Overview

Dataset statistics

Number of variables5
Number of observations6458
Missing cells1
Missing cells (%)< 0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.6 MiB
Average record size in memory252.4 B

Variable types

Numeric1
DateTime1
Categorical3

Alerts

modalidadeContrato is highly imbalanced (69.0%)Imbalance

Reproduction

Analysis started2025-11-26 17:56:28.231574
Analysis finished2025-11-26 17:56:30.120952
Duration1.89 second
Software versionydata-profiling vv4.18.0
Download configurationconfig.json

Variables

id
Real number (ℝ)

Distinct6457
Distinct (%)> 99.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean98588.072
Minimum7126
Maximum139986
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size50.6 KiB
2025-11-26T14:56:30.517136image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Quantile statistics

Minimum7126
5-th percentile67781.2
Q186110
median98620
Q3113106
95-th percentile127574.3
Maximum139986
Range132860
Interquartile range (IQR)26996

Descriptive statistics

Standard deviation19162.976
Coefficient of variation (CV)0.19437419
Kurtosis0.95922973
Mean98588.072
Median Absolute Deviation (MAD)13186.5
Skewness-0.60467936
Sum6.3668177 × 108
Variance3.6721965 × 108
MonotonicityNot monotonic
2025-11-26T14:56:31.300394image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1289712
 
< 0.1%
793671
 
< 0.1%
1114641
 
< 0.1%
1097521
 
< 0.1%
1105091
 
< 0.1%
1106731
 
< 0.1%
1111011
 
< 0.1%
1111781
 
< 0.1%
1112201
 
< 0.1%
1114551
 
< 0.1%
Other values (6447)6447
99.8%
ValueCountFrequency (%)
71261
< 0.1%
76611
< 0.1%
77531
< 0.1%
108341
< 0.1%
129181
< 0.1%
152561
< 0.1%
170391
< 0.1%
184491
< 0.1%
233181
< 0.1%
234511
< 0.1%
ValueCountFrequency (%)
1399861
< 0.1%
1333071
< 0.1%
1333011
< 0.1%
1332711
< 0.1%
1332421
< 0.1%
1331951
< 0.1%
1331921
< 0.1%
1331201
< 0.1%
1331011
< 0.1%
1330581
< 0.1%
Distinct370
Distinct (%)5.7%
Missing0
Missing (%)0.0%
Memory size50.6 KiB
Minimum2024-04-01 00:00:00
Maximum2025-04-30 00:00:00
Invalid dates0
Invalid dates (%)0.0%
2025-11-26T14:56:31.646749image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
2025-11-26T14:56:32.349740image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

modalidadeContrato
Categorical

Imbalance 

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size588.0 KiB
Pessoa Física
6099 
Pessoa Jurídica
 
359

Length

Max length15
Median length13
Mean length13.11118
Min length13

Characters and Unicode

Total characters84672
Distinct characters14
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 rowPessoa Física
2nd rowPessoa Física
3rd rowPessoa Física
4th rowPessoa Física
5th rowPessoa Física

Common Values

ValueCountFrequency (%)
Pessoa Física6099
94.4%
Pessoa Jurídica359
 
5.6%

Length

2025-11-26T14:56:32.701878image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-11-26T14:56:32.904607image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
pessoa6458
50.0%
física6099
47.2%
jurídica359
 
2.8%

Most occurring characters

ValueCountFrequency (%)
s19015
22.5%
a12916
15.3%
P6458
 
7.6%
e6458
 
7.6%
o6458
 
7.6%
6458
 
7.6%
í6458
 
7.6%
i6458
 
7.6%
c6458
 
7.6%
F6099
 
7.2%
Other values (4)1436
 
1.7%

Most occurring categories

ValueCountFrequency (%)
(unknown)84672
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
s19015
22.5%
a12916
15.3%
P6458
 
7.6%
e6458
 
7.6%
o6458
 
7.6%
6458
 
7.6%
í6458
 
7.6%
i6458
 
7.6%
c6458
 
7.6%
F6099
 
7.2%
Other values (4)1436
 
1.7%

Most occurring scripts

ValueCountFrequency (%)
(unknown)84672
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
s19015
22.5%
a12916
15.3%
P6458
 
7.6%
e6458
 
7.6%
o6458
 
7.6%
6458
 
7.6%
í6458
 
7.6%
i6458
 
7.6%
c6458
 
7.6%
F6099
 
7.2%
Other values (4)1436
 
1.7%

Most occurring blocks

ValueCountFrequency (%)
(unknown)84672
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
s19015
22.5%
a12916
15.3%
P6458
 
