Overview

Dataset statistics

Number of variables11
Number of observations204
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory19.7 KiB
Average record size in memory98.6 B

Variable types

Numeric10
Categorical1

Dataset

Description시도별 주민등록인구 대비 장애인 비율현황
Author경기복지재단(경기도장애인복지종합지원센터)
URLhttps://data.gg.go.kr/portal/data/service/selectServicePage.do?&infId=GXZ3U52K0Y5C1LH4DUJT24771389&infSeq=1

Alerts

주민등록인구수(명) is highly overall correlated with 주민등록남성인구수(명) and 5 other fieldsHigh correlation
주민등록남성인구수(명) is highly overall correlated with 주민등록인구수(명) and 5 other fieldsHigh correlation
주민등록여성인구수(명) is highly overall correlated with 주민등록인구수(명) and 5 other fieldsHigh correlation
등록장애인수(명) is highly overall correlated with 주민등록인구수(명) and 5 other fieldsHigh correlation
등록장애인남성수(명) is highly overall correlated with 주민등록인구수(명) and 5 other fieldsHigh correlation
등록장애인여성수(명) is highly overall correlated with 주민등록인구수(명) and 5 other fieldsHigh correlation
등록장애인비율(%) is highly overall correlated with 등록장애인남성비율(%) and 2 other fieldsHigh correlation
등록장애인남성비율(%) is highly overall correlated with 등록장애인비율(%) and 2 other fieldsHigh correlation
등록장애인여성비율(%) is highly overall correlated with 등록장애인비율(%) and 2 other fieldsHigh correlation
시도명 is highly overall correlated with 주민등록인구수(명) and 8 other fieldsHigh correlation
주민등록인구수(명) has unique valuesUnique
주민등록남성인구수(명) has unique valuesUnique
주민등록여성인구수(명) has unique valuesUnique
등록장애인수(명) has unique valuesUnique
등록장애인여성수(명) has unique valuesUnique

Reproduction

Analysis started2024-04-14 03:19:23.293490
Analysis finished2024-04-14 03:19:32.733012
Duration9.44 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

기준년도
Real number (ℝ)

Distinct12
Distinct (%)5.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2017.5
Minimum2012
Maximum2023
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2024-04-14T12:19:32.936724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2012
5-th percentile2012
Q12014.75
median2017.5
Q32020.25
95-th percentile2023
Maximum2023
Range11
Interquartile range (IQR)5.5

Descriptive statistics

Standard deviation3.4605447
Coefficient of variation (CV)0.0017152638
Kurtosis-1.2171428
Mean2017.5
Median Absolute Deviation (MAD)3
Skewness0
Sum411570
Variance11.975369
MonotonicityDecreasing
2024-04-14T12:19:33.023870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
2023 17
8.3%
2022 17
8.3%
2021 17
8.3%
2020 17
8.3%
2019 17
8.3%
2018 17
8.3%
2017 17
8.3%
2016 17
8.3%
2015 17
8.3%
2014 17
8.3%
Other values (2) 34
16.7%
ValueCountFrequency (%)
2012 17
8.3%
2013 17
8.3%
2014 17
8.3%
2015 17
8.3%
2016 17
8.3%
2017 17
8.3%
2018 17
8.3%
2019 17
8.3%
2020 17
8.3%
2021 17
8.3%
ValueCountFrequency (%)
2023 17
8.3%
2022 17
8.3%
2021 17
8.3%
2020 17
8.3%
2019 17
8.3%
2018 17
8.3%
2017 17
8.3%
2016 17
8.3%
2015 17
8.3%
2014 17
8.3%

시도명
Categorical

HIGH CORRELATION 

Distinct17
Distinct (%)8.3%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
강원
 
12
경기
 
12
경남
 
12
경북
 
12
광주
 
12
Other values (12)
144 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row강원
2nd row경기
3rd row경남
4th row경북
5th row광주

Common Values

ValueCountFrequency (%)
강원 12
 
5.9%
경기 12
 
5.9%
경남 12
 
5.9%
경북 12
 
5.9%
광주 12
 
5.9%
대구 12
 
5.9%
대전 12
 
5.9%
부산 12
 
5.9%
서울 12
 
5.9%
세종 12
 
5.9%
Other values (7) 84
41.2%

Length

2024-04-14T12:19:33.113745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
강원 12
 
