Overview

Dataset statistics

Number of variables12
Number of observations1165
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory121.9 KiB
Average record size in memory107.1 B

Variable types

Categorical5
Numeric6
Text1

Dataset

Description경기도_주민등록인구통계세대원수별세대수행정동별집계기본
Author경기도
URLhttps://data.gg.go.kr/portal/data/service/selectServicePage.do?&infId=VZNUIGPDZ6CQMNIHPYZJ34725423&infSeq=1

Alerts

1인세대비율 has constant value ""Constant
2인세대비율 has constant value ""Constant
3인세대비율 has constant value ""Constant
4인이상세대비율 has constant value ""Constant
총세대수 is highly overall correlated with 1인세대수 and 3 other fieldsHigh correlation
1인세대수 is highly overall correlated with 총세대수 and 3 other fieldsHigh correlation
2인세대수 is highly overall correlated with 총세대수 and 3 other fieldsHigh correlation
3인세대수 is highly overall correlated with 총세대수 and 3 other fieldsHigh correlation
4인이상세대수 is highly overall correlated with 총세대수 and 3 other fieldsHigh correlation
행정동코드 is highly skewed (γ1 = -32.80127705)Skewed

Reproduction

Analysis started2024-03-12 23:37:20.470753
Analysis finished2024-03-12 23:37:24.346238
Duration3.88 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

기준연월
Categorical

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size9.2 KiB
2016
596 
2017
569 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2017
2nd row2017
3rd row2017
4th row2017
5th row2017

Common Values

ValueCountFrequency (%)
2016 596
51.2%
2017 569
48.8%

Length

2024-03-13T08:37:24.424526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T08:37:24.556556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2016 596
51.2%
2017 569
48.8%

행정동코드
Real number (ℝ)

SKEWED 

Distinct607
Distinct (%)52.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean41315326
Minimum4136
Maximum41830410
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.4 KiB
2024-03-13T08:37:24.684104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4136
5-th percentile41115712
Q141190570
median41285520
Q341480540
95-th percentile41670520
Maximum41830410
Range41826274
Interquartile range (IQR)289970

Descriptive statistics

Standard deviation1227474.6
Coefficient of variation (CV)0.029709909
Kurtosis1104.9095
Mean41315326
Median Absolute Deviation (MAD)149863
Skewness-32.801277
Sum4.8132355 × 1010
Variance1.5066938 × 1012
MonotonicityNot monotonic
2024-03-13T08:37:24.831659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
41463520 2
 
0.2%
41570510 2
 
0.2%
41173510 2
 
0.2%
41273560 2
 
0.2%
41360550 2
 
0.2%
41360560 2
 
0.2%
41461310 2
 
0.2%
41461330 2
 
0.2%
41570520 2
 
0.2%
41171621 2
 
0.2%
Other values (597) 1145
98.3%
ValueCountFrequency (%)
4136 1
0.1%
41111560 2
0.2%
41111566 2
0.2%
41111571 2
0.2%
41111572 2
0.2%
41111573 2
0.2%
41111580 2
0.2%
41111591 2
0.2%
41111597 2
0.2%
41111598 2
0.2%
ValueCountFrequency (%)
41830410 2
0.2%
41830400 2
0.2%
41830395 2
0.2%
41830380 2
0.2%
41830370 2
0.2%
41830360 2
0.2%
41830350 2
0.2%
41830340 2
0.2%
41830330 2
0.2%
41830320 2
0.2%

행정동명
Text

Distinct547
Distinct (%)47.0%
Missing0
Missing (%)0.0%
Memory size9.2 KiB
2024-03-13T08:37:25.102618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length3.3845494
Min length2

Characters and Unicode

Total characters3943
Distinct characters196
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique12 ?
Unique (%)1.0%

Sample

1st row구갈동
2nd row상갈동
3rd row기흥동
4th row서농동
5th row구성동
ValueCountFrequency (%)
중앙동 15
 
1.3%
금곡동 6
 
0.5%
반월동 4
 
0.3%
위례동 4
 
0.3%
신장1동 4
 
0.3%
신촌동 4
 
0.3%
정자2동 4
 
0.3%
정자3동 4
 
0.3%
능곡동 4
 
0.3%
정자1동 4
 
0.3%
Other values (537) 1112
95.5%
2024-03-13T08:37:25.719453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 919
23.3%
면 209
 
5.3%
1 171
 
4.3%
2 163
 
4.1%
3 77
 
2.0%
산 70
 
1.8%
읍 68
 
1.7%
정 63
 
1.6%
곡 62
 
1.6%
신 58
 
1.5%
Other values (186) 2083
52.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3495
88.6%
Decimal Number 448
 