7.6%
e6458
 
7.6%
o6458
 
7.6%
6458
 
7.6%
í6458
 
7.6%
i6458
 
7.6%
c6458
 
7.6%
F6099
 
7.2%
Other values (4)1436
 
1.7%

plano
Categorical

Distinct9
Distinct (%)0.1%
Missing1
Missing (%)< 0.1%
Memory size458.3 KiB
Plano Anual - R$246,00
1635 
Plano Light Anual - R$178,00
1091 
Plano Light - R$178,00
894 
Plano Mensal - R$296,00
799 
Plano Light - R$148,00
566 
Other values (4)
1472 

Length

Max length28
Median length22
Mean length23.64643
Min length22

Characters and Unicode

Total characters152685
Distinct characters31
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 rowPlano Mensal - R$296,00
2nd rowPlano Light - R$148,00
3rd rowPlano Anual - R$246,00
4th rowPlano Light - R$148,00
5th rowPlano Light - R$148,00

Common Values

ValueCountFrequency (%)
Plano Anual - R$246,001635
25.3%
Plano Light Anual - R$178,001091
16.9%
Plano Light - R$178,00894
13.8%
Plano Mensal - R$296,00799
12.4%
Plano Light - R$148,00566
 
8.8%
Plano Light - R$246,00535
 
8.3%
Plano Light Anual - R$123,00472
 
7.3%
Plano Mensal - R$346,00454
 
7.0%
Plano Start - R$148,0011
 
0.2%
(Missing)1
 
< 0.1%

Length

2025-11-26T14:56:33.104605image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2025-11-26T14:56:33.419708image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
ValueCountFrequency (%)
plano6457
23.6%
6457
23.6%
light3558
13.0%
anual3198
11.7%
r$246,002170
 
7.9%
r$178,001985
 
7.2%
mensal1253
 
4.6%
r$296,00799
 
2.9%
r$148,00577
 
2.1%
r$123,00472
 
1.7%
Other values (2)465
 
1.7%

Most occurring characters

ValueCountFrequency (%)
20934
 
13.7%
012914
 
8.5%
a10919
 
7.2%
n10908
 
7.1%
l10908
 
7.1%
R6457
 
4.2%
,6457
 
4.2%
$6457
 
4.2%
P6457
 
4.2%
-6457
 
4.2%
Other values (21)53817
35.2%

Most occurring categories

ValueCountFrequency (%)
(unknown)152685
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
20934
 
13.7%
012914
 
8.5%
a10919
 
7.2%
n10908
 
7.1%
l10908
 
7.1%
R6457
 
4.2%
,6457
 
4.2%
$6457
 
4.2%
P6457
 
4.2%
-6457
 
4.2%
Other values (21)53817
35.2%

Most occurring scripts

ValueCountFrequency (%)
(unknown)152685
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
20934
 
13.7%
012914
 
8.5%
a10919
 
7.2%
n10908
 
7.1%
l10908
 
7.1%
R6457
 
4.2%
,6457
 
4.2%
$6457
 
4.2%
P6457
 
4.2%
-6457
 
4.2%
Other values (21)53817
35.2%

Most occurring blocks

ValueCountFrequency (%)
(unknown)152685
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
20934
 
13.7%
012914
 
8.5%
a10919
 
7.2%
n10908
 
7.1%
l10908
 
7.1%
R6457
 
4.2%
,6457
 
4.2%
$6457
 
4.2%
P6457
 
4.2%
-6457
 
4.2%
Other values (21)53817
35.2%

visita
Categorical

Distinct24
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size445.1 KiB
Sem Visita
1759 
Visita Virtual
786 
Livance - Botafogo
440 
Livance - Tatuapé
329 
Livance - Barra da Tijuca
308 
Other values (19)
2836 

Length

Max length27
Median length25
Mean length16.585785
Min length10

Characters and Unicode

Total characters107111
Distinct characters41
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 rowSem Visita
2nd rowLivance - Botafogo
3rd rowSem Visita
4th rowSem Visita
5th rowSem Visita

Common Values

ValueCountFrequency (%)
Sem Visita1759
27.2%
Visita Virtual786
12.2%
Livance - Botafogo440
 
6.8%
Livance - Tatuapé329
 
5.1%
Livance - Barra da Tijuca308
 
4.8%
Livance - Paulista293
 
4.5%
Livance - Vila Mariana259
 
4.0%
Livance - Campinas259
 
4.0%
Livance - Market Place239
 
3.7%
Livance - Perdizes228
 
3.5%
Other values (14)1558
24.1%

Length

2025-11-26T14:56:33.871145image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
livance3893
20.7%
3893
20.7%
visita2545
13.5%
sem1759
9.3%
virtual786
 
