Overview

Dataset statistics

Number of variables28
Number of observations3
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory781.0 B
Average record size in memory260.3 B

Variable types

Categorical24
Boolean4

Alerts

tipoCaso has constant value "Novo"Constant
cultEsc has constant value "N/realiz"Constant
NECROP has constant value "N/realiz"Constant
hiv has constant value "Pos"Constant
aids has constant value "S"Constant
DIABETES has constant value "False"Constant
ALCOOLISMO has constant value "False"Constant
MENTAL has constant value "False"Constant
DROGADICAO has constant value "False"Constant
motMudEsquema has constant value "Nulo"Constant
HISTOPATOL has constant value "N/realiz"Constant
Status_Resistencia has constant value "1"Constant
Cluster has constant value "0"Constant
faixaEtaria is highly overall correlated with sexo and 13 other fieldsHigh correlation
sexo is highly overall correlated with faixaEtaria and 4 other fieldsHigh correlation
ESCOLARID is highly overall correlated with faixaEtaria and 4 other fieldsHigh correlation
TIPOCUP is highly overall correlated with faixaEtaria and 4 other fieldsHigh correlation
sitAtual is highly overall correlated with faixaEtaria and 4 other fieldsHigh correlation
FORMACLIN1 is highly overall correlated with faixaEtaria and 4 other fieldsHigh correlation
classif is highly overall correlated with faixaEtaria and 13 other fieldsHigh correlation
descoberta is highly overall correlated with faixaEtaria and 4 other fieldsHigh correlation
bac is highly overall correlated with faixaEtaria and 13 other fieldsHigh correlation
BACOUTRO is highly overall correlated with faixaEtaria and 4 other fieldsHigh correlation
RX is highly overall correlated with faixaEtaria and 4 other fieldsHigh correlation
TABAGISMO is highly overall correlated with faixaEtaria and 4 other fieldsHigh correlation
tipoTrat is highly overall correlated with faixaEtaria and 4 other fieldsHigh correlation
idade is highly overall correlated with faixaEtaria and 13 other fieldsHigh correlation
Probabilidade is highly overall correlated with faixaEtaria and 13 other fieldsHigh correlation
faixaEtaria is uniformly distributedUniform
classif is uniformly distributedUniform
bac is uniformly distributedUniform
idade is uniformly distributedUniform
Probabilidade is uniformly distributedUniform
faixaEtaria has unique valuesUnique
classif has unique valuesUnique
bac has unique valuesUnique
idade has unique valuesUnique
Probabilidade has unique valuesUnique

Reproduction

Analysis started2023-10-31 19:30:00.620074
Analysis finished2023-10-31 19:30:03.300165
Duration2.68 seconds
Software versionpandas-profiling v3.6.6
Download configurationconfig.json

Variables

faixaEtaria
Categorical

HIGH CORRELATION  UNIFORM  UNIQUE 

Distinct3
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size48.0 B
20_29
1 
40_49
1 
30_39
1 

Length

Max length5
Median length5
Mean length5
Min length5

Characters and Unicode

Total characters15
Distinct characters6
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

Unique3 ?
Unique (%)100.0%

Sample

1st row20_29
2nd row40_49
3rd row30_39

Common Values

ValueCountFrequency (%)
20_29 1
33.3%
40_49 1
33.3%
30_39 1
33.3%

Length

2023-10-31T16:30:03.814173image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-10-31T16:30:03.956420image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
ValueCountFrequency (%)
20_29 1
33.3%
40_49 1
33.3%
30_39 1
33.3%

Most occurring characters

ValueCountFrequency (%)
0 3
20.0%
_ 3
20.0%
9 3
20.0%
2 2
13.3%
4 2
13.3%
3 2
13.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 12
80.0%
Connector Punctuation 3
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3
25.0%
9 3
25.0%
2 2
16.7%
4 2
16.7%
3 2
16.7%
Connector Punctuation
ValueCountFrequency (%)
_ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 15
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3
20.0%
_ 3
20.0%
9 3
20.0%
2 2
13.3%
4 2
13.3%
3 2
13.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 15
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3
20.0%
_ 3
20.0%
9 3
20.0%
2 2
13.3%
4 2
13.3%
3 2
13.3%

sexo
Categorical

Distinct2
Distinct (%)66.7%
Missing0
Missing (%)0.0%
Memory size151.0 B
F
2 
M
1 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters3
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)33.3%

Sample

1st rowF
2nd rowM
3rd rowF

Common Values

ValueCountFrequency (%)
F 2
66.7%
M 1
33.3%

Length

2023-10-31T16:30:04.078051image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-10-31T16:30:04.214025image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
ValueCountFrequency (%)
f 2
66.7%
m 1
33.3%

Most occurring characters

ValueCountFrequency (%)
F 2
66.7%
M 1
33.3%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 3
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
F 2
66.7%
M 1
33.3%

Most occurring scripts

ValueCountFrequency (%)
Latin 3
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
F 2
66.7%
M 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
F 2
66.7%
M 1
33.3%

ESCOLARID
Categorical

Distinct2
Distinct (%)66.7%
Missing0
Missing (%)0.0%
Memory size48.0 B
De 4 a 7 anos
2 
De 8 a 11 anos
1 

Length

Max length14
Median length13
Mean length13.333333
Min length13

Characters and Unicode

Total characters40
Distinct characters11
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

