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

Categorical6
Numeric2

Alerts

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

Reproduction

Analysis started2023-12-10 10:33:03.072570
Analysis finished2023-12-10 10:33:05.270927
Duration2.2 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

행정동코드
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
1114055000
100 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1114055000
2nd row1114055000
3rd row1114055000
4th row1114055000
5th row1114055000

Common Values

ValueCountFrequency (%)
1114055000 100
100.0%

Length

2023-12-10T19:33:05.419297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:33:05.605802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1114055000 100
100.0%

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

2023-12-10T19:33:05.864756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:33:06.132356image/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
중구
100 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
중구 100
100.0%

Length

2023-12-10T19:33:06.319293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:33:06.594267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
중구 100
100.0%

행정동명
Categorical

CONSTANT 

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

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
명동 100
100.0%

Length

2023-12-10T19:33:06.852616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:33:07.034279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
명동 100
100.0%

기준일자
Real number (ℝ)

Distinct42
Distinct (%)42.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20200360
Minimum20200301
Maximum20200418
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:33:07.278882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20200301
5-th percentile20200306
Q120200317
median20200329
Q320200411
95-th percentile20200417
Maximum20200418
Range117
Interquartile range (IQR)94

Descriptive statistics

Standard deviation47.183288
Coefficient of variation (CV)2.3357647 × 10-6
Kurtosis-1.9171751
Mean20200360
Median Absolute Deviation (MAD)23.5
Skewness0.15780242
Sum2.020036 × 109
Variance2226.2626
MonotonicityNot monotonic
2023-12-10T19:33:07.610921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=42)
ValueCountFrequency (%)
20200415 7
 
7.0%
20200410 5
 
5.0%
20200328 5
 
5.0%
20200321 5
 
5.0%
20200408 5
 
5.0%
20200404 4
 
4.0%
20200411 4
 
4.0%
20200418 4
 
4.0%
20200317 3
 
3.0%
20200331 3
 
3.0%
Other values (32) 55
55.0%
ValueCountFrequency (%)
20200301 1
1.0%
20200302 1
1.0%
20200303 1
1.0%
20200305 2
2.0%
20200306 2
2.0%
20200307 2
2.0%
20200308 2
2.0%
20200310 2
2.0%
20200311 2
2.0%
20200312 1
1.0%
ValueCountFrequency (%)
20200418 4
4.0%
20200417 3
3.0%
20200416 1
 
1.0%
20200415 7
7.0%
20200414 2
 
2.0%
20200413 2
 
2.0%
20200412 3
3.0%
20200411 4
4.0%
20200410 5
5.0%
20200409 1
 
1.0%

성별
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
F
45 
M
34 
X
21 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
F 45
45.0%
M 34
34.0%
X 21
21.0%

Length

2023-12-10T19:33:07.874915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:33:08.067059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
f 45
45.0%
m 34
34.0%
x 21
21.0%

연령대
Categorical

HIGH CORRELATION 

Distinct9
Distinct (%)9.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
25
33 
xx
21 
30
19 
35
12 
20
8 
Other values (4)
7 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique2 ?
Unique (%)2.0%

Sample

1st rowxx
2nd rowxx
3rd row25
4th rowxx
5th row30

Common Values

ValueCountFrequency (%)
25 33
33.0%
xx 21
21.0%
30 19
19.0%
35 12
 
12.0%
20 8
 
8.0%
40 3
 
3.0%
45 2
 
2.0%
50 1
 
1.0%
15 1
 
1.0%

Length

2023-12-10T19:33:08.320491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T19:33:08.558479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
25 33
33.0%
xx 21
21.0%
30 19
19.0%
35 12
 
12.0%
20 8
 
8.0%
40 3
 
3.0%
45 2
 
2.0%
50 1
 
1.0%
15 1
 
1.0%

소비인구(명)
Real number (ℝ)

Distinct6
Distinct (%)6.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean29.034015
Minimum22.861429
Maximum60.963812
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T19:33:08.881369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum22.861429
5-th percentile22.861429
Q122.861429
median22.861429
Q330.481906
95-th percentile46.103883
Maximum60.963812
Range38.102382
Interquartile range (IQR)7.6204765

Descriptive statistics

Standard deviation9.1711535
Coefficient of variation (CV)0.31587617
Kurtosis2.5614369
Mean29.034015
Median Absolute Deviation (MAD)0
Skewness1.723177
Sum2903.4015
Variance84.110056
MonotonicityNot monotonic
2023-12-10T19:33:09.153454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
22.86142941 56
56.0%
30.48190588 25
25.0%
38.10238235 8
 
8.0%
45.72285882 6
 
6.0%
53.34333529 3
 
3.0%
60.96381176 2
 
2.0%
ValueCountFrequency (%)
22.86142941 56
56.0%
30.48190588 25
25.0%
38.10238235 8
 
8.0%
45.72285882 6
 
6.0%
53.34333529 3
 
3.0%
60.96381176 2
 
2.0%
ValueCountFrequency (%)
60.96381176 2
 
2.0%
53.34333529 3
 
3.0%
45.72285882 6
 
6.0%
38.10238235 8
 
8.0%
30.48190588 25
25.0%
22.86142941 56
56.0%

Interactions

2023-12-10T19:33:03.840514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:33:03.392449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:33:04.038227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T19:33:03.628922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T19:33:09.334903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기준일자성별연령대소비인구(명)
기준일자1.0000.0000.1360.000
성별0.0001.0000.9320.431
연령대0.1360.9321.0000.000
소비인구(명)0.0000.4310.0001.000
2023-12-10T19:33:09.576952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연령대성별
연령대1.0000.673
성별0.6731.000
2023-12-10T19:33:09.779721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기준일자소비인구(명)성별연령대
기준일자1.0000.0960.0000.084
소비인구(명)0.0961.0000.1930.000
성별0.0000.1931.0000.673
연령대0.0840.0000.6731.000

Missing values

2023-12-10T19:33:04.826869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T19:33:05.160328image/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)
01114055000서울특별시중구명동20200302Xxx22.861429
11114055000서울특별시중구명동20200303Xxx22.861429
21114055000서울특별시중구명동20200305F2538.102382
31114055000서울특별시중구명동20200305Xxx22.861429
41114055000서울특별시중구명동20200306F3022.861429
51114055000서울특별시중구명동20200306M2538.102382
61114055000서울특별시중구명동20200307F2522.861429
71114055000서울특별시중구명동20200307M2530.481906
81114055000서울특별시중구명동20200308F2022.861429
91114055000서울특별시중구명동20200308F2530.481906
행정동코드시도명시군구명행정동명기준일자성별연령대소비인구(명)
901114055000서울특별시중구명동20200415M4522.861429
911114055000서울특별시중구명동20200416Xxx30.481906
921114055000서울특별시중구명동20200417M2545.722859
931114055000서울특별시중구명동20200417M3038.102382
941114055000서울특별시중구명동20200417Xxx38.102382
951114055000서울특별시중구명동20200418F2522.861429
961114055000서울특별시중구명동20200418F3030.481906
971114055000서울특별시중구명동20200418M2022.861429
981114055000서울특별시중구명동20200418M2538.102382
991114055000서울특별시중구명동20200301F2530.481906