4.2%
vila574
 
3.0%
botafogo440
 
2.3%
tatuapé329
 
1.7%
tijuca308
 
1.6%
da308
 
1.6%
Other values (22)3998
21.2%

Most occurring characters

ValueCountFrequency (%)
a14225
13.3%
i13242
12.4%
12375
 
11.6%
e7452
 
7.0%
n5579
 
5.2%
t5134
 
4.8%
c4711
 
4.4%
v4100
 
3.8%
V3905
 
3.6%
-3893
 
3.6%
Other values (31)32495
30.3%

Most occurring categories

ValueCountFrequency (%)
(unknown)107111
100.0%

Most frequent character per category

(unknown)
ValueCountFrequency (%)
a14225
13.3%
i13242
12.4%
12375
 
11.6%
e7452
 
7.0%
n5579
 
5.2%
t5134
 
4.8%
c4711
 
4.4%
v4100
 
3.8%
V3905
 
3.6%
-3893
 
3.6%
Other values (31)32495
30.3%

Most occurring scripts

ValueCountFrequency (%)
(unknown)107111
100.0%

Most frequent character per script

(unknown)
ValueCountFrequency (%)
a14225
13.3%
i13242
12.4%
12375
 
11.6%
e7452
 
7.0%
n5579
 
5.2%
t5134
 
4.8%
c4711
 
4.4%
v4100
 
3.8%
V3905
 
3.6%
-3893
 
3.6%
Other values (31)32495
30.3%

Most occurring blocks

ValueCountFrequency (%)
(unknown)107111
100.0%

Most frequent character per block

(unknown)
ValueCountFrequency (%)
a14225
13.3%
i13242
12.4%
12375
 
11.6%
e7452
 
7.0%
n5579
 
5.2%
t5134
 
4.8%
c4711
 
4.4%
v4100
 
3.8%
V3905
 
3.6%
-3893
 
3.6%
Other values (31)32495
30.3%

Interactions

2025-11-26T14:56:29.110007image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/

Correlations

2025-11-26T14:56:34.074872image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
idmodalidadeContratoplanovisita
id1.0000.0000.2470.082
modalidadeContrato0.0001.0000.1750.113
plano0.2470.1751.0000.086
visita0.0820.1130.0861.000

Missing values

2025-11-26T14:56:29.777220image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
A simple visualization of nullity by column.
2025-11-26T14:56:29.976861image/svg+xmlMatplotlib v3.10.0, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

iddataVendamodalidadeContratoplanovisita
0793672024-04-01Pessoa FísicaPlano Mensal - R$296,00Sem Visita
1793272024-04-01Pessoa FísicaPlano Light - R$148,00Livance - Botafogo
2793042024-04-01Pessoa FísicaPlano Anual - R$246,00Sem Visita
3792852024-04-01Pessoa FísicaPlano Light - R$148,00Sem Visita
4792842024-04-01Pessoa FísicaPlano Light - R$148,00Sem Visita
5792482024-04-01Pessoa FísicaPlano Light - R$148,00Sem Visita
6792432024-04-01Pessoa FísicaPlano Mensal - R$296,00Sem Visita
7792392024-04-01Pessoa FísicaPlano Light Anual - R$178,00Sem Visita
8792372024-04-01Pessoa FísicaPlano Light - R$148,00Sem Visita
9790372024-04-01Pessoa FísicaPlano Light - R$148,00Livance - Botafogo
iddataVendamodalidadeContratoplanovisita
64481300442025-04-30Pessoa FísicaPlano Light Anual - R$178,00Livance - Botafogo
64491300052025-04-30Pessoa FísicaPlano Light - R$246,00Livance - Tatuapé
64501295802025-04-30Pessoa FísicaPlano Anual - R$246,00Livance - Brigadeiro Psico
64511256342025-04-30Pessoa FísicaPlano Light Anual - R$178,00Livance - Santos Flex
64521254922025-04-30Pessoa FísicaPlano Light Anual - R$178,00Visita Virtual
64531221282025-04-30Pessoa FísicaPlano Light - R$246,00Livance - Santo André
64541184562025-04-30Pessoa FísicaPlano Light - R$246,00Visita Virtual
64551180142025-04-30Pessoa FísicaPlano Light - R$246,00Livance - Vila Mariana
64561119712025-04-30Pessoa FísicaPlano Light - R$246,00Livance - Perdizes
64571078802025-04-30Pessoa FísicaPlano Light Anual - R$178,00Livance - Brigadeiro Psico