Unique1 ?
Unique (%)33.3%

Sample

1st rowDe 4 a 7 anos
2nd rowDe 8 a 11 anos
3rd rowDe 4 a 7 anos

Common Values

ValueCountFrequency (%)
De 4 a 7 anos 2
66.7%
De 8 a 11 anos 1
33.3%

Length

2023-10-31T16:30:04.329359image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-10-31T16:30:04.485124image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
ValueCountFrequency (%)
de 3
20.0%
a 3
20.0%
anos 3
20.0%
4 2
13.3%
7 2
13.3%
8 1
 
6.7%
11 1
 
6.7%

Most occurring characters

ValueCountFrequency (%)
12
30.0%
a 6
15.0%
D 3
 
7.5%
e 3
 
7.5%
n 3
 
7.5%
o 3
 
7.5%
s 3
 
7.5%
4 2
 
5.0%
7 2
 
5.0%
1 2
 
5.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 18
45.0%
Space Separator 12
30.0%
Decimal Number 7
 
17.5%
Uppercase Letter 3
 
7.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 6
33.3%
e 3
16.7%
n 3
16.7%
o 3
16.7%
s 3
16.7%
Decimal Number
ValueCountFrequency (%)
4 2
28.6%
7 2
28.6%
1 2
28.6%
8 1
14.3%
Space Separator
ValueCountFrequency (%)
12
100.0%
Uppercase Letter
ValueCountFrequency (%)
D 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 21
52.5%
Common 19
47.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 6
28.6%
D 3
14.3%
e 3
14.3%
n 3
14.3%
o 3
14.3%
s 3
14.3%
Common
ValueCountFrequency (%)
12
63.2%
4 2
 
10.5%
7 2
 
10.5%
1 2
 
10.5%
8 1
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 40
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
12
30.0%
a 6
15.0%
D 3
 
7.5%
e 3
 
7.5%
n 3
 
7.5%
o 3
 
7.5%
s 3
 
7.5%
4 2
 
5.0%
7 2
 
5.0%
1 2
 
5.0%

TIPOCUP
Categorical

Distinct2
Distinct (%)66.7%
Missing0
Missing (%)0.0%
Memory size48.0 B
Desempregado
2 
Dona de Casa
1 

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters36
Distinct characters13
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 (%)33.3%

Sample

1st rowDona de Casa
2nd rowDesempregado
3rd rowDesempregado

Common Values

ValueCountFrequency (%)
Desempregado 2
66.7%
Dona de Casa 1
33.3%

Length

2023-10-31T16:30:04.621313image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-10-31T16:30:04.816391image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
ValueCountFrequency (%)
desempregado 2
40.0%
dona 1
20.0%
de 1
20.0%
casa 1
20.0%

Most occurring characters

ValueCountFrequency (%)
e 7
19.4%
a 5
13.9%
D 3
8.3%
s 3
8.3%
d 3
8.3%
o 3
8.3%
m 2
 
5.6%
p 2
 
5.6%
r 2
 
5.6%
g 2
 
5.6%
Other values (3) 4
11.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 30
83.3%
Uppercase Letter 4
 
11.1%
Space Separator 2
 
5.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 7
23.3%
a 5
16.7%
s 3
10.0%
d 3
10.0%
o 3
10.0%
m 2
 
6.7%
p 2
 
6.7%
r 2
 
6.7%
g 2
 
6.7%
n 1
 
3.3%
Uppercase Letter
ValueCountFrequency (%)
D 3
75.0%
C 1
 
25.0%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 34
94.4%
Common 2
 
5.6%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 7
20.6%
a 5
14.7%
D 3
8.8%
s 3
8.8%
d 3
8.8%
o 3
8.8%
m 2
 
5.9%
p 2
 
5.9%
r 2
 
5.9%
g 2
 
5.9%
Other values (2) 2
 
5.9%
Common
ValueCountFrequency (%)
2
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 36
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 7
19.4%
a 5
13.9%
D 3
8.3%
s 3
8.3%
d 3
8.3%
o 3
8.3%
m 2
 
5.6%
p 2
 
5.6%
r 2
 
5.6%
g 2
 
5.6%
Other values (3) 4
11.1%

sitAtual
Categorical

Distinct2
Distinct (%)66.7%
Missing0
Missing (%)0.0%
Memory size48.0 B
Cura
2 
Abandono
1 

Length

Max length8
Median length4
Mean length5.3333333
Min length4

Characters and Unicode

Total characters16
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

Unique1 ?
Unique (%)33.3%

Sample

1st rowAbandono
2nd rowCura
3rd rowCura

Common Values

ValueCountFrequency (%)
Cura 2
66.7%
Abandono 1
33.3%

Length

2023-10-31T16:30:04.951653image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-10-31T16:30:05.102072image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
ValueCountFrequency (%)
cura 2
66.7%
abandono 1
33.3%

Most occurring characters

ValueCountFrequency (%)
a 3
18.8%
C 2
12.5%
u 2
12.5%
r 2
12.5%
n 2
12.5%
o 2
12.5%
A 1
 
6.2%
b 1
 
6.2%
d 1
 
6.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 13
81.2%
Uppercase Letter 3
 
18.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 3
23.1%
u 2
15.4%
r 2
15.4%
n 2
15.4%
o 2
15.4%
b 1
 
7.7%
d 1
 
7.7%
Uppercase Letter
ValueCountFrequency (%)
C 2
66.7%
A 1
33.3%

Most occurring scripts

ValueCountFrequency (%)
Latin 16
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 3
18.8%
C 2
12.5%
u 2
12.5%
r 2
12.5%
n 2
12.5%
o 2
12.5%
A 1
 
6.2%
b 1
 
6.2%
d 1
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 16
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 3
18.8%
C 2
12.5%
u 2
12.5%
r 2
12.5%
n 2
12.5%
o 2
12.5%
A 1
 
