Overview

Dataset statistics

Number of variables12
Number of observations124
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory13.1 KiB
Average record size in memory108.1 B

Variable types

Categorical6
Numeric6

Dataset

Description경기도_주민등록인구통계세대원수별세대수시군구별집계기본
Author경기도
URLhttps://data.gg.go.kr/portal/data/service/selectServicePage.do?&infId=EO0FK86PNBCZZBAB1IUB33781162&infSeq=1

Alerts

1인세대비율 has constant value ""Constant
2인세대비율 has constant value ""Constant
3인세대비율 has constant value ""Constant
4인이상세대비율 has constant value ""Constant
시군코드 is highly overall correlated with 시군명High correlation
총세대수 is highly overall correlated with 1인세대수 and 4 other fieldsHigh correlation
1인세대수 is highly overall correlated with 총세대수 and 4 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
시군명 is highly overall correlated with 시군코드 and 2 other fieldsHigh correlation
총세대수 has unique valuesUnique
1인세대수 has unique valuesUnique
2인세대수 has unique valuesUnique
3인세대수 has unique valuesUnique

Reproduction

Analysis started2023-12-10 21:41:10.899579
Analysis finished2023-12-10 21:41:14.557959
Duration3.66 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

기준년월
Categorical

Distinct2
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
2017
62 
2016
62 

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 (%)
2017 62
50.0%
2016 62
50.0%

Length

2023-12-11T06:41:14.610910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T06:41:14.688010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2017 62
50.0%
2016 62
50.0%

시군코드
Real number (ℝ)

HIGH CORRELATION 

Distinct31
Distinct (%)25.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4142.4194
Minimum4111
Maximum4183
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2023-12-11T06:41:14.771294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4111
5-th percentile4113
Q14125
median4141
Q34159
95-th percentile4182
Maximum4183
Range72
Interquartile range (IQR)34

Descriptive statistics

Standard deviation20.62562
Coefficient of variation (CV)0.0049791241
Kurtosis-0.83496947
Mean4142.4194
Median Absolute Deviation (MAD)16
Skewness0.34922085
Sum513660
Variance425.41621
MonotonicityNot monotonic
2023-12-11T06:41:14.874131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
4111 4
 
3.2%
4113 4
 
3.2%
4183 4
 
3.2%
4182 4
 
3.2%
4180 4
 
3.2%
4167 4
 
3.2%
4165 4
 
3.2%
4163 4
 
3.2%
4161 4
 
3.2%
4159 4
 
3.2%
Other values (21) 84
67.7%
ValueCountFrequency (%)
4111 4
3.2%
4113 4
3.2%
4115 4
3.2%
4117 4
3.2%
4119 4
3.2%
4121 4
3.2%
4122 4
3.2%
4125 4
3.2%
4127 4
3.2%
4128 4
3.2%
ValueCountFrequency (%)
4183 4
3.2%
4182 4
3.2%
4180 4
3.2%
4167 4
3.2%
4165 4
3.2%
4163 4
3.2%
4161 4
3.2%
4159 4
3.2%
4157 4
3.2%
4155 4
3.2%

시군명
Categorical

HIGH CORRELATION 

Distinct38
Distinct (%)30.6%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
파주시
 
4
구리시
 
4
화성시
 
4
의정부시
 
4
양평군
 
4
Other values (33)
104 

Length

Max length8
Median length3
Mean length3.3306452
Min length3

Unique

Unique7 ?
Unique (%)5.6%

Sample

1st row수원시
2nd row성남시
3rd row의정부시
4th row안양시
5th row부천시

Common Values

ValueCountFrequency (%)
파주시 4
 
3.2%
구리시 4
 
3.2%
화성시 4
 
3.2%
의정부시 4
 
3.2%
양평군 4
 
3.2%
가평군 4
 
3.2%
광주시 4
 
3.2%
평택시 4
 
3.2%
동두천시 4
 
3.2%
연천군 4
 
3.2%
Other values (28) 84
67.7%

Length

2023-12-11T06:41:14.988809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
파주시 4
 