11.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 919
26.3%
면 209
 
6.0%
산 70
 
2.0%
읍 68
 
1.9%
정 63
 
1.8%
곡 62
 
1.8%
신 58
 
1.7%
양 58
 
1.7%
원 55
 
1.6%
안 51
 
1.5%
Other values (177) 1882
53.8%
Decimal Number
ValueCountFrequency (%)
1 171
38.2%
2 163
36.4%
3 77
17.2%
4 21
 
4.7%
7 4
 
0.9%
5 4
 
0.9%
6 4
 
0.9%
8 2
 
0.4%
9 2
 
0.4%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3495
88.6%
Common 448
 
11.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 919
26.3%
면 209
 
6.0%
산 70
 
2.0%
읍 68
 
1.9%
정 63
 
1.8%
곡 62
 
1.8%
신 58
 
1.7%
양 58
 
1.7%
원 55
 
1.6%
안 51
 
1.5%
Other values (177) 1882
53.8%
Common
ValueCountFrequency (%)
1 171
38.2%
2 163
36.4%
3 77
17.2%
4 21
 
4.7%
7 4
 
0.9%
5 4
 
0.9%
6 4
 
0.9%
8 2
 
0.4%
9 2
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3495
88.6%
ASCII 448
 
11.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 919
26.3%
면 209
 
6.0%
산 70
 
2.0%
읍 68
 
1.9%
정 63
 
1.8%
곡 62
 
1.8%
신 58
 
1.7%
양 58
 
1.7%
원 55
 
1.6%
안 51
 
1.5%
Other values (177) 1882
53.8%
ASCII
ValueCountFrequency (%)
1 171
38.2%
2 163
36.4%
3 77
17.2%
4 21
 
4.7%
7 4
 
0.9%
5 4
 
0.9%
6 4
 
0.9%
8 2
 
0.4%
9 2
 
0.4%

총세대수
Real number (ℝ)

HIGH CORRELATION 

Distinct1137
Distinct (%)97.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11493.047
Minimum73
Maximum241041
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.4 KiB
2024-03-13T08:37:25.995374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum73
5-th percentile1897.8
Q15223
median8589
Q312794
95-th percentile29984.8
Maximum241041
Range240968
Interquartile range (IQR)7571

Descriptive statistics

Standard deviation14357.913
Coefficient of variation (CV)1.2492695
Kurtosis72.697038
Mean11493.047
Median Absolute Deviation (MAD)3823
Skewness6.6231284
Sum13389400
Variance2.0614967 × 108
MonotonicityNot monotonic
2024-03-13T08:37:26.225567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10486 3
 
0.3%
9450 2
 
0.2%
10154 2
 
0.2%
10539 2
 
0.2%
6196 2
 
0.2%
1897 2
 
0.2%
4600 2
 
0.2%
3225 2
 
0.2%
10756 2
 
0.2%
9063 2
 
0.2%
Other values (1127) 1144
98.2%
ValueCountFrequency (%)
73 1
0.1%
75 1
0.1%
111 1
0.1%
121 1
0.1%
331 1
0.1%
347 1
0.1%
568 1
0.1%
574 1
0.1%
776 1
0.1%
784 1
0.1%
ValueCountFrequency (%)
241041 1
0.1%
148108 1
0.1%
120578 1
0.1%
105095 1
0.1%
102119 1
0.1%
94263 1
0.1%
92785 1
0.1%
81779 1
0.1%
80884 1
0.1%
77093 1
0.1%

1인세대수
Real number (ℝ)

HIGH CORRELATION 

Distinct1049
Distinct (%)90.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3676.5459
Minimum22
Maximum74951
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.4 KiB
2024-03-13T08:37:26.420567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum22
5-th percentile759.4
Q11667
median2695
Q34017
95-th percentile8941.8
Maximum74951
Range74929
Interquartile range (IQR)2350

Descriptive statistics

Standard deviation4642.6765
Coefficient of variation (CV)1.2627821
Kurtosis71.137986
Mean3676.5459
Median Absolute Deviation (MAD)1143
Skewness6.7930956
Sum4283176
Variance21554445
MonotonicityNot monotonic
2024-03-13T08:37:26.604615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1774 4
 
