Overview

Dataset statistics

Number of variables35
Number of observations408
Missing cells37
Missing cells (%)0.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory111.7 KiB
Average record size in memory280.3 B

Variable types

DateTime1
Categorical23
Numeric1
Unsupported1
Text9

Dataset

DescriptionPerfil de variables del formulario percepciones coco
Creatorinecol, UV
Authorinecol, UV
URL
Copyright(c) inecol, UV 2024

Alerts

l_Una vez que haya decidido participar, le solicitamos que acepte esta forma de consentimiento. is highly imbalanced (95.5%)Imbalance
l_municipio is highly imbalanced (62.7%)Imbalance
l_arboles_cerca is highly imbalanced (67.7%)Imbalance
l_area_verde_casa is highly imbalanced (61.8%)Imbalance
l_importancia_av_crisis_sanitaria is highly imbalanced (63.8%)Imbalance
l_vive_urb_quiere_rural is highly imbalanced (68.9%)Imbalance
l_habitantes_casa is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-08-02 19:50:19.505722
Analysis finished2024-08-02 19:50:23.438271
Duration3.93 seconds
Software versionydata-profiling vv4.6.4
Download configurationconfig.json

Variables

l_Marca temporal
Date

Distinct407
Distinct (%)100.0%
Missing1
Missing (%)0.2%
Memory size3.3 KiB
Minimum2020-10-22 10:58:43.180000
Maximum2022-05-11 12:24:53.990000
2024-08-02T13:50:23.578866image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
2024-08-02T13:50:24.034408image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

l_Una vez que haya decidido participar, le solicitamos que acepte esta forma de consentimiento.
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.5%
Missing1
Missing (%)0.2%
Memory size3.3 KiB
Sí acepto participar
405 
No acepto participar
 
2

Length

Max length20
Median length20
Mean length20
Min length20

Characters and Unicode

Total characters8140
Distinct characters12
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 rowSí acepto participar
2nd rowSí acepto participar
3rd rowSí acepto participar
4th rowSí acepto participar
5th rowSí acepto participar

Common Values

ValueCountFrequency (%)
Sí acepto participar 405
99.3%
No acepto participar 2
 
0.5%
(Missing) 1
 
0.2%

Length

2024-08-02T13:50:24.361187image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-08-02T13:50:24.691850image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
acepto 407
33.3%
participar 407
33.3%
sí 405
33.2%
no 2
 
0.2%

Most occurring characters

ValueCountFrequency (%)
a 1221
15.0%
p 1221
15.0%
814
10.0%
c 814
10.0%
t 814
10.0%
r 814
10.0%
i 814
10.0%
o 409
 
5.0%
e 407
 
5.0%
S 405
 
5.0%
Other values (2) 407
 
5.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 6919
85.0%
Space Separator 814
 
10.0%
Uppercase Letter 407
 
5.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 1221
17.6%
p 1221
17.6%
c 814
11.8%
t 814
11.8%
r 814
11.8%
i 814
11.8%
o 409
 
5.9%
e 407
 
5.9%
í 405
 
5.9%
Uppercase Letter
ValueCountFrequency (%)
S 405
99.5%
N 2
 
0.5%
Space Separator
ValueCountFrequency (%)
814
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 7326
90.0%
Common 814
 
10.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 1221
16.7%
p 1221
16.7%
c 814
11.1%
t 814
11.1%
r 814
11.1%
i 814
11.1%
o 409
 
5.6%
e 407
 
5.6%
S 405
 
5.5%
í 405
 
5.5%
Common
ValueCountFrequency (%)
814
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7735
95.0%
None 405
 
5.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 1221
15.8%
p 1221
15.8%
814
10.5%
c 814
10.5%
t 814
10.5%
r 814
10.5%
i 814
10.5%
o 409
 
5.3%
e 407
 
5.3%
S 405
 
5.2%
None
ValueCountFrequency (%)
í 405
100.0%

l_Sexo
Categorical

Distinct2
Distinct (%)0.5%
Missing1
Missing (%)0.2%
Memory size3.3 KiB
Mujer
274 
Hombre
133 

Length

Max length6
Median length5
Mean length5.326781327
Min length5

Characters and Unicode

Total characters2168
Distinct characters9
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 rowMujer
2nd rowMujer
3rd rowMujer
4th rowHombre
5th rowMujer

Common Values

ValueCountFrequency (%)
Mujer 274
67.2%
Hombre 133
32.6%
(Missing) 1
 
0.2%

Length

2024-08-02T13:50:24.989478image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-08-02T13:50:25.263698image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
mujer 274
67.3%
hombre 133
32.7%

Most occurring characters

ValueCountFrequency (%)
e 407
18.8%
r 407
18.8%
M 274
12.6%
u 274
12.6%
j 274
12.6%
H 133
 
6.1%
o 133
 
6.1%
m 133
 
6.1%
b 133
 
6.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 1761
81.2%
Uppercase Letter 407
 
18.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 407
23.1%
r 407
23.1%
u 274
15.6%
j 274
15.6%
o 133
 
7.6%
m 133
 
7.6%
b 133
 
7.6%
Uppercase Letter
ValueCountFrequency (%)
M 274
67.3%
H 133
32.7%

Most occurring scripts

ValueCountFrequency (%)
Latin 2168
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 407
18.8%
r 407
18.8%
M 274
12.6%
u 274
12.6%
j 274
12.6%
H 133
 
6.1%
o 133
 
6.1%
m 133
 
6.1%
b 133
 
6.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2168
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 407
18.8%
r 407
18.8%
M 274
12.6%
u 274
12.6%
j 274
12.6%
H 133
 
6.1%
o 133
 
6.1%
m 133
 
6.1%
b 133
 
6.1%

l_Edad
Categorical

Distinct14
Distinct (%)3.4%
Missing1
Missing (%)0.2%
Memory size3.3 KiB
41-45
69 
36-40
65 
31-35
55 
46-50
39 
51-55
32 
Other values (9)
147 

Length

Max length12
Median length5
Mean length5.250614251
Min length5

Characters and Unicode

Total characters2137
Distinct characters15
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

Unique3 ?
Unique (%)0.7%

Sample

1st row51-55
2nd row26-30
3rd row31-35
4th row66 o más
5th row26-30

Common Values

ValueCountFrequency (%)
41-45 69
16.9%
36-40 65
15.9%
31-35 55
13.5%
46-50 39
9.6%
51-55 32
7.8%
21-25 30
7.4%
26-30 29
7.1%
56-60 28
6.9%
66 o más 27
 
6.6%
61-65 25
 
6.1%
Other values (4) 8
 
2.0%

Length

2024-08-02T13:50:25.586321image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
41-45 69
14.9%
36-40 65
14.0%
31-35 56
12.1%
46-50 39
8.4%
51-55 32
6.9%
21-25 32
6.9%
26-30 30
6.5%
56-60 29
6.2%
66 27
 
5.8%
o 27
 
5.8%
Other values (3) 58
12.5%

Most occurring characters

ValueCountFrequency (%)
- 383
17.9%
5 346
16.2%
6 296
13.9%
4 242
11.3%
1 220
10.3%
3 207
9.7%
0 169
7.9%
2 100
 
4.7%
57
 
2.7%
o 27
 
1.3%
Other values (5) 90
 
4.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1586
74.2%
Dash Punctuation 383
 
17.9%
Lowercase Letter 108
 
5.1%
Space Separator 57
 
2.7%
Other Punctuation 3
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 346
21.8%
6 296
18.7%
4 242
15.3%
1 220
13.9%
3 207
13.1%
0 169
10.7%
2 100
 
6.3%
8 6
 
0.4%
Lowercase Letter
ValueCountFrequency (%)
o 27
25.0%
m 27
25.0%
á 27
25.0%
s 27
25.0%
Dash Punctuation
ValueCountFrequency (%)
- 383
100.0%
Space Separator
ValueCountFrequency (%)
57
100.0%
Other Punctuation
ValueCountFrequency (%)
, 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2029
94.9%
Latin 108
 
5.1%

Most frequent character per script

Common
ValueCountFrequency (%)
- 383
18.9%
5 346
17.1%
6 296
14.6%
4 242
11.9%
1 220
10.8%
3 207
10.2%
0 169
8.3%
2 100
 
4.9%
57
 
2.8%
8 6
 
0.3%
Latin
ValueCountFrequency (%)
o 27
25.0%
m 27
25.0%
á 27
25.0%
s 27
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2110
98.7%
None 27
 
1.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 383
18.2%
5 346
16.4%
6 296
14.0%
4 242
11.5%
1 220
10.4%
3 207
9.8%
0 169
8.0%
2 100
 
4.7%
57
 
2.7%
o 27
 
1.3%
Other values (4) 63
 
3.0%
None
ValueCountFrequency (%)
á 27
100.0%

l_Último nivel de estudios completo
Categorical

Distinct4
Distinct (%)1.0%
Missing1
Missing (%)0.2%
Memory size3.3 KiB
Posgrado
196 
Licenciatura
173 
Bachillerato
31 
Secundaria
 
7

Length

Max length12
Median length12
Mean length10.03931204
Min length8

Characters and Unicode

Total characters4086
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 rowPosgrado
2nd rowLicenciatura
3rd rowLicenciatura
4th rowPosgrado
5th rowPosgrado

Common Values

ValueCountFrequency (%)
Posgrado 196
48.0%
Licenciatura 173
42.4%
Bachillerato 31
 
7.6%
Secundaria 7
 
1.7%
(Missing) 1
 
0.2%

Length

2024-08-02T13:50:25.944757image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-08-02T13:50:26.257772image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
posgrado 196
48.2%
licenciatura 173
42.5%
bachillerato 31
 
7.6%
secundaria 7
 
1.7%

Most occurring characters

ValueCountFrequency (%)
a 618
15.1%
o 423
10.4%
r 407
10.0%
c 384
9.4%
i 384
9.4%
e 211
 
5.2%
t 204
 
5.0%
d 203
 
5.0%
P 196
 
4.8%
g 196
 
4.8%
Other values (8) 860
21.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 3679
90.0%
Uppercase Letter 407
 
10.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 618
16.8%
o 423
11.5%
r 407
11.1%
c 384
10.4%
i 384
10.4%
e 211
 
5.7%
t 204
 
5.5%
d 203
 
5.5%
g 196
 
5.3%
s 196
 
5.3%
Other values (4) 453
12.3%
Uppercase Letter
ValueCountFrequency (%)
P 196
48.2%
L 173
42.5%
B 31
 
7.6%
S 7
 
1.7%

Most occurring scripts

ValueCountFrequency (%)
Latin 4086
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 618
15.1%
o 423
10.4%
r 407
10.0%
c 384
9.4%
i 384
9.4%
e 211
 
5.2%
t 204
 
5.0%
d 203
 
5.0%
P 196
 
4.8%
g 196
 
4.8%
Other values (8) 860
21.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4086
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 618
15.1%
o 423
10.4%
r 407
10.0%
c 384
9.4%
i 384
9.4%
e 211
 
5.2%
t 204
 
5.0%
d 203
 
5.0%
P 196
 
4.8%
g 196
 
4.8%
Other values (8) 860
21.0%

l_¿Es actualmente empleado de un trabajo remunerado?
Categorical

Distinct17
Distinct (%)4.2%
Missing1
Missing (%)0.2%
Memory size3.3 KiB
Si, asalariado/recibe un sueldo fijo
220 
No, estudiante de tiempo completo
44 
Si, negocio propio informal
29 
Si, negocio propio formal
25 
No, jubilado
 
22
Other values (12)
67 

Length

Max length83
Median length36
Mean length33.4004914
Min length12

Characters and Unicode

Total characters13594
Distinct characters24
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

Unique5 ?
Unique (%)1.2%

Sample

1st rowSi, asalariado/recibe un sueldo fijo
2nd rowSi, asalariado/recibe un sueldo fijo
3rd rowSi, asalariado/recibe un sueldo fijo
4th rowNo, jubilado
5th rowNo, estudiante de tiempo completo

Common Values

ValueCountFrequency (%)
Si, asalariado/recibe un sueldo fijo 220
53.9%
No, estudiante de tiempo completo 44
 
10.8%
Si, negocio propio informal 29
 
7.1%
Si, negocio propio formal 25
 
6.1%
No, jubilado 22
 
5.4%
No, labores del hogar de tiempo completo 18
 
4.4%
No, actualmente desempleado 17
 
4.2%
Si, por comisiones 14
 
3.4%
Si, asalariado/recibe un sueldo fijo, Si, negocio propio formal 6
 
1.5%
Si, asalariado/recibe un sueldo fijo, Si, negocio propio informal 3
 
0.7%
Other values (7) 9
 
2.2%

Length

2024-08-02T13:50:26.612841image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
si 317
16.7%
un 232
12.2%
sueldo 232
12.2%
fijo 232
12.2%
asalariado/recibe 232
12.2%
no 109
 
5.8%
negocio 67
 
3.5%
propio 67
 
3.5%
tiempo 66
 
3.5%
completo 66
 
3.5%
Other values (11) 274
14.5%

Most occurring characters

ValueCountFrequency (%)
1553
11.4%
o 1477
10.9%
i 1349
 
9.9%
e 1211
 
8.9%
a 1165
 
8.6%
l 702
 
5.2%
d 659
 
4.8%
r 658
 
4.8%
s 586
 
4.3%
u 552
 
4.1%
Other values (14) 3682
27.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 10938
80.5%
Space Separator 1553
 
11.4%
Other Punctuation 677
 
5.0%
Uppercase Letter 426
 
3.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 1477
13.5%
i 1349
12.3%
e 1211
11.1%
a 1165
10.7%
l 702
 
