Overview

Dataset statistics

Number of variables8
Number of observations100
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.7 KiB
Average record size in memory68.3 B

Variable types

Categorical7
Numeric1

Alerts

시도명 has constant value ""Constant
시군구명 has constant value ""Constant
행정동코드 is highly overall correlated with 행정동명High correlation
행정동명 is highly overall correlated with 행정동코드High correlation
성별 is highly overall correlated with 연령대High correlation
연령대 is highly overall correlated with 성별High correlation

Reproduction

Analysis started2023-12-10 12:02:20.068345
Analysis finished2023-12-10 12:02:21.024931
Duration0.96 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

행정동코드
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
1111051500
60 
1111055000
26 
1111053000
14 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1111051500
2nd row1111051500
3rd row1111051500
4th row1111051500
5th row1111051500

Common Values

ValueCountFrequency (%)
1111051500 60
60.0%
1111055000 26
26.0%
1111053000 14
 
14.0%

Length

2023-12-10T21:02:21.129690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T21:02:21.280981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1111051500 60
60.0%
1111055000 26
26.0%
1111053000 14
 
14.0%

시도명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
서울특별시
100 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
서울특별시 100
100.0%

Length

2023-12-10T21:02:21.440552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T21:02:21.599040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
서울특별시 100
100.0%

시군구명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
종로구
100 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
종로구 100
100.0%

Length

2023-12-10T21:02:21.749627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T21:02:21.888107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
종로구 100
100.0%

행정동명
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
청운효자동
60 
부암동
26 
사직동
14 

Length

Max length5
Median length5
Mean length4.2
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
청운효자동 60
60.0%
부암동 26
26.0%
사직동 14
 
14.0%

Length

2023-12-10T21:02:22.089237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T21:02:22.238729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
청운효자동 60
60.0%
부암동 26
26.0%
사직동 14
 
14.0%

기준일자
Real number (ℝ)

Distinct44
Distinct (%)44.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20200433
Minimum20200307
Maximum20200527
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T21:02:22.415557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20200307
5-th percentile20200311
Q120200325
median20200425
Q320200514
95-th percentile20200525
Maximum20200527
Range220
Interquartile range (IQR)189.5

Descriptive statistics

Standard deviation87.136314
Coefficient of variation (CV)4.3135865 × 10-6
Kurtosis-1.6435497
Mean20200433
Median Absolute Deviation (MAD)93.5
Skewness-0.31225929
Sum2.0200433 × 109
Variance7592.7373
MonotonicityNot monotonic
2023-12-10T21:02:22.701014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=44)
ValueCountFrequency (%)
20200520 6
 
6.0%
20200425 6
 
6.0%
20200323 5
 
5.0%
20200511 5
 
5.0%
20200512 4
 
4.0%
20200408 4
 
4.0%
20200325 4
 
4.0%
20200518 4
 
4.0%
20200516 3
 
3.0%
20200523 3
 
3.0%
Other values (34) 56
56.0%
ValueCountFrequency (%)
20200307 1
 
1.0%
20200309 1
 
1.0%
20200310 1
 
1.0%
20200311 3
3.0%
20200312 1
 
1.0%
20200313 1
 
1.0%
20200314 3
3.0%
20200316 1
 
1.0%
20200317 2
2.0%
20200318 2
2.0%
ValueCountFrequency (%)
20200527 3
3.0%
20200526 1
 
1.0%
20200525 2
 
2.0%
20200523 3
3.0%
20200521 2
 
2.0%
20200520 6
6.0%
20200519 1
 
1.0%
20200518 4
4.0%
20200516 3
3.0%
20200514 2
 
2.0%

성별
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
M
53 
F
42 
X
 
5

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowM
2nd rowF
3rd rowM
4th rowM
5th rowF

Common Values

ValueCountFrequency (%)
M 53
53.0%
F 42
42.0%
X 5
 
5.0%

Length

2023-12-10T21:02:22.984480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T21:02:23.148528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
m 53
53.0%
f 42
42.0%
x 5
 
5.0%

연령대
Categorical

HIGH CORRELATION 

Distinct9
Distinct (%)9.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
45
19 
50
18 
35
14 
40
14 
30
11 
Other values (4)
24 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row35
2nd row50
3rd row35
4th row25
5th row45