0.3%
1821 3
 
0.3%
1380 3
 
0.3%
921 3
 
0.3%
1741 3
 
0.3%
3717 3
 
0.3%
1374 3
 
0.3%
2724 3
 
0.3%
3390 3
 
0.3%
1924 3
 
0.3%
Other values (1039) 1134
97.3%
ValueCountFrequency (%)
22 1
0.1%
23 1
0.1%
66 1
0.1%
74 1
0.1%
122 1
0.1%
134 1
0.1%
263 1
0.1%
277 1
0.1%
294 2
0.2%
332 1
0.1%
ValueCountFrequency (%)
74951 1
0.1%
47655 1
0.1%
44760 1
0.1%
43803 1
0.1%
37798 1
0.1%
33825 1
0.1%
32142 1
0.1%
28252 1
0.1%
25114 1
0.1%
23885 1
0.1%

2인세대수
Real number (ℝ)

HIGH CORRELATION 

Distinct1007
Distinct (%)86.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2311.3906
Minimum20
Maximum50708
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.4 KiB
2024-03-13T08:37:26.790479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20
5-th percentile460
Q11087
median1764
Q32541
95-th percentile5466.4
Maximum50708
Range50688
Interquartile range (IQR)1454

Descriptive statistics

Standard deviation2877.0186
Coefficient of variation (CV)1.2447133
Kurtosis85.593183
Mean2311.3906
Median Absolute Deviation (MAD)710
Skewness7.176587
Sum2692770
Variance8277236
MonotonicityNot monotonic
2024-03-13T08:37:26.979269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1130 3
 
0.3%
1044 3
 
0.3%
1237 3
 
0.3%
2015 3
 
0.3%
2284 3
 
0.3%
1520 3
 
0.3%
1618 3
 
0.3%
2088 3
 
0.3%
2075 3
 
0.3%
1932 3
 
0.3%
Other values (997) 1135
97.4%
ValueCountFrequency (%)
20 1
0.1%
21 1
0.1%
26 1
0.1%
29 1
0.1%
112 1
0.1%
113 1
0.1%
171 1
0.1%
179 1
0.1%
188 1
0.1%
195 1
0.1%
ValueCountFrequency (%)
50708 1
0.1%
29945 1
0.1%
24656 1
0.1%
21524 1
0.1%
19907 1
0.1%
18569 1
0.1%
17956 1
0.1%
16806 1
0.1%
16616 1
0.1%
15665 1
0.1%

3인세대수
Real number (ℝ)

HIGH CORRELATION 

Distinct995
Distinct (%)85.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2252.2927
Minimum6
Maximum47860
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.4 KiB
2024-03-13T08:37:27.133428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum6
5-th percentile238
Q1891
median1670
Q32592
95-th percentile6092
Maximum47860
Range47854
Interquartile range (IQR)1701

Descriptive statistics

Standard deviation2948.1087
Coefficient of variation (CV)1.3089368
Kurtosis66.633184
Mean2252.2927
Median Absolute Deviation (MAD)833
Skewness6.3047748
Sum2623921
Variance8691344.9
MonotonicityNot monotonic
2024-03-13T08:37:27.326964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2152 3
 
0.3%
1635 3
 
0.3%
1094 3
 
0.3%
1651 3
 
0.3%
302 3
 
0.3%
779 3
 
0.3%
1317 3
 
0.3%
1024 3
 
0.3%
824 3
 
0.3%
1121 3
 
0.3%
Other values (985) 1135
97.4%
ValueCountFrequency (%)
6 2
0.2%
9 1
0.1%
11 1
0.1%
48 1
0.1%
50 1
0.1%
63 1
0.1%
67 1
0.1%
96 1
0.1%
101 2
0.2%
106 1
0.1%
ValueCountFrequency (%)
47860 1
0.1%
32856 1
0.1%
22140 1
0.1%
21309 1
0.1%
17107 1
0.1%
16503 1
0.1%
16484 1
0.1%
16393 1
0.1%
16327 1
0.1%
16238 1
0.1%

4인이상세대수
Real number (ℝ)

HIGH CORRELATION 

Distinct1053
Distinct (%)90.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3252.818
Minimum14
Maximum67522
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.4 KiB
2024-03-13T08:37:27.483801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum14
5-th percentile260.2
Q11079
median2235
Q33790
95-th percentile8490.6
Maximum67522
Range67508
Interquartile range (IQR)2711

Descriptive statistics

Standard deviation4437.8501
Coefficient of variation (CV)1.3643094
Kurtosis59.417375
Mean3252.818
Median Absolute Deviation (MAD)1312
Skewness6.0216223
Sum3789533
Variance19694514
MonotonicityNot monotonic
2024-03-13T08:37:27.689786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1450 4
 