5.9%
세종 12
 
5.9%
충남 12
 
5.9%
제주 12
 
5.9%
전북 12
 
5.9%
전남 12
 
5.9%
인천 12
 
5.9%
울산 12
 
5.9%
서울 12
 
5.9%
경기 12
 
5.9%
Other values (7) 84
41.2%

주민등록인구수(명)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct204
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3028522.3
Minimum113117
Maximum13630821
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2024-04-14T12:19:33.213801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum113117
5-th percentile384031.1
Q11474380
median1886800
Q32955238
95-th percentile12213430
Maximum13630821
Range13517704
Interquartile range (IQR)1480858

Descriptive statistics

Standard deviation3213214.7
Coefficient of variation (CV)1.0609843
Kurtosis3.8358575
Mean3028522.3
Median Absolute Deviation (MAD)725994
Skewness2.2186852
Sum6.1781855 × 108
Variance1.0324749 × 1013
MonotonicityNot monotonic
2024-04-14T12:19:33.338330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1527807 1
 
0.5%
2487829 1
 
0.5%
1890630 1
 
0.5%
1852295 1
 
0.5%
636383 1
 
0.5%
2082200 1
 
0.5%
1580832 1
 
0.5%
1549507 1
 
0.5%
12522606 1
 
0.5%
3364702 1
 
0.5%
Other values (194) 194
95.1%
ValueCountFrequency (%)
113117 1
0.5%
122153 1
0.5%
156125 1
0.5%
210884 1
0.5%
242038 1
0.5%
280100 1
0.5%
314126 1
0.5%
340575 1
0.5%
355831 1
0.5%
371895 1
0.5%
ValueCountFrequency (%)
13630821 1
0.5%
13589432 1
0.5%
13565450 1
0.5%
13427014 1
0.5%
13239666 1
0.5%
13077153 1
0.5%
12873895 1
0.5%
12602784 1
0.5%
12522606 1
0.5%
12357830 1
0.5%

주민등록남성인구수(명)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct204
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1512037.1
Minimum57633
Maximum6855895
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2024-04-14T12:19:33.454503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum57633
5-th percentile191559.25
Q1731179
median944327
Q31481945.2
95-th percentile6148969.3
Maximum6855895
Range6798262
Interquartile range (IQR)750766.25

Descriptive statistics

Standard deviation1600228.8
Coefficient of variation (CV)1.0583264
Kurtosis4.0061422
Mean1512037.1
Median Absolute Deviation (MAD)349758
Skewness2.2447751
Sum3.0845557 × 108
Variance2.5607321 × 1012
MonotonicityNot monotonic
2024-04-14T12:19:33.573403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
768449 1
 
0.5%
1237291 1
 
0.5%
945654 1
 
0.5%
921415 1
 
0.5%
320091 1
 
0.5%
1057226 1
 
0.5%
797411 1
 
0.5%
781434 1
 
0.5%
6299812 1
 
0.5%
1694981 1
 
0.5%
Other values (194) 194
95.1%
ValueCountFrequency (%)
57633 1
0.5%
62205 1
0.5%
78862 1
0.5%
105752 1
0.5%
120995 1
0.5%
139734 1
0.5%
156831 1
0.5%
169845 1
0.5%
177568 1
0.5%
185678 1
0.5%
ValueCountFrequency (%)
6855895 1
0.5%
6839276 1
0.5%
6827298 1
0.5%
6754469 1
0.5%
6659995 1
0.5%
6577501 1
0.5%
6475323 1
0.5%
6333311 1
0.5%
6299812 1
0.5%
6219813 1
0.5%

주민등록여성인구수(명)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct204
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1516485.2
Minimum55484
Maximum6774926
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2024-04-14T12:19:33.690623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum55484
5-th percentile192471.85
Q1742654.75
median942523.5
Q31473292.8
95-th percentile6064461
Maximum6774926
Range6719442
Interquartile range (IQR)730638

Descriptive statistics

Standard deviation1613533.4
Coefficient of variation (CV)1.0639955
Kurtosis3.6790805
Mean1516485.2
Median Absolute Deviation (MAD)376814.5
Skewness2.1947399
Sum3.0936297 × 108
Variance2.6034902 × 1012
MonotonicityNot monotonic
2024-04-14T12:19:33.804659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
759358 1
 