6.4%
d 659
 
6.0%
r 658
 
6.0%
s 586
 
5.4%
u 552
 
5.0%
n 414
 
3.8%
Other values (9) 2165
19.8%
Other Punctuation
ValueCountFrequency (%)
, 445
65.7%
/ 232
34.3%
Uppercase Letter
ValueCountFrequency (%)
S 317
74.4%
N 109
 
25.6%
Space Separator
ValueCountFrequency (%)
1553
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 11364
83.6%
Common 2230
 
16.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 1477
13.0%
i 1349
11.9%
e 1211
10.7%
a 1165
10.3%
l 702
 
6.2%
d 659
 
5.8%
r 658
 
5.8%
s 586
 
5.2%
u 552
 
4.9%
n 414
 
3.6%
Other values (11) 2591
22.8%
Common
ValueCountFrequency (%)
1553
69.6%
, 445
 
20.0%
/ 232
 
10.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 13594
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1553
11.4%
o 1477
10.9%
i 1349
 
9.9%
e 1211
 
8.9%
a 1165
 
8.6%
l 702
 
5.2%
d 659
 
4.8%
r 658
 
4.8%
s 586
 
4.3%
u 552
 
4.1%
Other values (14) 3682
27.1%

l_empleado
Categorical

Distinct3
Distinct (%)0.7%
Missing1
Missing (%)0.2%
Memory size3.3 KiB
Si
302 
No
104 
Sí
 
1

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters814
Distinct characters5
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

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
Si 302
74.0%
No 104
 
25.5%
Sí 1
 
0.2%
(Missing) 1
 
0.2%

Length

2024-08-02T13:50:26.935829image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-08-02T13:50:27.205864image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
si 302
74.2%
no 104
 
25.6%
sí 1
 
0.2%

Most occurring characters

ValueCountFrequency (%)
S 303
37.2%
i 302
37.1%
N 104
 
12.8%
o 104
 
12.8%
í 1
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 407
50.0%
Lowercase Letter 407
50.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i 302
74.2%
o 104
 
25.6%
í 1
 
0.2%
Uppercase Letter
ValueCountFrequency (%)
S 303
74.4%
N 104
 
25.6%

Most occurring scripts

ValueCountFrequency (%)
Latin 814
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
S 303
37.2%
i 302
37.1%
N 104
 
12.8%
o 104
 
12.8%
í 1
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 813
99.9%
None 1
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
S 303
37.3%
i 302
37.1%
N 104
 
12.8%
o 104
 
12.8%
None
ValueCountFrequency (%)
í 1
100.0%

l_status
Categorical

Distinct16
Distinct (%)3.9%
Missing1
Missing (%)0.2%
Memory size3.3 KiB
Asalariado/Sueldo fijo
220 
Estudiante de tiempo completo
44 
Negocio propio informal
29 
Negocio propio formal
25 
Jubilado
 
22
Other values (11)
67 

Length

Max length59
Median length22
Mean length22.68796069
Min length8

Characters and Unicode

Total characters9234
Distinct characters29
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

Unique5 ?
Unique (%)1.2%

Sample

1st rowAsalariado/Sueldo fijo
2nd rowAsalariado/Sueldo fijo
3rd rowAsalariado/Sueldo fijo
4th rowJubilado
5th rowEstudiante de tiempo completo

Common Values

ValueCountFrequency (%)
Asalariado/Sueldo fijo 220
53.9%
Estudiante de tiempo completo 44
 
10.8%
Negocio propio informal 29
 
7.1%
Negocio propio formal 25
 
6.1%
Jubilado 22
 
5.4%
Desempleado 19
 
4.7%
Labores del hogar de tiempo completo 18
 
4.4%
Por comisiones 14
 
3.4%
Asalariado/Sueldo fijo/Negocio propio formal 6
 
1.5%
Asalariado/Sueldo fijo/Negocio propio informal 3
 
0.7%
Other values (6) 7
 
1.7%

Length

2024-08-02T13:50:27.531802image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
asalariado/sueldo 232
24.2%
fijo 220
23.0%
propio 67
 
7.0%
tiempo 64
 
6.7%
completo 64
 
6.7%
negocio 56
 
5.9%
estudiante 44
 
4.6%
formal 33
 
3.4%
informal 32
 
3.3%
jubilado 22
 
2.3%
Other values (12) 123
12.9%

Most occurring characters

ValueCountFrequency (%)
o 1358
14.7%
a 889
 
9.6%
i 798
 
8.6%
l 657
 
7.1%
e 651
 
7.1%
d 634
 
6.9%
613
 
6.6%
r 422
 
4.6%
s 352
 
3.8%
u 300
 
3.2%
Other values (19) 2560
27.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 7716
83.6%
Uppercase Letter 656
 
7.1%
Space Separator 613
 
6.6%
Other Punctuation 249
 
2.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 1358
17.6%
a 889
11.5%
i 798
10.3%
l 657
8.5%
e 651
8.4%
d 634
8.2%
r 422
 
5.5%
s 352
 
4.6%
u 300
 
3.9%
f 299
 
3.9%
Other values (9) 1356
17.6%
Uppercase Letter
ValueCountFrequency (%)
A 232
35.4%
S 232
35.4%
N 67
 
10.2%
E 45
 
6.9%
J 23
 
3.5%
D 20
 
3.0%
L 19
 
2.9%
P 18
 
2.7%
Space Separator
ValueCountFrequency (%)
613
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 249
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 8372
90.7%
Common 862
 
9.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 1358
16.2%
a 889
10.6%
i 798
 
9.5%
l 657
 
7.8%
e 651
 
7.8%
d 634
 
7.6%
r 422
 
5.0%
s 352
 
4.2%
u 300
 
3.6%
f 299
 
3.6%
Other values (17) 2012
24.0%
Common
ValueCountFrequency (%)
613
71.1%
/ 249
28.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 9234
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o 1358
14.7%
a 889
 
9.6%
i 798
 
8.6%
l 657
 
7.1%
e 651
 
7.1%
d 634
 
6.9%
613
 
6.6%
r 422
 
4.6%
s 352
 
3.8%
u 300
 
3.2%
Other values (19) 2560
27.7%

l_cp
Real number (ℝ)

Distinct113
Distinct (%)27.8%
Missing1
Missing (%)0.2%
Infinite0
Infinite (%)0.0%
Mean88816.20639
Minimum1130
Maximum111166
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.3 KiB
2024-08-02T13:50:27.929389image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Quantile statistics

Minimum1130
5-th percentile91000
Q191056
median91110
Q391500
95-th percentile91637
Maximum111166
Range110036
Interquartile range (IQR)444

Descriptive statistics

Standard deviation13092.64571
Coefficient of variation (CV)0.1474128004
Kurtosis30.35950618
Mean88816.20639
Median Absolute Deviation (MAD)90
Skewness-5.514445342
Sum36148196
Variance171417371.6
MonotonicityNot monotonic
2024-08-02T13:50:28.226514image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
91500 51
 
12.5%
91000 31
 
7.6%
91070 24
 
5.9%
91190 18
 
4.4%
91080 13
 
3.2%
91020 12
 
2.9%
91637 12
 
2.9%
91130 10
 
2.5%
91517 10
 
2.5%
91097 10
 
2.5%
Other values (103) 216
52.9%
ValueCountFrequency (%)
1130 1
 
0.2%
8030 1
 
0.2%
9040 1
 
0.2%
9100 4
1.0%
9109 1
 
0.2%
ValueCountFrequency (%)
111166 1
0.2%
96460 1
0.2%
94300 1
0.2%
94180 1
0.2%
94140 1
0.2%

l_municipio
Categorical

IMBALANCE 

Distinct20
Distinct (%)4.9%
Missing1
Missing (%)0.2%
Memory size3.3 KiB
Xalapa
269 
Coatepec
92 
Emiliano Zapata
 
14
Banderilla
 
10
Tlalnelhuayocan
 
3
Other values (15)
 
19

Length

Max length18
Median length6
Mean length7.152334152
Min length6

Characters and Unicode

Total characters2911
Distinct characters37
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

Unique12 ?
Unique (%)2.9%

Sample

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

Common Values

ValueCountFrequency (%)
Xalapa 269
65.9%
Coatepec 92
 
22.5%
Emiliano Zapata 14
 
3.4%
Banderilla 10
 
2.5%
Tlalnelhuayocan 3
 
0.7%
Estado de México 3
 
0.7%
Puebla 2
 
0.5%
Altotonga 2
 
0.5%
Huatusco 1
 
0.2%
Palenque 1
 
0.2%
Other values (10) 10
 
2.5%

Length

2024-08-02T13:50:28.427649image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
xalapa 269
62.9%
coatepec 92
 
21.5%
emiliano 14
 
3.3%
zapata 14
 
3.3%
banderilla 10
 
2.3%
méxico 4
 
0.9%
tlalnelhuayocan 3
 
0.7%
estado 3
 
0.7%
altotonga 2
 
0.5%
puebla 2
 
0.5%
Other values (15) 15
 
3.5%

Most occurring characters

ValueCountFrequency (%)
a 1010
34.7%
p 380
 
13.1%
l 324
 
11.1%
X 269
 
9.2%
e 214
 
7.4%
o 127
 
4.4%
t 119
 
4.1%
c 106
 
3.6%
C 95
 
3.3%
i 46
 
1.6%
Other values (27) 221
 
7.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 2460
84.5%
Uppercase Letter 426
 
14.6%
Space Separator 25
 
0.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 1010
41.1%
p 380
 
15.4%
l 324
 
13.2%
e 214
 
8.7%
o 127
 
5.2%
t 119
 
4.8%
c 106
 
4.3%
i 46
 
1.9%
n 39
 
1.6%
d 20
 
0.8%
Other values (14) 75
 
3.0%
Uppercase Letter
ValueCountFrequency (%)
X 269
63.1%
C 95
 
22.3%
E 17
 
4.0%
Z 15
 
3.5%
B 10
 
2.3%
M 5
 
1.2%
T 5
 
1.2%
P 4
 
0.9%
A 3
 
0.7%
H 1
 
0.2%
Other values (2) 2
 
0.5%
Space Separator
ValueCountFrequency (%)
25
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 2886
99.1%
Common 25
 
0.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 1010
35.0%
p 380
 
13.2%
l 324
 
11.2%
X 269
 
9.3%
e 214
 
7.4%
o 127
 
4.4%
t 119
 
4.1%
c 106
 
3.7%
C 95
 
3.3%
i 46
 
1.6%
Other values (26) 196
 
6.8%
Common
ValueCountFrequency (%)
25
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2905
99.8%
None 6
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 1010
34.8%
p 380
 
13.1%
l 324
 
11.2%
X 269
 
9.3%
e 214
 
7.4%
o 127
 
4.4%
t 119
 
4.1%
c 106
 
3.6%
C 95
 
3.3%
i 46
 
1.6%
Other values (25) 215
 
7.4%
None
ValueCountFrequency (%)
é 5
83.3%
á 1
 
16.7%

l_estado_civil
Categorical

Distinct7
Distinct (%)1.7%
Missing1
Missing (%)0.2%
Memory size3.3 KiB
Soltero (a)
184 
Casado (a)
140 
Unión libre
68 
Viudo (a)
 
5
Divorciado (a)
 
4
Other values (2)
 
6

Length

Max length14
Median length11
Mean length10.67567568
Min length9

Characters and Unicode

Total characters4345
Distinct characters25
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 rowCasado (a)
2nd rowSoltero (a)
3rd rowSoltero (a)
4th rowSoltero (a)
5th rowUnión libre

Common Values

ValueCountFrequency (%)
Soltero (a) 184
45.1%
Casado (a) 140
34.3%
Unión libre 68
 
16.7%
Viudo (a) 5
 
1.2%
Divorciado (a) 4
 
1.0%
No respondió 3
 
0.7%
Separado (a) 3
 
0.7%
(Missing) 1
 
0.2%

Length

2024-08-02T13:50:28.603101image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-08-02T13:50:28.781372image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
a 336
41.3%
soltero 184
22.6%
casado 140
17.2%
unión 68
 
8.4%
libre 68
 
8.4%
viudo 5
 
0.6%
divorciado 4
 
0.5%
no 3
 
0.4%
respondió 3
 
0.4%
separado 3
 
0.4%

Most occurring characters

ValueCountFrequency (%)
a 626
14.4%
o 530
12.2%
407
9.4%
( 336
 
7.7%
) 336
 
7.7%
r 262
 
6.0%
e 258
 
5.9%
l 252
 
5.8%
S 187
 
4.3%
t 184
 
4.2%
Other values (15) 967
22.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 2859
65.8%
Space Separator 407
 
9.4%
Uppercase Letter 407
 
9.4%
Open Punctuation 336
 
7.7%
Close Punctuation 336
 
7.7%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 626
21.9%
o 530
18.5%
r 262
9.2%
e 258
9.0%
l 252
8.8%
t 184
 
6.4%
d 155
 
5.4%
i 152
 
5.3%
s 143
 
5.0%
n 139
 
4.9%
Other values (6) 158
 
5.5%
Uppercase Letter
ValueCountFrequency (%)
S 187
45.9%
C 140
34.4%
U 68
 
16.7%
V 5
 
1.2%
D 4
 
1.0%
N 3
 
0.7%
Space Separator
ValueCountFrequency (%)
407
100.0%
Open Punctuation
ValueCountFrequency (%)
( 336
100.0%
Close Punctuation
ValueCountFrequency (%)
) 336
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 3266
75.2%
Common 1079
 
24.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 626
19.2%
o 530
16.2%
r 262
8.0%
e 258
7.9%
l 252
7.7%
S 187
 
5.7%
t 184
 
5.6%
d 155
 
4.7%
i 152
 
4.7%
s 143
 
4.4%
Other values (12) 517
15.8%
Common
ValueCountFrequency (%)
407
37.7%
( 336
31.1%
) 336
31.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4274
98.4%
None 71
 
