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
행정동코드 is highly imbalanced (50.8%)Imbalance
행정동명 is highly imbalanced (50.8%)Imbalance
성별 is highly imbalanced (52.1%)Imbalance

Reproduction

Analysis started2023-12-10 12:07:42.466360
Analysis finished2023-12-10 12:07:43.651009
Duration1.18 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

행정동코드
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
1111071000
80 
1111061500
19 
1111063000
 
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 (%)
1111071000 80
80.0%
1111061500 19
 
19.0%
1111063000 1
 
1.0%

Length

2023-12-10T21:07:43.752458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T21:07:43.887665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1111071000 80
80.0%
1111061500 19
 
19.0%
1111063000 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

2023-12-10T21:07:44.017808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T21:07:44.116429image/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

2023-12-10T21:07:44.213656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T21:07:44.317341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
종로구 100
100.0%

행정동명
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
숭인2동
80 
종로1.2.3.4가동
19 
종로5.6가동
 
1

Length

Max length11
Median length4
Mean length5.36
Min length4

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 (%)
숭인2동 80
80.0%
종로1.2.3.4가동 19
 
19.0%
종로5.6가동 1
 
1.0%

Length

2023-12-10T21:07:44.433440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T21:07:44.581379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
숭인2동 80
80.0%
종로1.2.3.4가동 19
 
19.0%
종로5.6가동 1
 
1.0%

기준일자
Real number (ℝ)

Distinct45
Distinct (%)45.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20200848
Minimum20200801
Maximum20201012
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T21:07:44.723971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20200801
5-th percentile20200803
Q120200811
median20200822
Q320200905
95-th percentile20200922
Maximum20201012
Range211
Interquartile range (IQR)94.25

Descriptive statistics

Standard deviation50.432309
Coefficient of variation (CV)2.4965441 × 10-6
Kurtosis0.11440585
Mean20200848
Median Absolute Deviation (MAD)14.5
Skewness1.0369409
Sum2.0200848 × 109
Variance2543.4178
MonotonicityNot monotonic
2023-12-10T21:07:44.883318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
20200816 6
 
6.0%
20200808 5
 
5.0%
20200908 4
 
4.0%
20200817 4
 
4.0%
20200906 4
 
4.0%
20200823 4
 
4.0%
20200922 3
 
3.0%
20200905 3
 
3.0%
20200806 3
 
3.0%
20200904 3
 
3.0%
Other values (35) 61
61.0%
ValueCountFrequency (%)
20200801 2
 
2.0%
20200802 3
3.0%
20200803 1
 
1.0%
20200804 2
 
2.0%
20200805 2
 
2.0%
20200806 3
3.0%
20200807 3
3.0%
20200808 5
5.0%
20200809 1
 
1.0%
20200810 3
3.0%
ValueCountFrequency (%)
20201012 1
 
1.0%
20201005 1
 
1.0%
20200928 1
 
1.0%
20200924 1
 
1.0%
20200922 3
3.0%
20200921 2
2.0%
20200918 1
 
1.0%
20200911 2
2.0%
20200910 1
 
1.0%
20200909 2
2.0%

성별
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
M
85 
F
 
8
X
 
7

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
M 85
85.0%
F 8
 
8.0%
X 7
 
7.0%

Length

2023-12-10T21:07:45.113696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T21:07:45.237917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
m 85
85.0%
f 8
 
8.0%
x 7
 
7.0%

연령대
Categorical

HIGH CORRELATION 

Distinct8
Distinct (%)8.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
70
39 
60
21 
65
18 
55
12 
xx
7 
Other values (3)
 
3

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique3 ?
Unique (%)3.0%

Sample

1st row70
2nd rowxx
3rd rowxx
4th row70
5th rowxx

Common Values

ValueCountFrequency (%)
70 39
39.0%
60 21
21.0%
65 18
18.0%
55 12
 
12.0%
xx 7
 
7.0%
50 1
 
1.0%
30 1
 
1.0%
35 1
 
1.0%

Length

2023-12-10T21:07:45.393671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T21:07:45.549463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
70 39
39.0%
60 21
21.0%
65 18
18.0%
55 12
 
12.0%
xx 7
 
7.0%
50 1
 
1.0%
30 1
 
1.0%
35 1
 
1.0%

소비인구(명)
Real number (ℝ)