6.2%
b 1
 
6.2%
d 1
 
6.2%

tipoCaso
Categorical

Distinct1
Distinct (%)33.3%
Missing0
Missing (%)0.0%
Memory size48.0 B
Novo
3 

Length

Max length4
Median length4
Mean length4
Min length4

Characters and Unicode

Total characters12
Distinct characters3
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 rowNovo
2nd rowNovo
3rd rowNovo

Common Values

ValueCountFrequency (%)
Novo 3
100.0%

Length

2023-10-31T16:30:05.219629image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-10-31T16:30:05.352726image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
ValueCountFrequency (%)
novo 3
100.0%

Most occurring characters

ValueCountFrequency (%)
o 6
50.0%
N 3
25.0%
v 3
25.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 9
75.0%
Uppercase Letter 3
 
25.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 6
66.7%
v 3
33.3%
Uppercase Letter
ValueCountFrequency (%)
N 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 12
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 6
50.0%
N 3
25.0%
v 3
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 12
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o 6
50.0%
N 3
25.0%
v 3
25.0%

FORMACLIN1
Categorical

Distinct2
Distinct (%)66.7%
Missing0
Missing (%)0.0%
Memory size48.0 B
Pul
2 
Pleural
1 

Length

Max length7
Median length3
Mean length4.3333333
Min length3

Characters and Unicode

Total characters13
Distinct characters6
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

Unique1 ?
Unique (%)33.3%

Sample

1st rowPul
2nd rowPleural
3rd rowPul

Common Values

ValueCountFrequency (%)
Pul 2
66.7%
Pleural 1
33.3%

Length

2023-10-31T16:30:05.469513image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-10-31T16:30:05.620438image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
ValueCountFrequency (%)
pul 2
66.7%
pleural 1
33.3%

Most occurring characters

ValueCountFrequency (%)
l 4
30.8%
P 3
23.1%
u 3
23.1%
e 1
 
7.7%
r 1
 
7.7%
a 1
 
7.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 10
76.9%
Uppercase Letter 3
 
23.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
l 4
40.0%
u 3
30.0%
e 1
 
10.0%
r 1
 
10.0%
a 1
 
10.0%
Uppercase Letter
ValueCountFrequency (%)
P 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 13
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
l 4
30.8%
P 3
23.1%
u 3
23.1%
e 1
 
7.7%
r 1
 
7.7%
a 1
 
7.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 13
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
l 4
30.8%
P 3
23.1%
u 3
23.1%
e 1
 
7.7%
r 1
 
7.7%
a 1
 
7.7%

classif
Categorical

HIGH CORRELATION  UNIFORM  UNIQUE 

Distinct3
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size48.0 B
P+E
1 
Ext
1 
Pul
1 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters9
Distinct characters7
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

Unique3 ?
Unique (%)100.0%

Sample

1st rowP+E
2nd rowExt
3rd rowPul

Common Values

ValueCountFrequency (%)
P+E 1
33.3%
Ext 1
33.3%
Pul 1
33.3%

Length

2023-10-31T16:30:05.734921image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-10-31T16:30:05.879287image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
ValueCountFrequency (%)
p+e 1
33.3%
ext 1
33.3%
pul 1
33.3%

Most occurring characters

ValueCountFrequency (%)
P 2
22.2%
E 2
22.2%
+ 1
11.1%
x 1
11.1%
t 1
11.1%
u 1
11.1%
l 1
11.1%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 4
44.4%
Lowercase Letter 4
44.4%
Math Symbol 1
 
11.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
x 1
25.0%
t 1
25.0%
u 1
25.0%
l 1
25.0%
Uppercase Letter
ValueCountFrequency (%)
P 2
50.0%
E 2
50.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 8
88.9%
Common 1
 
11.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
P 2
25.0%
E 2
25.0%
x 1
12.5%
t 1
12.5%
u 1
12.5%
l 1
12.5%
Common
ValueCountFrequency (%)
+ 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 9
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
P 2
22.2%
E 2
22.2%
+ 1
11.1%
x 1
11.1%
t 1
11.1%
u 1
11.1%
l 1
11.1%

descoberta
Categorical

Distinct2
Distinct (%)66.7%
Missing0
Missing (%)0.0%
Memory size48.0 B
Elucidacao Diagn. em Internacao
2 
Urgencia / Emergencia
1 

Length

Max length31
Median length31
Mean length27.666667
Min length21

Characters and Unicode

Total characters83
Distinct characters20
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)33.3%

Sample

1st rowUrgencia / Emergencia
2nd rowElucidacao Diagn. em Internacao
3rd rowElucidacao Diagn. em Internacao

Common Values

ValueCountFrequency (%)
Elucidacao Diagn. em Internacao 2
66.7%
Urgencia / Emergencia 1
33.3%

Length

2023-10-31T16:30:05.997752image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-10-31T16:30:06.130798image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
ValueCountFrequency (%)
elucidacao 2
18.2%
diagn 2
18.2%
em 2
18.2%
internacao 2
18.2%
urgencia 1
9.1%
1
9.1%
emergencia 1
9.1%

Most occurring characters

ValueCountFrequency (%)
a 12
14.5%
n 8
9.6%
c 8
9.6%
8
9.6%
e 7
 
8.4%
i 6
 
7.2%
g 4
 
4.8%
r 4
 
4.8%
o 4
 
4.8%
m 3
 
3.6%
Other values (10) 19
22.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 64
77.1%
Space Separator 8
 