1.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 626
14.6%
o 530
12.4%
407
9.5%
( 336
 
7.9%
) 336
 
7.9%
r 262
 
6.1%
e 258
 
6.0%
l 252
 
5.9%
S 187
 
4.4%
t 184
 
4.3%
Other values (14) 896
21.0%
None
ValueCountFrequency (%)
ó 71
100.0%

l_habitantes_casa
Unsupported

REJECTED  UNSUPPORTED 

Missing1
Missing (%)0.2%
Memory size3.3 KiB

l_tipo_casa
Categorical

Distinct7
Distinct (%)1.7%
Missing1
Missing (%)0.2%
Memory size3.3 KiB
Casa sola en colonia consolidada
172 
Casa en fraccionamiento o conjunto habitacional
111 
Casa en colonia popular
63 
Departamento en condominio
37 
Departamento en unidad habitacional
 
17
Other values (2)
 
7

Length

Max length47
Median length35
Mean length33.88943489
Min length8

Characters and Unicode

Total characters13793
Distinct characters24
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 rowCasa sola en colonia consolidada
2nd rowDepartamento en condominio
3rd rowCasa sola en colonia consolidada
4th rowCasa sola en colonia consolidada
5th rowCasa sola en colonia consolidada

Common Values

ValueCountFrequency (%)
Casa sola en colonia consolidada 172
42.2%
Casa en fraccionamiento o conjunto habitacional 111
27.2%
Casa en colonia popular 63
 
15.4%
Departamento en condominio 37
 
9.1%
Departamento en unidad habitacional 17
 
4.2%
Vecindad 6
 
1.5%
Situación de calle 1
 
0.2%
(Missing) 1
 
0.2%

Length

2024-08-02T13:50:29.073757image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-08-02T13:50:29.394611image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
casa 346
22.1%
colonia 235
15.0%
sola 172
11.0%
consolidada 172
11.0%
habitacional 128
 
8.2%
o 111
 
7.1%
conjunto 111
 
7.1%
fraccionamiento 111
 
7.1%
popular 63
 
4.0%
departamento 54
 
3.5%
Other values (5) 62
 
4.0%

Most occurring characters

ValueCountFrequency (%)
a 2245
16.3%
o 1897
13.8%
1559
11.3%
n 1531
11.1%
i 984
7.1%
c 913
6.6%
l 772
 
5.6%
s 690
 
5.0%
e 627
 
4.5%
t 459
 
3.3%
Other values (14) 2116
15.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 11827
85.7%
Space Separator 1559
 
11.3%
Uppercase Letter 407
 
3.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 2245
19.0%
o 1897
16.0%
n 1531
12.9%
i 984
8.3%
c 913
7.7%
l 772
 
6.5%
s 690
 
5.8%
e 627
 
5.3%
t 459
 
3.9%
d 428
 
3.6%
Other values (9) 1281
10.8%
Uppercase Letter
ValueCountFrequency (%)
C 346
85.0%
D 54
 
13.3%
V 6
 
1.5%
S 1
 
0.2%
Space Separator
ValueCountFrequency (%)
1559
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 12234
88.7%
Common 1559
 
11.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 2245
18.4%
o 1897
15.5%
n 1531
12.5%
i 984
8.0%
c 913
7.5%
l 772
 
6.3%
s 690
 
5.6%
e 627
 
5.1%
t 459
 
3.8%
d 428
 
3.5%
Other values (13) 1688
13.8%
Common
ValueCountFrequency (%)
1559
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 13792
> 99.9%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 2245
16.3%
o 1897
13.8%
1559
11.3%
n 1531
11.1%
i 984
7.1%
c 913
6.6%
l 772
 
5.6%
s 690
 
5.0%
e 627
 
4.5%
t 459
 
3.3%
Other values (13) 2115
15.3%
None
ValueCountFrequency (%)
ó 1
100.0%

l_contexto
Categorical

Distinct3
Distinct (%)0.7%
Missing1
Missing (%)0.2%
Memory size3.3 KiB
Urbano
312 
Rural o boscoso
88 
Urbano/boscoso
 
7

Length

Max length15
Median length6
Mean length8.083538084
Min length6

Characters and Unicode

Total characters3290
Distinct characters13
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

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
Urbano 312
76.5%
Rural o boscoso 88
 
21.6%
Urbano/boscoso 7
 
1.7%
(Missing) 1
 
0.2%

Length

2024-08-02T13:50:29.614194image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-08-02T13:50:29.764764image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
urbano 312
53.5%
rural 88
 
15.1%
o 88
 
15.1%
boscoso 88
 
15.1%
urbano/boscoso 7
 
1.2%

Most occurring characters

ValueCountFrequency (%)
o 692
21.0%
b 414
12.6%
r 407
12.4%
a 407
12.4%
U 319
9.7%
n 319
9.7%
s 190
 
5.8%
176
 
5.3%
c 95
 
2.9%
R 88
 
2.7%
Other values (3) 183
 
5.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 2700
82.1%
Uppercase Letter 407
 
12.4%
Space Separator 176
 
5.3%
Other Punctuation 7
 
0.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 692
25.6%
b 414
15.3%
r 407
15.1%
a 407
15.1%
n 319
11.8%
s 190
 
7.0%
c 95
 
3.5%
u 88
 
3.3%
l 88
 
3.3%
Uppercase Letter
ValueCountFrequency (%)
U 319
78.4%
R 88
 
21.6%
Space Separator
ValueCountFrequency (%)
176
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 3107
94.4%
Common 183
 
5.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 692
22.3%
b 414
13.3%
r 407
13.1%
a 407
13.1%
U 319
10.3%
n 319
10.3%
s 190
 
6.1%
c 95
 
3.1%
R 88
 
2.8%
u 88
 
2.8%
Common
ValueCountFrequency (%)
176
96.2%
/ 7
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3290
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o 692
21.0%
b 414
12.6%
r 407
12.4%
a 407
12.4%
U 319
9.7%
n 319
9.7%
s 190
 
5.8%
176
 
5.3%
c 95
 
2.9%
R 88
 
2.7%
Other values (3) 183
 
5.6%

l_arboles_cerca
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.5%
Missing1
Missing (%)0.2%
Memory size3.3 KiB
Sí
383 
No
 
24

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters814
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 rowSí
2nd rowNo
3rd rowSí
4th rowSí
5th rowSí

Common Values

ValueCountFrequency (%)
Sí 383
93.9%
No 24
 
5.9%
(Missing) 1
 
0.2%

Length

2024-08-02T13:50:29.920734image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-08-02T13:50:30.122546image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
sí 383
94.1%
no 24
 
5.9%

Most occurring characters

ValueCountFrequency (%)
S 383
47.1%
í 383
47.1%
N 24
 
2.9%
o 24
 
2.9%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 407
50.0%
Lowercase Letter 407
50.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
S 383
94.1%
N 24
 
5.9%
Lowercase Letter
ValueCountFrequency (%)
í 383
94.1%
o 24
 
5.9%

Most occurring scripts

ValueCountFrequency (%)
Latin 814
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
S 383
47.1%
í 383
47.1%
N 24
 
2.9%
o 24
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 431
52.9%
None 383
47.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
S 383
88.9%
N 24
 
5.6%
o 24
 
5.6%
None
ValueCountFrequency (%)
í 383
100.0%

l_areas_verdes
Categorical

Distinct2
Distinct (%)0.5%
Missing1
Missing (%)0.2%
Memory size3.3 KiB
Sí
338 
No
69 

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters814
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 rowSí
2nd rowNo
3rd rowSí
4th rowNo
5th rowSí

Common Values

ValueCountFrequency (%)
Sí 338
82.8%
No 69
 
16.9%
(Missing) 1
 
0.2%

Length

2024-08-02T13:50:30.359881image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-08-02T13:50:30.564945image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
sí 338
83.0%
no 69
 
17.0%

Most occurring characters

ValueCountFrequency (%)
S 338
41.5%
í 338
41.5%
N 69
 
8.5%
o 69
 
8.5%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 407
50.0%
Lowercase Letter 407
50.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
S 338
83.0%
N 69
 
17.0%
Lowercase Letter
ValueCountFrequency (%)
í 338
83.0%
o 69
 
17.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 814
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
S 338
41.5%
í 338
41.5%
N 69
 
8.5%
o 69
 
8.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 476
58.5%
None 338
41.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
S 338
71.0%
N 69
 
14.5%
o 69
 
14.5%
None
ValueCountFrequency (%)
í 338
100.0%

l_espacio_recreo
Categorical

Distinct2
Distinct (%)0.5%
Missing1
Missing (%)0.2%
Memory size3.3 KiB
Si
320 
No
87 

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters814
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 rowSi
5th rowSi

Common Values

ValueCountFrequency (%)
Si 320
78.4%
No 87
 
21.3%
(Missing) 1
 
0.2%

Length

2024-08-02T13:50:30.871404image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-08-02T13:50:31.144866image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
si 320
78.6%
no 87
 
21.4%

Most occurring characters

ValueCountFrequency (%)
S 320
39.3%
i 320
39.3%
N 87
 
10.7%
o 87
 
10.7%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 407
50.0%
Lowercase Letter 407
50.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
S 320
78.6%
N 87
 
21.4%
Lowercase Letter
ValueCountFrequency (%)
i 320
78.6%
o 87
 
21.4%

Most occurring scripts

ValueCountFrequency (%)
Latin 814
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
S 320
39.3%
i 320
39.3%
N 87
 
10.7%
o 87
 
10.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 814
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
S 320
39.3%
i 320
39.3%
N 87
 
10.7%
o 87
 
10.7%

l_sonidos_agradables
Categorical

Distinct43
Distinct (%)10.6%
Missing2
Missing (%)0.5%
Memory size3.3 KiB
El canto de diversas aves
231 
El canto de diversas aves/Viento
34 
El canto de diversas aves/Insectos
24 
Ninguno
 
20
El canto de diversas aves/Insectos/Viento
 
20
Other values (38)
77 

Length

Max length72
Median length25
Mean length26.75615764
Min length2

Characters and Unicode

Total characters10863
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

Unique23 ?
Unique (%)5.7%

Sample

1st rowEl canto de diversas aves
2nd rowEl canto de diversas aves/Insectos/Lluvia/Viento
3rd rowEl canto de diversas aves
4th rowEl canto de diversas aves
5th rowEl canto de diversas aves/Viento

Common Values

ValueCountFrequency (%)
El canto de diversas aves 231
56.6%
El canto de diversas aves/Viento 34
 
8.3%
El canto de diversas aves/Insectos 24
 
5.9%
Ninguno 20
 
4.9%
El canto de diversas aves/Insectos/Viento 20
 
4.9%
Viento 7
 
1.7%
El canto de diversas aves/Animales 6
 
1.5%
El canto de diversas aves/Río 5
 
1.2%
El canto de diversas aves/Viento/Lluvia 5
 
1.2%
Silecio 4
 
1.0%
Other values (33) 50
 
12.3%

Length

2024-08-02T13:50:31.498192image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
canto 360
31.9%
diversas 360
31.9%
aves 231
20.5%
aves/viento 34
 
3.0%
aves/insectos 24
 
2.1%
aves/insectos/viento 20
 
1.8%
ninguno 20
 
1.8%
viento 7
 
0.6%
aves/animales 6
 
0.5%
aves/río 5
 
0.4%
Other values (37) 61
 
5.4%

Most occurring characters

ValueCountFrequency (%)
1442
13.3%
e 1262
11.6%
s 1238
11.4%
a 1143
10.5%
v 745
 
6.9%
d 724
 
6.7%
n 578
 
5.3%
o 556
 
5.1%
i 526
 
4.8%
t 506
 
4.7%
Other values (25) 2143
19.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 8609
79.3%
Space Separator 1442
 
13.3%
Uppercase Letter 609
 
5.6%
Other Punctuation 203
 
1.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 1262
14.7%
s 1238
14.4%
a 1143
13.3%
v 745
8.7%
d 724
8.4%
n 578
6.7%
o 556
6.5%
i 526
6.1%
t 506
5.9%
c 430
 
5.0%
Other values (11) 901
10.5%
Uppercase Letter
ValueCountFrequency (%)
E 360
59.1%
V 86
 
14.1%
I 62
 
10.2%
A 26
 
4.3%
L 25
 
4.1%
N 21
 
3.4%
R 14
 
2.3%
S 7
 
1.1%
C 3
 
0.5%
M 2
 
0.3%
Other values (2) 3
 
0.5%
Space Separator
ValueCountFrequency (%)
1442
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 203
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 9218
84.9%
Common 1645
 
15.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 1262
13.7%
s 1238
13.4%
a 1143
12.4%
v 745
8.1%
d 724
7.9%
n 578
 
6.3%
o 556
 
6.0%
i 526
 
5.7%
t 506
 
5.5%
c 430
 
4.7%
Other values (23) 1510
16.4%
Common
ValueCountFrequency (%)
1442
87.7%
/ 203
 
12.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10846
99.8%
None 17
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1442
13.3%
e 1262
11.6%
s 1238
11.4%
a 1143
10.5%
v 745
 
6.9%
d 724
 
6.7%
n 578
 
5.3%
o 556
 
5.1%
i 526
 
4.8%
t 506
 
4.7%
Other values (23) 2126
19.6%
None
ValueCountFrequency (%)
í 15
88.2%
ú 2
 
11.8%

l_sonidos_desagradables
Text

Distinct129
Distinct (%)31.9%
Missing3
Missing (%)0.7%
Memory size3.3 KiB
2024-08-02T13:50:32.003242image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Length

Max length55
Median length43
Mean length15.00493827
Min length2

Characters and Unicode

Total characters6077
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

Unique83 ?
Unique (%)20.5%

Sample

1st rowAutomóviles
2nd rowAutomóviles/Camiones/Maquinaria
3rd rowVendedores
4th rowTráfico
5th rowAutomóviles
ValueCountFrequency (%)
automóviles 64
 