Distinct8
Distinct (%)8.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean32.519739
Minimum22.479082
Maximum89.91633
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T21:07:45.666607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum22.479082
5-th percentile22.479082
Q122.479082
median29.97211
Q337.465137
95-th percentile60.318871
Maximum89.91633
Range67.437247
Interquartile range (IQR)14.986055

Descriptive statistics

Standard deviation14.137816
Coefficient of variation (CV)0.43474567
Kurtosis4.5272687
Mean32.519739
Median Absolute Deviation (MAD)7.4930275
Skewness1.9895888
Sum3251.9739
Variance199.87784
MonotonicityNot monotonic
2023-12-10T21:07:45.813318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
22.479082395 46
46.0%
29.97210986 24
24.0%
44.95816479 9
 
9.0%
37.465137325 9
 
9.0%
52.451192255 6
 
6.0%
67.437247185 3
 
3.0%
89.91632958 2
 
2.0%
59.94421972 1
 
1.0%
ValueCountFrequency (%)
22.479082395 46
46.0%
29.97210986 24
24.0%
37.465137325 9
 
9.0%
44.95816479 9
 
9.0%
52.451192255 6
 
6.0%
59.94421972 1
 
1.0%
67.437247185 3
 
3.0%
89.91632958 2
 
2.0%
ValueCountFrequency (%)
89.91632958 2
 
2.0%
67.437247185 3
 
3.0%
59.94421972 1
 
1.0%
52.451192255 6
 
6.0%
44.95816479 9
 
9.0%
37.465137325 9
 
9.0%
29.97210986 24
24.0%
22.479082395 46
46.0%

Interactions

2023-12-10T21:07:43.145281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:07:42.878636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:07:43.273853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T21:07:43.009454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T21:07:45.945474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
행정동코드행정동명기준일자성별연령대소비인구(명)
행정동코드1.0001.0000.6720.7340.4030.054
행정동명1.0001.0000.6720.7340.4030.054
기준일자0.6720.6721.0000.6090.5210.201
성별0.7340.7340.6091.0000.7840.000
연령대0.4030.4030.5210.7841.0000.000
소비인구(명)0.0540.0540.2010.0000.0001.000
2023-12-10T21:07:46.094027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
행정동코드연령대성별행정동명
행정동코드1.0000.2720.3901.000
연령대0.2721.0000.6820.272
성별0.3900.6821.0000.390
행정동명1.0000.2720.3901.000
2023-12-10T21:07:46.227040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기준일자소비인구(명)행정동코드행정동명성별연령대
기준일자1.0000.0420.3540.3540.2850.310
소비인구(명)0.0421.0000.0200.0200.0000.000
행정동코드0.3540.0201.0001.0000.3900.272
행정동명0.3540.0201.0001.0000.3900.272
성별0.2850.0000.3900.3901.0000.682
연령대0.3100.0000.2720.2720.6821.000

Missing values

2023-12-10T21:07:43.419952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T21:07:43.572489image/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)
01111061500서울특별시종로구종로1.2.3.4가동20200922F7029.97211
11111061500서울특별시종로구종로1.2.3.4가동20200922Xxx29.97211
21111061500서울특별시종로구종로1.2.3.4가동20200804Xxx22.479082
31111061500서울특별시종로구종로1.2.3.4가동20200921F7022.479082
41111061500서울특별시종로구종로1.2.3.4가동20200921Xxx22.479082
51111061500서울특별시종로구종로1.2.3.4가동20200924M5522.479082
61111061500서울특별시종로구종로1.2.3.4가동20200810Xxx22.479082
71111061500서울특별시종로구종로1.2.3.4가동20200906M5022.479082
81111061500서울특별시종로구종로1.2.3.4가동20200922M7022.479082
91111061500서울특별시종로구종로1.2.3.4가동20200928Xxx22.479082
행정동코드시도명시군구명행정동명기준일자성별연령대소비인구(명)
901111071000서울특별시종로구숭인2동20200822M7037.465137
911111071000서울특별시종로구숭인2동20200906M7089.91633
921111071000서울특별시종로구숭인2동20200908M6022.479082
931111071000서울특별시종로구숭인2동20200908M6529.97211
941111071000서울특별시종로구숭인2동20200807M6522.479082
951111071000서울특별시종로구숭인2동20200909M7029.97211
961111071000서울특별시종로구숭인2동20200807M6029.97211
971111071000서울특별시종로구숭인2동20200911M6529.97211
981111071000서울특별시종로구숭인2동20200801Xxx29.97211
991111071000서울특별시종로구숭인2동20200801M5522.479082