9.6%
Uppercase Letter 8
 
9.6%
Other Punctuation 3
 
3.6%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 12
18.8%
n 8
12.5%
c 8
12.5%
e 7
10.9%
i 6
9.4%
g 4
 
6.2%
r 4
 
6.2%
o 4
 
6.2%
m 3
 
4.7%
l 2
 
3.1%
Other values (3) 6
9.4%
Uppercase Letter
ValueCountFrequency (%)
E 3
37.5%
D 2
25.0%
I 2
25.0%
U 1
 
12.5%
Other Punctuation
ValueCountFrequency (%)
. 2
66.7%
/ 1
33.3%
Space Separator
ValueCountFrequency (%)
8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 72
86.7%
Common 11
 
13.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 12
16.7%
n 8
11.1%
c 8
11.1%
e 7
9.7%
i 6
8.3%
g 4
 
5.6%
r 4
 
5.6%
o 4
 
5.6%
m 3
 
4.2%
E 3
 
4.2%
Other values (7) 13
18.1%
Common
ValueCountFrequency (%)
8
72.7%
. 2
 
18.2%
/ 1
 
9.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 83
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 12
14.5%
n 8
9.6%
c 8
9.6%
8
9.6%
e 7
 
8.4%
i 6
 
7.2%
g 4
 
4.8%
r 4
 
4.8%
o 4
 
4.8%
m 3
 
3.6%
Other values (10) 19
22.9%

bac
Categorical

HIGH CORRELATION  UNIFORM  UNIQUE 

Distinct3
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size48.0 B
N/realiz
1 
Neg
1 
Pos
1 

Length

Max length8
Median length3
Mean length4.6666667
Min length3

Characters and Unicode

Total characters14
Distinct characters12
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

Unique3 ?
Unique (%)100.0%

Sample

1st rowN/realiz
2nd rowNeg
3rd rowPos

Common Values

ValueCountFrequency (%)
N/realiz 1
33.3%
Neg 1
33.3%
Pos 1
33.3%

Length

2023-10-31T16:30:06.248893image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-10-31T16:30:06.393365image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
ValueCountFrequency (%)
n/realiz 1
33.3%
neg 1
33.3%
pos 1
33.3%

Most occurring characters

ValueCountFrequency (%)
N 2
14.3%
e 2
14.3%
/ 1
7.1%
r 1
7.1%
a 1
7.1%
l 1
7.1%
i 1
7.1%
z 1
7.1%
g 1
7.1%
P 1
7.1%
Other values (2) 2
14.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 10
71.4%
Uppercase Letter 3
 
21.4%
Other Punctuation 1
 
7.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 2
20.0%
r 1
10.0%
a 1
10.0%
l 1
10.0%
i 1
10.0%
z 1
10.0%
g 1
10.0%
o 1
10.0%
s 1
10.0%
Uppercase Letter
ValueCountFrequency (%)
N 2
66.7%
P 1
33.3%
Other Punctuation
ValueCountFrequency (%)
/ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 13
92.9%
Common 1
 
7.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 2
15.4%
e 2
15.4%
r 1
7.7%
a 1
7.7%
l 1
7.7%
i 1
7.7%
z 1
7.7%
g 1
7.7%
P 1
7.7%
o 1
7.7%
Common
ValueCountFrequency (%)
/ 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 14
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 2
14.3%
e 2
14.3%
/ 1
7.1%
r 1
7.1%
a 1
7.1%
l 1
7.1%
i 1
7.1%
z 1
7.1%
g 1
7.1%
P 1
7.1%
Other values (2) 2
14.3%

BACOUTRO
Categorical

Distinct2
Distinct (%)66.7%
Missing0
Missing (%)0.0%
Memory size48.0 B
N/realiz
2 
Pos
1 

Length

Max length8
Median length8
Mean length6.3333333
Min length3

Characters and Unicode

Total characters19
Distinct characters11
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 (%)33.3%

Sample

1st rowPos
2nd rowN/realiz
3rd rowN/realiz

Common Values

ValueCountFrequency (%)
N/realiz 2
66.7%
Pos 1
33.3%

Length

2023-10-31T16:30:06.513191image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-10-31T16:30:06.651648image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
ValueCountFrequency (%)
n/realiz 2
66.7%
pos 1
33.3%

Most occurring characters

ValueCountFrequency (%)
N 2
10.5%
/ 2
10.5%
r 2
10.5%
e 2
10.5%
a 2
10.5%
l 2
10.5%
i 2
10.5%
z 2
10.5%
P 1
5.3%
o 1
5.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 14
73.7%
Uppercase Letter 3
 
15.8%
Other Punctuation 2
 
10.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
r 2
14.3%
e 2
14.3%
a 2
14.3%
l 2
14.3%
i 2
14.3%
z 2
14.3%
o 1
7.1%
s 1
7.1%
Uppercase Letter
ValueCountFrequency (%)
N 2
66.7%
P 1
33.3%
Other Punctuation
ValueCountFrequency (%)
/ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 17
89.5%
Common 2
 
10.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 2
11.8%
r 2
11.8%
e 2
11.8%
a 2
11.8%
l 2
11.8%
i 2
11.8%
z 2
11.8%
P 1
5.9%
o 1
5.9%
s 1
5.9%
Common
ValueCountFrequency (%)
/ 2
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 19
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 2
10.5%
/ 2
10.5%
r 2
10.5%
e 2
10.5%
a 2
10.5%
l 2
10.5%
i 2
10.5%
z 2
10.5%
P 1
5.3%
o 1
5.3%

cultEsc
Categorical

Distinct1
Distinct (%)33.3%
Missing0
Missing (%)0.0%
Memory size48.0 B
N/realiz
3 

