Overview

Dataset statistics

Number of variables28
Number of observations4
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1000.0 B
Average record size in memory250.0 B

Variable types

Categorical23
Boolean5

Alerts

sitAtual has constant value "Cura"Constant
FORMACLIN1 has constant value "Pul"Constant
classif has constant value "Pul"Constant
bac has constant value "Pos"Constant
BACOUTRO has constant value "N/realiz"Constant
NECROP has constant value "N/realiz"Constant
hiv has constant value "Neg"Constant
aids has constant value "False"Constant
DIABETES has constant value "False"Constant
ALCOOLISMO has constant value "False"Constant
MENTAL has constant value "False"Constant
TABAGISMO has constant value "False"Constant
tipoTrat has constant value "Supervisionado"Constant
HISTOPATOL has constant value "N/realiz"Constant
Status_Resistencia has constant value "1"Constant
Cluster has constant value "1"Constant
faixaEtaria is highly overall correlated with sexo and 6 other fieldsHigh correlation
sexo is highly overall correlated with faixaEtaria and 3 other fieldsHigh correlation
ESCOLARID is highly overall correlated with faixaEtaria and 10 other fieldsHigh correlation
TIPOCUP is highly overall correlated with faixaEtaria and 4 other fieldsHigh correlation
tipoCaso is highly overall correlated with faixaEtaria and 3 other fieldsHigh correlation
descoberta is highly overall correlated with ESCOLARID and 5 other fieldsHigh correlation
cultEsc is highly overall correlated with ESCOLARID and 1 other fieldsHigh correlation
RX is highly overall correlated with ESCOLARID and 2 other fieldsHigh correlation
DROGADICAO is highly overall correlated with faixaEtaria and 4 other fieldsHigh correlation
motMudEsquema is highly overall correlated with ESCOLARID and 2 other fieldsHigh correlation
idade is highly overall correlated with faixaEtaria and 6 other fieldsHigh correlation
Probabilidade is highly overall correlated with faixaEtaria and 10 other fieldsHigh correlation
ESCOLARID is uniformly distributedUniform
Probabilidade is uniformly distributedUniform
ESCOLARID has unique valuesUnique
Probabilidade has unique valuesUnique

Reproduction

Analysis started2023-10-31 19:38:54.519391
Analysis finished2023-10-31 19:38:56.599240
Duration2.08 seconds
Software versionpandas-profiling v3.6.6
Download configurationconfig.json

Variables

faixaEtaria
Categorical

Distinct3
Distinct (%)75.0%
Missing0
Missing (%)0.0%
Memory size64.0 B
40_49
2 
20_29
1 
50_59
1 

Length

Max length5
Median length5
Mean length5
Min length5

Characters and Unicode

Total characters20
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

Unique2 ?
Unique (%)50.0%

Sample

1st row20_29
2nd row40_49
3rd row40_49
4th row50_59

Common Values

ValueCountFrequency (%)
40_49 2
50.0%
20_29 1
25.0%
50_59 1
25.0%

Length

2023-10-31T16:38:56.661952image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-10-31T16:38:56.809106image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
ValueCountFrequency (%)
40_49 2
50.0%
20_29 1
25.0%
50_59 1
25.0%

Most occurring characters

ValueCountFrequency (%)
4 4
20.0%
0 4
20.0%
_ 4
20.0%
9 4
20.0%
2 2
10.0%
5 2
10.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 16
80.0%
Connector Punctuation 4
 
20.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 4
25.0%
0 4
25.0%
9 4
25.0%
2 2
12.5%
5 2
12.5%
Connector Punctuation
ValueCountFrequency (%)
_ 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 20
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
4 4
20.0%
0 4
20.0%
_ 4
20.0%
9 4
20.0%
2 2
10.0%
5 2
10.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 20
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 4
20.0%
0 4
20.0%
_ 4
20.0%
9 4
20.0%
2 2
10.0%
5 2
10.0%

sexo
Categorical

Distinct2
Distinct (%)50.0%
Missing0
Missing (%)0.0%
Memory size160.0 B
F
3 
M
1 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters4
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 (%)25.0%

Sample

1st rowF
2nd rowF
3rd rowF
4th rowM

Common Values

ValueCountFrequency (%)
F 3
75.0%
M 1
 
25.0%

Length

2023-10-31T16:38:56.928841image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-10-31T16:38:57.068447image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
ValueCountFrequency (%)
f 3
75.0%
m 1
 
25.0%

Most occurring characters

ValueCountFrequency (%)
F 3
75.0%
M 1
 
25.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 4
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
F 3
75.0%
M 1
 
25.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 4
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
F 3
75.0%
M 1
 
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
F 3
75.0%
M 1
 
25.0%

ESCOLARID
Categorical

HIGH CORRELATION  UNIFORM  UNIQUE 

Distinct4
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size64.0 B
De 4 a 7 anos
1 
De 8 a 11 anos
1 
De 1 a 3 anos
1 
De 12 a 14 anos
1 

Length

Max length15
Median length14.5
Mean length13.75
Min length13

Characters and Unicode

Total characters55
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

Unique4 ?
Unique (%)100.0%

Sample

1st rowDe 4 a 7 anos
2nd rowDe 8 a 11 anos
3rd rowDe 1 a 3 anos
4th rowDe 12 a 14 anos

Common Values

ValueCountFrequency (%)
De 4 a 7 anos 1
25.0%
De 8 a 11 anos 1
25.0%
De 1 a 3 anos 1
25.0%
De 12 a 14 anos 1
25.0%