15.2%
tráfico 26
 
6.2%
música 25
 
6.0%
ninguno 24
 
5.7%
vendedores 23
 
5.5%
camiones 17
 
4.0%
maquinaria 14
 
3.3%
automóviles/camiones 13
 
3.1%
automóviles/música 8
 
1.9%
sirenas 7
 
1.7%
Other values (124) 199
47.4%
2024-08-02T13:50:32.777580image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 591
 
9.7%
i 574
 
9.4%
s 547
 
9.0%
o 514
 
8.5%
a 404
 
6.6%
n 324
 
5.3%
r 278
 
4.6%
/ 264
 
4.3%
m 251
 
4.1%
d 234
 
3.9%
Other values (30) 2096
34.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 5123
84.3%
Uppercase Letter 669
 
11.0%
Other Punctuation 264
 
4.3%
Space Separator 21
 
0.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 591
11.5%
i 574
11.2%
s 547
10.7%
o 514
10.0%
a 404
 
7.9%
n 324
 
6.3%
r 278
 
5.4%
m 251
 
4.9%
d 234
 
4.6%
u 225
 
4.4%
Other values (15) 1181
23.1%
Uppercase Letter
ValueCountFrequency (%)
A 167
25.0%
M 128
19.1%
C 105
15.7%
V 101
15.1%
T 59
 
8.8%
S 35
 
5.2%
L 28
 
4.2%
N 24
 
3.6%
G 7
 
1.0%
P 5
 
0.7%
Other values (3) 10
 
1.5%
Other Punctuation
ValueCountFrequency (%)
/ 264
100.0%
Space Separator
ValueCountFrequency (%)
21
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 5792
95.3%
Common 285
 
4.7%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 591
 
10.2%
i 574
 
9.9%
s 547
 
9.4%
o 514
 
8.9%
a 404
 
7.0%
n 324
 
5.6%
r 278
 
4.8%
m 251
 
4.3%
d 234
 
4.0%
u 225
 
3.9%
Other values (28) 1850
31.9%
Common
ValueCountFrequency (%)
/ 264
92.6%
21
 
7.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5774
95.0%
None 303
 
5.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 591
 
10.2%
i 574
 
9.9%
s 547
 
9.5%
o 514
 
8.9%
a 404
 
7.0%
n 324
 
5.6%
r 278
 
4.8%
/ 264
 
4.6%
m 251
 
4.3%
d 234
 
4.1%
Other values (26) 1793
31.1%
None
ValueCountFrequency (%)
ó 158
52.1%
ú 82
27.1%
á 62
 
20.5%
í 1
 
0.3%

l_area_verde_casa
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.7%
Missing1
Missing (%)0.2%
Memory size3.3 KiB
Si
353 
No
51 
No sé
 
3

Length

Max length5
Median length2
Mean length2.022113022
Min length2

Characters and Unicode

Total characters823
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 rowSi
2nd rowNo
3rd rowSi
4th rowSi
5th rowSi

Common Values

ValueCountFrequency (%)
Si 353
86.5%
No 51
 
12.5%
No sé 3
 
0.7%
(Missing) 1
 
0.2%

Length

2024-08-02T13:50:33.123468image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-08-02T13:50:33.401893image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
si 353
86.1%
no 54
 
13.2%
sé 3
 
0.7%

Most occurring characters

ValueCountFrequency (%)
S 353
42.9%
i 353
42.9%
N 54
 
6.6%
o 54
 
6.6%
3
 
0.4%
s 3
 
0.4%
é 3
 
0.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 413
50.2%
Uppercase Letter 407
49.5%
Space Separator 3
 
0.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i 353
85.5%
o 54
 
13.1%
s 3
 
0.7%
é 3
 
0.7%
Uppercase Letter
ValueCountFrequency (%)
S 353
86.7%
N 54
 
13.3%
Space Separator
ValueCountFrequency (%)
3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 820
99.6%
Common 3
 
0.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
S 353
43.0%
i 353
43.0%
N 54
 
6.6%
o 54
 
6.6%
s 3
 
0.4%
é 3
 
0.4%
Common
ValueCountFrequency (%)
3
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 820
99.6%
None 3
 
0.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
S 353
43.0%
i 353
43.0%
N 54
 
6.6%
o 54
 
6.6%
3
 
0.4%
s 3
 
0.4%
None
ValueCountFrequency (%)
é 3
100.0%

l_freq_visita_area_verde
Categorical

Distinct6
Distinct (%)1.5%
Missing1
Missing (%)0.2%
Memory size3.3 KiB
Nunca
100 
Pocas veces al año
90 
Varias veces a la semana
87 
Pocas veces al mes
82 
Diariamente
47 

Length

Max length24
Median length18
Mean length15.25307125
Min length5

Characters and Unicode

Total characters6208
Distinct characters21
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 rowSiempre
2nd rowNunca
3rd rowPocas veces al año
4th rowPocas veces al año
5th rowPocas veces al año

Common Values

ValueCountFrequency (%)
Nunca 100
24.5%
Pocas veces al año 90
22.1%
Varias veces a la semana 87
21.3%
Pocas veces al mes 82
20.1%
Diariamente 47
11.5%
Siempre 1
 
0.2%
(Missing) 1
 
0.2%

Length

2024-08-02T13:50:33.799749image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-08-02T13:50:34.154519image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
veces 259
21.9%
pocas 172
14.5%
al 172
14.5%
nunca 100
 
8.4%
año 90
 
7.6%
varias 87
 
7.3%
a 87
 
7.3%
semana 87
 
7.3%
mes 82
 
6.9%
diariamente 47
 
4.0%

Most occurring characters

ValueCountFrequency (%)
a 1150
18.5%
864
13.9%
e 783
12.6%
s 687
11.1%
c 531
8.6%
o 262
 
4.2%
v 259
 
4.2%
l 259
 
4.2%
n 234
 
3.8%
m 217
 
3.5%
Other values (11) 962
15.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 4937
79.5%
Space Separator 864
 
13.9%
Uppercase Letter 407
 
6.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 1150
23.3%
e 783
15.9%
s 687
13.9%
c 531
10.8%
o 262
 
5.3%
v 259
 
5.2%
l 259
 
5.2%
n 234
 
4.7%
m 217
 
4.4%
i 182
 
3.7%
Other values (5) 373
 
7.6%
Uppercase Letter
ValueCountFrequency (%)
P 172
42.3%
N 100
24.6%
V 87
21.4%
D 47
 
11.5%
S 1
 
0.2%
Space Separator
ValueCountFrequency (%)
864
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 5344
86.1%
Common 864
 
13.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 1150
21.5%
e 783
14.7%
s 687
12.9%
c 531
9.9%
o 262
 
4.9%
v 259
 
4.8%
l 259
 
4.8%
n 234
 
4.4%
m 217
 
4.1%
i 182
 
3.4%
Other values (10) 780
14.6%
Common
ValueCountFrequency (%)
864
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6118
98.6%
None 90
 
1.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 1150
18.8%
864
14.1%
e 783
12.8%
s 687
11.2%
c 531
8.7%
o 262
 
4.3%
v 259
 
4.2%
l 259
 
4.2%
n 234
 
3.8%
m 217
 
3.5%
Other values (10) 872
14.3%
None
ValueCountFrequency (%)
ñ 90
100.0%

l_importancia_av_crisis_sanitaria
Categorical

IMBALANCE 

Distinct5
Distinct (%)1.2%
Missing1
Missing (%)0.2%
Memory size3.3 KiB
Considerablemente importantes
345 
Moderadamente importantes
 
31
Mas o menos importantes
 
24
Poco importantes
 
5
Nada importantes
 
2

Length

Max length29
Median length29
Mean length28.11793612
Min length16

Characters and Unicode

Total characters11444
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 rowConsiderablemente importantes
2nd rowConsiderablemente importantes
3rd rowConsiderablemente importantes
4th rowConsiderablemente importantes
5th rowConsiderablemente importantes

Common Values

ValueCountFrequency (%)
Considerablemente importantes 345
84.6%
Moderadamente importantes 31
 
7.6%
Mas o menos importantes 24
 
5.9%
Poco importantes 5
 
1.2%
Nada importantes 2
 
0.5%
(Missing) 1
 
0.2%

Length

2024-08-02T13:50:34.543746image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-08-02T13:50:34.854564image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
importantes 407
47.2%
considerablemente 345
40.0%
moderadamente 31
 
3.6%
mas 24
 
2.8%
o 24
 
2.8%
menos 24
 
2.8%
poco 5
 
0.6%
nada 2
 
0.2%

Most occurring characters

ValueCountFrequency (%)
e 1904
16.6%
t 1190
10.4%
n 1152
10.1%
a 842
7.4%
o 841
7.3%
m 807
7.1%
s 800
7.0%
r 783
6.8%
i 752
 
6.6%
455
 
4.0%
Other values (9) 1918
16.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 10582
92.5%
Space Separator 455
 
4.0%
Uppercase Letter 407
 
3.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 1904
18.0%
t 1190
11.2%
n 1152
10.9%
a 842
8.0%
o 841
7.9%
m 807
7.6%
s 800
7.6%
r 783
7.4%
i 752
 
7.1%
d 409
 
3.9%
Other values (4) 1102
10.4%
Uppercase Letter
ValueCountFrequency (%)
C 345
84.8%
M 55
 
13.5%
P 5
 
1.2%
N 2
 
0.5%
Space Separator
ValueCountFrequency (%)
455
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 10989
96.0%
Common 455
 
4.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 1904
17.3%
t 1190
10.8%
n 1152
10.5%
a 842
7.7%
o 841
7.7%
m 807
7.3%
s 800
7.3%
r 783
7.1%
i 752
 
6.8%
d 409
 
3.7%
Other values (8) 1509
13.7%
Common
ValueCountFrequency (%)
455
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11444
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 1904
16.6%
t 1190
10.4%
n 1152
10.1%
a 842
7.4%
o 841
7.3%
m 807
7.1%
s 800
7.0%
r 783
6.8%
i 752
 
6.6%
455
 
4.0%
Other values (9) 1918
16.8%

l_conoces_veg_rodea
Categorical

Distinct2
Distinct (%)0.5%
Missing1
Missing (%)0.2%
Memory size3.3 KiB
Sí
296 
No
111 

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters814
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 rowSí
2nd rowNo
3rd rowSí
4th rowSí
5th rowSí

Common Values

ValueCountFrequency (%)
Sí 296
72.5%
No 111
 
27.2%
(Missing) 1
 
0.2%

Length

2024-08-02T13:50:35.181048image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-08-02T13:50:35.438605image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
sí 296
72.7%
no 111
 
27.3%

Most occurring characters

ValueCountFrequency (%)
S 296
36.4%
í 296
36.4%
N 111
 
13.6%
o 111
 
13.6%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 407
50.0%
Lowercase Letter 407
50.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
S 296
72.7%
N 111
 
27.3%
Lowercase Letter
ValueCountFrequency (%)
í 296
72.7%
o 111
 
27.3%

Most occurring scripts

ValueCountFrequency (%)
Latin 814
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
S 296
36.4%
í 296
36.4%
N 111
 
13.6%
o 111
 
13.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 518
63.6%
None 296
36.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
S 296
57.1%
N 111
 
21.4%
o 111
 
21.4%
None
ValueCountFrequency (%)
í 296
100.0%

l_ventana
Text

Distinct209
Distinct (%)51.4%
Missing1
Missing (%)0.2%
Memory size3.3 KiB
2024-08-02T13:50:35.762638image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Length

Max length66
Median length44
Mean length16.13759214
Min length5

Characters and Unicode

Total characters6568
Distinct characters50
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

Unique166 ?
Unique (%)40.8%

Sample

1st rowBosque
2nd rowCasas
3rd rowBosque/Aves/Mariposas
4th rowCasas/Cerro de las Culebras
5th rowÁrboles
ValueCountFrequency (%)
árboles 56
 
11.4%
casas 35
 
7.1%
casas/árboles 15
 
3.1%
árboles/casas 15
 
3.1%
verdes 14
 
2.9%
bosque 14
 
2.9%
perote 12
 
2.4%
orizaba 9
 
1.8%
árboles/plantas 8
 
1.6%
árboles/áreas 7
 
1.4%
Other values (214) 306
62.3%
2024-08-02T13:50:36.572533image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
s 856
13.0%
a 715
10.9%
e 689
10.5%
o 509
 
7.7%
r 495
 
7.5%
/ 455
 
6.9%
l 416
 
6.3%
C 273
 
4.2%
b 269
 
4.1%
Á 249
 
3.8%
Other values (40) 1642
25.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 5060
77.0%
Uppercase Letter 920
 
14.0%
Other Punctuation 455
 
6.9%
Space Separator 133
 
2.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
s 856
16.9%
a 715
14.1%
e 689
13.6%
o 509
10.1%
r 495
9.8%
l 416
8.2%
b 269
 
5.3%
i 172
 
3.4%
t 168
 
3.3%
n 156
 
3.1%
Other values (17) 615
12.2%
Uppercase Letter
ValueCountFrequency (%)
C 273
29.7%
Á 249
27.1%
P 115
12.5%
A 59
 
6.4%
B 39
 
4.2%
M 32
 
3.5%
J 32
 
3.5%
E 19
 
2.1%
V 18
 
2.0%
F 18
 
2.0%
Other values (11) 66
 
7.2%
Other Punctuation
ValueCountFrequency (%)
/ 455
100.0%
Space Separator
ValueCountFrequency (%)
133
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 5980
91.0%
Common 588
 
9.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
s 856
14.3%
a 715
12.0%
e 689
11.5%
o 509
 
