Overview

Dataset statistics

Number of variables8
Number of observations100
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.8 KiB
Average record size in memory69.3 B

Variable types

Categorical6
Numeric2

Alerts

시도명 has constant value ""Constant
시군구명 has constant value ""Constant
행정동코드 is highly overall correlated with 기준일자 and 1 other fieldsHigh correlation
행정동명 is highly overall correlated with 기준일자 and 1 other fieldsHigh correlation
기준일자 is highly overall correlated with 행정동코드 and 1 other fieldsHigh correlation

Reproduction

Analysis started2023-12-10 11:54:01.594485
Analysis finished2023-12-10 11:54:03.889861
Duration2.3 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

행정동코드
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
1111053000
55 
1111051500
45 

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 (%)
1111053000 55
55.0%
1111051500 45
45.0%

Length

2023-12-10T20:54:04.032857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T20:54:04.213898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1111053000 55
55.0%
1111051500 45
45.0%

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

2023-12-10T20:54:04.412259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T20:54:04.596226image/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

2023-12-10T20:54:04.765807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T20:54:04.926364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
종로구 100
100.0%

행정동명
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
사직동
55 
청운효자동
45 

Length

Max length5
Median length3
Mean length3.9
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
사직동 55
55.0%
청운효자동 45
45.0%

Length

2023-12-10T20:54:05.131103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T20:54:05.345244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
사직동 55
55.0%
청운효자동 45
45.0%

기준일자
Real number (ℝ)

HIGH CORRELATION 

Distinct48
Distinct (%)48.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20200361
Minimum20200301
Maximum20200530
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T20:54:05.559045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20200301
5-th percentile20200303
Q120200311
median20200320
Q320200415
95-th percentile20200509
Maximum20200530
Range229
Interquartile range (IQR)104

Descriptive statistics

Standard deviation73.225372
Coefficient of variation (CV)3.6249536 × 10-6
Kurtosis-0.10696678
Mean20200361
Median Absolute Deviation (MAD)14.5
Skewness1.1632261
Sum2.0200361 × 109
Variance5361.9552
MonotonicityNot monotonic
2023-12-10T20:54:05.844558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=48)
ValueCountFrequency (%)
20200314 5
 
5.0%
20200306 4
 
4.0%
20200324 4
 
4.0%
20200313 4
 
4.0%
20200327 4
 
4.0%
20200305 4
 
4.0%
20200320 4
 
4.0%
20200311 3
 
3.0%
20200319 3
 
3.0%
20200309 3
 
3.0%
Other values (38) 62
62.0%
ValueCountFrequency (%)
20200301 2
2.0%
20200302 2
2.0%
20200303 3
3.0%
20200304 3
3.0%
20200305 4
4.0%
20200306 4
4.0%
20200307 2
2.0%
20200309 3
3.0%
20200311 3
3.0%
20200312 1
 
1.0%
ValueCountFrequency (%)
20200530 1
 
1.0%
20200528 2
2.0%
20200521 1
 
1.0%
20200515 1
 
1.0%
20200509 1
 
1.0%
20200508 2
2.0%
20200507 2
2.0%
20200502 3
3.0%
20200501 1
 
1.0%
20200430 2
2.0%

성별
Categorical

Distinct2
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
M
67 
F
33 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
M 67
67.0%
F 33
33.0%

Length

2023-12-10T20:54:06.082137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T20:54:06.245701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
m 67
67.0%
f 33
33.0%

연령대
Real number (ℝ)

Distinct11
Distinct (%)11.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean40.3
Minimum15
Maximum65
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T20:54:06.417231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum15
5-th percentile20
Q130
median45
Q350
95-th percentile55
Maximum65
Range50
Interquartile range (IQR)20

Descriptive statistics

Standard deviation11.344469
Coefficient of variation (CV)0.28150046
Kurtosis-0.84392575
Mean40.3
Median Absolute Deviation (MAD)5
Skewness-0.31923681
Sum4030
Variance128.69697
MonotonicityNot monotonic
2023-12-10T20:54:06.633053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
45 25
25.0%
50 17
17.0%
25 12
12.0%
30 11
11.0%
40 10
 