Length

2023-10-31T16:38:57.194671image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-10-31T16:38:57.364625image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
ValueCountFrequency (%)
de 4
20.0%
a 4
20.0%
anos 4
20.0%
4 1
 
5.0%
7 1
 
5.0%
8 1
 
5.0%
11 1
 
5.0%
1 1
 
5.0%
3 1
 
5.0%
12 1
 
5.0%

Most occurring characters

ValueCountFrequency (%)
16
29.1%
a 8
14.5%
1 5
 
9.1%
D 4
 
7.3%
e 4
 
7.3%
n 4
 
7.3%
o 4
 
7.3%
s 4
 
7.3%
4 2
 
3.6%
7 1
 
1.8%
Other values (3) 3
 
5.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 24
43.6%
Space Separator 16
29.1%
Decimal Number 11
20.0%
Uppercase Letter 4
 
7.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 5
45.5%
4 2
 
18.2%
7 1
 
9.1%
8 1
 
9.1%
3 1
 
9.1%
2 1
 
9.1%
Lowercase Letter
ValueCountFrequency (%)
a 8
33.3%
e 4
16.7%
n 4
16.7%
o 4
16.7%
s 4
16.7%
Space Separator
ValueCountFrequency (%)
16
100.0%
Uppercase Letter
ValueCountFrequency (%)
D 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 28
50.9%
Common 27
49.1%

Most frequent character per script

Common
ValueCountFrequency (%)
16
59.3%
1 5
 
18.5%
4 2
 
7.4%
7 1
 
3.7%
8 1
 
3.7%
3 1
 
3.7%
2 1
 
3.7%
Latin
ValueCountFrequency (%)
a 8
28.6%
D 4
14.3%
e 4
14.3%
n 4
14.3%
o 4
14.3%
s 4
14.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 55
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
16
29.1%
a 8
14.5%
1 5
 
9.1%
D 4
 
7.3%
e 4
 
7.3%
n 4
 
7.3%
o 4
 
7.3%
s 4
 
7.3%
4 2
 
3.6%
7 1
 
1.8%
Other values (3) 3
 
5.5%

TIPOCUP
Categorical

Distinct2
Distinct (%)50.0%
Missing0
Missing (%)0.0%
Memory size64.0 B
Outra
3 
Desempregado
1 

Length

Max length12
Median length5
Mean length6.75
Min length5

Characters and Unicode

Total characters27
Distinct characters13
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 (%)25.0%

Sample

1st rowDesempregado
2nd rowOutra
3rd rowOutra
4th rowOutra

Common Values

ValueCountFrequency (%)
Outra 3
75.0%
Desempregado 1
 
25.0%

Length

2023-10-31T16:38:57.511708image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-10-31T16:38:57.674484image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
ValueCountFrequency (%)
outra 3
75.0%
desempregado 1
 
25.0%

Most occurring characters

ValueCountFrequency (%)
r 4
14.8%
a 4
14.8%
O 3
11.1%
u 3
11.1%
t 3
11.1%
e 3
11.1%
D 1
 
3.7%
s 1
 
3.7%
m 1
 
3.7%
p 1
 
3.7%
Other values (3) 3
11.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 23
85.2%
Uppercase Letter 4
 
14.8%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
r 4
17.4%
a 4
17.4%
u 3
13.0%
t 3
13.0%
e 3
13.0%
s 1
 
4.3%
m 1
 
4.3%
p 1
 
4.3%
g 1
 
4.3%
d 1
 
4.3%
Uppercase Letter
ValueCountFrequency (%)
O 3
75.0%
D 1
 
25.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 27
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
r 4
14.8%
a 4
14.8%
O 3
11.1%
u 3
11.1%
t 3
11.1%
e 3
11.1%
D 1
 
3.7%
s 1
 
3.7%
m 1
 
3.7%
p 1
 
3.7%
Other values (3) 3
11.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 27
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
r 4
14.8%
a 4
14.8%
O 3
11.1%
u 3
11.1%
t 3
11.1%
e 3
11.1%
D 1
 
3.7%
s 1
 
3.7%
m 1
 
3.7%
p 1
 
3.7%
Other values (3) 3
11.1%

sitAtual
Categorical

Distinct1
Distinct (%)25.0%
Missing0
Missing (%)0.0%
Memory size64.0 B
Cura
4 

Length

Max length4
Median length4
Mean length4
Min length4

Characters and Unicode

Total characters16
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 rowCura
2nd rowCura
3rd rowCura
4th rowCura

Common Values

ValueCountFrequency (%)
Cura 4
100.0%

Length

2023-10-31T16:38:57.827949image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-10-31T16:38:57.978283image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
ValueCountFrequency (%)
cura 4
100.0%

Most occurring characters

ValueCountFrequency (%)
C 4
25.0%
u 4
25.0%
r 4
25.0%
a 4
25.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 12
75.0%
Uppercase Letter 4
 
25.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
u 4
33.3%
r 4
33.3%
a 4
33.3%
Uppercase Letter
ValueCountFrequency (%)
C 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 16
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
C 4
25.0%
u 4
25.0%
r 4
25.0%
a 4
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 16
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
C 4
25.0%
u 4
25.0%
r 4
25.0%
a 4
25.0%

tipoCaso
Categorical

Distinct2
Distinct (%)50.0%
Missing0
Missing (%)0.0%
Memory size64.0 B
Novo
3 
Recidiva
1 

Length

Max length8
Median length4
Mean length5
Min length4

Characters and Unicode

Total characters20
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 (%)25.0%