8.5%
r 495
 
8.3%
l 416
 
7.0%
C 273
 
4.6%
b 269
 
4.5%
Á 249
 
4.2%
i 172
 
2.9%
Other values (38) 1337
22.4%
Common
ValueCountFrequency (%)
/ 455
77.4%
133
 
22.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6248
95.1%
None 320
 
4.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
s 856
13.7%
a 715
11.4%
e 689
11.0%
o 509
 
8.1%
r 495
 
7.9%
/ 455
 
7.3%
l 416
 
6.7%
C 273
 
4.4%
b 269
 
4.3%
i 172
 
2.8%
Other values (35) 1399
22.4%
None
ValueCountFrequency (%)
Á 249
77.8%
í 33
 
10.3%
ñ 19
 
5.9%
ó 18
 
5.6%
ú 1
 
0.3%

l_disfruta_entorno
Categorical

Distinct5
Distinct (%)1.2%
Missing1
Missing (%)0.2%
Memory size3.3 KiB
Considerablemente
238 
Moderadamente
98 
Mas o menos
60 
Poco
 
10
Nada
 
1

Length

Max length17
Median length17
Mean length14.8009828
Min length4

Characters and Unicode

Total characters6024
Distinct characters18
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 rowConsiderablemente
2nd rowMas o menos
3rd rowConsiderablemente
4th rowConsiderablemente
5th rowConsiderablemente

Common Values

ValueCountFrequency (%)
Considerablemente 238
58.3%
Moderadamente 98
24.0%
Mas o menos 60
 
14.7%
Poco 10
 
2.5%
Nada 1
 
0.2%
(Missing) 1
 
0.2%

Length

2024-08-02T13:50:36.957404image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-08-02T13:50:37.260011image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
considerablemente 238
45.2%
moderadamente 98
18.6%
mas 60
 
11.4%
o 60
 
11.4%
menos 60
 
11.4%
poco 10
 
1.9%
nada 1
 
0.2%

Most occurring characters

ValueCountFrequency (%)
e 1306
21.7%
n 634
10.5%
a 496
 
8.2%
o 476
 
7.9%
d 435
 
7.2%
m 396
 
6.6%
s 358
 
5.9%
t 336
 
5.6%
r 336
 
5.6%
C 238
 
4.0%
Other values (8) 1013
16.8%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 5497
91.3%
Uppercase Letter 407
 
6.8%
Space Separator 120
 
2.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 1306
23.8%
n 634
11.5%
a 496
 
9.0%
o 476
 
8.7%
d 435
 
7.9%
m 396
 
7.2%
s 358
 
6.5%
t 336
 
6.1%
r 336
 
6.1%
b 238
 
4.3%
Other values (3) 486
 
8.8%
Uppercase Letter
ValueCountFrequency (%)
C 238
58.5%
M 158
38.8%
P 10
 
2.5%
N 1
 
0.2%
Space Separator
ValueCountFrequency (%)
120
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 5904
98.0%
Common 120
 
2.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 1306
22.1%
n 634
10.7%
a 496
 
8.4%
o 476
 
8.1%
d 435
 
7.4%
m 396
 
6.7%
s 358
 
6.1%
t 336
 
5.7%
r 336
 
5.7%
C 238
 
4.0%
Other values (7) 893
15.1%
Common
ValueCountFrequency (%)
120
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6024
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 1306
21.7%
n 634
10.5%
a 496
 
8.2%
o 476
 
7.9%
d 435
 
7.2%
m 396
 
6.6%
s 358
 
5.9%
t 336
 
5.6%
r 336
 
5.6%
C 238
 
4.0%
Other values (8) 1013
16.8%

t_Escribe 5 palabras asociadas a lo que más has disfrutado del confinamiento voluntario
Text

Distinct390
Distinct (%)95.8%
Missing1
Missing (%)0.2%
Memory size3.3 KiB
2024-08-02T13:50:37.706122image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Length

Max length199
Median length90
Mean length48.48402948
Min length2

Characters and Unicode

Total characters19733
Distinct characters71
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique375 ?
Unique (%)92.1%

Sample

1st rowsalir a caminar con mi familia y perrhijos al area verde detras del parque el haya
2nd rowFamilia, unión, paz, juegos, cuidado
3rd rowsoledad, creatividad, tranquilidad, bosque, río.
4th rowLeer, autoreflexion, hacer ejercicio, relajarme meditar
5th rowPaz Amor Solidaridad Respeto Armonía
ValueCountFrequency (%)
familia 125
 
5.2%
tiempo 105
 
4.3%
y 74
 
3.1%
tranquilidad 74
 
3.1%
casa 65
 
2.7%
descanso 48
 
2.0%
mi 46
 
1.9%
convivencia 43
 
1.8%
no 37
 
1.5%
con 33
 
1.4%
Other values (642) 1770
73.1%
2024-08-02T13:50:38.740730image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2312
 
11.7%
a 2251
 
11.4%
i 1744
 
8.8%
e 1459
 
7.4%
o 1232
 
6.2%
r 1169
 
5.9%
, 1010
 
5.1%
n 951
 
4.8%
c 914
 
4.6%
s 869
 
4.4%
Other values (61) 5822
29.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 15684
79.5%
Space Separator 2312
 
11.7%
Other Punctuation 1103
 
5.6%
Uppercase Letter 575
 
2.9%
Control 35
 
0.2%
Decimal Number 18
 
0.1%
Close Punctuation 5
 
< 0.1%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 2251
14.4%
i 1744
11.1%
e 1459
9.3%
o 1232
 
7.9%
r 1169
 
7.5%
n 951
 
6.1%
c 914
 
5.8%
s 869
 
5.5%
d 788
 
5.0%
l 742
 
4.7%
Other values (21) 3565
22.7%
Uppercase Letter
ValueCountFrequency (%)
T 82
14.3%
C 68
11.8%
F 67
11.7%
E 43
 
7.5%
A 39
 
6.8%
N 36
 
6.3%
L 36
 
6.3%
P 30
 
5.2%
S 30
 
5.2%
D 29
 
5.0%
Other values (14) 115
20.0%
Other Punctuation
ValueCountFrequency (%)
, 1010
91.6%
. 79
 
7.2%
; 9
 
0.8%
/ 3
 
0.3%
¿ 1
 
0.1%
? 1
 
0.1%
Decimal Number
ValueCountFrequency (%)
2 4
22.2%
4 4
22.2%
5 3
16.7%
1 3
16.7%
3 3
16.7%
7 1
 
5.6%
Space Separator
ValueCountFrequency (%)
2312
100.0%
Control
ValueCountFrequency (%)
35
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 16259
82.4%
Common 3474
 
17.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 2251
13.8%
i 1744
10.7%
e 1459
 
9.0%
o 1232
 
7.6%
r 1169
 
7.2%
n 951
 
5.8%
c 914
 
5.6%
s 869
 
5.3%
d 788
 
4.8%
l 742
 
4.6%
Other values (45) 4140
25.5%
Common
ValueCountFrequency (%)
2312
66.6%
, 1010
29.1%
. 79
 
2.3%
35
 
1.0%
; 9
 
0.3%
) 5
 
0.1%
2 4
 
0.1%
4 4
 
0.1%
5 3
 
0.1%
1 3
 
0.1%
Other values (6) 10
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 19493
98.8%
None 240
 
1.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2312
11.9%
a 2251
11.5%
i 1744
 
8.9%
e 1459
 
7.5%
o 1232
 
6.3%
r 1169
 
6.0%
, 1010
 
5.2%
n 951
 
4.9%
c 914
 
4.7%
s 869
 
4.5%
Other values (52) 5582
28.6%
None
ValueCountFrequency (%)
ó 101
42.1%
í 54
22.5%
á 46
19.2%
ú 18
 
7.5%
ñ 10
 
4.2%
é 8
 
3.3%
¿ 1
 
0.4%
Á 1
 
0.4%
Ñ 1
 
0.4%

l_disfrutado_confinamiento
Text

Distinct370
Distinct (%)90.9%
Missing1
Missing (%)0.2%
Memory size3.3 KiB
2024-08-02T13:50:39.120600image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Length

Max length65
Median length51
Mean length36.5012285
Min length4

Characters and Unicode

Total characters14856
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

Unique354 ?
Unique (%)87.0%

Sample

1st rowCaminar/Familia/Mascotas/Áreas verdes/Parque
2nd rowFamilia/Unión/Paz/Juegos/Cuidado
3rd rowSoledad/Creatividad/Tranquilidad/Bosque/Río
4th rowLeer/Autoreflexión/Ejercicio/Relajarme/Meditar
5th rowPaz/Amor/Solidaridad/Respeto/Armonía
ValueCountFrequency (%)
familia 10
 
1.8%
he 8
 
1.4%
tenido 8
 
1.4%
confinamiento 8
 
1.4%
por 8
 
1.4%
trabajo 8
 
1.4%
casa 8
 
1.4%
no 8
 
1.4%
tiempo 7
 
1.3%
televisión 7
 
1.3%
Other values (418) 472
85.5%
2024-08-02T13:50:40.350396image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 1823
 
12.3%
i 1643
 
11.1%
/ 1222
 
8.2%
e 1038
 
7.0%
o 914
 
6.2%
n 814
 
5.5%
r 773
 
5.2%
c 641
 
4.3%
d 598
 
4.0%
s 553
 
3.7%
Other values (45) 4837
32.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 11829
79.6%
Uppercase Letter 1639
 
11.0%
Other Punctuation 1222
 
8.2%
Space Separator 166
 
1.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 1823
15.4%
i 1643
13.9%
e 1038
8.8%
o 914
 
7.7%
n 814
 
6.9%
r 773
 
6.5%
c 641
 
5.4%
d 598
 
5.1%
s 553
 
4.7%
l 547
 
4.6%
Other values (20) 2485
21.0%
Uppercase Letter
ValueCountFrequency (%)
C 293
17.9%
T 232
14.2%
F 188
11.5%
A 125
7.6%
S 113
 
6.9%
D 94
 
5.7%
E 82
 
5.0%
P 80
 
4.9%
L 79
 
4.8%
M 76
 
4.6%
Other values (13) 277
16.9%
Other Punctuation
ValueCountFrequency (%)
/ 1222
100.0%
Space Separator
ValueCountFrequency (%)
166
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 13468
90.7%
Common 1388
 
9.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 1823
13.5%
i 1643
 
12.2%
e 1038
 
7.7%
o 914
 
6.8%
n 814
 
6.0%
r 773
 
5.7%
c 641
 
4.8%
d 598
 
4.4%
s 553
 
4.1%
l 547
 
4.1%
Other values (43) 4124
30.6%
Common
ValueCountFrequency (%)
/ 1222
88.0%
166
 
12.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 14592
98.2%
None 264
 
1.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 1823
 
12.5%
i 1643
 
11.3%
/ 1222
 
8.4%
e 1038
 
7.1%
o 914
 
6.3%
n 814
 
5.6%
r 773
 
5.3%
c 641
 
4.4%
d 598
 
4.1%
s 553
 
3.8%
Other values (38) 4573
31.3%
None
ValueCountFrequency (%)
ó 155
58.7%
í 42
 
15.9%
á 26
 
9.8%
ú 20
 
7.6%
Á 10
 
3.8%
ñ 6
 
2.3%
é 5
 
1.9%

t_Escribe 5 palabras asociadas a lo que menos has disfrutado durante el confinamiento voluntario
Text

Distinct393
Distinct (%)96.6%
Missing1
Missing (%)0.2%
Memory size3.3 KiB
2024-08-02T13:50:40.894039image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Length

Max length198
Median length106
Mean length49.99262899
Min length4

Characters and Unicode

Total characters20347
Distinct characters74
Distinct categories9 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique379 ?
Unique (%)93.1%

Sample

1st rowel poco respeto de mucha gente a las medidas sanitarias
2nd rowIncertidumbre, miedo, estrés, insomnio, flojera
3rd rowsoledad, aislamiento, familia lejos, sin noción del tiempo, infodemia
4th rowNo salir en bicicleta ni a correr ni caminar con mis perritos
5th rowPreocupación, enfermedad, covid, dinero, desempleo
ValueCountFrequency (%)
no 124
 
5.0%
a 66
 
2.6%
encierro 64
 
2.6%
y 58
 
2.3%
trabajo 47
 
1.9%
estrés 46
 
1.8%
ansiedad 43
 
1.7%
salir 42
 
1.7%
aislamiento 40
 
1.6%
amigos 38
 
1.5%
Other values (745) 1930
77.3%
2024-08-02T13:50:41.924900image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2452
12.1%
a 1988
 
9.8%
e 1773
 
8.7%
i 1670
 
8.2%
o 1453
 
7.1%
s 1282
 
6.3%
r 1276
 
6.3%
n 1149
 
5.6%
, 882
 
4.3%
c 830
 
4.1%
Other values (64) 5592
27.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 16240
79.8%
Space Separator 2452
 
12.1%
Other Punctuation 992
 
4.9%
Uppercase Letter 597
 
2.9%
Control 33
 
0.2%
Decimal Number 16
 
0.1%
Close Punctuation 10
 
< 0.1%
Open Punctuation 5
 
< 0.1%
Dash Punctuation 2
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 1988
12.2%
e 1773
10.9%
i 1670
10.3%
o 1453
8.9%
s 1282
 
7.9%
r 1276
 
7.9%
n 1149
 
7.1%
c 830
 
5.1%
d 797
 
4.9%
t 790
 
4.9%
Other values (22) 3232
19.9%
Uppercase Letter
ValueCountFrequency (%)
E 106
17.8%
A 69
11.6%
N 66
11.1%
S 45
7.5%
I 41
 
6.9%
C 41
 
6.9%
R 40
 
6.7%
T 31
 
5.2%
M 25
 
4.2%
D 23
 
3.9%
Other values (14) 110
18.4%
Other Punctuation
ValueCountFrequency (%)
, 882
88.9%
. 96
 