3.1%
의왕시 4
 
3.1%
수원시 4
 
3.1%
용인시 4
 
3.1%
고양시 4
 
3.1%
성남시 4
 
3.1%
부천시 4
 
3.1%
안양시 4
 
3.1%
안산시 4
 
3.1%
오산시 4
 
3.1%
Other values (28) 91
69.5%

총세대수
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct124
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1050507.2
Minimum20903
Maximum5738319
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2023-12-11T06:41:15.096752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20903
5-th percentile42425.25
Q1127387.75
median382886
Q31522074
95-th percentile4392068.9
Maximum5738319
Range5717416
Interquartile range (IQR)1394686.2

Descriptive statistics

Standard deviation1382551.6
Coefficient of variation (CV)1.3160801
Kurtosis2.2168936
Mean1050507.2
Median Absolute Deviation (MAD)323438
Skewness1.7312406
Sum1.3026289 × 108
Variance1.911449 × 1012
MonotonicityNot monotonic
2023-12-11T06:41:15.216137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5738319 1
 
0.8%
84289 1
 
0.8%
50544 1
 
0.8%
29212 1
 
0.8%
21656 1
 
0.8%
47889 1
 
0.8%
68354 1
 
0.8%
80790 1
 
0.8%
131303 1
 
0.8%
243098 1
 
0.8%
Other values (114) 114
91.9%
ValueCountFrequency (%)
20903 1
0.8%
21585 1
0.8%
21656 1
0.8%
23454 1
0.8%
29212 1
0.8%
29840 1
0.8%
42420 1
0.8%
42455 1
0.8%
47889 1
0.8%
48892 1
0.8%
ValueCountFrequency (%)
5738319 1
0.8%
5619675 1
0.8%
4868548 1
0.8%
4766165 1
0.8%
4751240 1
0.8%
4731479 1
0.8%
4409014 1
0.8%
4296047 1
0.8%
3995603 1
0.8%
3951103 1
0.8%

1인세대수
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct124
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean336761.78
Minimum5603
Maximum1954951
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2023-12-11T06:41:15.343811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5603
5-th percentile16046.75
Q135077.25
median129765.5
Q3406522
95-th percentile1213555.2
Maximum1954951
Range1949348
Interquartile range (IQR)371444.75

Descriptive statistics

Standard deviation438092.01
Coefficient of variation (CV)1.3008959
Kurtosis2.7379407
Mean336761.78
Median Absolute Deviation (MAD)109701
Skewness1.7980357
Sum41758461
Variance1.9192461 × 1011
MonotonicityNot monotonic
2023-12-11T06:41:15.514549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1954951 1
 
0.8%
26868 1
 
0.8%
21088 1
 
0.8%
13273 1
 
0.8%
9884 1
 
0.8%
18252 1
 
0.8%
27937 1
 
0.8%
25199 1
 
0.8%
42513 1
 
0.8%
76822 1
 
0.8%
Other values (114) 114
91.9%
ValueCountFrequency (%)
5603 1
0.8%
6525 1
0.8%
9884 1
0.8%
9886 1
0.8%
13273 1
0.8%
13751 1
0.8%
15998 1
0.8%
16323 1
0.8%
16422 1
0.8%
16488 1
0.8%
ValueCountFrequency (%)
1954951 1
0.8%
1871169 1
0.8%
1626727 1
0.8%
1592519 1
0.8%
1486409 1
0.8%
1423905 1
0.8%
1215563 1
0.8%
1202178 1
0.8%
1200761 1
0.8%
1188523 1
0.8%

2인세대수
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct124
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean210232.06
Minimum3838
Maximum1050022
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2023-12-11T06:41:15.652822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3838
5-th percentile9762.65
Q126925.5
median79872.5
Q3316334.25
95-th percentile862408.4
Maximum1050022
Range1046184
Interquartile range (IQR)289408.75

Descriptive statistics

Standard deviation268180.43
Coefficient of variation (CV)1.2756401
Kurtosis1.8115898
Mean210232.06
Median Absolute Deviation (MAD)67279.5
Skewness1.6407532
Sum26068775
Variance7.1920744 × 1010
MonotonicityNot monotonic
2023-12-11T06:41:15.786954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1050022 1
 