Sample

1st rowNovo
2nd rowNovo
3rd rowNovo
4th rowRecidiva

Common Values

ValueCountFrequency (%)
Novo 3
75.0%
Recidiva 1
 
25.0%

Length

2023-10-31T16:38:58.104156image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-10-31T16:38:58.266200image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
ValueCountFrequency (%)
novo 3
75.0%
recidiva 1
 
25.0%

Most occurring characters

ValueCountFrequency (%)
o 6
30.0%
v 4
20.0%
N 3
15.0%
i 2
 
10.0%
R 1
 
5.0%
e 1
 
5.0%
c 1
 
5.0%
d 1
 
5.0%
a 1
 
5.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 16
80.0%
Uppercase Letter 4
 
20.0%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 6
37.5%
v 4
25.0%
i 2
 
12.5%
e 1
 
6.2%
c 1
 
6.2%
d 1
 
6.2%
a 1
 
6.2%
Uppercase Letter
ValueCountFrequency (%)
N 3
75.0%
R 1
 
25.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 20
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 6
30.0%
v 4
20.0%
N 3
15.0%
i 2
 
10.0%
R 1
 
5.0%
e 1
 
5.0%
c 1
 
5.0%
d 1
 
5.0%
a 1
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 20
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o 6
30.0%
v 4
20.0%
N 3
15.0%
i 2
 
10.0%
R 1
 
5.0%
e 1
 
5.0%
c 1
 
5.0%
d 1
 
5.0%
a 1
 
5.0%

FORMACLIN1
Categorical

Distinct1
Distinct (%)25.0%
Missing0
Missing (%)0.0%
Memory size64.0 B
Pul
4 

Length

Max length3
Median length3
Mean length3
Min length3

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 rowPul
2nd rowPul
3rd rowPul
4th rowPul

Common Values

ValueCountFrequency (%)
Pul 4
100.0%

Length

2023-10-31T16:38:58.379493image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-10-31T16:38:58.513684image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
ValueCountFrequency (%)
pul 4
100.0%

Most occurring characters

ValueCountFrequency (%)
P 4
33.3%
u 4
33.3%
l 4
33.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 8
66.7%
Uppercase Letter 4
33.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
u 4
50.0%
l 4
50.0%
Uppercase Letter
ValueCountFrequency (%)
P 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 12
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
P 4
33.3%
u 4
33.3%
l 4
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 12
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
P 4
33.3%
u 4
33.3%
l 4
33.3%

classif
Categorical

Distinct1
Distinct (%)25.0%
Missing0
Missing (%)0.0%
Memory size64.0 B
Pul
4 

Length

Max length3
Median length3
Mean length3
Min length3

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 rowPul
2nd rowPul
3rd rowPul
4th rowPul

Common Values

ValueCountFrequency (%)
Pul 4
100.0%

Length

2023-10-31T16:38:58.620394image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-10-31T16:38:58.755550image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
ValueCountFrequency (%)
pul 4
100.0%

Most occurring characters

ValueCountFrequency (%)
P 4
33.3%
u 4
33.3%
l 4
33.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 8
66.7%
Uppercase Letter 4
33.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
u 4
50.0%
l 4
50.0%
Uppercase Letter
ValueCountFrequency (%)
P 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 12
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
P 4
33.3%
u 4
33.3%
l 4
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 12
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
P 4
33.3%
u 4
33.3%
l 4
33.3%

descoberta
Categorical

Distinct3
Distinct (%)75.0%
Missing0
Missing (%)0.0%
Memory size64.0 B
Urgencia / Emergencia
2 
Elucidacao Diagn. em Internacao
1 
Investigacao de Contatos
1 

Length

Max length31
Median length27.5
Mean length24.25
Min length21

Characters and Unicode

Total characters97
Distinct characters23
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

Unique2 ?
Unique (%)50.0%

Sample

1st rowElucidacao Diagn. em Internacao
2nd rowUrgencia / Emergencia
3rd rowInvestigacao de Contatos
4th rowUrgencia / Emergencia

Common Values

ValueCountFrequency (%)
Urgencia / Emergencia 2
50.0%
Elucidacao Diagn. em Internacao 1
25.0%
Investigacao de Contatos 1
25.0%

Length

2023-10-31T16:38:58.865268image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-10-31T16:38:59.018678image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
ValueCountFrequency (%)
urgencia 2
15.4%
2
15.4%
emergencia 2
15.4%
elucidacao 1
7.7%
diagn 1
7.7%
em 1
7.7%
internacao 1
7.7%
investigacao 1
7.7%
de 1
7.7%
contatos 1
7.7%

Most occurring characters

ValueCountFrequency (%)
a 12
12.4%
e 10
10.3%
n 9
9.3%
9
9.3%
c 8
 
8.2%
i 7
 
7.2%
g 6
 
6.2%
o 5
 
5.2%
r 5
 
5.2%
t 4
 
4.1%
Other values (13) 22
22.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 76
78.4%
Space Separator 9
 
9.3%
Uppercase Letter 9
 
9.3%
Other Punctuation 3
 
3.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 12
15.8%
e 10
13.2%
n 9
11.8%
c 8
10.5%
i 7
9.2%
g 6
7.9%
o 5
6.6%
r 5
6.6%
t 4
 
5.3%
m 3
 
3.9%
Other values (5) 7
9.2%
Uppercase Letter
ValueCountFrequency (%)
E 3
33.3%
I 2
22.2%
U 2
22.2%
D 1
 