Length

Max length8
Median length8
Mean length8
Min length8

Characters and Unicode

Total characters24
Distinct characters8
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 rowN/realiz
2nd rowN/realiz
3rd rowN/realiz

Common Values

ValueCountFrequency (%)
N/realiz 3
100.0%

Length

2023-10-31T16:30:06.768332image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-10-31T16:30:06.900252image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
ValueCountFrequency (%)
n/realiz 3
100.0%

Most occurring characters

ValueCountFrequency (%)
N 3
12.5%
/ 3
12.5%
r 3
12.5%
e 3
12.5%
a 3
12.5%
l 3
12.5%
i 3
12.5%
z 3
12.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 18
75.0%
Uppercase Letter 3
 
12.5%
Other Punctuation 3
 
12.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
r 3
16.7%
e 3
16.7%
a 3
16.7%
l 3
16.7%
i 3
16.7%
z 3
16.7%
Uppercase Letter
ValueCountFrequency (%)
N 3
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 21
87.5%
Common 3
 
12.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 3
14.3%
r 3
14.3%
e 3
14.3%
a 3
14.3%
l 3
14.3%
i 3
14.3%
z 3
14.3%
Common
ValueCountFrequency (%)
/ 3
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 24
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 3
12.5%
/ 3
12.5%
r 3
12.5%
e 3
12.5%
a 3
12.5%
l 3
12.5%
i 3
12.5%
z 3
12.5%

RX
Categorical

Distinct2
Distinct (%)66.7%
Missing0
Missing (%)0.0%
Memory size48.0 B
Susp TB
2 
Susp c/cavid
1 

Length

Max length12
Median length7
Mean length8.6666667
Min length7

Characters and Unicode

Total characters26
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

Unique1 ?
Unique (%)33.3%

Sample

1st rowSusp TB
2nd rowSusp TB
3rd rowSusp c/cavid

Common Values

ValueCountFrequency (%)
Susp TB 2
66.7%
Susp c/cavid 1
33.3%

Length

2023-10-31T16:30:07.004063image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-10-31T16:30:07.143193image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
ValueCountFrequency (%)
susp 3
50.0%
tb 2
33.3%
c/cavid 1
 
16.7%

Most occurring characters

ValueCountFrequency (%)
S 3
11.5%
u 3
11.5%
s 3
11.5%
p 3
11.5%
3
11.5%
T 2
7.7%
B 2
7.7%
c 2
7.7%
/ 1
 
3.8%
a 1
 
3.8%
Other values (3) 3
11.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 15
57.7%
Uppercase Letter 7
26.9%
Space Separator 3
 
11.5%
Other Punctuation 1
 
3.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
u 3
20.0%
s 3
20.0%
p 3
20.0%
c 2
13.3%
a 1
 
6.7%
v 1
 
6.7%
i 1
 
6.7%
d 1
 
6.7%
Uppercase Letter
ValueCountFrequency (%)
S 3
42.9%
T 2
28.6%
B 2
28.6%
Space Separator
ValueCountFrequency (%)
3
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 22
84.6%
Common 4
 
15.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
S 3
13.6%
u 3
13.6%
s 3
13.6%
p 3
13.6%
T 2
9.1%
B 2
9.1%
c 2
9.1%
a 1
 
4.5%
v 1
 
4.5%
i 1
 
4.5%
Common
ValueCountFrequency (%)
3
75.0%
/ 1
 
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 26
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
S 3
11.5%
u 3
11.5%
s 3
11.5%
p 3
11.5%
3
11.5%
T 2
7.7%
B 2
7.7%
c 2
7.7%
/ 1
 
3.8%
a 1
 
3.8%
Other values (3) 3
11.5%

NECROP
Categorical

Distinct1
Distinct (%)33.3%
Missing0
Missing (%)0.0%
Memory size48.0 B
N/realiz
3 

Length

Max length8
Median length8
Mean length8
Min length8

Characters and Unicode

Total characters24
Distinct characters8
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 rowN/realiz
2nd rowN/realiz
3rd rowN/realiz

Common Values

ValueCountFrequency (%)
N/realiz 3
100.0%

Length

2023-10-31T16:30:07.256854image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-10-31T16:30:07.392210image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
ValueCountFrequency (%)
n/realiz 3
100.0%

Most occurring characters

ValueCountFrequency (%)
N 3
12.5%
/ 3
12.5%
r 3
12.5%
e 3
12.5%
a 3
12.5%
l 3
12.5%
i 3
12.5%
z 3
12.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 18
75.0%
Uppercase Letter 3
 
12.5%
Other Punctuation 3
 
12.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
r 3
16.7%
e 3
16.7%
a 3
16.7%
l 3
16.7%
i 3
16.7%
z 3
16.7%
Uppercase Letter
ValueCountFrequency (%)
N 3
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 21
87.5%
Common 3
 
12.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 3
14.3%
r 3
14.3%
e 3
14.3%
a 3
14.3%
l 3
14.3%
i 3
14.3%
z 3
14.3%
Common
ValueCountFrequency (%)
/ 3
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 24
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 3
12.5%
/ 3
12.5%
r 3
12.5%
e 3
12.5%
a 3
12.5%
l 3
12.5%
i 3
12.5%
z 3
12.5%

hiv
Categorical

Distinct1
Distinct (%)33.3%
Missing0
Missing (%)0.0%
Memory size48.0 B
Pos
3 

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters9
Distinct characters3
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 rowPos
2nd rowPos
3rd rowPos

