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 기준일자 and 2 other fieldsHigh correlation
행정동명 is highly overall correlated with 기준일자 and 2 other fieldsHigh correlation
기준일자 is highly overall correlated with 행정동코드 and 1 other fieldsHigh correlation
소비인구(명) is highly overall correlated with 행정동코드 and 1 other fieldsHigh correlation
성별 is highly overall correlated with 연령대High correlation
연령대 is highly overall correlated with 성별High correlation

Reproduction

Analysis started2023-12-10 12:19:28.264292
Analysis finished2023-12-10 12:19:29.296409
Duration1.03 second
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
70 
1111061500
30 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1111053000
2nd row1111053000
3rd row1111053000
4th row1111053000
5th row1111053000

Common Values

ValueCountFrequency (%)
1111053000 70
70.0%
1111061500 30
30.0%

Length

2023-12-10T21:19:29.381646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T21:19:29.510339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1111053000 70
70.0%
1111061500 30
30.0%

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

2023-12-10T21:19:29.644224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T21:19:29.746282image/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

2023-12-10T21:19:29.845356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T21:19:29.939856image/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
70 
종로1.2.3.4가동
30 

Length

Max length11
Median length3
Mean length5.4
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
사직동 70
70.0%
종로1.2.3.4가동 30
30.0%

Length

2023-12-10T21:19:30.063226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T21:19:30.210004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
사직동 70
70.0%
종로1.2.3.4가동 30
30.0%

기준일자
Real number (ℝ)

HIGH CORRELATION 

Distinct51
Distinct (%)51.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20190898
Minimum20190801
Maximum20191031
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T21:19:30.352662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20190801
5-th percentile20190801
Q120190803
median20190905
Q320191009
95-th percentile20191026
Maximum20191031
Range230
Interquartile range (IQR)206

Descriptive statistics

Standard deviation91.4596
Coefficient of variation (CV)4.5297442 × 10-6
Kurtosis-1.6118019
Mean20190898
Median Absolute Deviation (MAD)102
Skewness0.25460459
Sum2.0190898 × 109
Variance8364.8585
MonotonicityNot monotonic
2023-12-10T21:19:30.532438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20190803 12
 
12.0%
20190802 8
 
8.0%
20190801 6
 
6.0%
20190804 6
 
6.0%
20190928 3
 
3.0%
20190905 3
 
3.0%
20191004 2
 
2.0%
20191021 2
 
2.0%
20191018 2
 
2.0%
20191026 2
 
2.0%
Other values (41) 54
54.0%
ValueCountFrequency (%)
20190801 6
6.0%
20190802 8
8.0%
20190803 12
12.0%
20190804 6
6.0%
20190806 1
 
1.0%
20190809 1
 
1.0%
20190810 2
 
2.0%
20190811 1
 
1.0%
20190814 1
 
1.0%
20190817 1
 
1.0%
ValueCountFrequency (%)
20191031 1
1.0%
20191030 1
1.0%
20191028 1
1.0%
20191027 2
2.0%
20191026 2
2.0%
20191025 1
1.0%
20191023 1
1.0%
20191021 2
2.0%
20191020 1
1.0%
20191019 2
2.0%

성별
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
M
79 
F
17 
X
 
4

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
M 79
79.0%
F 17
 
17.0%
X 4
 
4.0%

Length

2023-12-10T21:19:30.675721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T21:19:30.795081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
m 79
79.0%
f 17
 
17.0%
x 4
 
4.0%

연령대
Categorical

HIGH CORRELATION 

Distinct11
Distinct (%)11.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
20
29 
25
27 
30
11 
55
7 
40
6 
Other values (6)
20 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique1 ?
Unique (%)1.0%

Sample

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

Common Values

ValueCountFrequency (%)
20 29
29.0%
25 27
27.0%
30 11
 
11.0%
55 7
 
7.0%
40 6
 
6.0%
15 5
 
5.0%
50 4
 
4.0%
xx 4
 
4.0%
35 3
 
3.0%
45 3
 
3.0%

Length

2023-12-10T21:19:30.917773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
20 29
29.0%
25 27
27.0%
30 11
 
11.0%
55 7
 
7.0%
40 6
 
6.0%
15 5
 
5.0%
50 4
 
4.0%
xx 4
 
4.0%
35 3
 
3.0%
45 3
 
3.0%

소비인구(명)
Real number (ℝ)