11.1%
C 1
 
11.1%
Other Punctuation
ValueCountFrequency (%)
/ 2
66.7%
. 1
33.3%
Space Separator
ValueCountFrequency (%)
9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 85
87.6%
Common 12
 
12.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 12
14.1%
e 10
11.8%
n 9
10.6%
c 8
9.4%
i 7
8.2%
g 6
 
7.1%
o 5
 
5.9%
r 5
 
5.9%
t 4
 
4.7%
m 3
 
3.5%
Other values (10) 16
18.8%
Common
ValueCountFrequency (%)
9
75.0%
/ 2
 
16.7%
. 1
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 97
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 12
12.4%
e 10
10.3%
n 9
9.3%
9
9.3%
c 8
 
8.2%
i 7
 
7.2%
g 6
 
6.2%
o 5
 
5.2%
r 5
 
5.2%
t 4
 
4.1%
Other values (13) 22
22.7%

bac
Categorical

Distinct1
Distinct (%)25.0%
Missing0
Missing (%)0.0%
Memory size64.0 B
Pos
4 

Length

Max length3
Median length3
Mean length3
Min length3

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 rowPos
2nd rowPos
3rd rowPos
4th rowPos

Common Values

ValueCountFrequency (%)
Pos 4
100.0%

Length

2023-10-31T16:38:59.145280image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-10-31T16:38:59.278097image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
ValueCountFrequency (%)
pos 4
100.0%

Most occurring characters

ValueCountFrequency (%)
P 4
33.3%
o 4
33.3%
s 4
33.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 8
66.7%
Uppercase Letter 4
33.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 4
50.0%
s 4
50.0%
Uppercase Letter
ValueCountFrequency (%)
P 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 12
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
P 4
33.3%
o 4
33.3%
s 4
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 12
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
P 4
33.3%
o 4
33.3%
s 4
33.3%

BACOUTRO
Categorical

Distinct1
Distinct (%)25.0%
Missing0
Missing (%)0.0%
Memory size64.0 B
N/realiz
4 

Length

Max length8
Median length8
Mean length8
Min length8

Characters and Unicode

Total characters32
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
4th rowN/realiz

Common Values

ValueCountFrequency (%)
N/realiz 4
100.0%

Length

2023-10-31T16:38:59.386512image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-10-31T16:38:59.522830image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
ValueCountFrequency (%)
n/realiz 4
100.0%

Most occurring characters

ValueCountFrequency (%)
N 4
12.5%
/ 4
12.5%
r 4
12.5%
e 4
12.5%
a 4
12.5%
l 4
12.5%
i 4
12.5%
z 4
12.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 24
75.0%
Uppercase Letter 4
 
12.5%
Other Punctuation 4
 
12.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
r 4
16.7%
e 4
16.7%
a 4
16.7%
l 4
16.7%
i 4
16.7%
z 4
16.7%
Uppercase Letter
ValueCountFrequency (%)
N 4
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 28
87.5%
Common 4
 
12.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 4
14.3%
r 4
14.3%
e 4
14.3%
a 4
14.3%
l 4
14.3%
i 4
14.3%
z 4
14.3%
Common
ValueCountFrequency (%)
/ 4
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 32
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 4
12.5%
/ 4
12.5%
r 4
12.5%
e 4
12.5%
a 4
12.5%
l 4
12.5%
i 4
12.5%
z 4
12.5%

cultEsc
Categorical

Distinct2
Distinct (%)50.0%
Missing0
Missing (%)0.0%
Memory size64.0 B
N/realiz
3 
Neg
1 

Length

Max length8
Median length8
Mean length6.75
Min length3

Characters and Unicode

Total characters27
Distinct characters9
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 (%)25.0%

Sample

1st rowN/realiz
2nd rowNeg
3rd rowN/realiz
4th rowN/realiz

Common Values

ValueCountFrequency (%)
N/realiz 3
75.0%
Neg 1
 
25.0%

Length

2023-10-31T16:38:59.640189image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-10-31T16:38:59.787212image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
ValueCountFrequency (%)
n/realiz 3
75.0%
neg 1
 
25.0%

Most occurring characters

ValueCountFrequency (%)
N 4
14.8%
e 4
14.8%
/ 3
11.1%
r 3
11.1%
a 3
11.1%
l 3
11.1%
i 3
11.1%
z 3
11.1%
g 1
 
3.7%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 20
74.1%
Uppercase Letter 4
 
14.8%
Other Punctuation 3
 
11.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 4
20.0%
r 3
15.0%
a 3
15.0%
l 3
15.0%
i 3
15.0%
z 3
15.0%
g 1
 
5.0%
Uppercase Letter
ValueCountFrequency (%)
N 4
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 24
88.9%
Common 3
 
11.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 4
16.7%
e 4
16.7%
r 3
12.5%
a 3
12.5%
l 3
12.5%
i 3
12.5%
z 3
12.5%
g 1
 
4.2%
Common
ValueCountFrequency (%)
/ 3
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 27
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 4
14.8%
e 4
14.8%
/ 3
11.1%
r 3
11.1%
a 3
11.1%
l 3
11.1%
i 3
11.1%
z 3
11.1%
g 1
 
3.7%

RX
Categorical

Distinct2
Distinct (%)50.0%
Missing0
Missing (%)0.0%
Memory size64.0 B
Susp TB
3 
N/realiz
1 

Length

Max length8
Median length7
Mean length7.25
Min length7

Characters and Unicode

Total characters29
Distinct characters15
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 (%)25.0%