0.3%
1740 3
 
0.3%
1584 3
 
0.3%
3702 3
 
0.3%
1511 3
 
0.3%
895 3
 
0.3%
2299 3
 
0.3%
492 3
 
0.3%
4399 3
 
0.3%
2693 3
 
0.3%
Other values (1043) 1134
97.3%
ValueCountFrequency (%)
14 2
0.2%
19 1
0.1%
20 1
0.1%
48 1
0.1%
51 1
0.1%
59 1
0.1%
63 1
0.1%
90 1
0.1%
100 1
0.1%
101 1
0.1%
ValueCountFrequency (%)
67522 1
0.1%
53165 1
0.1%
31452 1
0.1%
31034 1
0.1%
29979 1
0.1%
28268 1
0.1%
26925 1
0.1%
26873 1
0.1%
25739 1
0.1%
25553 1
0.1%

1인세대비율
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size9.2 KiB
0
1165 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 1165
100.0%

Length

2024-03-13T08:37:27.892087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T08:37:27.987972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1165
100.0%

2인세대비율
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size9.2 KiB
0
1165 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 1165
100.0%

Length

2024-03-13T08:37:28.085321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T08:37:28.190911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1165
100.0%

3인세대비율
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size9.2 KiB
0
1165 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 1165
100.0%

Length

2024-03-13T08:37:28.316796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T08:37:28.713942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1165
100.0%

4인이상세대비율
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size9.2 KiB
0
1165 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 1165
100.0%

Length

2024-03-13T08:37:28.798971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T08:37:28.883644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1165
100.0%

Interactions

2024-03-13T08:37:23.669472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:37:20.838911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:37:21.379071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:37:21.889261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:37:22.490425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:37:23.151868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:37:23.750459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:37:20.909347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:37:21.454503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:37:22.006348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:37:22.560448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:37:23.226424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:37:23.822954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:37:20.993400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:37:21.548440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:37:22.084943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:37:22.838493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:37:23.304991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:37:23.901061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:37:21.090241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:37:21.631110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:37:22.169589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:37:22.918731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:37:23.414688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:37:23.972692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:37:21.181626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:37:21.714225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:37:22.244813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:37:22.988647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:37:23.504769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:37:24.054916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:37:21.290915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:37:21.806517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:37:22.357505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:37:23.061229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:37:23.585715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-13T08:37:28.947358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기준연월행정동코드총세대수1인세대수2인세대수3인세대수4인이상세대수
기준연월1.000NaN0.1330.0980.0940.0620.046
행정동코드NaN1.000NaNNaNNaNNaNNaN
총세대수0.133NaN1.0000.9680.9490.9480.910
1인세대수0.098NaN0.9681.0000.8720.8430.826
2인세대수0.094NaN0.9490.8721.0000.9920.977
3인세대수0.062NaN0.9480.8430.9921.0000.992
4인이상세대수0.046NaN0.9100.8260.9770.9921.000
2024-03-13T08:37:29.097726image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
행정동코드총세대수1인세대수2인세대수3인세대수4인이상세대수기준연월
행정동코드1.000-0.215-0.186-0.186-0.240-0.2210.000
총세대수-0.2151.0000.8640.9750.9640.9230.100
1인세대수-0.1860.8641.0000.8720.7260.6350.074
2인세대수-0.1860.9750.8721.0000.9400.8740.100
3인세대수-0.2400.9640.7260.9401.0000.9800.067
4인이상세대수-0.2210.9230.6350.8740.9801.0000.049
기준연월0.0000.1000.0740.1000.0670.0491.000

Missing values

2024-03-13T08:37:24.166312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-13T08:37:24.291907image/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

기준연월행정동코드행정동명총세대수1인세대수2인세대수3인세대수4인이상세대수1인세대비율2인세대비율3인세대비율4인이상세대비율
0201741463520구갈동1163745962131204628640000
1201741463530상갈동1740950693429327856330000
2201741463540기흥동854123191960176824940000
3201741463550서농동1047638431731197529270000
4201741463560구성동1442129283438319248630000
5201741463570마북동1185625772659270039200000
6201741463585동백동26708466444076184114530000
7201741463586상하동886619341796192132150000
8201741463590보정동1295427452725298145030000
9201741465510풍덕천1동1440143962787306541530000
기준연월행정동코드행정동명총세대수1인세대수2인세대수3인세대수4인이상세대수1인세대비율2인세대비율3인세대비율4인이상세대비율
1155201641830320강하면221810296272742880000
1156201641830330양서면54562166144882410180000
1157201641830340옥천면349815948664465920000
1158201641830350서종면4213196510505086900000
1159201641830360단월면18088535072332150000
1160201641830370청운면19369385822092070000
1161201641830380양동면223710316642692730000
1162201641830395지평면335115649543944390000
1163201641830400용문면707028321713103014950000
1164201641830410개군면237910436703153510000