Common Values

ValueCountFrequency (%)
45 19
19.0%
50 18
18.0%
35 14
14.0%
40 14
14.0%
30 11
11.0%
25 8
8.0%
55 8
8.0%
xx 5
 
5.0%
60 3
 
3.0%

Length

2023-12-10T21:02:23.308157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T21:02:23.473704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
45 19
19.0%
50 18
18.0%
35 14
14.0%
40 14
14.0%
30 11
11.0%
25 8
8.0%
55 8
8.0%
xx 5
 
5.0%
60 3
 
3.0%

소비인구(명)
Categorical

Distinct3
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
22.86142941
68 
30.48190588
27 
38.10238235
 
5

Length

Max length11
Median length11
Mean length11
Min length11

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row22.86142941
2nd row30.48190588
3rd row22.86142941
4th row22.86142941
5th row38.10238235

Common Values

ValueCountFrequency (%)
22.86142941 68
68.0%
30.48190588 27
 
27.0%
38.10238235 5
 
5.0%

Length

2023-12-10T21:02:23.690169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T21:02:24.292234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
22.86142941 68
68.0%
30.48190588 27
 
27.0%
38.10238235 5
 
5.0%

Interactions

2023-12-10T21:02:20.560344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T21:02:24.420860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
행정동코드행정동명기준일자성별연령대소비인구(명)
행정동코드1.0001.0000.0000.5510.7000.151
행정동명1.0001.0000.0000.5510.7000.151
기준일자0.0000.0001.0000.0000.0000.292
성별0.5510.5510.0001.0000.9670.156
연령대0.7000.7000.0000.9671.0000.000
소비인구(명)0.1510.1510.2920.1560.0001.000
2023-12-10T21:02:24.631394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
행정동코드연령대성별소비인구(명)행정동명
행정동코드1.0000.3940.2360.0441.000
연령대0.3941.0000.7580.0000.394
성별0.2360.7581.0000.0450.236
소비인구(명)0.0440.0000.0451.0000.044
행정동명1.0000.3940.2360.0441.000
2023-12-10T21:02:24.809515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기준일자행정동코드행정동명성별연령대소비인구(명)
기준일자1.0000.0000.0000.0000.0000.131
행정동코드0.0001.0001.0000.2360.3940.044
행정동명0.0001.0001.0000.2360.3940.044
성별0.0000.2360.2361.0000.7580.045
연령대0.0000.3940.3940.7581.0000.000
소비인구(명)0.1310.0440.0440.0450.0001.000

Missing values

2023-12-10T21:02:20.753588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T21:02:20.948839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

행정동코드시도명시군구명행정동명기준일자성별연령대소비인구(명)
01111051500서울특별시종로구청운효자동20200327M3522.861429
11111051500서울특별시종로구청운효자동20200504F5030.481906
21111051500서울특별시종로구청운효자동20200506M3522.861429
31111051500서울특별시종로구청운효자동20200512M2522.861429
41111051500서울특별시종로구청운효자동20200506F4538.102382
51111051500서울특별시종로구청운효자동20200316F4522.861429
61111051500서울특별시종로구청운효자동20200508F2522.861429
71111051500서울특별시종로구청운효자동20200312M4022.861429
81111051500서울특별시종로구청운효자동20200408F4022.861429
91111051500서울특별시종로구청운효자동20200313M3030.481906
행정동코드시도명시군구명행정동명기준일자성별연령대소비인구(명)
901111055000서울특별시종로구부암동20200408M4522.861429
911111055000서울특별시종로구부암동20200328M5530.481906
921111055000서울특별시종로구부암동20200328F4530.481906
931111055000서울특별시종로구부암동20200516M5022.861429
941111055000서울특별시종로구부암동20200323M3022.861429
951111055000서울특별시종로구부암동20200318F5530.481906
961111055000서울특별시종로구부암동20200314F5030.481906
971111055000서울특별시종로구부암동20200311F6022.861429
981111055000서울특별시종로구부암동20200311F4522.861429
991111055000서울특별시종로구부암동20200307F4530.481906