Common Values

ValueCountFrequency (%)
Pos 3
100.0%

Length

2023-10-31T16:30:07.499933image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-10-31T16:30:07.648524image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
ValueCountFrequency (%)
pos 3
100.0%

Most occurring characters

ValueCountFrequency (%)
P 3
33.3%
o 3
33.3%
s 3
33.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 6
66.7%
Uppercase Letter 3
33.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 3
50.0%
s 3
50.0%
Uppercase Letter
ValueCountFrequency (%)
P 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 9
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
P 3
33.3%
o 3
33.3%
s 3
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 9
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
P 3
33.3%
o 3
33.3%
s 3
33.3%

aids
Categorical

Distinct1
Distinct (%)33.3%
Missing0
Missing (%)0.0%
Memory size48.0 B
S
3 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters3
Distinct characters1
Distinct categories1 ?
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 rowS
2nd rowS
3rd rowS

Common Values

ValueCountFrequency (%)
S 3
100.0%

Length

2023-10-31T16:30:07.754459image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-10-31T16:30:07.890081image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
ValueCountFrequency (%)
s 3
100.0%

Most occurring characters

ValueCountFrequency (%)
S 3
100.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 3
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
S 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 3
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
S 3
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
S 3
100.0%

DIABETES
Boolean

Distinct1
Distinct (%)33.3%
Missing0
Missing (%)0.0%
Memory size27.0 B
False
3 
ValueCountFrequency (%)
False 3
100.0%
2023-10-31T16:30:08.002398image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/

ALCOOLISMO
Boolean

Distinct1
Distinct (%)33.3%
Missing0
Missing (%)0.0%
Memory size27.0 B
False
3 
ValueCountFrequency (%)
False 3
100.0%
2023-10-31T16:30:08.123497image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/

MENTAL
Boolean

Distinct1
Distinct (%)33.3%
Missing0
Missing (%)0.0%
Memory size27.0 B
False
3 
ValueCountFrequency (%)
False 3
100.0%
2023-10-31T16:30:08.236134image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/

DROGADICAO
Boolean

Distinct1
Distinct (%)33.3%
Missing0
Missing (%)0.0%
Memory size27.0 B
False
3 
ValueCountFrequency (%)
False 3
100.0%
2023-10-31T16:30:08.351913image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/

TABAGISMO
Categorical

Distinct2
Distinct (%)66.7%
Missing0
Missing (%)0.0%
Memory size48.0 B
N
2 
S
1 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters3
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)33.3%

Sample

1st rowN
2nd rowN
3rd rowS

Common Values

ValueCountFrequency (%)
N 2
66.7%
S 1
33.3%

Length

2023-10-31T16:30:08.462973image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-10-31T16:30:08.599623image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
ValueCountFrequency (%)
n 2
66.7%
s 1
33.3%

Most occurring characters

ValueCountFrequency (%)
N 2
66.7%
S 1
33.3%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 3
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
N 2
66.7%
S 1
33.3%

Most occurring scripts

ValueCountFrequency (%)
Latin 3
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 2
66.7%
S 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 2
66.7%
S 1
33.3%

motMudEsquema
Categorical

Distinct1
Distinct (%)33.3%
Missing0
Missing (%)0.0%
Memory size48.0 B
Nulo
3 

Length

Max length4
Median length4
Mean length4
Min length4

Characters and Unicode

Total characters12
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 rowNulo
2nd rowNulo
3rd rowNulo

Common Values

ValueCountFrequency (%)
Nulo 3
100.0%

Length

2023-10-31T16:30:08.716057image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-10-31T16:30:08.846502image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
ValueCountFrequency (%)
nulo 3
100.0%

Most occurring characters

ValueCountFrequency (%)
N 3
25.0%
u 3
25.0%
l 3
25.0%
o 3
25.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 9
75.0%
Uppercase Letter 3
 
25.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
u 3
33.3%
l 3
33.3%
o 3
33.3%
Uppercase Letter
ValueCountFrequency (%)
N 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 12
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 3
25.0%
u 3
25.0%
l 3
25.0%
o 3
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 12
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 3
25.0%
u 3
25.0%
l 3
25.0%
o 3
25.0%

tipoTrat
Categorical

Distinct2
Distinct (%)66.7%
Missing0
Missing (%)0.0%
Memory size48.0 B
Supervisionado
2 
Auto-Administrado
1 

Length

Max length17
Median length14
Mean length15
Min length14

Characters and Unicode

Total characters45
Distinct characters16
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 (%)33.3%

Sample

1st rowAuto-Administrado
2nd rowSupervisionado
3rd rowSupervisionado

Common Values

ValueCountFrequency (%)
Supervisionado 2
66.7%
Auto-Administrado 1
33.3%

Length

2023-10-31T16:30:08.959880image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-10-31T16:30:09.109543image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
ValueCountFrequency (%)
supervisionado 2
66.7%
auto-administrado 1
33.3%

Most occurring characters

ValueCountFrequency (%)
i 6
13.3%
o 6
13.3%
d 4
 
8.9%
u 3
 
6.7%
r 3
 
6.7%
s 3
 
6.7%
n 3
 
6.7%
a 3
 
6.7%
S 2
 
4.4%
p 2
 
4.4%
Other values (6) 10
22.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 40
88.9%
Uppercase Letter 4
 
8.9%
Dash Punctuation 1
 
2.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i 6
15.0%
o 6
15.0%
d 4
10.0%
u 3
7.5%
r 3
7.5%
s 3
7.5%
n 3
7.5%
a 3
7.5%
p 2
 