0.8%
17793 1
 
0.8%
12778 1
 
0.8%
7092 1
 
0.8%
5111 1
 
0.8%
11534 1
 
0.8%
15299 1
 
0.8%
17973 1
 
0.8%
28400 1
 
0.8%
44006 1
 
0.8%
Other values (114) 114
91.9%
ValueCountFrequency (%)
3838 1
0.8%
4278 1
0.8%
5111 1
0.8%
5150 1
0.8%
7092 1
0.8%
7274 1
0.8%
9728 1
0.8%
9959 1
0.8%
11534 1
0.8%
11844 1
0.8%
ValueCountFrequency (%)
1050022 1
0.8%
1005094 1
0.8%
973082 1
0.8%
959162 1
0.8%
942924 1
0.8%
925768 1
0.8%
868028 1
0.8%
830564 1
0.8%
827123 1
0.8%
791784 1
0.8%

3인세대수
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct124
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean204118.42
Minimum2894
Maximum1089017
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2023-12-11T06:41:15.942215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2894
5-th percentile7197.2
Q126557
median76379.5
Q3305569.5
95-th percentile915442
Maximum1089017
Range1086123
Interquartile range (IQR)279012.5

Descriptive statistics

Standard deviation274869.98
Coefficient of variation (CV)1.3466202
Kurtosis2.1920544
Mean204118.42
Median Absolute Deviation (MAD)64717.5
Skewness1.7507264
Sum25310684
Variance7.5553504 × 1010
MonotonicityNot monotonic
2023-12-11T06:41:16.077719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1089017 1
 
0.8%
16907 1
 
0.8%
7190 1
 
0.8%
3997 1
 
0.8%
2897 1
 
0.8%
7699 1
 
0.8%
10829 1
 
0.8%
15413 1
 
0.8%
25972 1
 
0.8%
45031 1
 
0.8%
Other values (114) 114
91.9%
ValueCountFrequency (%)
2894 1
0.8%
2897 1
0.8%
3997 1
0.8%
4102 1
0.8%
4279 1
0.8%
4769 1
0.8%
7190 1
0.8%
7238 1
0.8%
7267 1
0.8%
7472 1
0.8%
ValueCountFrequency (%)
1089017 1
0.8%
1066457 1
0.8%
997375 1
0.8%
976403 1
0.8%
928428 1
0.8%
917520 1
0.8%
917158 1
0.8%
905718 1
0.8%
834067 1
0.8%
822890 1
0.8%

4인이상세대수
Real number (ℝ)

HIGH CORRELATION 

Distinct123
Distinct (%)99.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean299394.95
Minimum3655
Maximum1676955
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.2 KiB
2023-12-11T06:41:16.202789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3655
5-th percentile8795.3
Q135155.25
median106315.5
Q3413901.25
95-th percentile1273967.5
Maximum1676955
Range1673300
Interquartile range (IQR)378746

Descriptive statistics

Standard deviation408601.37
Coefficient of variation (CV)1.364757
Kurtosis2.3748549
Mean299394.95
Median Absolute Deviation (MAD)90234.5
Skewness1.7824684
Sum37124974
Variance1.6695508 × 1011
MonotonicityNot monotonic
2023-12-11T06:41:16.338206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
24484 2
 
1.6%
1644329 1
 
0.8%
18448 1
 
0.8%
3764 1
 
0.8%
10404 1
 
0.8%
14289 1
 
0.8%
22205 1
 
0.8%
34418 1
 
0.8%
77239 1
 
0.8%
41520 1
 
0.8%
Other values (113) 113
91.1%
ValueCountFrequency (%)
3655 1
0.8%
3764 1
0.8%
4713 1
0.8%
4850 1
0.8%
7183 1
0.8%
7882 1
0.8%
8735 1
0.8%
9137 1
0.8%
9405 1
0.8%
9488 1
0.8%
ValueCountFrequency (%)
1676955 1
0.8%
1644329 1
0.8%
1455904 1
0.8%
1450655 1
0.8%
1440089 1
0.8%
1411682 1
0.8%
1278516 1
0.8%
1248193 1
0.8%
1147906 1
0.8%
1118850 1
0.8%

1인세대비율
Categorical

CONSTANT 

Distinct1
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
0
124 

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 (%)
0 124
100.0%

Length

2023-12-11T06:41:16.460851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T06:41:16.549567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 124
100.0%