Sample

1st rowSusp TB
2nd rowSusp TB
3rd rowN/realiz
4th rowSusp TB

Common Values

ValueCountFrequency (%)
Susp TB 3
75.0%
N/realiz 1
 
25.0%

Length

2023-10-31T16:38:59.911568image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-10-31T16:39:00.060916image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
ValueCountFrequency (%)
susp 3
42.9%
tb 3
42.9%
n/realiz 1
 
14.3%

Most occurring characters

ValueCountFrequency (%)
S 3
10.3%
u 3
10.3%
s 3
10.3%
p 3
10.3%
3
10.3%
T 3
10.3%
B 3
10.3%
N 1
 
3.4%
/ 1
 
3.4%
r 1
 
3.4%
Other values (5) 5
17.2%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 15
51.7%
Uppercase Letter 10
34.5%
Space Separator 3
 
10.3%
Other Punctuation 1
 
3.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
u 3
20.0%
s 3
20.0%
p 3
20.0%
r 1
 
6.7%
e 1
 
6.7%
a 1
 
6.7%
l 1
 
6.7%
i 1
 
6.7%
z 1
 
6.7%
Uppercase Letter
ValueCountFrequency (%)
S 3
30.0%
T 3
30.0%
B 3
30.0%
N 1
 
10.0%
Space Separator
ValueCountFrequency (%)
3
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 25
86.2%
Common 4
 
13.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
S 3
12.0%
u 3
12.0%
s 3
12.0%
p 3
12.0%
T 3
12.0%
B 3
12.0%
N 1
 
4.0%
r 1
 
4.0%
e 1
 
4.0%
a 1
 
4.0%
Other values (3) 3
12.0%
Common
ValueCountFrequency (%)
3
75.0%
/ 1
 
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 29
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
S 3
10.3%
u 3
10.3%
s 3
10.3%
p 3
10.3%
3
10.3%
T 3
10.3%
B 3
10.3%
N 1
 
3.4%
/ 1
 
3.4%
r 1
 
3.4%
Other values (5) 5
17.2%

NECROP
Categorical

Distinct1
Distinct (%)25.0%
Missing0
Missing (%)0.0%
Memory size64.0 B
N/realiz
4 

Length

Max length8
Median length8
Mean length8
Min length8

Characters and Unicode

Total characters32
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
4th rowN/realiz

Common Values

ValueCountFrequency (%)
N/realiz 4
100.0%

Length

2023-10-31T16:39:00.178111image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-10-31T16:39:00.311564image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
ValueCountFrequency (%)
n/realiz 4
100.0%

Most occurring characters

ValueCountFrequency (%)
N 4
12.5%
/ 4
12.5%
r 4
12.5%
e 4
12.5%
a 4
12.5%
l 4
12.5%
i 4
12.5%
z 4
12.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 24
75.0%
Uppercase Letter 4
 
12.5%
Other Punctuation 4
 
12.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
r 4
16.7%
e 4
16.7%
a 4
16.7%
l 4
16.7%
i 4
16.7%
z 4
16.7%
Uppercase Letter
ValueCountFrequency (%)
N 4
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 28
87.5%
Common 4
 
12.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 4
14.3%
r 4
14.3%
e 4
14.3%
a 4
14.3%
l 4
14.3%
i 4
14.3%
z 4
14.3%
Common
ValueCountFrequency (%)
/ 4
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 32
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 4
12.5%
/ 4
12.5%
r 4
12.5%
e 4
12.5%
a 4
12.5%
l 4
12.5%
i 4
12.5%
z 4
12.5%

hiv
Categorical

Distinct1
Distinct (%)25.0%
Missing0
Missing (%)0.0%
Memory size64.0 B
Neg
4 

Length

Max length3
Median length3
Mean length3
Min length3

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 rowNeg
2nd rowNeg
3rd rowNeg
4th rowNeg

Common Values

ValueCountFrequency (%)
Neg 4
100.0%

Length

2023-10-31T16:39:00.419205image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-10-31T16:39:00.553017image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
ValueCountFrequency (%)
neg 4
100.0%

Most occurring characters

ValueCountFrequency (%)
N 4
33.3%
e 4
33.3%
g 4
33.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 8
66.7%
Uppercase Letter 4
33.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 4
50.0%
g 4
50.0%
Uppercase Letter
ValueCountFrequency (%)
N 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 12
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 4
33.3%
e 4
33.3%
g 4
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 12
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 4
33.3%
e 4
33.3%
g 4
33.3%

aids
Boolean

Distinct1
Distinct (%)25.0%
Missing0
Missing (%)0.0%
Memory size36.0 B
False
4 
ValueCountFrequency (%)
False 4
100.0%
2023-10-31T16:39:00.674445image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/

DIABETES
Boolean

Distinct1
Distinct (%)25.0%
Missing0
Missing (%)0.0%
Memory size36.0 B
False
4 
ValueCountFrequency (%)
False 4
100.0%
2023-10-31T16:39:00.795715image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/

ALCOOLISMO
Boolean

Distinct1
Distinct (%)25.0%
Missing0
Missing (%)0.0%
Memory size36.0 B
False
4 
ValueCountFrequency (%)
False 4
100.0%
2023-10-31T16:39:00.915744image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/

MENTAL
Boolean

Distinct1
Distinct (%)25.0%
Missing0
Missing (%)0.0%
Memory size36.0 B
False
4 
ValueCountFrequency (%)
False 4
100.0%
2023-10-31T16:39:01.037663image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/