9.7%
; 6
 
0.6%
/ 3
 
0.3%
" 2
 
0.2%
! 1
 
0.1%
: 1
 
0.1%
' 1
 
0.1%
Decimal Number
ValueCountFrequency (%)
2 4
25.0%
3 3
18.8%
5 3
18.8%
4 3
18.8%
1 3
18.8%
Space Separator
ValueCountFrequency (%)
2452
100.0%
Control
ValueCountFrequency (%)
33
100.0%
Close Punctuation
ValueCountFrequency (%)
) 10
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 16837
82.7%
Common 3510
 
17.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 1988
11.8%
e 1773
10.5%
i 1670
9.9%
o 1453
 
8.6%
s 1282
 
7.6%
r 1276
 
7.6%
n 1149
 
6.8%
c 830
 
4.9%
d 797
 
4.7%
t 790
 
4.7%
Other values (46) 3829
22.7%
Common
ValueCountFrequency (%)
2452
69.9%
, 882
 
25.1%
. 96
 
2.7%
33
 
0.9%
) 10
 
0.3%
; 6
 
0.2%
( 5
 
0.1%
2 4
 
0.1%
3 3
 
0.1%
5 3
 
0.1%
Other values (8) 16
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 20099
98.8%
None 248
 
1.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2452
12.2%
a 1988
 
9.9%
e 1773
 
8.8%
i 1670
 
8.3%
o 1453
 
7.2%
s 1282
 
6.4%
r 1276
 
6.3%
n 1149
 
5.7%
, 882
 
4.4%
c 830
 
4.1%
Other values (57) 5344
26.6%
None
ValueCountFrequency (%)
ó 119
48.0%
é 55
22.2%
í 29
 
11.7%
ñ 22
 
8.9%
á 17
 
6.9%
ú 5
 
2.0%
É 1
 
0.4%

l_menos_disfrutado_confinamiento
Text

Distinct327
Distinct (%)80.3%
Missing1
Missing (%)0.2%
Memory size3.3 KiB
2024-08-02T13:50:42.413539image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Length

Max length63
Median length48
Mean length32.86977887
Min length4

Characters and Unicode

Total characters13378
Distinct characters56
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

Unique299 ?
Unique (%)73.5%

Sample

1st rowIncertidumbre/Miedo/Inconciencia
2nd rowIncertidumbre/Miedo/Estrés/Insomnio/Flojera
3rd rowSoledad/Aislamiento/Infodemia/Atemporalidad
4th rowAislamiento/Soledad
5th rowPreocupación/Enfermedad/Covid/Dinero/Desempleo
ValueCountFrequency (%)
aislamiento/encierro 21
 
4.5%
exceso 14
 
3.0%
trabajo 13
 
2.8%
encierro 11
 
2.4%
encierro/aislamiento 9
 
1.9%
ninguna 8
 
1.7%
aislamiento/soledad 5
 
1.1%
no 5
 
1.1%
tenido 4
 
0.9%
confinamiento 4
 
0.9%
Other values (343) 372
79.8%
2024-08-02T13:50:43.295622image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
i 1377
 
10.3%
e 1236
 
9.2%
a 1094
 
8.2%
o 1020
 
7.6%
/ 968
 
7.2%
n 925
 
6.9%
s 869
 
6.5%
r 868
 
6.5%
t 634
 
4.7%
d 558
 
4.2%
Other values (46) 3829
28.6%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 10935
81.7%
Uppercase Letter 1377
 
10.3%
Other Punctuation 969
 
7.2%
Space Separator 95
 
0.7%
Close Punctuation 1
 
< 0.1%
Decimal Number 1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i 1377
12.6%
e 1236
11.3%
a 1094
10.0%
o 1020
9.3%
n 925
8.5%
s 869
7.9%
r 868
7.9%
t 634
 
5.8%
d 558
 
5.1%
c 495
 
4.5%
Other values (20) 1859
17.0%
Uppercase Letter
ValueCountFrequency (%)
A 276
20.0%
E 272
19.8%
D 102
 
7.4%
C 102
 
7.4%
S 87
 
6.3%
I 82
 
6.0%
M 73
 
5.3%
P 70
 
5.1%
T 60
 
4.4%
V 57
 
4.1%
Other values (11) 196
14.2%
Other Punctuation
ValueCountFrequency (%)
/ 968
99.9%
, 1
 
0.1%
Space Separator
ValueCountFrequency (%)
95
100.0%
Close Punctuation
ValueCountFrequency (%)
] 1
100.0%
Decimal Number
ValueCountFrequency (%)
0 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 12312
92.0%
Common 1066
 
8.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
i 1377
11.2%
e 1236
 
10.0%
a 1094
 
8.9%
o 1020
 
8.3%
n 925
 
7.5%
s 869
 
7.1%
r 868
 
7.1%
t 634
 
5.1%
d 558
 
4.5%
c 495
 
4.0%
Other values (41) 3236
26.3%
Common
ValueCountFrequency (%)
/ 968
90.8%
95
 
8.9%
] 1
 
0.1%
, 1
 
0.1%
0 1
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 13174
98.5%
None 204
 
1.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
i 1377
 
10.5%
e 1236
 
9.4%
a 1094
 
8.3%
o 1020
 
7.7%
/ 968
 
7.3%
n 925
 
7.0%
s 869
 
6.6%
r 868
 
6.6%
t 634
 
4.8%
d 558
 
4.2%
Other values (40) 3625
27.5%
None
ValueCountFrequency (%)
ó 98
48.0%
é 62
30.4%
í 25
 
12.3%
ñ 15
 
7.4%
á 3
 
1.5%
ú 1
 
0.5%

l_vive_urb_quiere_rural
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.7%
Missing1
Missing (%)0.2%
Memory size3.3 KiB
Sí
373 
Me da igual
 
22
No
 
12

Length

Max length11
Median length2
Mean length2.486486486
Min length2

Characters and Unicode

Total characters1012
Distinct characters13
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 rowSí
2nd rowSí
3rd rowSí
4th rowSí
5th rowSí

Common Values

ValueCountFrequency (%)
Sí 373
91.4%
Me da igual 22
 
5.4%
No 12
 
2.9%
(Missing) 1
 
0.2%

Length

2024-08-02T13:50:43.572554image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-08-02T13:50:43.824022image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
sí 373
82.7%
me 22
 
4.9%
da 22
 
4.9%
igual 22
 
4.9%
no 12
 
2.7%

Most occurring characters

ValueCountFrequency (%)
S 373
36.9%
í 373
36.9%
44
 
4.3%
a 44
 
4.3%
M 22
 
2.2%
e 22
 
2.2%
d 22
 
2.2%
i 22
 
2.2%
g 22
 
2.2%
u 22
 
2.2%
Other values (3) 46
 
4.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 561
55.4%
Uppercase Letter 407
40.2%
Space Separator 44
 
4.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
í 373
66.5%
a 44
 
7.8%
e 22
 
3.9%
d 22
 
3.9%
i 22
 
3.9%
g 22
 
3.9%
u 22
 
3.9%
l 22
 
3.9%
o 12
 
2.1%
Uppercase Letter
ValueCountFrequency (%)
S 373
91.6%
M 22
 
5.4%
N 12
 
2.9%
Space Separator
ValueCountFrequency (%)
44
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 968
95.7%
Common 44
 
4.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
S 373
38.5%
í 373
38.5%
a 44
 
4.5%
M 22
 
2.3%
e 22
 
2.3%
d 22
 
2.3%
i 22
 
2.3%
g 22
 
2.3%
u 22
 
2.3%
l 22
 
2.3%
Other values (2) 24
 
2.5%
Common
ValueCountFrequency (%)
44
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 639
63.1%
None 373
36.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
S 373
58.4%
44
 
6.9%
a 44
 
6.9%
M 22
 
3.4%
e 22
 
3.4%
d 22
 
3.4%
i 22
 
3.4%
g 22
 
3.4%
u 22
 
3.4%
l 22
 
3.4%
Other values (2) 24
 
3.8%
None
ValueCountFrequency (%)
í 373
100.0%

l_vive_rur_quiere_urb
Categorical

Distinct3
Distinct (%)0.7%
Missing1
Missing (%)0.2%
Memory size3.3 KiB
No
310 
Me da igual
52 
Sí
45 

Length

Max length11
Median length2
Mean length3.14987715
Min length2

Characters and Unicode

Total characters1282
Distinct characters13
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 rowNo
5th rowNo

Common Values

ValueCountFrequency (%)
No 310
76.0%
Me da igual 52
 
12.7%
Sí 45
 
11.0%
(Missing) 1
 
0.2%

Length

2024-08-02T13:50:44.199008image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-08-02T13:50:44.482249image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
no 310
60.7%
me 52
 
10.2%
da 52
 
10.2%
igual 52
 
10.2%
sí 45
 
8.8%

Most occurring characters

ValueCountFrequency (%)
N 310
24.2%
o 310
24.2%
104
 
8.1%
a 104
 
8.1%
M 52
 
4.1%
e 52
 
4.1%
d 52
 
4.1%
i 52
 
4.1%
g 52
 
4.1%
u 52
 
4.1%
Other values (3) 142
11.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 771
60.1%
Uppercase Letter 407
31.7%
Space Separator 104
 
8.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 310
40.2%
a 104
 
13.5%
e 52
 
6.7%
d 52
 
6.7%
i 52
 
6.7%
g 52
 
6.7%
u 52
 
6.7%
l 52
 
6.7%
í 45
 
5.8%
Uppercase Letter
ValueCountFrequency (%)
N 310
76.2%
M 52
 
12.8%
S 45
 
11.1%
Space Separator
ValueCountFrequency (%)
104
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1178
91.9%
Common 104
 
8.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 310
26.3%
o 310
26.3%
a 104
 
8.8%
M 52
 
4.4%
e 52
 
4.4%
d 52
 
4.4%
i 52
 
4.4%
g 52
 
4.4%
u 52
 
4.4%
l 52
 
4.4%
Other values (2) 90
 
7.6%
Common
ValueCountFrequency (%)
104
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1237
96.5%
None 45
 
3.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 310
25.1%
o 310
25.1%
104
 
8.4%
a 104
 
8.4%
M 52
 
4.2%
e 52
 
4.2%
d 52
 
4.2%
i 52
 
4.2%
g 52
 
4.2%
u 52
 
4.2%
Other values (2) 97
 
7.8%
None
ValueCountFrequency (%)
í 45
100.0%

l_participa_act_conservacion
Categorical

Distinct3
Distinct (%)0.7%
Missing1
Missing (%)0.2%
Memory size3.3 KiB
No
235 
Sí
171 
No por ahora
 
1

Length

Max length12
Median length2
Mean length2.024570025
Min length2

Characters and Unicode

Total characters824
Distinct characters9
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 rowSí
2nd rowNo
3rd rowSí
4th rowSí
5th rowSí

Common Values

ValueCountFrequency (%)
No 235
57.6%
Sí 171
41.9%
No por ahora 1
 
0.2%
(Missing) 1
 
0.2%

Length

2024-08-02T13:50:44.784192image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-08-02T13:50:45.077989image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
ValueCountFrequency (%)
no 236
57.7%
sí 171
41.8%
por 1
 
0.2%
ahora 1
 
0.2%

Most occurring characters

ValueCountFrequency (%)
o 238
28.9%
N 236
28.6%
S 171
20.8%
í 171
20.8%
2
 
0.2%
r 2
 
0.2%
a 2
 
0.2%
p 1
 
0.1%
h 1
 
0.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 415
50.4%
Uppercase Letter 407
49.4%
Space Separator 2
 
0.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 238
57.3%
í 171
41.2%
r 2
 
0.5%
a 2
 
0.5%
p 1
 
0.2%
h 1
 
0.2%
Uppercase Letter
ValueCountFrequency (%)
N 236
58.0%
S 171
42.0%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 822
99.8%
Common 2
 
0.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 238
29.0%
N 236
28.7%
S 171
20.8%
í 171
20.8%
r 2
 
0.2%
a 2
 
0.2%
p 1
 
0.1%
h 1
 
0.1%
Common
ValueCountFrequency (%)
2
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 653
79.2%
None 171
 
20.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o 238
36.4%
N 236
36.1%
S 171
26.2%
2
 
0.3%
r 2
 
0.3%
a 2
 
0.3%
p 1
 
0.2%
h 1
 
0.2%
None
ValueCountFrequency (%)
í 171
100.0%

l_actividades_conservacion
Text

Distinct127
Distinct (%)31.1%
Missing0
Missing (%)0.0%
Memory size3.3 KiB
2024-08-02T13:50:45.498455image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Length

Max length71
Median length60
Mean length16.84068627
Min length6

Characters and Unicode

Total characters6871
Distinct characters50
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

Unique85 ?
Unique (%)20.8%

Sample

1st rowCustodios del Archipiélago/Pulsos terricolas
2nd rowNinguno
3rd rowEducación ambiental
4th rowNinguno
5th rowMaestría de sustentabilidad
ValueCountFrequency (%)
ninguno 149
23.8%
reforestación 26
 
4.1%
sembrando/reforestación 23
 
3.7%
ambiental 22
 
3.5%
limpieza 21
 
3.3%
educación 20
 
3.2%
y 12
 
1.9%
del 11
 
1.8%
áreas 11
 
1.8%
huertos 10
 
1.6%
Other values (176) 322
51.4%
2024-08-02T13:50:46.402659image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
n 663
 
9.6%
e 625
 
9.1%
a 611
 
8.9%
i 600
 
8.7%
o 465
 
6.8%
r 346
 
5.0%
u 317
 
4.6%
317
 
4.6%
s 315
 
4.6%
c 299
 
4.4%
Other values (40) 2313
33.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 5874
85.5%
Uppercase Letter 555
 
