casa pero con uso de cubeta externa 1
 
0.2%

Length

2024-01-31T13:58:37.019295image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
baño 489
12.8%
de 458
12.0%
taza 456
12.0%
a 456
12.0%
la 456
12.0%
casa 455
11.9%
agua 429
11.3%
integrado 429
11.3%
en 36
 
0.9%
seco 33
 
0.9%
Other values (17) 111
 
2.9%

Most occurring characters

ValueCountFrequency (%)
a 4581
24.4%
3313
17.6%
o 1088
 
5.8%
e 1048
 
5.6%
t 959
 
5.1%
d 915
 
4.9%
g 860
 
4.6%
r 562
 
3.0%
c 556
 
3.0%
n 525
 
2.8%
Other values (19) 4377
23.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 14051
74.8%
Space Separator 3313
 
17.6%
Uppercase Letter 498
 
2.7%
Close Punctuation 460
 
2.4%
Open Punctuation 460
 
2.4%
Other Punctuation 2
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 4581
32.6%
o 1088
 
7.7%
e 1048
 
7.5%
t 959
 
6.8%
d 915
 
6.5%
g 860
 
6.1%
r 562
 
4.0%
c 556
 
4.0%
n 525
 
3.7%
i 521
 
3.7%
Other values (9) 2436
17.3%
Uppercase Letter
ValueCountFrequency (%)
B 490
98.4%
D 3
 
0.6%
L 3
 
0.6%
P 1
 
0.2%
N 1
 
0.2%
Other Punctuation
ValueCountFrequency (%)
, 1
50.0%
/ 1
50.0%
Space Separator
ValueCountFrequency (%)
3313
100.0%
Close Punctuation
ValueCountFrequency (%)
) 460
100.0%
Open Punctuation
ValueCountFrequency (%)
( 460
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 14549
77.5%
Common 4235
 
22.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 4581
31.5%
o 1088
 
7.5%
e 1048
 
7.2%
t 959
 
6.6%
d 915
 
6.3%
g 860
 
5.9%
r 562
 
3.9%
c 556
 
3.8%
n 525
 
3.6%
i 521
 
3.6%
Other values (14) 2934
20.2%
Common
ValueCountFrequency (%)
3313
78.2%
) 460
 
10.9%
( 460
 
10.9%
, 1
 
< 0.1%
/ 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 18293
97.4%
None 491
 
2.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 4581
25.0%
3313
18.1%
o 1088
 
5.9%
e 1048
 
5.7%
t 959
 
5.2%
d 915
 
5.0%
g 860
 
4.7%
r 562
 
3.1%
c 556
 
3.0%
n 525
 
2.9%
Other values (17) 3886
21.2%
None
ValueCountFrequency (%)
ñ 490
99.8%
ó 1
 
0.2%

limpio_seguridad_baño
Categorical

MISSING 

Distinct2
Distinct (%)5.6%
Missing461
Missing (%)92.8%
Memory size4.0 KiB
Si
21 
No
15 

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters72
Distinct characters4
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowSi
2nd rowNo
3rd rowSi
4th rowNo
5th rowNo

Common Values

ValueCountFrequency (%)
Si 21
 
4.2%
No 15
 
3.0%
(Missing) 461
92.8%

Length

2024-01-31T13:58:37.345088image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-31T13:58:37.612472image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
si 21
58.3%
no 15
41.7%

Most occurring characters

ValueCountFrequency (%)
S 21
29.2%
i 21
29.2%
N 15
20.8%
o 15
20.8%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 36
50.0%
Lowercase Letter 36
50.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
S 21
58.3%
N 15
41.7%
Lowercase Letter
ValueCountFrequency (%)
i 21
58.3%
o 15
41.7%

Most occurring scripts

ValueCountFrequency (%)
Latin 72
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
S 21
29.2%
i 21
29.2%
N 15
20.8%
o 15
20.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 72
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
S 21
29.2%
i 21
29.2%
N 15
20.8%
o 15
20.8%
Distinct5
Distinct (%)1.0%
Missing1
Missing (%)0.2%
Memory size4.0 KiB
Si
292 
No
199 
Yo soy responsable
 
2
No estoy segura
 
2
No hay responsable
 
1

Length

Max length18
Median length2
Mean length2.149193548
Min length2

Characters and Unicode

Total characters1066
Distinct characters19
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)0.2%

Sample

1st rowNo
2nd rowSi
3rd rowSi
4th rowSi
5th rowSi

Common Values

ValueCountFrequency (%)
Si 292
58.8%
No 199
40.0%
Yo soy responsable 2
 
0.4%
No estoy segura 2
 
0.4%
No hay responsable 1
 
0.2%
(Missing) 1
 
0.2%

Length

2024-01-31T13:58:37.848385image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-31T13:58:38.031255image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
si 292
57.7%
no 202
39.9%
responsable 3
 
0.6%
yo 2
 
0.4%
soy 2
 
0.4%
estoy 2
 
0.4%
segura 2
 
0.4%
hay 1
 
0.2%

Most occurring characters

ValueCountFrequency (%)
S 292
27.4%
i 292
27.4%
o 211
19.8%
N 202
18.9%
s 12
 
1.1%
e 10
 
0.9%
10
 
0.9%
a 6
 
0.6%
y 5
 
0.5%
r 5
 
0.5%
Other values (9) 21
 
2.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 560
52.5%
Uppercase Letter 496
46.5%
Space Separator 10
 
0.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i 292
52.1%
o 211
37.7%
s 12
 
2.1%
e 10
 
1.8%
a 6
 
1.1%
y 5
 
0.9%
r 5
 
0.9%
p 3
 
0.5%
n 3
 
0.5%
b 3
 
0.5%
Other values (5) 10
 
1.8%
Uppercase Letter
ValueCountFrequency (%)
S 292
58.9%
N 202
40.7%
Y 2
 
0.4%
Space Separator
ValueCountFrequency (%)
10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1056
99.1%
Common 10
 
0.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
S 292
27.7%
i 292
27.7%
o 211
20.0%
N 202
19.1%
s 12
 
1.1%
e 10
 
0.9%
a 6
 
0.6%
y 5
 
0.5%
r 5
 
0.5%
p 3
 
0.3%
Other values (8) 18
 
1.7%
Common
ValueCountFrequency (%)
10
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1066
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
S 292
27.4%
i 292
27.4%
o 211
19.8%
N 202
18.9%
s 12
 
1.1%
e 10
 
0.9%
10
 
0.9%
a 6
 
0.6%
y 5
 
0.5%
r 5
 
0.5%
Other values (9) 21
 
2.0%

limpio_responsable_saneamiento
Categorical

IMBALANCE  MISSING 

Distinct10
Distinct (%)3.5%
Missing213
Missing (%)42.9%
Memory size4.0 KiB
CMAS
267 
Autogestión
 
4
Comite local
 
3
A todos
 
3
A la comunidad
 
2
Other values (5)
 
5

Length

Max length21
Median length4
Mean length4.450704225
Min length4

Characters and Unicode

Total characters1264
Distinct characters26
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique5 ?
Unique (%)1.8%

Sample

1st rowCMAS
2nd rowCMAS
3rd rowCMAS
4th rowCMAS
5th rowCMAS

Common Values

ValueCountFrequency (%)
CMAS 267
53.7%
Autogestión 4
 
0.8%
Comite local 3
 
0.6%
A todos 3
 
0.6%
A la comunidad 2
 
0.4%
Instituciones/Civiles 1
 
0.2%
Sendas A.C. 1
 
0.2%
Junta del agua 1
 
0.2%
CAEV 1
 
0.2%
Comite local/CMAS 1
 
0.2%
(Missing) 213
42.9%

Length

2024-01-31T13:58:38.216491image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-31T13:58:38.403607image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
cmas 267
89.6%
a 5
 
1.7%
autogestión 4
 
1.3%
comite 4
 
1.3%
local 3
 
1.0%
todos 3
 
1.0%
la 2
 
0.7%
comunidad 2
 
0.7%
instituciones/civiles 1
 
0.3%
sendas 1
 
0.3%
Other values (6) 6
 
2.0%

Most occurring characters

ValueCountFrequency (%)
A 279
22.1%
C 275
21.8%
S 269
21.3%
M 268
21.2%
o 21
 
1.7%
t 18
 
1.4%
i 14
 
1.1%
14
 
1.1%
e 12
 
0.9%
a 12
 
0.9%
Other values (16) 82
 
6.5%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 1095
86.6%
Lowercase Letter 151
 