DROGADICAO
Categorical

Distinct2
Distinct (%)50.0%
Missing0
Missing (%)0.0%
Memory size64.0 B
N
3 
S
1 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters4
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 (%)25.0%

Sample

1st rowS
2nd rowN
3rd rowN
4th rowN

Common Values

ValueCountFrequency (%)
N 3
75.0%
S 1
 
25.0%

Length

2023-10-31T16:39:01.145799image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-10-31T16:39:01.285105image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
ValueCountFrequency (%)
n 3
75.0%
s 1
 
25.0%

Most occurring characters

ValueCountFrequency (%)
N 3
75.0%
S 1
 
25.0%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 4
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
N 3
75.0%
S 1
 
25.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 4
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 3
75.0%
S 1
 
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 3
75.0%
S 1
 
25.0%

TABAGISMO
Boolean

Distinct1
Distinct (%)25.0%
Missing0
Missing (%)0.0%
Memory size36.0 B
False
4 
ValueCountFrequency (%)
False 4
100.0%
2023-10-31T16:39:01.414276image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/

motMudEsquema
Categorical

Distinct2
Distinct (%)50.0%
Missing0
Missing (%)0.0%
Memory size64.0 B
Nulo
3 
Intolerancia/Toxicidade
1 

Length

Max length23
Median length4
Mean length8.75
Min length4

Characters and Unicode

Total characters35
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 (%)25.0%

Sample

1st rowNulo
2nd rowNulo
3rd rowIntolerancia/Toxicidade
4th rowNulo

Common Values

ValueCountFrequency (%)
Nulo 3
75.0%
Intolerancia/Toxicidade 1
 
25.0%

Length

2023-10-31T16:39:01.541220image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-10-31T16:39:01.702532image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
ValueCountFrequency (%)
nulo 3
75.0%
intolerancia/toxicidade 1
 
25.0%

Most occurring characters

ValueCountFrequency (%)
o 5
14.3%
l 4
11.4%
N 3
8.6%
u 3
8.6%
a 3
8.6%
i 3
8.6%
n 2
 
5.7%
e 2
 
5.7%
c 2
 
5.7%
d 2
 
5.7%
Other values (6) 6
17.1%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 29
82.9%
Uppercase Letter 5
 
14.3%
Other Punctuation 1
 
2.9%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 5
17.2%
l 4
13.8%
u 3
10.3%
a 3
10.3%
i 3
10.3%
n 2
 
6.9%
e 2
 
6.9%
c 2
 
6.9%
d 2
 
6.9%
t 1
 
3.4%
Other values (2) 2
 
6.9%
Uppercase Letter
ValueCountFrequency (%)
N 3
60.0%
I 1
 
20.0%
T 1
 
20.0%
Other Punctuation
ValueCountFrequency (%)
/ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 34
97.1%
Common 1
 
2.9%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 5
14.7%
l 4
11.8%
N 3
8.8%
u 3
8.8%
a 3
8.8%
i 3
8.8%
n 2
 
5.9%
e 2
 
5.9%
c 2
 
5.9%
d 2
 
5.9%
Other values (5) 5
14.7%
Common
ValueCountFrequency (%)
/ 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 35
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o 5
14.3%
l 4
11.4%
N 3
8.6%
u 3
8.6%
a 3
8.6%
i 3
8.6%
n 2
 
5.7%
e 2
 
5.7%
c 2
 
5.7%
d 2
 
5.7%
Other values (6) 6
17.1%

tipoTrat
Categorical

Distinct1
Distinct (%)25.0%
Missing0
Missing (%)0.0%
Memory size64.0 B
Supervisionado
4 

Length

Max length14
Median length14
Mean length14
Min length14

Characters and Unicode

Total characters56
Distinct characters12
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowSupervisionado
2nd rowSupervisionado
3rd rowSupervisionado
4th rowSupervisionado

Common Values

ValueCountFrequency (%)
Supervisionado 4
100.0%

Length

2023-10-31T16:39:01.820823image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-10-31T16:39:01.956427image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
ValueCountFrequency (%)
supervisionado 4
100.0%

Most occurring characters

ValueCountFrequency (%)
i 8
14.3%
o 8
14.3%
S 4
7.1%
u 4
7.1%
p 4
7.1%
e 4
7.1%
r 4
7.1%
v 4
7.1%
s 4
7.1%
n 4
7.1%
Other values (2) 8
14.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 52
92.9%
Uppercase Letter 4
 
7.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
i 8
15.4%
o 8
15.4%
u 4
7.7%
p 4
7.7%
e 4
7.7%
r 4
7.7%
v 4
7.7%
s 4
7.7%
n 4
7.7%
a 4
7.7%
Uppercase Letter
ValueCountFrequency (%)
S 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 56
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
i 8
14.3%
o 8
14.3%
S 4
7.1%
u 4
7.1%
p 4
7.1%
e 4
7.1%
r 4
7.1%
v 4
7.1%
s 4
7.1%
n 4
7.1%
Other values (2) 8
14.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 56
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
i 8
14.3%
o 8
14.3%
S 4
7.1%
u 4
7.1%
p 4
7.1%
e 4
7.1%
r 4
7.1%
v 4
7.1%
s 4
7.1%
n 4
7.1%
Other values (2) 8
14.3%

idade
Categorical

Distinct3
Distinct (%)75.0%
Missing0
Missing (%)0.0%
Memory size64.0 B
40_54
2 
23_39
1 
Mais de 54
1 