8.1%
Space Separator 317
 
4.6%
Other Punctuation 125
 
1.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
n 663
11.3%
e 625
10.6%
a 611
10.4%
i 600
10.2%
o 465
 
7.9%
r 346
 
5.9%
u 317
 
5.4%
s 315
 
5.4%
c 299
 
5.1%
d 246
 
4.2%
Other values (18) 1387
23.6%
Uppercase Letter
ValueCountFrequency (%)
N 154
27.7%
R 92
16.6%
S 61
 
11.0%
C 45
 
8.1%
L 36
 
6.5%
E 29
 
5.2%
P 24
 
4.3%
D 21
 
3.8%
H 18
 
3.2%
T 13
 
2.3%
Other values (10) 62
11.2%
Space Separator
ValueCountFrequency (%)
317
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 125
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 6429
93.6%
Common 442
 
6.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
n 663
 
10.3%
e 625
 
9.7%
a 611
 
9.5%
i 600
 
9.3%
o 465
 
7.2%
r 346
 
5.4%
u 317
 
4.9%
s 315
 
4.9%
c 299
 
4.7%
d 246
 
3.8%
Other values (38) 1942
30.2%
Common
ValueCountFrequency (%)
317
71.7%
/ 125
 
28.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6638
96.6%
None 233
 
3.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
n 663
 
10.0%
e 625
 
9.4%
a 611
 
9.2%
i 600
 
9.0%
o 465
 
7.0%
r 346
 
5.2%
u 317
 
4.8%
317
 
4.8%
s 315
 
4.7%
c 299
 
4.5%
Other values (35) 2080
31.3%
None
ValueCountFrequency (%)
ó 182
78.1%
á 27
 
11.6%
í 16
 
6.9%
é 6
 
2.6%
ñ 2
 
0.9%

t_¿Qué le gustaría que mejorara con relación a los espacios verdes de Xalapa y Coatepec, tomando en cuenta circunstacias como COVID-19?
Text

Distinct377
Distinct (%)92.6%
Missing1
Missing (%)0.2%
Memory size3.3 KiB
2024-08-02T13:50:46.912670image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Length

Max length571
Median length147
Mean length64.16953317
Min length1

Characters and Unicode

Total characters26117
Distinct characters78
Distinct categories9 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique357 ?
Unique (%)87.7%

Sample

1st rowmejor mantenimiento de areas verdes, particularmente de las islas
2nd rowQue no los descuiden tanto
3rd rowQue los espacios verdes se protejan de las invasiones, de la tala y mal uso.
4th rowDistribución y abundancia
5th rowQue sigan abierto con las medidas preventivas
ValueCountFrequency (%)
que 226
 
6.1%
y 196
 
5.3%
más 99
 
2.7%
verdes 84
 
2.3%
los 82
 
2.2%
para 74
 
2.0%
las 73
 
2.0%
se 67
 
1.8%
espacios 67
 
1.8%
no 58
 
1.6%
Other values (1059) 2671
72.2%
2024-08-02T13:50:47.854818image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3972
15.2%
e 2889
11.1%
a 2538
 
9.7%
s 1958
 
7.5%
o 1566
 
6.0%
r 1560
 
6.0%
n 1432
 
5.5%
i 1397
 
5.3%
d 973
 
3.7%
c 943
 
3.6%
Other values (68) 6889
26.4%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 21140
80.9%
Space Separator 3972
 
15.2%
Uppercase Letter 629
 
2.4%
Other Punctuation 323
 
1.2%
Close Punctuation 17
 
0.1%
Open Punctuation 13
 
< 0.1%
Decimal Number 10
 
< 0.1%
Dash Punctuation 7
 
< 0.1%
Control 6
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 2889
13.7%
a 2538
12.0%
s 1958
 
9.3%
o 1566
 
7.4%
r 1560
 
7.4%
n 1432
 
6.8%
i 1397
 
6.6%
d 973
 
4.6%
c 943
 
4.5%
u 887
 
4.2%
Other values (23) 4997
23.6%
Uppercase Letter
ValueCountFrequency (%)
Q 107
17.0%
M 95
15.1%
S 59
9.4%
E 54
8.6%
A 46
7.3%
C 41
 
6.5%
L 38
 
6.0%
N 32
 
5.1%
R 23
 
3.7%
P 21
 
3.3%
Other values (15) 113
18.0%
Other Punctuation
ValueCountFrequency (%)
, 173
53.6%
. 131
40.6%
/ 5
 
1.5%
" 4
 
1.2%
; 3
 
0.9%
' 2
 
0.6%
¡ 2
 
0.6%
! 2
 
0.6%
? 1
 
0.3%
Decimal Number
ValueCountFrequency (%)
2 4
40.0%
0 2
20.0%
1 1
 
10.0%
3 1
 
10.0%
4 1
 
10.0%
6 1
 
10.0%
Space Separator
ValueCountFrequency (%)
3972
100.0%
Close Punctuation
ValueCountFrequency (%)
) 17
100.0%
Open Punctuation
ValueCountFrequency (%)
( 13
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%
Control
ValueCountFrequency (%)
6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 21769
83.4%
Common 4348
 
16.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 2889
13.3%
a 2538
11.7%
s 1958
 
9.0%
o 1566
 
7.2%
r 1560
 
7.2%
n 1432
 
6.6%
i 1397
 
6.4%
d 973
 
4.5%
c 943
 
4.3%
u 887
 
4.1%
Other values (48) 5626
25.8%
Common
ValueCountFrequency (%)
3972
91.4%
, 173
 
4.0%
. 131
 
3.0%
) 17
 
0.4%
( 13
 
0.3%
- 7
 
0.2%
6
 
0.1%
/ 5
 
0.1%
2 4
 
0.1%
" 4
 
0.1%
Other values (10) 16
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 25680
98.3%
None 437
 
1.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3972
15.5%
e 2889
11.2%
a 2538
 
9.9%
s 1958
 
7.6%
o 1566
 
6.1%
r 1560
 
6.1%
n 1432
 
5.6%
i 1397
 
5.4%
d 973
 
3.8%
c 943
 
3.7%
Other values (59) 6452
25.1%
None
ValueCountFrequency (%)
á 206
47.1%
ó 102
23.3%
í 45
 
10.3%
é 40
 
9.2%
ú 23
 
5.3%
ñ 15
 
3.4%
Á 3
 
0.7%
¡ 2
 
0.5%
à 1
 
0.2%

l_gustaria_que_mejorara
Text

Distinct137
Distinct (%)33.7%
Missing1
Missing (%)0.2%
Memory size3.3 KiB
2024-08-02T13:50:48.270161image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Length

Max length110
Median length58
Mean length26.03685504
Min length1

Characters and Unicode

Total characters10597
Distinct characters47
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

Unique86 ?
Unique (%)21.1%

Sample

1st rowMantenimiento de áreas verdes
2nd rowMantenimiento de áreas verdes
3rd rowProtección de áreas verdes
4th rowDistribución/Abundancia
5th rowParques abiertos
ValueCountFrequency (%)
áreas 229
20.7%
verdes 162
14.6%
abiertas 64
 
5.8%
más 59
 
5.3%
parques 47
 
4.2%
mantenimiento 43
 
3.9%
mantener 38
 
3.4%
verdes/mantenimiento 22
 
2.0%
seguridad 20
 
1.8%
abiertos/mantener 20
 
1.8%
Other values (166) 404
36.5%
2024-08-02T13:50:48.984569image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 1655
15.6%
a 974
 
9.2%
s 914
 
8.6%
r 908
 
8.6%
827
 
7.8%
i 650
 
6.1%
n 618
 
5.8%
d 530
 
5.0%
t 491
 
4.6%
o 351
 
3.3%
Other values (37) 2679
25.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 8908
84.1%
Space Separator 827
 
7.8%
Uppercase Letter 636
 
6.0%
Other Punctuation 226
 
2.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 1655
18.6%
a 974
10.9%
s 914
10.3%
r 908
10.2%
i 650
 
7.3%
n 618
 
6.9%
d 530
 
5.9%
t 491
 
5.5%
o 351
 
3.9%
á 334
 
3.7%
Other values (18) 1483
16.6%
Uppercase Letter
ValueCountFrequency (%)
M 247
38.8%
C 75
 
11.8%
S 71
 
11.2%
P 54
 
8.5%
R 46
 
7.2%
L 42
 
6.6%
D 26
 
4.1%
N 21
 
3.3%
V 10
 
1.6%
I 10
 
1.6%
Other values (7) 34
 
5.3%
Space Separator
ValueCountFrequency (%)
827
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 226
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 9544
90.1%
Common 1053
 
9.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 1655
17.3%
a 974
10.2%
s 914
9.6%
r 908
9.5%
i 650
 
6.8%
n 618
 
6.5%
d 530
 
5.6%
t 491
 
5.1%
o 351
 
3.7%
á 334
 
3.5%
Other values (35) 2119
22.2%
Common
ValueCountFrequency (%)
827
78.5%
/ 226
 
21.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10115
95.5%
None 482
 
4.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 1655
16.4%
a 974
9.6%
s 914
9.0%
r 908
9.0%
827
 
8.2%
i 650
 
6.4%
n 618
 
6.1%
d 530
 
5.2%
t 491
 
4.9%
o 351
 
3.5%
Other values (31) 2197
21.7%
None
ValueCountFrequency (%)
á 334
69.3%
ó 102
 
21.2%
í 22
 
4.6%
é 15
 
3.1%
Á 8
 
1.7%
ñ 1
 
0.2%

Interactions

2024-08-02T13:50:21.316640image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/

Missing values

2024-08-02T13:50:21.650776image/svg+xmlMatplotlib v3.8.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-08-02T13:50:22.543010image/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