5.0%
e 2
 
5.0%
Other values (3) 5
12.5%
Uppercase Letter
ValueCountFrequency (%)
S 2
50.0%
A 2
50.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 44
97.8%
Common 1
 
2.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
i 6
13.6%
o 6
13.6%
d 4
9.1%
u 3
 
6.8%
r 3
 
6.8%
s 3
 
6.8%
n 3
 
6.8%
a 3
 
6.8%
S 2
 
4.5%
p 2
 
4.5%
Other values (5) 9
20.5%
Common
ValueCountFrequency (%)
- 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 45
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
i 6
13.3%
o 6
13.3%
d 4
 
8.9%
u 3
 
6.7%
r 3
 
6.7%
s 3
 
6.7%
n 3
 
6.7%
a 3
 
6.7%
S 2
 
4.4%
p 2
 
4.4%
Other values (6) 10
22.2%

idade
Categorical

HIGH CORRELATION  UNIFORM  UNIQUE 

Distinct3
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size48.0 B
0_22
1 
40_54
1 
23_39
1 

Length

Max length5
Median length5
Mean length4.6666667
Min length4

Characters and Unicode

Total characters14
Distinct characters7
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

Unique3 ?
Unique (%)100.0%

Sample

1st row0_22
2nd row40_54
3rd row23_39

Common Values

ValueCountFrequency (%)
0_22 1
33.3%
40_54 1
33.3%
23_39 1
33.3%

Length

2023-10-31T16:30:09.228696image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-10-31T16:30:09.379882image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
ValueCountFrequency (%)
0_22 1
33.3%
40_54 1
33.3%
23_39 1
33.3%

Most occurring characters

ValueCountFrequency (%)
_ 3
21.4%
2 3
21.4%
0 2
14.3%
4 2
14.3%
3 2
14.3%
5 1
 
7.1%
9 1
 
7.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 11
78.6%
Connector Punctuation 3
 
21.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 3
27.3%
0 2
18.2%
4 2
18.2%
3 2
18.2%
5 1
 
9.1%
9 1
 
9.1%
Connector Punctuation
ValueCountFrequency (%)
_ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 14
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
_ 3
21.4%
2 3
21.4%
0 2
14.3%
4 2
14.3%
3 2
14.3%
5 1
 
7.1%
9 1
 
7.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 14
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
_ 3
21.4%
2 3
21.4%
0 2
14.3%
4 2
14.3%
3 2
14.3%
5 1
 
7.1%
9 1
 
7.1%

HISTOPATOL
Categorical

Distinct1
Distinct (%)33.3%
Missing0
Missing (%)0.0%
Memory size48.0 B
N/realiz
3 

Length

Max length8
Median length8
Mean length8
Min length8

Characters and Unicode

Total characters24
Distinct characters8
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 rowN/realiz
2nd rowN/realiz
3rd rowN/realiz

Common Values

ValueCountFrequency (%)
N/realiz 3
100.0%

Length

2023-10-31T16:30:09.506478image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-10-31T16:30:09.647341image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
ValueCountFrequency (%)
n/realiz 3
100.0%

Most occurring characters

ValueCountFrequency (%)
N 3
12.5%
/ 3
12.5%
r 3
12.5%
e 3
12.5%
a 3
12.5%
l 3
12.5%
i 3
12.5%
z 3
12.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 18
75.0%
Uppercase Letter 3
 
12.5%
Other Punctuation 3
 
12.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
r 3
16.7%
e 3
16.7%
a 3
16.7%
l 3
16.7%
i 3
16.7%
z 3
16.7%
Uppercase Letter
ValueCountFrequency (%)
N 3
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 21
87.5%
Common 3
 
12.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 3
14.3%
r 3
14.3%
e 3
14.3%
a 3
14.3%
l 3
14.3%
i 3
14.3%
z 3
14.3%
Common
ValueCountFrequency (%)
/ 3
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 24
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 3
12.5%
/ 3
12.5%
r 3
12.5%
e 3
12.5%
a 3
12.5%
l 3
12.5%
i 3
12.5%
z 3
12.5%

Status_Resistencia
Categorical

Distinct1
Distinct (%)33.3%
Missing0
Missing (%)0.0%
Memory size48.0 B
1
3 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters3
Distinct characters1
Distinct categories1 ?
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 row1
2nd row1
3rd row1

Common Values

ValueCountFrequency (%)
1 3
100.0%

Length

2023-10-31T16:30:09.761207image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-10-31T16:30:09.900504image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
ValueCountFrequency (%)
1 3
100.0%

Most occurring characters

ValueCountFrequency (%)
1 3
100.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 3
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 3
100.0%

Cluster
Categorical

Distinct1
Distinct (%)33.3%
Missing0
Missing (%)0.0%
Memory size48.0 B
0
3 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters3
Distinct characters1
Distinct categories1 ?
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 row0
2nd row0
3rd row0

Common Values

ValueCountFrequency (%)
0 3
100.0%

Length

2023-10-31T16:30:10.005128image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-10-31T16:30:10.135100image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
ValueCountFrequency (%)
0 3
100.0%

Most occurring characters

ValueCountFrequency (%)
0 3
100.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 3
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 3
100.0%

Probabilidade
Categorical

HIGH CORRELATION  UNIFORM  UNIQUE 

Distinct3
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size48.0 B
0.39424201040664203
1 
0.28457588664308664
1 
0.4416289673559519
1 

Length

Max length19
Median length19
Mean length18.666667
Min length18

Characters and Unicode

Total characters56
Distinct characters11
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