11.9%
Space Separator 14
 
1.1%
Other Punctuation 4
 
0.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 21
13.9%
t 18
11.9%
i 14
9.3%
e 12
7.9%
a 12
7.9%
l 12
7.9%
s 11
7.3%
n 10
6.6%
u 9
 
6.0%
d 9
 
6.0%
Other values (5) 23
15.2%
Uppercase Letter
ValueCountFrequency (%)
A 279
25.5%
C 275
25.1%
S 269
24.6%
M 268
24.5%
I 1
 
0.1%
J 1
 
0.1%
E 1
 
0.1%
V 1
 
0.1%
Other Punctuation
ValueCountFrequency (%)
/ 2
50.0%
. 2
50.0%
Space Separator
ValueCountFrequency (%)
14
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1246
98.6%
Common 18
 
1.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
A 279
22.4%
C 275
22.1%
S 269
21.6%
M 268
21.5%
o 21
 
1.7%
t 18
 
1.4%
i 14
 
1.1%
e 12
 
1.0%
a 12
 
1.0%
l 12
 
1.0%
Other values (13) 66
 
5.3%
Common
ValueCountFrequency (%)
14
77.8%
/ 2
 
11.1%
. 2
 
11.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1260
99.7%
None 4
 
0.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
A 279
22.1%
C 275
21.8%
S 269
21.3%
M 268
21.3%
o 21
 
1.7%
t 18
 
1.4%
i 14
 
1.1%
14
 
1.1%
e 12
 
1.0%
a 12
 
1.0%
Other values (15) 78
 
6.2%
None
ValueCountFrequency (%)
ó 4
100.0%

limpio_destino_agua_servida
Categorical

IMBALANCE 

Distinct17
Distinct (%)3.4%
Missing1
Missing (%)0.2%
Memory size4.0 KiB
Drenaje
387 
Fosa séptica
47 
Río, Arroyo
 
16
Sistema doméstico de raíces
 
15
Pozo de absorción
 
10
Other values (12)
 
21

Length

Max length52
Median length7
Mean length8.774193548
Min length7

Characters and Unicode

Total characters4352
Distinct characters37
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9 ?
Unique (%)1.8%

Sample

1st rowPozo de absorción
2nd rowDrenaje
3rd rowDrenaje
4th rowDrenaje
5th rowDrenaje

Common Values

ValueCountFrequency (%)
Drenaje 387
77.9%
Fosa séptica 47
 
9.5%
Río, Arroyo 16
 
3.2%
Sistema doméstico de raíces 15
 
3.0%
Pozo de absorción 10
 
2.0%
Desconozco 8
 
1.6%
Biodigestor 2
 
0.4%
A la calle 2
 
0.4%
Biodigestor/Pozo de absorción 1
 
0.2%
Lavado de patio 1
 
0.2%
Other values (7) 7
 
1.4%

Length

2024-01-31T13:58:38.618326image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
drenaje 387
59.9%
fosa 48
 
7.4%
séptica 47
 
7.3%
de 31
 
4.8%
río 16
 
2.5%
arroyo 16
 
2.5%
sistema 15
 
2.3%
doméstico 15
 
2.3%
raíces 15
 
2.3%
absorción 11
 
1.7%
Other values (22) 45
 
7.0%

Most occurring characters

ValueCountFrequency (%)
e 858
19.7%
a 547
12.6%
r 461
10.6%
n 410
9.4%
D 395
9.1%
j 387
8.9%
o 203
 
4.7%
s 176
 
4.0%
150
 
3.4%
c 109
 
2.5%
Other values (27) 656
15.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 3662
84.1%
Uppercase Letter 518
 
11.9%
Space Separator 150
 
3.4%
Other Punctuation 22
 
0.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 858
23.4%
a 547
14.9%
r 461
12.6%
n 410
11.2%
j 387
10.6%
o 203
 
5.5%
s 176
 
4.8%
c 109
 
3.0%
i 105
 
2.9%
t 84
 
2.3%
Other values (14) 322
 
8.8%
Uppercase Letter
ValueCountFrequency (%)
D 395
76.3%
F 48
 
9.3%
A 19
 
3.7%
R 18
 
3.5%
S 15
 
2.9%
P 12
 
2.3%
B 5
 
1.0%
T 4
 
0.8%
L 1
 
0.2%
J 1
 
0.2%
Other Punctuation
ValueCountFrequency (%)
, 17
77.3%
/ 5
 
22.7%
Space Separator
ValueCountFrequency (%)
150
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 4180
96.0%
Common 172
 
4.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 858
20.5%
a 547
13.1%
r 461
11.0%
n 410
9.8%
D 395
9.4%
j 387
9.3%
o 203
 
4.9%
s 176
 
4.2%
c 109
 
2.6%
i 105
 
2.5%
Other values (24) 529
12.7%
Common
ValueCountFrequency (%)
150
87.2%
, 17
 
9.9%
/ 5
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4243
97.5%
None 109
 
2.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 858
20.2%
a 547
12.9%
r 461
10.9%
n 410
9.7%
D 395
9.3%
j 387
9.1%
o 203
 
4.8%
s 176
 
4.1%
150
 
3.5%
c 109
 
2.6%
Other values (24) 547
12.9%
None
ValueCountFrequency (%)
é 63
57.8%
í 33
30.3%
ó 13
 
11.9%
Distinct3
Distinct (%)0.6%
Missing1
Missing (%)0.2%
Memory size4.0 KiB
No sé
266 
No
190 
40 

Length

Max length5
Median length5
Mean length3.608870968
Min length2

Characters and Unicode

Total characters1790
Distinct characters7
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd rowNo
4th row
5th rowNo

Common Values

ValueCountFrequency (%)
No sé 266
53.5%
No 190
38.2%
40
 
8.0%
(Missing) 1
 
0.2%

Length

2024-01-31T13:58:38.793246image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-31T13:58:38.944872image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
no 456
59.8%
266
34.9%
40
 
5.2%

Most occurring characters

ValueCountFrequency (%)
N 456
25.5%
o 456
25.5%
266
14.9%
s 266
14.9%
é 266
14.9%
S 40
 
2.2%
í 40
 
2.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1028
57.4%
Uppercase Letter 496
27.7%
Space Separator 266
 
14.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 456
44.4%
s 266
25.9%
é 266
25.9%
í 40
 
3.9%
Uppercase Letter
ValueCountFrequency (%)
N 456
91.9%
S 40
 
8.1%
Space Separator
ValueCountFrequency (%)
266
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1524
85.1%
Common 266
 
14.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 456
29.9%
o 456
29.9%
s 266
17.5%
é 266
17.5%
S 40
 
2.6%
í 40
 
2.6%
Common
ValueCountFrequency (%)
266
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1484
82.9%
None 306
 
17.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 456
30.7%
o 456
30.7%
266
17.9%
s 266
17.9%
S 40
 
2.7%
None
ValueCountFrequency (%)
é 266
86.9%
í 40
 
13.1%
Distinct30
Distinct (%)54.5%
Missing442
Missing (%)88.9%
Memory size4.0 KiB
2024-01-31T13:58:39.254935image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Length

Max length104
Median length65
Mean length25.52727273
Min length2

Characters and Unicode

Total characters1404
Distinct characters37
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique24 ?
Unique (%)43.6%

Sample

1st rowNo lo sé
2nd rowEntramado de raíces, biodigestor
3rd rowAguas grises al sistema de raíces/Sin aguas negras
4th rowAguas grises a un biofiltro, después pozo de absorción/Aguas negras a fosa séptica
5th rowAguas grises al patio/Aguas negras al Biodigestor/Hoyo en la tierra
ValueCountFrequency (%)
al 30
 
11.7%
aguas 21
 
8.2%
grises 18
 
7.0%
negras 15
 
5.9%
no 14
 
5.5%
a 14
 
5.5%
drenaje 13
 
5.1%
12
 
4.7%
lo 12
 
4.7%
de 10
 
3.9%
Other values (54) 97
37.9%
2024-01-31T13:58:39.895188image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
202
14.4%
a 164
11.7%
s 145
10.3%
e 119
 
8.5%
r 91
 
6.5%
g 78
 
5.6%
o 75
 
5.3%
l 75
 
5.3%
i 72
 
5.1%
n 55
 
3.9%
Other values (27) 328
23.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1106
78.8%
Space Separator 202
 
14.4%
Uppercase Letter 75
 
5.3%
Other Punctuation 21
 
1.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 164
14.8%
s 145
13.1%
e 119
10.8%
r 91
8.2%
g 78
7.1%
o 75
6.8%
l 75
6.8%
i 72
6.5%
n 55
 