HIGH CORRELATION 

Distinct12
Distinct (%)12.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean33.74
Minimum22
Maximum133
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T21:19:31.035342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum22
5-th percentile22
Q122
median22
Q337
95-th percentile81
Maximum133
Range111
Interquartile range (IQR)15

Descriptive statistics

Standard deviation21.62846
Coefficient of variation (CV)0.64103321
Kurtosis8.630481
Mean33.74
Median Absolute Deviation (MAD)0
Skewness2.7976753
Sum3374
Variance467.7903
MonotonicityNot monotonic
2023-12-10T21:19:31.145734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
22 54
54.0%
30 17
 
17.0%
37 12
 
12.0%
44 5
 
5.0%
74 3
 
3.0%
133 2
 
2.0%
81 2
 
2.0%
52 1
 
1.0%
96 1
 
1.0%
59 1
 
1.0%
Other values (2) 2
 
2.0%
ValueCountFrequency (%)
22 54
54.0%
30 17
 
17.0%
37 12
 
12.0%
44 5
 
5.0%
52 1
 
1.0%
59 1
 
1.0%
66 1
 
1.0%
74 3
 
3.0%
81 2
 
2.0%
89 1
 
1.0%
ValueCountFrequency (%)
133 2
 
2.0%
96 1
 
1.0%
89 1
 
1.0%
81 2
 
2.0%
74 3
 
3.0%
66 1
 
1.0%
59 1
 
1.0%
52 1
 
1.0%
44 5
5.0%
37 12
12.0%

Interactions

2023-12-10T21:19:28.769012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:19:28.580718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:19:28.871536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:19:28.676115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T21:19:31.246328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
행정동코드행정동명기준일자성별연령대소비인구(명)
행정동코드1.0000.9990.5610.2320.1880.761
행정동명0.9991.0000.5610.2320.1880.761
기준일자0.5610.5611.0000.0000.0000.000
성별0.2320.2320.0001.0000.8340.137
연령대0.1880.1880.0000.8341.0000.000
소비인구(명)0.7610.7610.0000.1370.0001.000
2023-12-10T21:19:31.370638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연령대행정동코드행정동명성별
연령대1.0000.1680.1680.697
행정동코드0.1681.0000.9760.377
행정동명0.1680.9761.0000.377
성별0.6970.3770.3771.000
2023-12-10T21:19:31.544524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기준일자소비인구(명)행정동코드행정동명성별연령대
기준일자1.000-0.3510.6990.6990.0000.000
소비인구(명)-0.3511.0000.5670.5670.0800.000
행정동코드0.6990.5671.0000.9760.3770.168
행정동명0.6990.5670.9761.0000.3770.168
성별0.0000.0800.3770.3771.0000.697
연령대0.0000.0000.1680.1680.6971.000

Missing values

2023-12-10T21:19:29.028230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T21:19:29.229648image/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)
01111053000서울특별시종로구사직동20190904M3522
11111053000서울특별시종로구사직동20190928M2537
21111053000서울특별시종로구사직동20190907M2037
31111053000서울특별시종로구사직동20190929M2530
41111053000서울특별시종로구사직동20190904M2022
51111053000서울특별시종로구사직동20190811M2522
61111053000서울특별시종로구사직동20190809M5530
71111053000서울특별시종로구사직동20191011M2030
81111053000서울특별시종로구사직동20190905M2522
91111053000서울특별시종로구사직동20191012M2037
행정동코드시도명시군구명행정동명기준일자성별연령대소비인구(명)
901111061500서울특별시종로구종로1.2.3.4가동20190802F3037
911111061500서울특별시종로구종로1.2.3.4가동20190802F2574
921111061500서울특별시종로구종로1.2.3.4가동20190802F2037
931111061500서울특별시종로구종로1.2.3.4가동20190804F2044
941111061500서울특별시종로구종로1.2.3.4가동20190801M3522
951111061500서울특별시종로구종로1.2.3.4가동20190801M2581
961111061500서울특별시종로구종로1.2.3.4가동20190801M2074
971111061500서울특별시종로구종로1.2.3.4가동20190801M1522
981111061500서울특별시종로구종로1.2.3.4가동20190801F2537
991111061500서울특별시종로구종로1.2.3.4가동20190801F2037