Length

Max length10
Median length5
Mean length6.25
Min length5

Characters and Unicode

Total characters25
Distinct characters14
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)50.0%

Sample

1st row23_39
2nd row40_54
3rd row40_54
4th rowMais de 54

Common Values

ValueCountFrequency (%)
40_54 2
50.0%
23_39 1
25.0%
Mais de 54 1
25.0%

Length

2023-10-31T16:39:02.072318image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-10-31T16:39:02.227623image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
ValueCountFrequency (%)
40_54 2
33.3%
23_39 1
16.7%
mais 1
16.7%
de 1
16.7%
54 1
16.7%

Most occurring characters

ValueCountFrequency (%)
4 5
20.0%
_ 3
12.0%
5 3
12.0%
0 2
 
8.0%
3 2
 
8.0%
2
 
8.0%
2 1
 
4.0%
9 1
 
4.0%
M 1
 
4.0%
a 1
 
4.0%
Other values (4) 4
16.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 14
56.0%
Lowercase Letter 5
 
20.0%
Connector Punctuation 3
 
12.0%
Space Separator 2
 
8.0%
Uppercase Letter 1
 
4.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 5
35.7%
5 3
21.4%
0 2
 
14.3%
3 2
 
14.3%
2 1
 
7.1%
9 1
 
7.1%
Lowercase Letter
ValueCountFrequency (%)
a 1
20.0%
i 1
20.0%
s 1
20.0%
d 1
20.0%
e 1
20.0%
Connector Punctuation
ValueCountFrequency (%)
_ 3
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%
Uppercase Letter
ValueCountFrequency (%)
M 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 19
76.0%
Latin 6
 
24.0%

Most frequent character per script

Common
ValueCountFrequency (%)
4 5
26.3%
_ 3
15.8%
5 3
15.8%
0 2
 
10.5%
3 2
 
10.5%
2
 
10.5%
2 1
 
5.3%
9 1
 
5.3%
Latin
ValueCountFrequency (%)
M 1
16.7%
a 1
16.7%
i 1
16.7%
s 1
16.7%
d 1
16.7%
e 1
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 25
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 5
20.0%
_ 3
12.0%
5 3
12.0%
0 2
 
8.0%
3 2
 
8.0%
2
 
8.0%
2 1
 
4.0%
9 1
 
4.0%
M 1
 
4.0%
a 1
 
4.0%
Other values (4) 4
16.0%

HISTOPATOL
Categorical

Distinct1
Distinct (%)25.0%
Missing0
Missing (%)0.0%
Memory size64.0 B
N/realiz
4 

Length

Max length8
Median length8
Mean length8
Min length8

Characters and Unicode

Total characters32
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
4th rowN/realiz

Common Values

ValueCountFrequency (%)
N/realiz 4
100.0%

Length

2023-10-31T16:39:02.350989image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-10-31T16:39:02.490971image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
ValueCountFrequency (%)
n/realiz 4
100.0%

Most occurring characters

ValueCountFrequency (%)
N 4
12.5%
/ 4
12.5%
r 4
12.5%
e 4
12.5%
a 4
12.5%
l 4
12.5%
i 4
12.5%
z 4
12.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 24
75.0%
Uppercase Letter 4
 
12.5%
Other Punctuation 4
 
12.5%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
r 4
16.7%
e 4
16.7%
a 4
16.7%
l 4
16.7%
i 4
16.7%
z 4
16.7%
Uppercase Letter
ValueCountFrequency (%)
N 4
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 28
87.5%
Common 4
 
12.5%

Most frequent character per script

Latin
ValueCountFrequency (%)
N 4
14.3%
r 4
14.3%
e 4
14.3%
a 4
14.3%
l 4
14.3%
i 4
14.3%
z 4
14.3%
Common
ValueCountFrequency (%)
/ 4
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 32
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
N 4
12.5%
/ 4
12.5%
r 4
12.5%
e 4
12.5%
a 4
12.5%
l 4
12.5%
i 4
12.5%
z 4
12.5%

Status_Resistencia
Categorical

Distinct1
Distinct (%)25.0%
Missing0
Missing (%)0.0%
Memory size64.0 B
1
4 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters4
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
4th row1

Common Values

ValueCountFrequency (%)
1 4
100.0%

Length

2023-10-31T16:39:02.598174image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-10-31T16:39:03.228453image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
ValueCountFrequency (%)
1 4
100.0%

Most occurring characters

ValueCountFrequency (%)
1 4
100.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 4
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 4
100.0%

Cluster
Categorical

Distinct1
Distinct (%)25.0%
Missing0
Missing (%)0.0%
Memory size64.0 B
1
4 

Length

Max length1
Median length1
Mean length1
Min length1

Characters and Unicode

Total characters4
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
4th row1

Common Values

ValueCountFrequency (%)
1 4
100.0%

Length

2023-10-31T16:39:03.335687image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-10-31T16:39:03.473168image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
ValueCountFrequency (%)
1 4
100.0%

Most occurring characters

ValueCountFrequency (%)
1 4
100.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4
100.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 4
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 4
100.0%

Probabilidade
Categorical

HIGH CORRELATION  UNIFORM  UNIQUE 

Distinct4
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size64.0 B
0.28968234395794423
1 
0.3027694902809071
1 
0.2013750686572229
1 
0.21357264163761477
1 

Length

Max length19
Median length18.5
Mean length18.5
Min length18

Characters and Unicode

Total characters74
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

Unique4 ?
Unique (%)100.0%

Sample

1st row0.28968234395794423
2nd row0.3027694902809071
3rd row0.2013750686572229
4th row0.21357264163761477