5.0%
u 53
 
4.8%
Other values (15) 179
16.2%
Uppercase Letter
ValueCountFrequency (%)
A 44
58.7%
N 14
 
18.7%
S 8
 
10.7%
B 3
 
4.0%
T 2
 
2.7%
F 1
 
1.3%
C 1
 
1.3%
H 1
 
1.3%
E 1
 
1.3%
Other Punctuation
ValueCountFrequency (%)
/ 16
76.2%
, 5
 
23.8%
Space Separator
ValueCountFrequency (%)
202
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1181
84.1%
Common 223
 
15.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 164
13.9%
s 145
12.3%
e 119
10.1%
r 91
 
7.7%
g 78
 
6.6%
o 75
 
6.4%
l 75
 
6.4%
i 72
 
6.1%
n 55
 
4.7%
u 53
 
4.5%
Other values (24) 254
21.5%
Common
ValueCountFrequency (%)
202
90.6%
/ 16
 
7.2%
, 5
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1379
98.2%
None 25
 
1.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
202
14.6%
a 164
11.9%
s 145
10.5%
e 119
 
8.6%
r 91
 
6.6%
g 78
 
5.7%
o 75
 
5.4%
l 75
 
5.4%
i 72
 
5.2%
n 55
 
4.0%
Other values (23) 303
22.0%
None
ValueCountFrequency (%)
é 15
60.0%
í 6
 
24.0%
ó 3
 
12.0%
á 1
 
4.0%

limpio_destino_drenaje
Categorical

MISSING 

Distinct28
Distinct (%)7.3%
Missing114
Missing (%)22.9%
Memory size4.0 KiB
No
180 
Sí/A los ríos
67 
Desconozco
40 
Sí/Planta de tratamiento
26 
19 
Other values (23)
51 

Length

Max length29
Median length2
Mean length8.023498695
Min length2

Characters and Unicode

Total characters3073
Distinct characters37
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique14 ?
Unique (%)3.7%

Sample

1st rowSí/A los ríos
2nd rowSí/A los ríos
3rd rowSí/Al caño
4th rowSí/A los ríos
5th rowNo

Common Values

ValueCountFrequency (%)
No 180
36.2%
Sí/A los ríos 67
 
13.5%
Desconozco 40
 
8.0%
Sí/Planta de tratamiento 26
 
5.2%
19
 
3.8%
Tal vez/A los ríos 8
 
1.6%
Sí/Al arroyo 6
 
1.2%
Sí/Al mar 6
 
1.2%
Sí/Al drenaje 5
 
1.0%
Sí/Al alcantarillado 4
 
0.8%
Other values (18) 22
 
4.4%
(Missing) 114
22.9%

Length

2024-01-31T13:58:40.122519image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
no 181
27.7%
los 77
11.8%
ríos 77
11.8%
sí/a 72
 
11.0%
desconozco 40
 
6.1%
de 28
 
4.3%
tratamiento 28
 
4.3%
sí/planta 26
 
4.0%
sí/al 25
 
3.8%
20
 
3.1%
Other values (31) 80
12.2%

Most occurring characters

ValueCountFrequency (%)
o 516
16.8%
271
 
8.8%
í 229
 
7.5%
s 207
 
6.7%
a 188
 
6.1%
N 181
 
5.9%
l 168
 
5.5%
r 152
 
4.9%
S 150
 
4.9%
/ 143
 
4.7%
Other values (27) 868
28.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 2126
69.2%
Uppercase Letter 530
 
17.2%
Space Separator 271
 
8.8%
Other Punctuation 146
 
4.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 516
24.3%
í 229
10.8%
s 207
9.7%
a 188
 
8.8%
l 168
 
7.9%
r 152
 
7.1%
e 128
 
6.0%
t 121
 
5.7%
n 112
 
5.3%
c 93
 
4.4%
Other values (14) 212
10.0%
Uppercase Letter
ValueCountFrequency (%)
N 181
34.2%
S 150
28.3%
A 113
21.3%
D 40
 
7.5%
P 28
 
5.3%
T 12
 
2.3%
B 2
 
0.4%
L 2
 
0.4%
F 1
 
0.2%
R 1
 
0.2%
Other Punctuation
ValueCountFrequency (%)
/ 143
97.9%
, 3
 
2.1%
Space Separator
ValueCountFrequency (%)
271
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 2656
86.4%
Common 417
 
13.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 516
19.4%
í 229
 
8.6%
s 207
 
7.8%
a 188
 
7.1%
N 181
 
6.8%
l 168
 
6.3%
r 152
 
5.7%
S 150
 
5.6%
e 128
 
4.8%
t 121
 
4.6%
Other values (24) 616
23.2%
Common
ValueCountFrequency (%)
271
65.0%
/ 143
34.3%
, 3
 
0.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2841
92.5%
None 232
 
7.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o 516
18.2%
271
 
9.5%
s 207
 
7.3%
a 188
 
6.6%
N 181
 
6.4%
l 168
 
5.9%
r 152
 
5.4%
S 150
 
5.3%
/ 143
 
5.0%
e 128
 
4.5%
Other values (24) 737
25.9%
None
ValueCountFrequency (%)
í 229
98.7%
ñ 2
 
0.9%
é 1
 
0.4%
Distinct4
Distinct (%)0.8%
Missing1
Missing (%)0.2%
Memory size4.0 KiB
289 
Desconozco
141 
No pago
36 
No
30 

Length

Max length10
Median length2
Mean length4.637096774
Min length2

Characters and Unicode

Total characters2300
Distinct characters14
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo pago
2nd row
3rd row
4th row
5th rowDesconozco

Common Values

ValueCountFrequency (%)
289
58.1%
Desconozco 141
28.4%
No pago 36
 
7.2%
No 30
 
6.0%
(Missing) 1
 
0.2%

Length

2024-01-31T13:58:40.338923image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-31T13:58:40.550040image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
289
54.3%
desconozco 141
26.5%
no 66
 
12.4%
pago 36
 
6.8%

Most occurring characters

ValueCountFrequency (%)
o 525
22.8%
S 289
12.6%
í 289
12.6%
c 282
12.3%
D 141
 
6.1%
e 141
 
6.1%
s 141
 
6.1%
n 141
 
6.1%
z 141
 
6.1%
N 66
 
2.9%
Other values (4) 144
 
6.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1768
76.9%
Uppercase Letter 496
 
21.6%
Space Separator 36
 
1.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 525
29.7%
í 289
16.3%
c 282
16.0%
e 141
 
8.0%
s 141
 
8.0%
n 141
 
8.0%
z 141
 
8.0%
p 36
 
2.0%
a 36
 
2.0%
g 36
 
2.0%
Uppercase Letter
ValueCountFrequency (%)
S 289
58.3%
D 141
28.4%
N 66
 
13.3%
Space Separator
ValueCountFrequency (%)
36
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 2264
98.4%
Common 36
 
1.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 525
23.2%
S 289
12.8%
í 289
12.8%
c 282
12.5%
D 141
 
6.2%
e 141
 
6.2%
s 141
 
6.2%
n 141
 
6.2%
z 141
 
6.2%
N 66
 
2.9%
Other values (3) 108
 
4.8%
Common
ValueCountFrequency (%)
36
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2011
87.4%
None 289
 
12.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o 525
26.1%
S 289
14.4%
c 282
14.0%
D 141
 
7.0%
e 141
 
7.0%
s 141
 
7.0%
n 141
 
7.0%
z 141
 
7.0%
N 66
 
3.3%
36
 
1.8%
Other values (3) 108
 
5.4%
None
ValueCountFrequency (%)
í 289
100.0%

limpio_percep_calidad_servicio
Categorical

MISSING 

Distinct5
Distinct (%)1.2%
Missing68
Missing (%)13.7%
Memory size4.0 KiB
Regular
164 
Bueno
141 
Malo
69 
Pésimo
44 
Excelente
 
11

Length

Max length9
Median length7
Mean length5.808857809
Min length4

Characters and Unicode

Total characters2492
Distinct characters20
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowMalo
2nd rowPésimo
3rd rowPésimo
4th rowMalo
5th rowPésimo

Common Values

ValueCountFrequency (%)
Regular 164
33.0%
Bueno 141
28.4%
Malo 69
13.9%
Pésimo 44
 
8.9%
Excelente 11
 
2.2%
(Missing) 68
13.7%

Length

2024-01-31T13:58:40.770853image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-31T13:58:41.060094image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
regular 164
38.2%
bueno 141
32.9%
malo 69
16.1%
pésimo 44
 
