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

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 12:07:51.965303
Analysis finished2023-12-10 12:07:53.076929
Duration1.11 second
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
1111061500
75 
1111071000
24 
1111065000
 
1

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique1 ?
Unique (%)1.0%

Sample

1st row1111061500
2nd row1111061500
3rd row1111061500
4th row1111061500
5th row1111061500

Common Values

ValueCountFrequency (%)
1111061500 75
75.0%
1111071000 24
 
24.0%
1111065000 1
 
1.0%

Length

2023-12-10T21:07:53.160667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T21:07:53.285291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1111061500 75
75.0%
1111071000 24
 
24.0%
1111065000 1
 
1.0%

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

2023-12-10T21:07:53.422659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T21:07:53.535718image/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

2023-12-10T21:07:53.666334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T21:07:53.922514image/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
종로1.2.3.4가동
75 
숭인2동
24 
혜화동
 
1

Length

Max length11
Median length11
Mean length9.24
Min length3

Unique

Unique1 ?
Unique (%)1.0%

Sample

1st row종로1.2.3.4가동
2nd row종로1.2.3.4가동
3rd row종로1.2.3.4가동
4th row종로1.2.3.4가동
5th row종로1.2.3.4가동

Common Values

ValueCountFrequency (%)
종로1.2.3.4가동 75
75.0%
숭인2동 24
 
24.0%
혜화동 1
 
1.0%

Length

2023-12-10T21:07:54.086668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T21:07:54.251636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
종로1.2.3.4가동 75
75.0%
숭인2동 24
 
24.0%
혜화동 1
 
1.0%

기준일자
Real number (ℝ)

Distinct38
Distinct (%)38.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20190868
Minimum20190801
Maximum20191023
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T21:07:54.431148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20190801
5-th percentile20190803
Q120190812
median20190903
Q320190905
95-th percentile20190931
Maximum20191023
Range222
Interquartile range (IQR)93

Descriptive statistics

Standard deviation57.016633
Coefficient of variation (CV)2.8238823 × 10-6
Kurtosis-0.2830411
Mean20190868
Median Absolute Deviation (MAD)75.5
Skewness0.50910298
Sum2.0190868 × 109
Variance3250.8965
MonotonicityNot monotonic
2023-12-10T21:07:54.632327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=38)
ValueCountFrequency (%)
20190903 16
16.0%
20190905 11
 
11.0%
20190904 8
 
8.0%
20190804 6
 
6.0%
20190803 4
 
4.0%
20190801 4
 
4.0%
20190907 4
 
4.0%
20190810 3
 
3.0%
20190817 3
 
3.0%
20190820 3
 
3.0%
Other values (28) 38
38.0%
ValueCountFrequency (%)
20190801 4
4.0%
20190803 4
4.0%
20190804 6
6.0%
20190805 2
 
2.0%
20190807 1
 
1.0%
20190808 1
 
1.0%
20190809 1
 
1.0%
20190810 3
3.0%
20190811 2
 
2.0%
20190812 2
 
2.0%
ValueCountFrequency (%)
20191023 1
1.0%
20191014 1
1.0%
20191010 1
1.0%
20191008 1
1.0%
20191001 1
1.0%
20190927 1
1.0%
20190921 1
1.0%
20190920 1
1.0%
20190911 1
1.0%
20190909 1
1.0%

성별
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
M
54 
F
42 
X
 
4

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
M 54
54.0%
F 42
42.0%
X 4
 
4.0%

Length

2023-12-10T21:07:54.829161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T21:07:54.946420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
m 54
54.0%
f 42
42.0%
x 4
 
4.0%

연령대
Categorical

HIGH CORRELATION 

Distinct11
Distinct (%)11.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
70
25 
60
14 
50
9 
55
9 
65
8 
Other values (6)
35 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row50
2nd rowxx
3rd row60
4th row45
5th row70

Common Values

ValueCountFrequency (%)
70 25
25.0%
60 14
14.0%
50 9
 
9.0%
55 9
 
9.0%
65 8
 
8.0%
45 7
 
7.0%
30 7
 
7.0%
35 7
 
7.0%
25 5
 
5.0%
40 5
 
5.0%

Length

2023-12-10T21:07:55.083508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
70 25
25.0%
60 14
14.0%
50 9
 