2인세대비율
Categorical

CONSTANT 

Distinct1
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
0
124 

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 (%)
0 124
100.0%

Length

2023-12-11T06:41:16.630794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T06:41:16.990060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 124
100.0%

3인세대비율
Categorical

CONSTANT 

Distinct1
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
0
124 

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 (%)
0 124
100.0%

Length

2023-12-11T06:41:17.072258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T06:41:17.164504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 124
100.0%

4인이상세대비율
Categorical

CONSTANT 

Distinct1
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
0
124 

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 (%)
0 124
100.0%

Length

2023-12-11T06:41:17.265114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T06:41:17.396271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 124
100.0%

Interactions

2023-12-11T06:41:13.872464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:41:11.257969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:41:11.789674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:41:12.273419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:41:13.032155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:41:13.453632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:41:13.948082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:41:11.338933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:41:11.870563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:41:12.366598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:41:13.112306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:41:13.523509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:41:14.020091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:41:11.433451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:41:11.945191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:41:12.450322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:41:13.185911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:41:13.595064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:41:14.105376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:41:11.548127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:41:12.028359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:41:12.540969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:41:13.259128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:41:13.673697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:41:14.184648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:41:11.626082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:41:12.101874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:41:12.624821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:41:13.321771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:41:13.739582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:41:14.262764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:41:11.703125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:41:12.182190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:41:12.717391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:41:13.387037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T06:41:13.804086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T06:41:17.456106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기준년월시군코드시군명총세대수1인세대수2인세대수3인세대수4인이상세대수
기준년월1.0000.0000.0000.0000.0000.0000.0000.000
시군코드0.0001.0001.0000.5240.6440.2460.3910.512
시군명0.0001.0001.0000.8930.8960.8310.8480.889
총세대수0.0000.5240.8931.0000.9870.9740.9580.995
1인세대수0.0000.6440.8960.9871.0000.9560.8980.983
2인세대수0.0000.2460.8310.9740.9561.0000.9280.967
3인세대수0.0000.3910.8480.9580.8980.9281.0000.962
4인이상세대수0.0000.5120.8890.9950.9830.9670.9621.000
2023-12-11T06:41:17.566111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군명기준년월
시군명1.0000.000
기준년월0.0001.000
2023-12-11T06:41:17.651171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군코드총세대수1인세대수2인세대수3인세대수4인이상세대수기준년월시군명
시군코드1.000-0.309-0.284-0.286-0.345-0.3450.0000.865
총세대수-0.3091.0000.9950.9980.9970.9940.0000.501
1인세대수-0.2840.9951.0000.9950.9870.9830.0000.508
2인세대수-0.2860.9980.9951.0000.9940.9880.0000.409
3인세대수-0.3450.9970.9870.9941.0000.9960.0000.445
4인이상세대수-0.3450.9940.9830.9880.9961.0000.0000.494
기준년월0.0000.0000.0000.0000.0000.0001.0000.000
시군명0.8650.5010.5080.4090.4450.4940.0001.000

Missing values

2023-12-11T06:41:14.376569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T06:41:14.506935image/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

기준년월시군코드시군명총세대수1인세대수2인세대수3인세대수4인이상세대수1인세대비율2인세대비율3인세대비율4인이상세대비율
020174111수원시573831919549511050022108901716443290000
120174113성남시4751240162672795916291715812481930000
220174115의정부시21299796963334594264228055514150000
320174117안양시26982757400435499305795518287510000
420174119부천시3995603121556382712383406711188500000
520174121광명시15209554133053195063231254650190000
620174122평택시24088099171194823284117765975860000
720174125동두천시508424196178117916873621069680000
820174127안산시335446612021786280666194349047880000
920174128고양시4868548148640997308299737514116820000
기준년월시군코드시군명총세대수1인세대수2인세대수3인세대수4인이상세대수1인세대비율2인세대비율3인세대비율4인이상세대비율
11420174155안성시77456291801738113022178730000
11520174157김포시152052451123220430974437620000
11620174159화성시269782881004963550363816840000
11720174161광주시140112458043120027707354010000
11820174163양주시85089274291940816130221220000
11920174165포천시68779286801572610825135480000
12020174167여주시4889219041119687806100770000
12120174180연천군2158598865150289436550000
12220174182가평군29840137517274410247130000
12320174183양평군531862275413555747294050000