10.0%
55 9
 
9.0%
20 6
 
6.0%
35 6
 
6.0%
60 2
 
2.0%
65 1
 
1.0%
ValueCountFrequency (%)
15 1
 
1.0%
20 6
 
6.0%
25 12
12.0%
30 11
11.0%
35 6
 
6.0%
40 10
 
10.0%
45 25
25.0%
50 17
17.0%
55 9
 
9.0%
60 2
 
2.0%
ValueCountFrequency (%)
65 1
 
1.0%
60 2
 
2.0%
55 9
 
9.0%
50 17
17.0%
45 25
25.0%
40 10
 
10.0%
35 6
 
6.0%
30 11
11.0%
25 12
12.0%
20 6
 
6.0%

소비인구(명)
Categorical

Distinct5
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
22.86142941
66 
30.48190588
22 
38.10238235
9 
45.72285882
 
2
53.34333529
 
1

Length

Max length11
Median length11
Mean length11
Min length11

Unique

Unique1 ?
Unique (%)1.0%

Sample

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

Common Values

ValueCountFrequency (%)
22.86142941 66
66.0%
30.48190588 22
 
22.0%
38.10238235 9
 
9.0%
45.72285882 2
 
2.0%
53.34333529 1
 
1.0%

Length

2023-12-10T20:54:06.852995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T20:54:07.052830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
22.86142941 66
66.0%
30.48190588 22
 
22.0%
38.10238235 9
 
9.0%
45.72285882 2
 
2.0%
53.34333529 1
 
1.0%

Interactions

2023-12-10T20:54:03.185031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:54:02.830719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:54:03.350013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T20:54:02.997838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T20:54:07.207793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
행정동코드행정동명기준일자성별연령대소비인구(명)
행정동코드1.0000.9990.9270.0840.0000.192
행정동명0.9991.0000.9270.0840.0000.192
기준일자0.9270.9271.0000.0000.1770.180
성별0.0840.0840.0001.0000.3770.000
연령대0.0000.0000.1770.3771.0000.000
소비인구(명)0.1920.1920.1800.0000.0001.000
2023-12-10T20:54:07.420889image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
소비인구(명)행정동코드성별행정동명
소비인구(명)1.0000.2300.0000.230
행정동코드0.2301.0000.0530.980
성별0.0000.0531.0000.053
행정동명0.2300.9800.0531.000
2023-12-10T20:54:07.638422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기준일자연령대행정동코드행정동명성별소비인구(명)
기준일자1.0000.1160.7480.7480.0000.120
연령대0.1161.0000.0000.0000.2940.000
행정동코드0.7480.0001.0000.9800.0530.230
행정동명0.7480.0000.9801.0000.0530.230
성별0.0000.2940.0530.0531.0000.000
소비인구(명)0.1200.0000.2300.2300.0001.000

Missing values

2023-12-10T20:54:03.555614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T20:54:03.790597image/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)
01111051500서울특별시종로구청운효자동20200306F5022.861429
11111051500서울특별시종로구청운효자동20200418M2038.102382
21111051500서울특별시종로구청운효자동20200415F5522.861429
31111051500서울특별시종로구청운효자동20200502F3522.861429
41111051500서울특별시종로구청운효자동20200423M4522.861429
51111051500서울특별시종로구청운효자동20200501M3030.481906
61111051500서울특별시종로구청운효자동20200530M4022.861429
71111051500서울특별시종로구청운효자동20200509M3522.861429
81111051500서울특별시종로구청운효자동20200528M5522.861429
91111051500서울특별시종로구청운효자동20200404F6522.861429
행정동코드시도명시군구명행정동명기준일자성별연령대소비인구(명)
901111053000서울특별시종로구사직동20200313F4530.481906
911111053000서울특별시종로구사직동20200311M4530.481906
921111053000서울특별시종로구사직동20200311M4022.861429
931111053000서울특별시종로구사직동20200325M5022.861429
941111053000서울특별시종로구사직동20200311M2030.481906
951111053000서울특별시종로구사직동20200309M4530.481906
961111053000서울특별시종로구사직동20200309M3022.861429
971111053000서울특별시종로구사직동20200327M4530.481906
981111053000서울특별시종로구사직동20200301F5022.861429
991111053000서울특별시종로구사직동20200328F4530.481906