9.0%
55 9
 
9.0%
65 8
 
8.0%
45 7
 
7.0%
30 7
 
7.0%
35 7
 
7.0%
25 5
 
5.0%
40 5
 
5.0%

소비인구(명)
Real number (ℝ)

Distinct9
Distinct (%)9.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean31.67
Minimum22
Maximum81
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T21:07:55.230340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum22
5-th percentile22
Q122
median22
Q337
95-th percentile59.35
Maximum81
Range59
Interquartile range (IQR)15

Descriptive statistics

Standard deviation13.484038
Coefficient of variation (CV)0.42576692
Kurtosis2.0452886
Mean31.67
Median Absolute Deviation (MAD)0
Skewness1.5598624
Sum3167
Variance181.81929
MonotonicityNot monotonic
2023-12-10T21:07:55.396832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
22 52
52.0%
30 15
 
15.0%
37 13
 
13.0%
52 8
 
8.0%
44 6
 
6.0%
66 3
 
3.0%
81 1
 
1.0%
74 1
 
1.0%
59 1
 
1.0%
ValueCountFrequency (%)
22 52
52.0%
30 15
 
15.0%
37 13
 
13.0%
44 6
 
6.0%
52 8
 
8.0%
59 1
 
1.0%
66 3
 
3.0%
74 1
 
1.0%
81 1
 
1.0%
ValueCountFrequency (%)
81 1
 
1.0%
74 1
 
1.0%
66 3
 
3.0%
59 1
 
1.0%
52 8
 
8.0%
44 6
 
6.0%
37 13
 
13.0%
30 15
 
15.0%
22 52
52.0%

Interactions

2023-12-10T21:07:52.530665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:07:52.287795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:07:52.638047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:07:52.398373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T21:07:55.510533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
행정동코드행정동명기준일자성별연령대소비인구(명)
행정동코드1.0001.0000.5140.6510.6000.000
행정동명1.0001.0000.5140.6510.6000.000
기준일자0.5140.5141.0000.5160.5610.000
성별0.6510.6510.5161.0000.8340.000
연령대0.6000.6000.5610.8341.0000.273
소비인구(명)0.0000.0000.0000.0000.2731.000
2023-12-10T21:07:55.683950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
행정동코드연령대성별행정동명
행정동코드1.0000.4140.3121.000
연령대0.4141.0000.6960.414
성별0.3120.6961.0000.312
행정동명1.0000.4140.3121.000
2023-12-10T21:07:55.812731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기준일자소비인구(명)행정동코드행정동명성별연령대
기준일자1.000-0.0540.4090.4090.4290.341
소비인구(명)-0.0541.0000.0000.0000.0000.121
행정동코드0.4090.0001.0001.0000.3120.414
행정동명0.4090.0001.0001.0000.3120.414
성별0.4290.0000.3120.3121.0000.696
연령대0.3410.1210.4140.4140.6961.000

Missing values

2023-12-10T21:07:52.802304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T21:07:52.991440image/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)
01111061500서울특별시종로구종로1.2.3.4가동20190822F5022
11111061500서울특별시종로구종로1.2.3.4가동20190903Xxx52
21111061500서울특별시종로구종로1.2.3.4가동20190803F6022
31111061500서울특별시종로구종로1.2.3.4가동20190904F4537
41111061500서울특별시종로구종로1.2.3.4가동20190801M7030
51111061500서울특별시종로구종로1.2.3.4가동20190803F7022
61111061500서울특별시종로구종로1.2.3.4가동20190804M3022
71111061500서울특별시종로구종로1.2.3.4가동20190905F3522
81111061500서울특별시종로구종로1.2.3.4가동20190904M3544
91111061500서울특별시종로구종로1.2.3.4가동20190826M7022
행정동코드시도명시군구명행정동명기준일자성별연령대소비인구(명)
901111071000서울특별시종로구숭인2동20190809M7052
911111071000서울특별시종로구숭인2동20190808M6522
921111071000서울특별시종로구숭인2동20190807M7030
931111071000서울특별시종로구숭인2동20190816M6522
941111071000서울특별시종로구숭인2동20190805M7022
951111071000서울특별시종로구숭인2동20190805M6530
961111071000서울특별시종로구숭인2동20190804M7022
971111071000서울특별시종로구숭인2동20190804M6037
981111071000서울특별시종로구숭인2동20190804F6030
991111071000서울특별시종로구숭인2동20190803M7037