l_Marca temporall_Una vez que haya decidido participar, le solicitamos que acepte esta forma de consentimiento.l_Sexol_Edadl_Último nivel de estudios completol_¿Es actualmente empleado de un trabajo remunerado?l_empleadol_statusl_cpl_municipiol_estado_civill_habitantes_casal_tipo_casal_contextol_arboles_cercal_areas_verdesl_espacio_recreol_sonidos_agradablesl_sonidos_desagradablesl_area_verde_casal_freq_visita_area_verdel_importancia_av_crisis_sanitarial_conoces_veg_rodeal_ventanal_disfruta_entornot_Escribe 5 palabras asociadas a lo que más has disfrutado del confinamiento voluntariol_disfrutado_confinamientot_Escribe 5 palabras asociadas a lo que menos has disfrutado durante el confinamiento voluntariol_menos_disfrutado_confinamientol_vive_urb_quiere_rurall_vive_rur_quiere_urbl_participa_act_conservacionl_actividades_conservaciont_¿Qué le gustaría que mejorara con relación a los espacios verdes de Xalapa y Coatepec, tomando en cuenta circunstacias como COVID-19?l_gustaria_que_mejorara
02020-10-22 10:58:43.180Sí acepto participarMujer51-55PosgradoSi, asalariado/recibe un sueldo fijoSiAsalariado/Sueldo fijo91056.0XalapaCasado (a)5 o másCasa sola en colonia consolidadaUrbanoSíSíSiNaNNaNSiSiempreConsiderablemente importantesSíBosqueConsiderablementesalir a caminar con mi familia y perrhijos al area verde detras del parque el hayaCaminar/Familia/Mascotas/Áreas verdes/Parqueel poco respeto de mucha gente a las medidas sanitariasIncertidumbre/Miedo/InconcienciaSíNoSíCustodios del Archipiélago/Pulsos terricolasmejor mantenimiento de areas verdes, particularmente de las islasMantenimiento de áreas verdes
12020-10-26 11:15:09.800Sí acepto participarMujer26-30LicenciaturaSi, asalariado/recibe un sueldo fijoSiAsalariado/Sueldo fijo91400.0XalapaSoltero (a)2Departamento en condominioUrbanoNoNoNoEl canto de diversas avesAutomóvilesNoNuncaConsiderablemente importantesNoCasasMas o menosFamilia, unión, paz, juegos, cuidadoFamilia/Unión/Paz/Juegos/CuidadoIncertidumbre, miedo, estrés, insomnio, flojeraIncertidumbre/Miedo/Estrés/Insomnio/FlojeraSíNoNoNingunoQue no los descuiden tantoMantenimiento de áreas verdes
22020-10-26 11:23:27.470Sí acepto participarMujer31-35LicenciaturaSi, asalariado/recibe un sueldo fijoSiAsalariado/Sueldo fijo91517.0CoatepecSoltero (a)1Casa sola en colonia consolidadaRural o boscosoSíSíSiEl canto de diversas aves/Insectos/Lluvia/VientoAutomóviles/Camiones/MaquinariaSiPocas veces al añoConsiderablemente importantesSíBosque/Aves/MariposasConsiderablementesoledad, creatividad, tranquilidad, bosque, río.Soledad/Creatividad/Tranquilidad/Bosque/Ríosoledad, aislamiento, familia lejos, sin noción del tiempo, infodemiaSoledad/Aislamiento/Infodemia/AtemporalidadSíNoSíEducación ambientalQue los espacios verdes se protejan de las invasiones, de la tala y mal uso.Protección de áreas verdes
32020-10-26 11:25:19.230Sí acepto participarHombre66 o másPosgradoNo, jubiladoNoJubilado91500.0CoatepecSoltero (a)2Casa sola en colonia consolidadaUrbanoSíNoSiEl canto de diversas avesVendedoresSiPocas veces al añoConsiderablemente importantesSíCasas/Cerro de las CulebrasConsiderablementeLeer, autoreflexion, hacer ejercicio, relajarme meditarLeer/Autoreflexión/Ejercicio/Relajarme/MeditarNo salir en bicicleta ni a correr ni caminar con mis perritosAislamiento/SoledadSíNoSíNingunoDistribución y abundanciaDistribución/Abundancia
42020-10-26 11:28:27.110Sí acepto participarMujer26-30PosgradoNo, estudiante de tiempo completoNoEstudiante de tiempo completo91040.0XalapaUnión libre4Casa sola en colonia consolidadaUrbanoSíSíSiEl canto de diversas avesTráficoSiPocas veces al añoConsiderablemente importantesSíÁrbolesConsiderablementePaz \nAmor \nSolidaridad \nRespeto\nArmoníaPaz/Amor/Solidaridad/Respeto/ArmoníaPreocupación, enfermedad, covid, dinero, desempleoPreocupación/Enfermedad/Covid/Dinero/DesempleoSíNoSíMaestría de sustentabilidadQue sigan abierto con las medidas preventivasParques abiertos
52020-10-26 11:35:27.210Sí acepto participarMujer36-40PosgradoSi, asalariado/recibe un sueldo fijoSiAsalariado/Sueldo fijo91000.0XalapaUnión libre3Casa en fraccionamiento o conjunto habitacionalUrbanoSíSíSiEl canto de diversas aves/VientoAutomóvilesSiVarias veces a la semanaConsiderablemente importantesSíCasas/Árboles/Plantas/Mariposas/AutosConsiderablementeEstar con mi familia todo el tiempo, poder cocinar para mi familia, disfrutar de mi jardín, arreglar mi casaFamilia/Cocinar/Jardín/Arreglar/CasaNo poder ir a la playa o a pasear, la escasez de algunos productos en los supermercados, que mi hijo no vaya a la escuelaAislamiento/EncierroSíNoSíReforestaciónPreservarlos y protegerlos de invasiones ilegales para que futuras generaciones puedan disfrutar de aire limpioProtección de áreas verdes
62020-10-26 11:43:50.480Sí acepto participarMujer41-45PosgradoSi, asalariado/recibe un sueldo fijoSiAsalariado/Sueldo fijo91180.0XalapaCasado (a)5 o másCasa en colonia popularUrbanoSíSíNoEl canto de diversas avesAutomóviles/VendedoresSiPocas veces al añoConsiderablemente importantesSíCasas/Pico de Orizaba/Cofre de Perote/MacuiltepecConsiderablementeSeguros, sanos, tranquilos, ocupados, juntosCuidado/Seguridad/Tranquilidad/Ocupaciones/UniónVecinos inconscientes sin protección.InconcienciaSíNoSíReforestaciónEl aseo de las áreas para prevenir fauna nociva. Concientizar a la población y que la recolección de basura sea frecuente.Mantenimiento de áreas verdes/Concientización/Recolección de basura
72020-10-26 11:48:33.870Sí acepto participarMujer66 o másLicenciaturaNo, labores del hogar de tiempo completoNoLabores del hogar de tiempo completo91637.0XalapaUnión libre2Casa en fraccionamiento o conjunto habitacionalUrbanoSíSíSiEl canto de diversas avesTráfico/MúsicaSiPocas veces al mesConsiderablemente importantesNoÁrbolesConsiderablementeNaturaleza y canto de pájarosNaturaleza/El canto de las avesNo socializar ni ver familiaSoledadSíNoNoNingunoMucha más limpieza y promover está en los espacios verdes , colocar botes de basura y recoger la basura de estos , no abandonarlos llenos .Limpieza de áreas verdes/Difusión/Promoción/Botes de basura
82020-10-26 11:57:56.260Sí acepto participarMujer51-55LicenciaturaSi, negocio propio formalSiNegocio propio formal91517.0CoatepecSoltero (a)1Casa sola en colonia consolidadaRural o boscosoSíSíSiEl canto de diversas aves/Viento/RíoAutomóvilesSiDiariamenteConsiderablemente importantesSíÁrbolesConsiderablementeEl bosque, leer, observar, escribir, reflexionarBosque/Leer/Observar/Escribir/ReflexionarViajar, tapabocas, salir, gel, miedoDesinfectantes/Miedo/IncertidumbreSíNoNoNingunoQue los parques estén abiertos, sembrar más árboles y floresParques abiertos/Árboles
92020-10-26 11:58:52.440Sí acepto participarMujer51-55PosgradoSi, negocio propio formalSiNegocio propio formal91540.0CoatepecCasado (a)3Casa en colonia popularRural o boscosoSíSíSiEl canto de diversas aves/RíoVendedores/Música/MaquinariaSiVarias veces a la semanaConsiderablemente importantesSíÁrbolesConsiderablementeA mi hijo y gataFamilia/MascotasMi hijo extraña a sus amigosExtrañamientoSíSíSíPromoción/LombricompostaSeguridadSeguridad
l_Marca temporall_Una vez que haya decidido participar, le solicitamos que acepte esta forma de consentimiento.l_Sexol_Edadl_Último nivel de estudios completol_¿Es actualmente empleado de un trabajo remunerado?l_empleadol_statusl_cpl_municipiol_estado_civill_habitantes_casal_tipo_casal_contextol_arboles_cercal_areas_verdesl_espacio_recreol_sonidos_agradablesl_sonidos_desagradablesl_area_verde_casal_freq_visita_area_verdel_importancia_av_crisis_sanitarial_conoces_veg_rodeal_ventanal_disfruta_entornot_Escribe 5 palabras asociadas a lo que más has disfrutado del confinamiento voluntariol_disfrutado_confinamientot_Escribe 5 palabras asociadas a lo que menos has disfrutado durante el confinamiento voluntariol_menos_disfrutado_confinamientol_vive_urb_quiere_rurall_vive_rur_quiere_urbl_participa_act_conservacionl_actividades_conservaciont_¿Qué le gustaría que mejorara con relación a los espacios verdes de Xalapa y Coatepec, tomando en cuenta circunstacias como COVID-19?l_gustaria_que_mejorara
3982021-07-08 14:39:14.190Sí acepto participarMujer51-55PosgradoSi, asalariado/recibe un sueldo fijoSiAsalariado/Sueldo fijo91170.0XalapaCasado (a)3Casa sola en colonia consolidadaUrbanoSíSíSiEl canto de diversas aves/VientoAutomóvilesSiPocas veces al añoConsiderablemente importantesSíÁrboles/PlantasConsiderablementeLos pájaros y lo verde de los arbolesÁreas verdes/Pájaros/ÁrbolesEstar con mis. FamiliaresEncierro/AislamientoSíNoNoNingunoNada por el momentoNada
3992021-08-20 13:57:37.500Sí acepto participarMujer21-25LicenciaturaNo, estudiante de tiempo completoNoEstudiante de tiempo completo91090.0XalapaSoltero (a)1Casa sola en colonia consolidadaUrbanoSíSíSiEl canto de diversas aves/Viento/LluviaAutomóviles/Cláxon/CampanasSiVarias veces a la semanaConsiderablemente importantesSíCasas/Autos/Árboles/Tiendas/Sol/Nubes/CallesModeradamentereflexión, tiempo de descanso, independencia, aprendizaje, gratitudReflexión/Descanso/Independencia/Aprendizaje/Gratitudsoledad, aburrimiento, caos, miedo, distanciaSoledad/Aburrimiento/Caos/Miedo/DistanciaSíNoSíPláticas/Talleres/Senderismola limpieza y el alumbradoLimpieza/Iluminación
4002021-08-23 13:43:32.150Sí acepto participarHombre36-40LicenciaturaNo, estudiante de tiempo completoNoEstudiante de tiempo completo91180.0XalapaSoltero (a)1Casa sola en colonia consolidadaUrbanoSíSíSiEl canto de diversas aves/VientoAutomóviles/Cláxon/Maquinaria/VendedoresSiVarias veces a la semanaConsiderablemente importantesSíÁrboles/PlantasModeradamenteTiempo y espacio conmigo mismoTimepo/Espacio/Introspeccióncontacto con amigos y gente nuevaContacto/Aislamiento/Amistades/EncierroSíMe da igualNoMantenimiento de áreas verdesEn áreas verdes de la ciudad, me gustaría que los vecinos a los que les corresponde ese espacio, pudieran involucrarse más en su cuidado. Pienso que de esa forma estas áreas se pueden mantener y disminuye el riesgo a que desaparezcanMantenimiento de áreas verdes
4012021-08-24 18:25:02.960Sí acepto participarMujer26-30PosgradoNo, estudiante de tiempo completoNoEstudiante de tiempo completo91075.0XalapaCasado (a)1Casa en colonia popularUrbanoNoNoNoEl canto de diversas avesAutomóviles/MaquinariaNoPocas veces al mesConsiderablemente importantesSíPlantasMas o menostiempo para conocerme mejor, paz, disfrutar más el contacto con la naturaleza, meditarTiempo/Concentración/Paz/Naturaleza/Meditarsoledad, no poder hacer muchas actidades que comunmente hago como: salir con mis amigos, visitar parques, hacer ejercicio, salir a bailar, en ocasiones no poder estar en contacto con la naturalezaSoledad/AislamientoSíSíSíReforestaciónQue existierá un mayor sentido de pertenencia de la población y las autoridades, que se colocarán más señaleticas con respecto a lo que no se debe hacer en estos lugares, en el caso que no sean lugares de libre aceso mantenerlos abierto tomando todas las medidas necesarias de prevención, generar una mayor conciencia en la población sobre la necesidad que tenemos como seres humanos dependientes de un oxigeno limpio de cuidar todos estos espacios verdes que tenemos, ya que no hay nada mejor que poder respirar un aire puro y más en estos tiempos de covit.Mantener abiertas áreas verdes/Concientización
4022021-09-28 14:31:45.800Sí acepto participarMujer36-40PosgradoSi, asalariado/recibe un sueldo fijoSiAsalariado/Sueldo fijo91090.0XalapaUnión libre2Casa en fraccionamiento o conjunto habitacionalUrbanoSíSíSiEl canto de diversas aves/Insectos/VientoVendedores/VoceadoresSiVarias veces a la semanaConsiderablemente importantesSíCasas/Jardín/ÁrbolesConsiderablementejardín, teletrabajo, ejercicio en casa, familia, comer en casa.Jardín/Homoffice/Ejercicio/Familia/Comernoticias, estrés, internet, lento, enfermedadNoticias/Estrés/Virtualidad/EnfermedadSíMe da igualSíReforestación/Difusión/DivulgaciónMás iluminación nocturna, más seguridad, más limpieza o remoción de residuos solidos.Seguridad/Limpieza/Iluminación
4032021-12-01 20:18:23.930Sí acepto participarHombre41-45LicenciaturaSi, asalariado/recibe un sueldo fijo, Si, por comisiones, Si, negocio propio formalSiAsalariado/Sueldo fijo/Por comisiones/Negocio propio formal91190.0XalapaUnión libre4Casa sola en colonia consolidadaUrbanoSíSíSiEl canto de diversas avesAutomóviles/CamionesSiVarias veces a la semanaConsiderablemente importantesSíCasas/ÁrbolesConsiderablementeFamilia, comidas, perros, libros, tvFamilia/Comida/Mascotas/Libros/Ver televisiónRedes sociales, aparatos tecnológicosRedes sociales/TegnologíaSíNoNoNingunoLimpieza de áreas verdes, árboles frutales en camellones y parquesLimpieza de áreas verdes/Árboles/Más áreas verdes/Mantener abiertas áreas verdes
4042021-12-06 15:24:07.300Sí acepto participarMujer41-45LicenciaturaNo, labores del hogar de tiempo completoNoLabores del hogar de tiempo completo91199.0XalapaCasado (a)5 o másCasa en fraccionamiento o conjunto habitacionalUrbanoSíSíSiEl canto de diversas avesNingunoSiVarias veces a la semanaConsiderablemente importantesSíÁrbolesConsiderablementeFamilia, espacios abiertos, ejercicio al aire libre.Familia/Espacio/Ejercicio/Aire libreVida socialVida SocialSíNoNoSembrando/ReforestaciónCuidado por parte de las autoridades de todos los espacios al aire libreCuidado/Mantenimiento
4052022-05-09 20:42:44.770Sí acepto participarHombre31-35LicenciaturaNo, estudiante de tiempo completoNoEstudiante de tiempo completo72150.0XalapaSoltero (a)3Casa en fraccionamiento o conjunto habitacionalUrbanoSíSíSiEl canto de diversas aves/InsectosCamionesSiPocas veces al añoConsiderablemente importantesNoCasas/VegetaciónConsiderablemente1) Tranquilidad 2) Espacio 3) Familia 4) Comodidad 5) ConvenienciaTranquilidad/Espacio/Familia/Comodidad/Convivencia1) Confinamiento 2) Muerte 3) Tristeza 4) Soledad 5) DistanciaConfinamiento/Muerte/Tristeza/Soledad/DistanciaSíNoNoNingunoQue pudieran estar dispuestos de tal forma que pudieran ser seguros para caminarse, y que existiera concientización sobre cierto uso, actividades, para estos espacios.Seguridad/Mantener abiertas áreas verdes
4062022-05-11 12:24:53.990No acepto participarMujer41-45PosgradoSi, asalariado/recibe un sueldo fijo, Si, negocio propio formalSiAsalariado/Sueldo fijo/Negocio propio formal91550.0CoatepecSoltero (a)2Casa sola en colonia consolidadaRural o boscosoSíSíSiEl canto de diversas aves/InsectosFiestasSiDiariamenteConsiderablemente importantesSíÁrboles/Cerro/Bosque/SiembraConsiderablementeNo he tenido confinamiento, mi trabajo no lo permiteNo he tenido confinamiento por trabajofilas, tiempo, excesos, paranoia, inconvenientesFilas/Tiempo/Excesos/Paranoia/InconvenientesSíNoSíTratamiento de aguas residuales/Siembra/Reforestaciónque se abrieran no veo razon para cerrarlosMantener abiertas áreas verdes
407NaTNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNSembrando/ReforestaciónNaNNaN