10.3%
excelente 11
 
2.6%

Most occurring characters

ValueCountFrequency (%)
e 338
13.6%
u 305
12.2%
o 254
10.2%
l 244
9.8%
a 233
9.3%
R 164
6.6%
g 164
6.6%
r 164
6.6%
n 152
6.1%
B 141
5.7%
Other values (10) 333
13.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 2063
82.8%
Uppercase Letter 429
 
17.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 338
16.4%
u 305
14.8%
o 254
12.3%
l 244
11.8%
a 233
11.3%
g 164
7.9%
r 164
7.9%
n 152
7.4%
é 44
 
2.1%
s 44
 
2.1%
Other values (5) 121
 
5.9%
Uppercase Letter
ValueCountFrequency (%)
R 164
38.2%
B 141
32.9%
M 69
16.1%
P 44
 
10.3%
E 11
 
2.6%

Most occurring scripts

ValueCountFrequency (%)
Latin 2492
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 338
13.6%
u 305
12.2%
o 254
10.2%
l 244
9.8%
a 233
9.3%
R 164
6.6%
g 164
6.6%
r 164
6.6%
n 152
6.1%
B 141
5.7%
Other values (10) 333
13.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2448
98.2%
None 44
 
1.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 338
13.8%
u 305
12.5%
o 254
10.4%
l 244
10.0%
a 233
9.5%
R 164
6.7%
g 164
6.7%
r 164
6.7%
n 152
6.2%
B 141
5.8%
Other values (9) 289
11.8%
None
ValueCountFrequency (%)
é 44
100.0%

limpio_percep_costo_saneamiento
Categorical

MISSING 

Distinct5
Distinct (%)1.2%
Missing89
Missing (%)17.9%
Memory size4.0 KiB
Regular
194 
Bueno
122 
Poco
44 
Inaceptable
42 
Excelente
 
6

Length

Max length11
Median length9
Mean length6.519607843
Min length4

Characters and Unicode

Total characters2660
Distinct characters18
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowRegular
2nd rowInaceptable
3rd rowPoco
4th rowRegular
5th rowInaceptable

Common Values

ValueCountFrequency (%)
Regular 194
39.0%
Bueno 122
24.5%
Poco 44
 
8.9%
Inaceptable 42
 
8.5%
Excelente 6
 
1.2%
(Missing) 89
17.9%

Length

2024-01-31T13:58:41.339285image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-31T13:58:41.521861image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
regular 194
47.5%
bueno 122
29.9%
poco 44
 
10.8%
inaceptable 42
 
10.3%
excelente 6
 
1.5%

Most occurring characters

ValueCountFrequency (%)
e 418
15.7%
u 316
11.9%
a 278
10.5%
l 242
9.1%
o 210
7.9%
r 194
7.3%
R 194
7.3%
g 194
7.3%
n 170
6.4%
B 122
 
4.6%
Other values (8) 322
12.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 2252
84.7%
Uppercase Letter 408
 
15.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 418
18.6%
u 316
14.0%
a 278
12.3%
l 242
10.7%
o 210
9.3%
r 194
8.6%
g 194
8.6%
n 170
7.5%
c 92
 
4.1%
t 48
 
2.1%
Other values (3) 90
 
4.0%
Uppercase Letter
ValueCountFrequency (%)
R 194
47.5%
B 122
29.9%
P 44
 
10.8%
I 42
 
10.3%
E 6
 
1.5%

Most occurring scripts

ValueCountFrequency (%)
Latin 2660
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 418
15.7%
u 316
11.9%
a 278
10.5%
l 242
9.1%
o 210
7.9%
r 194
7.3%
R 194
7.3%
g 194
7.3%
n 170
6.4%
B 122
 
4.6%
Other values (8) 322
12.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2660
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 418
15.7%
u 316
11.9%
a 278
10.5%
l 242
9.1%
o 210
7.9%
r 194
7.3%
R 194
7.3%
g 194
7.3%
n 170
6.4%
B 122
 
4.6%
Other values (8) 322
12.1%

limpio_sabe_uso_dinero_tarifa_saneamiento
Categorical

IMBALANCE  MISSING 

Distinct19
Distinct (%)4.7%
Missing89
Missing (%)17.9%
Memory size4.0 KiB
No
303 
Sí/Mantenimiento
36 
Sí/Tratamiento de aguas
 
21
 
20
Sí/Desvío de dinero
 
6
Other values (14)
 
22

Length

Max length45
Median length2
Mean length5.906862745
Min length2

Characters and Unicode

Total characters2410
Distinct characters33
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique9 ?
Unique (%)2.2%

Sample

1st rowNo
2nd rowSí/Mantenimiento
3rd rowNo
4th rowSí/Para extender la red de abastecimiento
5th rowNo

Common Values

ValueCountFrequency (%)
No 303
61.0%
Sí/Mantenimiento 36
 
7.2%
Sí/Tratamiento de aguas 21
 
4.2%
20
 
4.0%
Sí/Desvío de dinero 6
 
1.2%
Sí/Costos de operación 4
 
0.8%
Sí/Mantenimiento, Tratamiento de aguas 3
 
0.6%
Sí/Mantenimiento, Pago de servicios, Salarios 2
 
0.4%
Sí/Salarios 2
 
0.4%
Sí/Para extender la red de abastecimiento 2
 
0.4%
Other values (9) 9
 
1.8%
(Missing) 89
 
17.9%

Length

2024-01-31T13:58:41.723453image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
no 304
59.7%
sí/mantenimiento 42
 
8.3%
de 41
 
8.1%
aguas 26
 
5.1%
sí/tratamiento 22
 
4.3%
20
 
3.9%
sí/desvío 6
 
1.2%
dinero 6
 
1.2%
operación 5
 
1.0%
sí/costos 4
 
0.8%
Other values (19) 33
 
6.5%

Most occurring characters

ValueCountFrequency (%)
o 418
17.3%
N 305
12.7%
e 190
 
7.9%
a 183
 
7.6%
n 175
 
7.3%
t 152
 
6.3%
i 142
 
5.9%
S 109
 
4.5%
í 108
 
4.5%
101
 
4.2%
Other values (23) 527
21.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1715
71.2%
Uppercase Letter 501
 
20.8%
Space Separator 101
 
4.2%
Other Punctuation 93
 
3.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 418
24.4%
e 190
11.1%
a 183
10.7%
n 175
10.2%
t 152
 
8.9%
i 142
 
8.3%
í 108
 
6.3%
m 72
 
4.2%
s 58
 
3.4%
r 56
 
3.3%
Other values (12) 161
 
9.4%
Uppercase Letter
ValueCountFrequency (%)
N 305
60.9%
S 109
 
21.8%
M 43
 
8.6%
T 27
 
5.4%
D 6
 
1.2%
C 6
 
1.2%
P 4
 
0.8%
I 1
 
0.2%
Other Punctuation
ValueCountFrequency (%)
/ 83
89.2%
, 10
 
10.8%
Space Separator
ValueCountFrequency (%)
101
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 2216
92.0%
Common 194
 
8.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 418
18.9%
N 305
13.8%
e 190
8.6%
a 183
8.3%
n 175
7.9%
t 152
 
6.9%
i 142
 
6.4%
S 109
 
4.9%
í 108
 
4.9%
m 72
 
3.2%
Other values (20) 362
16.3%
Common
ValueCountFrequency (%)
101
52.1%
/ 83
42.8%
, 10
 
5.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2296
95.3%
None 114
 
4.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o 418
18.2%
N 305
13.3%
e 190
8.3%
a 183
8.0%
n 175
 
7.6%
t 152
 
6.6%
i 142
 
6.2%
S 109
 
4.7%
101
 
4.4%
/ 83
 
3.6%
Other values (21) 438
19.1%
None
ValueCountFrequency (%)
í 108
94.7%
ó 6
 
5.3%
Distinct3
Distinct (%)0.6%
Missing1
Missing (%)0.2%
Memory size4.0 KiB
No
269 
178 
No sé
49 

Length

Max length5
Median length2
Mean length2.296370968
Min length2

Characters and Unicode

Total characters1139
Distinct characters7
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo sé
3rd row
4th rowNo
5th rowNo

Common Values

ValueCountFrequency (%)
No 269
54.1%
178
35.8%
No sé 49
 
9.9%
(Missing) 1
 
0.2%

Length

2024-01-31T13:58:41.977061image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-31T13:58:42.227564image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
no 318
58.3%
178
32.7%
49
 