Common Values

ValueCountFrequency (%)
0.28968234395794423 1
25.0%
0.3027694902809071 1
25.0%
0.2013750686572229 1
25.0%
0.21357264163761477 1
25.0%

Length

2023-10-31T16:39:03.584148image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-10-31T16:39:03.744673image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
ValueCountFrequency (%)
0.28968234395794423 1
25.0%
0.3027694902809071 1
25.0%
0.2013750686572229 1
25.0%
0.21357264163761477 1
25.0%

Most occurring characters

ValueCountFrequency (%)
2 11
14.9%
0 10
13.5%
7 9
12.2%
9 7
9.5%
6 7
9.5%
3 7
9.5%
4 6
8.1%
1 5
6.8%
. 4
 
5.4%
8 4
 
5.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 70
94.6%
Other Punctuation 4
 
5.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 11
15.7%
0 10
14.3%
7 9
12.9%
9 7
10.0%
6 7
10.0%
3 7
10.0%
4 6
8.6%
1 5
7.1%
8 4
 
5.7%
5 4
 
5.7%
Other Punctuation
ValueCountFrequency (%)
. 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 74
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 11
14.9%
0 10
13.5%
7 9
12.2%
9 7
9.5%
6 7
9.5%
3 7
9.5%
4 6
8.1%
1 5
6.8%
. 4
 
5.4%
8 4
 
5.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 74
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 11
14.9%
0 10
13.5%
7 9
12.2%
9 7
9.5%
6 7
9.5%
3 7
9.5%
4 6
8.1%
1 5
6.8%
. 4
 
5.4%
8 4
 
5.4%

Correlations

2023-10-31T16:39:03.881243image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
faixaEtariasexoESCOLARIDTIPOCUPtipoCasodescobertacultEscRXDROGADICAOmotMudEsquemaidadeProbabilidade
faixaEtaria1.0000.7071.0000.7070.7070.0000.0000.0000.7070.0001.0001.000
sexo0.7071.0001.0000.0000.0000.0000.0000.0000.0000.0000.7071.000
ESCOLARID1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
TIPOCUP0.7070.0001.0001.0000.0000.7070.0000.0000.0000.0000.7071.000
tipoCaso0.7070.0001.0000.0001.0000.0000.0000.0000.0000.0000.7071.000
descoberta0.0000.0001.0000.7070.0001.0000.0000.7070.7070.7070.0001.000
cultEsc0.0000.0001.0000.0000.0000.0001.0000.0000.0000.0000.0001.000
RX0.0000.0001.0000.0000.0000.7070.0001.0000.0000.0000.0001.000
DROGADICAO0.7070.0001.0000.0000.0000.7070.0000.0001.0000.0000.7071.000
motMudEsquema0.0000.0001.0000.0000.0000.7070.0000.0000.0001.0000.0001.000
idade1.0000.7071.0000.7070.7070.0000.0000.0000.7070.0001.0001.000
Probabilidade1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000

Missing values

2023-10-31T16:38:55.860847image/svg+xmlMatplotlib v3.6.0, https://matplotlib.org/
A simple visualization of nullity by column.
2023-10-31T16:38:56.401112image/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
105420_29FDe 4 a 7 anosDesempregadoCuraNovoPulPulElucidacao Diagn. em InternacaoPosN/realizN/realizSusp TBN/realizNegNNNNSNNuloSupervisionado23_39N/realiz110.289682
145940_49FDe 8 a 11 anosOutraCuraNovoPulPulUrgencia / EmergenciaPosN/realizNegSusp TBN/realizNegNNNNNNNuloSupervisionado40_54N/realiz110.302769
52840_49FDe 1 a 3 anosOutraCuraNovoPulPulInvestigacao de ContatosPosN/realizN/realizN/realizN/realizNegNNNNNNIntolerancia/ToxicidadeSupervisionado40_54N/realiz110.201375
21850_59MDe 12 a 14 anosOutraCuraRecidivaPulPulUrgencia / EmergenciaPosN/realizN/realizSusp TBN/realizNegNNNNNNNuloSupervisionadoMais de 54N/realiz110.213573
faixaEtariasexoESCOLARIDTIPOCUPsitAtualtipoCasoFORMACLIN1classifdescobertabacBACOUTROcultEscRXNECROPhivaidsDIABETESALCOOLISMOMENTALDROGADICAOTABAGISMOmotMudEsquematipoTratidadeHISTOPATOLStatus_ResistenciaClusterProbabilidade
105420_29FDe 4 a 7 anosDesempregadoCuraNovoPulPulElucidacao Diagn. em InternacaoPosN/realizN/realizSusp TBN/realizNegNNNNSNNuloSupervisionado23_39N/realiz110.289682
145940_49FDe 8 a 11 anosOutraCuraNovoPulPulUrgencia / EmergenciaPosN/realizNegSusp TBN/realizNegNNNNNNNuloSupervisionado40_54N/realiz110.302769
52840_49FDe 1 a 3 anosOutraCuraNovoPulPulInvestigacao de ContatosPosN/realizN/realizN/realizN/realizNegNNNNNNIntolerancia/ToxicidadeSupervisionado40_54N/realiz110.201375
21850_59MDe 12 a 14 anosOutraCuraRecidivaPulPulUrgencia / EmergenciaPosN/realizN/realizSusp TBN/realizNegNNNNNNNuloSupervisionadoMais de 54N/realiz110.213573