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 13:15:44.448719
Analysis finished2023-12-10 13:15:45.663192
Duration1.21 second
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
1111051500
100 

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 100
100.0%

Length

2023-12-10T22:15:45.762452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:15:45.959421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1111051500 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

2023-12-10T22:15:46.143171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:15:46.280288image/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

2023-12-10T22:15:46.430628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:15:46.582928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
종로구 100
100.0%

행정동명
Categorical

CONSTANT 

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

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
청운효자동 100
100.0%

Length

2023-12-10T22:15:46.738649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:15:46.883410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
청운효자동 100
100.0%

기준일자
Real number (ℝ)

Distinct6
Distinct (%)6.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20190803
Minimum20190801
Maximum20190806
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T22:15:47.033702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20190801
5-th percentile20190801
Q120190802
median20190803
Q320190805
95-th percentile20190806
Maximum20190806
Range5
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1.6174553
Coefficient of variation (CV)8.0108517 × 10-8
Kurtosis-1.1920453
Mean20190803
Median Absolute Deviation (MAD)1
Skewness0.2440673
Sum2.0190803 × 109
Variance2.6161616
MonotonicityIncreasing
2023-12-10T22:15:47.225961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
20190803 22
22.0%
20190801 21
21.0%
20190805 21
21.0%
20190802 20
20.0%
20190804 9
9.0%
20190806 7
 
7.0%
ValueCountFrequency (%)
20190801 21
21.0%
20190802 20
20.0%
20190803 22
22.0%
20190804 9
9.0%
20190805 21
21.0%
20190806 7
 
7.0%
ValueCountFrequency (%)
20190806 7
 
7.0%
20190805 21
21.0%
20190804 9
9.0%
20190803 22
22.0%
20190802 20
20.0%
20190801 21
21.0%

성별
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
F
50 
M
45 
X
 
5

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
F 50
50.0%
M 45
45.0%
X 5
 
5.0%

Length

2023-12-10T22:15:47.503056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:15:47.662521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
f 50
50.0%
m 45
45.0%
x 5
 
5.0%

연령대
Categorical

HIGH CORRELATION 

Distinct13
Distinct (%)13.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
30
11 
25
10 
35
10 
40
10 
45
10 
Other values (8)
49 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique1 ?
Unique (%)1.0%

Sample

1st row20
2nd row25
3rd row30
4th row35
5th row40

Common Values

ValueCountFrequency (%)
30 11
11.0%
25 10
10.0%
35 10
10.0%
40 10
10.0%
45 10
10.0%
50 9
9.0%
55 9
9.0%
20 7
7.0%
60 7
7.0%
70 7
7.0%
Other values (3) 10
10.0%

Length

2023-12-10T22:15:47.841690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
30 11
11.0%
25 10
10.0%
35 10
10.0%
40 10
10.0%
45 10
10.0%
50 9
9.0%
55 9
9.0%
20 7
7.0%
60 7
7.0%
70 7
7.0%
Other values (3) 10
10.0%

소비인구(명)
Real number (ℝ)

Distinct29
Distinct (%)29.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean82.57
Minimum22
Maximum310
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T22:15:48.029518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum22
5-th percentile22
Q137
median59
Q397.75
95-th percentile236.4
Maximum310
Range288
Interquartile range (IQR)60.75

Descriptive statistics

Standard deviation68.106461
Coefficient of variation (CV)0.824833
Kurtosis2.6306016
Mean82.57
Median Absolute Deviation (MAD)29
Skewness1.7200766
Sum8257
Variance4638.49
MonotonicityNot monotonic
2023-12-10T22:15:48.222601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
22 13
13.0%
30 11
11.0%
44 11
11.0%
52 8
 
8.0%
66 6
 
6.0%
81 6
 
6.0%
37 5
 
5.0%
74 5
 
5.0%
140 4
 
4.0%
59 4
 
4.0%
Other values (19) 27
27.0%
ValueCountFrequency (%)
22 13
13.0%
30 11
11.0%
37 5
 
5.0%
44 11
11.0%
52 8
8.0%
59 4
 
4.0%
66 6
6.0%
74 5
 
5.0%
81 6
6.0%
89 4
 
4.0%
ValueCountFrequency (%)
310 1
1.0%
303 2
2.0%
273 1
1.0%
244 1
1.0%
236 1
1.0%
229 1
1.0%
221 1
1.0%
185 1
1.0%
177 1
1.0%
163 1
1.0%

Interactions

2023-12-10T22:15:45.042238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:15:44.784233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:15:45.176489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T22:15:44.917624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T22:15:48.354568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기준일자성별연령대소비인구(명)
기준일자1.0000.1620.0000.000
성별0.1621.0000.8150.641
연령대0.0000.8151.0000.445
소비인구(명)0.0000.6410.4451.000
2023-12-10T22:15:48.502156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
성별연령대
성별1.0000.642
연령대0.6421.000
2023-12-10T22:15:48.662067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기준일자소비인구(명)성별연령대
기준일자1.000-0.1380.0340.000
소비인구(명)-0.1381.0000.4690.195
성별0.0340.4691.0000.642
연령대0.0000.1950.6421.000

Missing values

2023-12-10T22:15:45.368657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T22:15:45.588791image/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)
01111051500서울특별시종로구청운효자동20190801F2022
11111051500서울특별시종로구청운효자동20190801F2544
21111051500서울특별시종로구청운효자동20190801F3074
31111051500서울특별시종로구청운효자동20190801F3552
41111051500서울특별시종로구청운효자동20190801F4074
51111051500서울특별시종로구청운효자동20190801F4566
61111051500서울특별시종로구청운효자동20190801F5081
71111051500서울특별시종로구청운효자동20190801F5552
81111051500서울특별시종로구청운효자동20190801F6044
91111051500서울특별시종로구청운효자동20190801F6544
행정동코드시도명시군구명행정동명기준일자성별연령대소비인구(명)
901111051500서울특별시종로구청운효자동20190805M5537
911111051500서울특별시종로구청운효자동20190805M7044
921111051500서울특별시종로구청운효자동20190805Xxx156
931111051500서울특별시종로구청운효자동20190806F3059
941111051500서울특별시종로구청운효자동20190806F3522
951111051500서울특별시종로구청운효자동20190806F4044
961111051500서울특별시종로구청운효자동20190806F4589
971111051500서울특별시종로구청운효자동20190806F5066
981111051500서울특별시종로구청운효자동20190806F5522
991111051500서울특별시종로구청운효자동20190806F6022