9.0%

Most occurring characters

ValueCountFrequency (%)
N 318
27.9%
o 318
27.9%
S 178
15.6%
í 178
15.6%
49
 
4.3%
s 49
 
4.3%
é 49
 
4.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 594
52.2%
Uppercase Letter 496
43.5%
Space Separator 49
 
4.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 318
53.5%
í 178
30.0%
s 49
 
8.2%
é 49
 
8.2%
Uppercase Letter
ValueCountFrequency (%)
N 318
64.1%
S 178
35.9%
Space Separator
ValueCountFrequency (%)
49
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1090
95.7%
Common 49
 
4.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 318
29.2%
o 318
29.2%
S 178
16.3%
í 178
16.3%
s 49
 
4.5%
é 49
 
4.5%
Common
ValueCountFrequency (%)
49
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 912
80.1%
None 227
 
19.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 318
34.9%
o 318
34.9%
S 178
19.5%
49
 
5.4%
s 49
 
5.4%
None
ValueCountFrequency (%)
í 178
78.4%
é 49
 
21.6%
Distinct2
Distinct (%)0.4%
Missing1
Missing (%)0.2%
Memory size4.0 KiB
No
410 
86 

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters992
Distinct characters4
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowNo
2nd rowNo
3rd row
4th rowNo
5th rowNo

Common Values

ValueCountFrequency (%)
No 410
82.5%
86
 
17.3%
(Missing) 1
 
0.2%

Length

2024-01-31T13:58:42.510939image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-31T13:58:42.704017image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
no 410
82.7%
86
 
17.3%

Most occurring characters

ValueCountFrequency (%)
N 410
41.3%
o 410
41.3%
S 86
 
8.7%
í 86
 
8.7%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 496
50.0%
Lowercase Letter 496
50.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
N 410
82.7%
S 86
 
17.3%
Lowercase Letter
ValueCountFrequency (%)
o 410
82.7%
í 86
 
17.3%

Most occurring scripts

ValueCountFrequency (%)
Latin 992
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 410
41.3%
o 410
41.3%
S 86
 
8.7%
í 86
 
8.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 906
91.3%
None 86
 
8.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 410
45.3%
o 410
45.3%
S 86
 
9.5%
None
ValueCountFrequency (%)
í 86
100.0%
Distinct130
Distinct (%)38.8%
Missing162
Missing (%)32.6%
Memory size4.0 KiB
2024-01-31T13:58:43.219919image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Length

Max length149
Median length126
Mean length20.19701493
Min length2

Characters and Unicode

Total characters6766
Distinct characters62
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique105 ?
Unique (%)31.3%

Sample

1st rowAmigos del río Pixquiac, Parque lineal Quetzalapa
2nd rowNinguna
3rd rowAgua pasa por mi casa, Custodios del archipielago
4th rowConservación y cuidado del río Pixquiac
5th rowCustodios del archipielago
ValueCountFrequency (%)
desconozco 128
 
13.6%
de 56
 
6.0%
del 56
 
6.0%
agua 34
 
3.6%
sendas 25
 
2.7%
río 25
 
2.7%
pixquiac 21
 
2.2%
la 20
 
2.1%
ninguna 18
 
1.9%
custodios 17
 
1.8%
Other values (213) 541
57.5%
2024-01-31T13:58:44.347170image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
o 795
 
11.7%
606
 
9.0%
e 553
 
8.2%
a 541
 
8.0%
c 449
 
6.6%
i 369
 
5.5%
n 361
 
5.3%
s 342
 
5.1%
d 272
 
4.0%
l 261
 
3.9%
Other values (52) 2217
32.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 5167
76.4%
Uppercase Letter 867
 
12.8%
Space Separator 606
 
9.0%
Other Punctuation 111
 
1.6%
Decimal Number 14
 
0.2%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 795
15.4%
e 553
10.7%
a 541
10.5%
c 449
8.7%
i 369
 
7.1%
n 361
 
7.0%
s 342
 
6.6%
d 272
 
5.3%
l 261
 
5.1%
u 191
 
3.7%
Other values (20) 1033
20.0%
Uppercase Letter
ValueCountFrequency (%)
D 162
18.7%
C 129
14.9%
A 116
13.4%
S 91
10.5%
P 58
 
6.7%
N 58
 
6.7%
E 45
 
5.2%
G 28
 
3.2%
L 27
 
3.1%
I 22
 
2.5%
Other values (14) 131
15.1%
Decimal Number
ValueCountFrequency (%)
0 6
42.9%
3 3
21.4%
2 3
21.4%
4 2
 
14.3%
Other Punctuation
ValueCountFrequency (%)
, 100
90.1%
. 11
 
9.9%
Space Separator
ValueCountFrequency (%)
606
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 6034
89.2%
Common 732
 
10.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 795
13.2%
e 553
 
9.2%
a 541
 
9.0%
c 449
 
7.4%
i 369
 
6.1%
n 361
 
6.0%
s 342
 
5.7%
d 272
 
4.5%
l 261
 
4.3%
u 191
 
3.2%
Other values (44) 1900
31.5%
Common
ValueCountFrequency (%)
606
82.8%
, 100
 
13.7%
. 11
 
1.5%
0 6
 
0.8%
3 3
 
0.4%
2 3
 
0.4%
4 2
 
0.3%
- 1
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6679
98.7%
None 87
 
1.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o 795
 
11.9%
606
 
9.1%
e 553
 
8.3%
a 541
 
8.1%
c 449
 
6.7%
i 369
 
5.5%
n 361
 
5.4%
s 342
 
5.1%
d 272
 
4.1%
l 261
 
3.9%
Other values (47) 2130
31.9%
None
ValueCountFrequency (%)
í 28
32.2%
ó 23
26.4%
ñ 15
17.2%
é 14
16.1%
á 7
 
8.0%

limpio_conocimiento_iniciativa
Categorical

MISSING 

Distinct2
Distinct (%)0.5%
Missing123
Missing (%)24.7%
Memory size4.0 KiB
No
294 
80 

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters748
Distinct characters4
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row
2nd rowNo
3rd rowNo
4th rowNo
5th rowNo

Common Values

ValueCountFrequency (%)
No 294
59.2%
80
 
16.1%
(Missing) 123
24.7%

Length

2024-01-31T13:58:44.764578image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-31T13:58:45.077054image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
no 294
78.6%
80
 
21.4%

Most occurring characters

ValueCountFrequency (%)
N 294
39.3%
o 294
39.3%
S 80
 
10.7%
í 80
 
10.7%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 374
50.0%
Lowercase Letter 374
50.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
N 294
78.6%
S 80
 
21.4%
Lowercase Letter
ValueCountFrequency (%)
o 294
78.6%
í 80
 
21.4%

Most occurring scripts

ValueCountFrequency (%)
Latin 748
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 294
39.3%
o 294
39.3%
S 80
 
10.7%
í 80
 
10.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 668
89.3%
None 80
 
10.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 294
44.0%
o 294
44.0%
S 80
 
12.0%
None
ValueCountFrequency (%)
í 80
100.0%
Distinct51
Distinct (%)18.3%
Missing219
Missing (%)44.1%
Memory size4.0 KiB
2024-01-31T13:58:45.526001image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Length

Max length87
Median length10
Mean length14.29856115
Min length2

Characters and Unicode

Total characters3975
Distinct characters56
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique36 ?
Unique (%)12.9%

Sample

1st rowDesconozco
2nd rowDesconozco
3rd rowCreación de humedales artificiales
4th rowDesconozco
5th rowDesconozco
ValueCountFrequency (%)
desconozco 193
40.5%
del 20
 
4.2%
la 16
 
3.4%
comunidad 13
 
2.7%
río 10
 
2.1%
de 10
 
2.1%
sedeño 9
 
1.9%
gobierno 8
 
1.7%
propia 8
 
1.7%
gestión 8
 
1.7%
Other values (85) 182
38.2%
2024-01-31T13:58:46.347825image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
o 746
18.8%
c 447
11.2%
e 356
 
9.0%
s 285
 
7.2%
n 271
 
6.8%
D 206
 
5.2%
202
 
5.1%
z 200
 
5.0%
a 198
 
5.0%
i 151
 
3.8%
Other values (46) 913
23.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 3255
81.9%
Uppercase Letter 477
 
12.0%
Space Separator 202
 
5.1%
Other Punctuation 36
 
0.9%
Decimal Number 4
 
0.1%
Final Punctuation 1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 746
22.9%
c 447
13.7%
e 356
10.9%
s 285
 