Unique3 ?
Unique (%)100.0%

Sample

1st row0.39424201040664203
2nd row0.28457588664308664
3rd row0.4416289673559519

Common Values

ValueCountFrequency (%)
0.39424201040664203 1
33.3%
0.28457588664308664 1
33.3%
0.4416289673559519 1
33.3%

Length

2023-10-31T16:30:10.559540image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-10-31T16:30:10.709774image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
ValueCountFrequency (%)
0.39424201040664203 1
33.3%
0.28457588664308664 1
33.3%
0.4416289673559519 1
33.3%

Most occurring characters

ValueCountFrequency (%)
4 9
16.1%
0 8
14.3%
6 8
14.3%
2 5
8.9%
8 5
8.9%
5 5
8.9%
3 4
7.1%
9 4
7.1%
. 3
 
5.4%
1 3
 
5.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 53
94.6%
Other Punctuation 3
 
5.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 9
17.0%
0 8
15.1%
6 8
15.1%
2 5
9.4%
8 5
9.4%
5 5
9.4%
3 4
7.5%
9 4
7.5%
1 3
 
5.7%
7 2
 
3.8%
Other Punctuation
ValueCountFrequency (%)
. 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 56
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
4 9
16.1%
0 8
14.3%
6 8
14.3%
2 5
8.9%
8 5
8.9%
5 5
8.9%
3 4
7.1%
9 4
7.1%
. 3
 
5.4%
1 3
 
5.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 56
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 9
16.1%
0 8
14.3%
6 8
14.3%
2 5
8.9%
8 5
8.9%
5 5
8.9%
3 4
7.1%
9 4
7.1%
. 3
 
5.4%
1 3
 
5.4%

Correlations

2023-10-31T16:30:10.854188image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
faixaEtariasexoESCOLARIDTIPOCUPsitAtualFORMACLIN1classifdescobertabacBACOUTRORXTABAGISMOtipoTratidadeProbabilidade
faixaEtaria1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
sexo1.0001.0000.0000.0000.0000.0001.0000.0001.0000.0000.0000.0000.0001.0001.000
ESCOLARID1.0000.0001.0000.0000.0000.0001.0000.0001.0000.0000.0000.0000.0001.0001.000
TIPOCUP1.0000.0000.0001.0000.0000.0001.0000.0001.0000.0000.0000.0000.0001.0001.000
sitAtual1.0000.0000.0000.0001.0000.0001.0000.0001.0000.0000.0000.0000.0001.0001.000
FORMACLIN11.0000.0000.0000.0000.0001.0001.0000.0001.0000.0000.0000.0000.0001.0001.000
classif1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
descoberta1.0000.0000.0000.0000.0000.0001.0001.0001.0000.0000.0000.0000.0001.0001.000
bac1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
BACOUTRO1.0000.0000.0000.0000.0000.0001.0000.0001.0001.0000.0000.0000.0001.0001.000
RX1.0000.0000.0000.0000.0000.0001.0000.0001.0000.0001.0000.0000.0001.0001.000
TABAGISMO1.0000.0000.0000.0000.0000.0001.0000.0001.0000.0000.0001.0000.0001.0001.000
tipoTrat1.0000.0000.0000.0000.0000.0001.0000.0001.0000.0000.0000.0001.0001.0001.000
idade1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
Probabilidade1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000

Missing values

2023-10-31T16:30:02.588618image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
A simple visualization of nullity by column.
2023-10-31T16:30:03.105251image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

faixaEtariasexoESCOLARIDTIPOCUPsitAtualtipoCasoFORMACLIN1classifdescobertabacBACOUTROcultEscRXNECROPhivaidsDIABETESALCOOLISMOMENTALDROGADICAOTABAGISMOmotMudEsquematipoTratidadeHISTOPATOLStatus_ResistenciaClusterProbabilidade
46220_29FDe 4 a 7 anosDona de CasaAbandonoNovoPulP+EUrgencia / EmergenciaN/realizPosN/realizSusp TBN/realizPosSNNNNNNuloAuto-Administrado0_22N/realiz100.394242
33140_49MDe 8 a 11 anosDesempregadoCuraNovoPleuralExtElucidacao Diagn. em InternacaoNegN/realizN/realizSusp TBN/realizPosSNNNNNNuloSupervisionado40_54N/realiz100.284576
88430_39FDe 4 a 7 anosDesempregadoCuraNovoPulPulElucidacao Diagn. em InternacaoPosN/realizN/realizSusp c/cavidN/realizPosSNNNNSNuloSupervisionado23_39N/realiz100.441629
faixaEtariasexoESCOLARIDTIPOCUPsitAtualtipoCasoFORMACLIN1classifdescobertabacBACOUTROcultEscRXNECROPhivaidsDIABETESALCOOLISMOMENTALDROGADICAOTABAGISMOmotMudEsquematipoTratidadeHISTOPATOLStatus_ResistenciaClusterProbabilidade
46220_29FDe 4 a 7 anosDona de CasaAbandonoNovoPulP+EUrgencia / EmergenciaN/realizPosN/realizSusp TBN/realizPosSNNNNNNuloAuto-Administrado0_22N/realiz100.394242
33140_49MDe 8 a 11 anosDesempregadoCuraNovoPleuralExtElucidacao Diagn. em InternacaoNegN/realizN/realizSusp TBN/realizPosSNNNNNNuloSupervisionado40_54N/realiz100.284576
88430_39FDe 4 a 7 anosDesempregadoCuraNovoPulPulElucidacao Diagn. em InternacaoPosN/realizN/realizSusp c/cavidN/realizPosSNNNNSNuloSupervisionado23_39N/realiz100.441629