8.8%
n 271
 
8.3%
z 200
 
6.1%
a 198
 
6.1%
i 151
 
4.6%
l 108
 
3.3%
d 102
 
3.1%
Other values (17) 391
12.0%
Uppercase Letter
ValueCountFrequency (%)
D 206
43.2%
C 40
 
8.4%
A 38
 
8.0%
S 33
 
6.9%
G 28
 
5.9%
P 26
 
5.5%
L 24
 
5.0%
R 14
 
2.9%
N 13
 
2.7%
W 12
 
2.5%
Other values (12) 43
 
9.0%
Decimal Number
ValueCountFrequency (%)
0 2
50.0%
2 1
25.0%
3 1
25.0%
Other Punctuation
ValueCountFrequency (%)
, 31
86.1%
. 5
 
13.9%
Space Separator
ValueCountFrequency (%)
202
100.0%
Final Punctuation
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 3732
93.9%
Common 243
 
6.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 746
20.0%
c 447
12.0%
e 356
9.5%
s 285
 
7.6%
n 271
 
7.3%
D 206
 
5.5%
z 200
 
5.4%
a 198
 
5.3%
i 151
 
4.0%
l 108
 
2.9%
Other values (39) 764
20.5%
Common
ValueCountFrequency (%)
202
83.1%
, 31
 
12.8%
. 5
 
2.1%
0 2
 
0.8%
1
 
0.4%
2 1
 
0.4%
3 1
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3927
98.8%
None 47
 
1.2%
Punctuation 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o 746
19.0%
c 447
11.4%
e 356
9.1%
s 285
 
7.3%
n 271
 
6.9%
D 206
 
5.2%
202
 
5.1%
z 200
 
5.1%
a 198
 
5.0%
i 151
 
3.8%
Other values (41) 865
22.0%
None
ValueCountFrequency (%)
ó 18
38.3%
í 15
31.9%
ñ 10
21.3%
é 4
 
8.5%
Punctuation
ValueCountFrequency (%)
1
100.0%
Distinct2
Distinct (%)0.4%
Missing1
Missing (%)0.2%
Memory size4.0 KiB
Si
250 
No
246 

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters992
Distinct characters4
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowSi
2nd rowNo
3rd rowSi
4th rowNo
5th rowNo

Common Values

ValueCountFrequency (%)
Si 250
50.3%
No 246
49.5%
(Missing) 1
 
0.2%

Length

2024-01-31T13:58:46.678706image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-31T13:58:46.968955image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
si 250
50.4%
no 246
49.6%

Most occurring characters

ValueCountFrequency (%)
S 250
25.2%
i 250
25.2%
N 246
24.8%
o 246
24.8%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 496
50.0%
Lowercase Letter 496
50.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
S 250
50.4%
N 246
49.6%
Lowercase Letter
ValueCountFrequency (%)
i 250
50.4%
o 246
49.6%

Most occurring scripts

ValueCountFrequency (%)
Latin 992
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
S 250
25.2%
i 250
25.2%
N 246
24.8%
o 246
24.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 992
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
S 250
25.2%
i 250
25.2%
N 246
24.8%
o 246
24.8%

limpio_observaciones
Text

MISSING 

Distinct175
Distinct (%)82.2%
Missing284
Missing (%)57.1%
Memory size4.0 KiB
2024-01-31T13:58:47.400832image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Length

Max length777
Median length192
Mean length90.82159624
Min length1

Characters and Unicode

Total characters19345
Distinct characters78
Distinct categories10 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique166 ?
Unique (%)77.9%

Sample

1st rowQuisiera saber de qué río o de donde viene el agua que uso en mi casa y si no lo estamos destruyendo
2nd rowNinguna
3rd row Me parece que es injusto que las localidades más cercanas a los mantos acuíferos no tengan red hidráulica, lo que hace que tengan que traerla desde los ríos o nacimientos hasta sus casas a través de mangueras que se dañan fácilmente provocado desperdicio de agua por fugas, mordeduras de roedores, etc. En Rancho Viejo solo hay comités de Agua formado por personas de la comunidad y hace difícil conseguir una red por el casiquismo. Las personas no valoran el agua porque no hay tandeos, siempre tienen la llave abierta desperdiciando el líquido porque su cooperación es la misma, no existe medidor para quien ya cuenta con su manguera. Ojo ahí 👀
4th rowno
5th rowA pesar de desconocer ciertas cosas dentro de esta encuesta, me preocupa mi localidad, porque considero que Coatepec y sus alrededores tiene ríos muy bonitos y cada año se contaminan más y más, además de que en lo personal, es triste ver como también la inseguridad afecta las actividades para acudir a ellos (ir a caminar, convivir en familia o amistades, nadar, etc.)
ValueCountFrequency (%)
de 173
 
5.3%
que 128
 
3.9%
y 105
 
3.2%
el 93
 
2.8%
agua 92
 
2.8%
la 92
 
2.8%
en 74
 
2.3%
no 64
 
2.0%
del 62
 
1.9%
a 57
 
1.7%
Other values (966) 2334
71.3%
2024-01-31T13:58:48.427797image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3172
16.4%
e 1989
 
10.3%
a 1979
 
10.2%
o 1287
 
6.7%
s 1129
 
5.8%
n 1121
 
5.8%
r 951
 
4.9%
i 933
 
4.8%
c 764
 
3.9%
u 763
 
3.9%
Other values (68) 5257
27.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 15371
79.5%
Space Separator 3172
 
16.4%
Uppercase Letter 528
 
2.7%
Other Punctuation 239
 
1.2%
Decimal Number 15
 
0.1%
Control 5
 
< 0.1%
Close Punctuation 5
 
< 0.1%
Open Punctuation 5
 
< 0.1%
Dash Punctuation 3
 
< 0.1%
Other Symbol 2
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 1989
12.9%
a 1979
12.9%
o 1287
 
8.4%
s 1129
 
7.3%
n 1121
 
7.3%
r 951
 
6.2%
i 933
 
6.1%
c 764
 
5.0%
u 763
 
5.0%
t 704
 
4.6%
Other values (23) 3751
24.4%
Uppercase Letter
ValueCountFrequency (%)
N 85
16.1%
E 54
10.2%
M 50
 
9.5%
S 46
 
8.7%
A 40
 
7.6%
C 32
 
6.1%
D 26
 
4.9%
O 25
 
4.7%
G 24
 
4.5%
L 19
 
3.6%
Other values (14) 127
24.1%
Other Punctuation
ValueCountFrequency (%)
. 113
47.3%
, 90
37.7%
? 15
 
6.3%
¿ 9
 
3.8%
! 8
 
3.3%
: 3
 
1.3%
@ 1
 
0.4%
Decimal Number
ValueCountFrequency (%)
2 4
26.7%
1 4
26.7%
5 2
13.3%
4 2
13.3%
0 1
 
6.7%
6 1
 
6.7%
3 1
 
6.7%
Other Symbol
ValueCountFrequency (%)
👍 1
50.0%
👀 1
50.0%
Space Separator
ValueCountFrequency (%)
3172
100.0%
Control
ValueCountFrequency (%)
5
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 15899
82.2%
Common 3446
 
17.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 1989
12.5%
a 1979
12.4%
o 1287
 
8.1%
s 1129
 
7.1%
n 1121
 
7.1%
r 951
 
6.0%
i 933
 
5.9%
c 764
 
4.8%
u 763
 
4.8%
t 704
 
4.4%
Other values (47) 4279
26.9%
Common
ValueCountFrequency (%)
3172
92.0%
. 113
 
3.3%
, 90
 
2.6%
? 15
 
0.4%
¿ 9
 
0.3%
! 8
 
0.2%
5
 
0.1%
) 5
 
0.1%
( 5
 
0.1%
2 4
 
0.1%
Other values (11) 20
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 19045
98.4%
None 300
 
1.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3172
16.7%
e 1989
10.4%
a 1979
 
10.4%
o 1287
 
6.8%
s 1129
 
5.9%
n 1121
 
5.9%
r 951
 
5.0%
i 933
 
4.9%
c 764
 
4.0%
u 763
 
4.0%
Other values (58) 4957
26.0%
None
ValueCountFrequency (%)
í 79
26.3%
ó 73
24.3%
á 68
22.7%
é 35
11.7%
ñ 19
 
6.3%
ú 14
 
4.7%
¿ 9
 
3.0%
👍 1
 
0.3%
ü 1
 
0.3%
👀 1
 
0.3%

Interactions

2024-01-31T13:58:09.409503image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-31T13:58:07.840793image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-31T13:58:08.719089image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-31T13:58:09.664749image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-31T13:58:08.221068image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-31T13:58:08.892315image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-31T13:58:09.871142image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-31T13:58:08.483300image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-01-31T13:58:09.158880image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Missing values

2024-01-31T13:58:10.354601image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-31T13:58:11.040227image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

limpio_fechalimpio_generolimpio_edadlimpio_nivel_estudioslimpio_actividad_economicalimpio_cplimpio_contextolimpio_municipiolimpio_colonialimpio_habitanteslimpio_tipo_casalimpio_disponibilidad_agualimpio_mes_sin_serviciolimpio_dias_sin_servlimpio_razon_NA_checarlimpio_obtencion_agualimpio_almacenamientolimpio_acarreolimpio_fuente_abastolimpio_nombre_fuentelimpio_instancialimpio_gasto_agualimpio_usoslimpio_valoracion_serviciolimpio_informacion_calidadlimpio_agua_beberlimpio_percepcion_pagolimpio_freq_pagolimpio_entidad_pagolimpio_visita_cuerpolimpio_negativa_visitalimpio_afimartiva_visitalimpio_cuerpo_cercanolimpio_nombre_rio_cercanolimpio_percepcion_seguridad_rio_cercanolimpio_tipo_bañolimpio_seguridad_bañolimpio_conoce_responsable_saneamientolimpio_responsable_saneamientolimpio_destino_agua_servidalimpio_separacion_negra_grislimpio_vertido_aguas_griseslimpio_destino_drenajelimpio_incluye_pago_saneamientolimpio_percep_calidad_serviciolimpio_percep_costo_saneamientolimpio_sabe_uso_dinero_tarifa_saneamientolimpio_conocimiento_gestion_integral_participativalimpio_participacion_gestion_participativalimpio_iniciativas_conocidaslimpio_conocimiento_iniciativalimpio_conocimiento_iniciativas_saneamientolimpio_conocimiento_art_1_y₄limpio_observaciones
0NaTNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
12022-10-25 09:59:13.806Femenino24.0UniversidadNo, actualmente desempleado91320.0RuralAcajeteCentro3.0Casa única en el terrenoNoMarzo, Abril, Mayo4 a 6NaNNaNCubetas, Tinaco, PiletaFemenino, 54 / Femenino, 24RíoNaNDesconozco150Lavar trastes/Limpieza de vivienda/BañoRegularGarrafón/EmbotelladaLo justoAnualCMASNaNRealizar limpiezaRíoSedeñoNoBaño (taza) de agua integrado a la casaNaNNoNaNPozo de absorciónNoNaNNaNNo pagoMaloRegularNaNNoNoNaNNaNNaNSiNaN
22022-10-25 10:19:43.177Masculino27.0UniversidadSí, negocio propio formal91050.0UrbanoXalapaTamborel4.0Casa única en el terrenoNingún mesNo faltaNo aplicaNaNTinacoNaNDesconozcoNaNCMAS100Limpieza de vivienda/Lavar ropaExcelenteNoGarrafón/EmbotelladaNadaMensualCMASNaNActividad recreativaRíoPixquiacAlgunosBaño (taza) de agua integrado a la casaNaNSiCMASDrenajeNoNaNSí/A los ríosPésimoInaceptableNoNo séNoNaNNaNNaNNoNaN
32022-10-25 10:30:20.585Femenino28.0UniversidadSí, asalariado/a-recibe un sueldo fijo91100.0UrbanoXalapaRevolución2.0Casa única en el terrenoNingún mesNo faltaNo aplicaDe ningún ladoTinacoNo aplicaRíoPixquiacCMAS100TodasBuenaNoGarrafón/EmbotelladaPocoMensualCMASNaNMonitorear su estado/Una vez al mesManantialManantial LagunillaNoBaño (taza) de agua integrado a la casaNaNSiCMASDrenajeNoNaNSí/A los ríosPésimoPocoSí/MantenimientoAmigos del río Pixquiac, Parque lineal QuetzalapaNaNSiNaN
42022-10-25 10:45:20.144Femenino33.0PosgradoSí, asalariado/a-recibe un sueldo fijo91017.0UrbanoXalapaRafael Hernández Ochoa4.0Casa que comparte terreno con otra (s)NoJulio4 a 6Por ReparaciónDe ningún ladoTamboNo aplicaPresaSedeñoCMAS20NaNBuenaNoGarrafón/EmbotelladaLo justoMensualCMASNaNActividad recreativaRíoSedeñoTal vezBaño (taza) de agua integrado a la casaNaNSiCMASDrenajeNaNSí/Al cañoMaloRegularNoNoNoNingunaNoNaNNoNaN
52022-10-25 10:59:49.364Femenino42.0PosgradoSí, asalariado/a-recibe un sueldo fijo91584.0UrbanoCoatepecFraccionamiento San José4.0Casa única en el terrenoNingún mesNo faltaNo aplicaPipaCisternaNaNDesconozcoNaNCMAS120Baño/Lavar trastes/Lavar ropaExcelenteNoDe la llave con filtroMuchoMensualCMASNaNActividad recreativa/Cada dos mesesRíoPixquiacNoBaño (taza) de agua integrado a la casaNaNSiCMASDrenajeNoNaNSí/A los ríosDesconozcoPésimoInaceptableSí/Para extender la red de abastecimientoNoNoNaNNoDesconozcoNoNaN
62022-10-25 11:12:24.308Femenino31.0UniversidadSí, negocio propio informal91190.0UrbanoXalapaLos Cántaros2.0Casa única en el terrenoNoMayoNo faltaNo aplicaTinacoTinacoNaNPresaDesconozcoCMASDesconozcoBaño/Lavar trastes/Lavar ropaExcelenteNoGarrafón/EmbotelladaLo justoMensualCMASNoDesconozco cuál esNaNNo lo séNaNTal vezBaño (taza) de agua integrado a la casaNaNNoNaNDrenajeNo séNaNNoDesconozcoBuenoBuenoNoNoNoNaNNoNaNSiQuisiera saber de qué río o de donde viene el agua que uso en mi casa y si no lo estamos destruyendo
72022-10-25 11:37:52.599Femenino50.0PosgradoSí, asalariado/a-recibe un sueldo fijo91540.0UrbanoCoatepecCampo Viejo2.0Casa única en el terrenoMayo, JunioNo faltaNo aplicaCisternaCisternaNo aplicaDesconozcoRío PixquiacCMAS50Beber/Baño/Limpieza de viviendaBuenaNoDe la llave con filtroMuchoMensualCMASNoDesconozco cuál esNaNNo lo séNaNNoBaño (taza) de agua integrado a la casaNaNNoNaNDrenajeNo séNaNNoMaloRegularNoNoAgua pasa por mi casa, Custodios del archipielagoNoDesconozcoNoNaN
82022-10-25 11:45:57.456Femenino32.0PosgradoSí, por comisiones91070.0UrbanoXalapaFrancisco I. Madero2.0Casa única en el terrenoNingún mesNo faltaNo aplicaLluviaCubetasNo aplicaPresaNaNGestión Propia80Limpieza de vivienda/Cocinar/BañoBuenaNoDe la llave con filtroLo justoMensualCMASNoDesconozco cuál esNaNAguas negrasNaNNoBaño (taza) de agua integrado a la casaNaNSiCMASDrenajeNo séNaNNoDesconozcoNaNNaNNoConservación y cuidado del río PixquiacNoNaNSiNaN
92022-10-25 11:49:32.884Masculino32.0UniversidadSí, asalariado/a-recibe un sueldo fijo91025.0UrbanoXalapaArroyo Blanco5.0Casa que comparte terreno con otra (s)Marzo, Abril1 a 3Aguas TurbiasLluviaCubetasNaNRíoHuitzilapanCMAS160Lavar trastes/Limpieza de vivienda/Baño/Cocinar/Ducha/Regar plantasBuenaNoGarrafón/EmbotelladaLo justoAnualCMASNoEstá en Propiedad PrivadaNaNRíoPixquiacNoBaño (taza) de cubeta en exterior (caseta)SiSiCMASDrenajeNoNaNSí/A los ríosMaloRegularNoNoNoNaNNaNNaNNoNaN
limpio_fechalimpio_generolimpio_edadlimpio_nivel_estudioslimpio_actividad_economicalimpio_cplimpio_contextolimpio_municipiolimpio_colonialimpio_habitanteslimpio_tipo_casalimpio_disponibilidad_agualimpio_mes_sin_serviciolimpio_dias_sin_servlimpio_razon_NA_checarlimpio_obtencion_agualimpio_almacenamientolimpio_acarreolimpio_fuente_abastolimpio_nombre_fuentelimpio_instancialimpio_gasto_agualimpio_usoslimpio_valoracion_serviciolimpio_informacion_calidadlimpio_agua_beberlimpio_percepcion_pagolimpio_freq_pagolimpio_entidad_pagolimpio_visita_cuerpolimpio_negativa_visitalimpio_afimartiva_visitalimpio_cuerpo_cercanolimpio_nombre_rio_cercanolimpio_percepcion_seguridad_rio_cercanolimpio_tipo_bañolimpio_seguridad_bañolimpio_conoce_responsable_saneamientolimpio_responsable_saneamientolimpio_destino_agua_servidalimpio_separacion_negra_grislimpio_vertido_aguas_griseslimpio_destino_drenajelimpio_incluye_pago_saneamientolimpio_percep_calidad_serviciolimpio_percep_costo_saneamientolimpio_sabe_uso_dinero_tarifa_saneamientolimpio_conocimiento_gestion_integral_participativalimpio_participacion_gestion_participativalimpio_iniciativas_conocidaslimpio_conocimiento_iniciativalimpio_conocimiento_iniciativas_saneamientolimpio_conocimiento_art_1_y₄limpio_observaciones
4872023-05-14 16:27:29.491Masculino51.0PosgradoSí, asalariado/a-recibe un sueldo fijo91026.0UrbanoXalapaFrancisco Ferrer Guardia2.0DepartamentoNoAbril, Mayo7 a 9Por TandeosDe ningún ladoTinacoNo aplicaDesconozcoDesconozcoNaN160Lavar trastes/Lavar ropa/Baño/DuchaBuenaNoGarrafón/EmbotelladaPocoMensualEstá incluido en el pago de mi rentaNoEstá contaminadoNaNRíoSordoNoBaño (taza) de agua integrado a la casaNaNNoNaNDrenajeNoNaNNoDesconozcoRegularPocoNoNoNoNaNNoNaNSiNaN
4882023-05-14 18:14:15.549Femenino65.0UniversidadSí, asalariado/a-recibe un sueldo fijo91560.0UrbanoCoatepecEmiliano Zapata1.0Casa única en el terrenoNingún mesNo faltaNo aplicaDe ningún ladoCubetasNaNDesconozcoNaNNaN50Baño/Lavar trastes/Beber/MascotasBuenaNoDe la llave con filtroMuchoMensualCMASNoEstá contaminadoNaNRíoPixquiacNoBaño (taza) de agua integrado a la casaNaNSiCMASDrenajeNoNaNNoBuenoPocoSí/Tratamiento de aguasNoAutogestiónNoNaNNoGracias por recordarnos que TODXS tenemos derecho de vivir en las mejores condiciones incluyendo , por supuesto el abastecimiento de agua potable para nuestras necesidades de vida.
4892023-05-14 21:50:31.414Femenino38.0UniversidadSí, asalariado/a-recibe un sueldo fijo91050.0UrbanoXalapaSalud1.0DepartamentoNingún mesNo faltaNo aplicaNaNTinacoNaNDesconozcoDesconozcoNaNDesconozcoDucha/Baño/Lavar trastes/BeberExcelenteNoDe la llave con filtroPocoNo pagoEstá incluido en el pago de mi rentaNaNActividad recreativa/Fines de semanaRíoPixquiacTal vezBaño (taza) de agua integrado a la casaNaNNoNaNDrenajeNo séNaNNoDesconozcoNaNNaNNoINECOL, HuitzilapanDesconozcoNoGracias por hacer este ejercicio. Me di cuenta que desconozco de dónde viene y a dónde va el agua que ocupo cotidianamente
4902023-05-14 23:11:44.701Masculino38.0UniversidadSí, asalariado/a-recibe un sueldo fijo91240.0UrbanoXicoCentro2.0Casa única en el terrenoNingún mesNo faltaNo aplicaNacimiento/RíoTinacoMasculino, 38ManantialDesconozcoNaN100Lavar trastes/Lavar ropa/Limpieza de viviendaExcelenteNoGarrafón/EmbotelladaLo justoMensualCMASNaNActividad recreativaRíoDesconozcoTal vezBaño (taza) de agua integrado a la casaNaNNoNaNDrenajeNo séNaNNoRegularBuenoNoNoNoDesconozcoNoDesconozcoSiNo
4912023-05-15 07:31:59.075Femenino63.0UniversidadNo, labores del hogar de tiempo completo91517.0RuralCoatepecLa Pitaya3.0Casa única en el terrenoMarzo, AbrilNo faltaNo aplicaNaNNaNNaNManantialDesconozcoNaN250Ducha/Cocinar/Lavar ropa/Lavar trastesExcelenteDe la llave con filtroPocoAnualCMASNaNRitualRíoPixquiacBaño seco incorporado a la casaSiSiA todosBiodigestor anaeróbicoNoTodo al biodigestorNaNDesconozcoNaNNaNNoNoSENDAS, Global water watchGestión PropiaNoGracias!!!!
4922023-05-15 12:17:55.984Masculino32.0UniversidadSí, asalariado/a-recibe un sueldo fijo91030.0UrbanoXalapaJosé Cardel5.0Casa única en el terrenoMayoNo faltaNo aplicaDe ningún ladoTinacoNo aplicaPresaPresa de los ColibríesNaN220Limpieza de viviendaBuenaNoGarrafón/EmbotelladaLo justoMensualCMASNoEstá contaminadoNaNLago, LagunaLos LagosNoBaño (taza) de agua integrado a la casaNaNSiCMASDrenajeNo séNaNSí/Al arroyoMaloRegularNoNoNoNaNNoNaNSiNaN
4932023-05-16 06:56:15.906Femenino38.0PosgradoSí, asalariado/a-recibe un sueldo fijo91094.0UrbanoXalapaMártires de Chicago4.0Casa única en el terrenoMarzo4 a 6Por TandeosVecinosCisterna, TinacoNaNRíoSedeñoNaN120Baño/Lavar trastes/Lavar ropa/Mascotas/Regar plantas/Cocinar/DuchaExcelenteNoDe la llave con filtroMuchoMensualCMASNaNActividad recreativa/TrimestralManantialEl ChorritoNoBaño (taza) de agua integrado a la casaNaNSiCMASDrenajeNoNaNTal vez/A los ríosBuenoRegularNaNNoNaNNoNaNSiNaN
4942023-05-16 18:39:27.253Femenino43.0UniversidadSí, asalariado/a-recibe un sueldo fijo91180.0UrbanoXalapaSebastian Lerdo de Tejada5.0Casa única en el terrenoNoAbril, Mayo1 a 3Por TandeosGarrafónTambo, CisternaMasculino, 43 / Femenino, 43RíoDesconozcoNaNDesconozcoLavar trastes/Lavar ropa/BañoBuenaNoGarrafón/EmbotelladaMuchoAnualCMASNaNNaNRíoPixquiacNoBaño (taza) de agua integrado a la casaNaNNoNaNDrenajeNoNaNNoRegularRegularNoNoNoDesconozcoNoDesconozcoSiOrganización ciudadana para cerrar empresas como coca cola y Nestlé en coatepec que tienen agua los 365 días del año para la elaboración de productos dañinos para la salud. Existe incongruencia
4952023-05-17 22:41:19.984Femenino38.0PosgradoSí, por comisiones91057.0UrbanoXalapaCoapexpan4.0Casa única en el terrenoNoMarzo, Abril4 a 6Por TandeosTinacoTinacoNingunoRíoPixquiacNaN30Lavar trastes/Lavar ropa/Cocinar/BañoBuenaNoDe la llave con filtroPocoMensualCMASNaNActividad recreativaRíoPixquiacNoBaño (taza) de agua integrado a la casaNaNSiCMASDrenajeNoNaNTal vez/Planta de tratamientoBuenoPocoSí/MantenimientoNoAutogestiónNoFideagua, Porgrama PixquiacNoCompartan información sobre estos temas para público general
4962023-05-21 12:53:42.392Masculino36.0UniversidadSí, asalariado/a-recibe un sueldo fijo91247.0RuralXicoSan Marcos4.0Casa única en el terrenoMayo, Junio1 a 3NaNNaNTinacoMasculino, 34 / Masculino, 36ManantialAgua BenditaNaN80Lavar ropa/Cocinar/BañoBuenaNoHervidaLo justoMensualCMASNoNaNNaNRíoHuehueyapanTal vezBaño (taza) de agua integrado a la casaNaNNoNaNDrenajeNoNaNNoRegularRegularNaNNo séNoNaNNaNNaNSiNaN