0.5%
1250538 1
 
0.5%
944976 1
 
0.5%
930880 1
 
0.5%
316292 1
 
0.5%
1024974 1
 
0.5%
783421 1
 
0.5%
768073 1
 
0.5%
6222794 1
 
0.5%
1669721 1
 
0.5%
Other values (194) 194
95.1%
ValueCountFrequency (%)
55484 1
0.5%
59948 1
0.5%
77263 1
0.5%
105132 1
0.5%
121043 1
0.5%
140366 1
0.5%
157295 1
0.5%
170730 1
0.5%
178263 1
0.5%
186217 1
0.5%
ValueCountFrequency (%)
6774926 1
0.5%
6750156 1
0.5%
6738152 1
0.5%
6672545 1
0.5%
6579671 1
0.5%
6499652 1
0.5%
6398572 1
0.5%
6269473 1
0.5%
6222794 1
0.5%
6138017 1
0.5%

등록장애인수(명)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct204
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean150858.42
Minimum7081
Maximum586421
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2024-04-14T12:19:33.925202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7081
5-th percentile12875.15
Q171436.25
median129136
Q3169998.25
95-th percentile506322.25
Maximum586421
Range579340
Interquartile range (IQR)98562

Descriptive statistics

Standard deviation128818.83
Coefficient of variation (CV)0.85390546
Kurtosis3.3373367
Mean150858.42
Median Absolute Deviation (MAD)48309.5
Skewness1.935836
Sum30775117
Variance1.659429 × 1010
MonotonicityNot monotonic
2024-04-14T12:19:34.034418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
100520 1
 
0.5%
115694 1
 
0.5%
141578 1
 
0.5%
130345 1
 
0.5%
34278 1
 
0.5%
126406 1
 
0.5%
94688 1
 
0.5%
98324 1
 
0.5%
512882 1
 
0.5%
179070 1
 
0.5%
Other values (194) 194
95.1%
ValueCountFrequency (%)
7081 1
0.5%
7202 1
0.5%
7943 1
0.5%
9079 1
0.5%
9845 1
0.5%
10623 1
0.5%
11404 1
0.5%
12046 1
0.5%
12346 1
0.5%
12630 1
0.5%
ValueCountFrequency (%)
586421 1
0.5%
584834 1
0.5%
578668 1
0.5%
569726 1
0.5%
559878 1
0.5%
547386 1
0.5%
533259 1
0.5%
522437 1
0.5%
512882 1
0.5%
508330 1
0.5%

등록장애인남성수(명)
Real number (ℝ)

HIGH CORRELATION 

Distinct202
Distinct (%)99.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean87581.176
Minimum4141
Maximum349212
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2024-04-14T12:19:34.145906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4141
5-th percentile7719.25
Q141806
median71976
Q3100112.25
95-th percentile301976.2
Maximum349212
Range345071
Interquartile range (IQR)58306.25

Descriptive statistics

Standard deviation76330.822
Coefficient of variation (CV)0.8715437
Kurtosis3.584976
Mean87581.176
Median Absolute Deviation (MAD)29713.5
Skewness1.9989656
Sum17866560
Variance5.8263944 × 109
MonotonicityNot monotonic
2024-04-14T12:19:34.262646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
56117 2
 
1.0%
75683 2
 
1.0%
68376 1
 
0.5%
75500 1
 
0.5%
71020 1
 
0.5%
18822 1
 
0.5%
72848 1
 
0.5%
54283 1
 
0.5%
57441 1
 
0.5%
306117 1
 
0.5%
Other values (192) 192
94.1%
ValueCountFrequency (%)
4141 1
0.5%
4200 1
0.5%
4660 1
0.5%
5325 1
0.5%
5787 1
0.5%
6248 1
0.5%
6749 1
0.5%
7176 1
0.5%
7364 1
0.5%
7531 1
0.5%
ValueCountFrequency (%)
349212 1
0.5%
347994 1
0.5%
344091 1
0.5%
338704 1
0.5%
332872 1
0.5%
325883 1
0.5%
317854 1
0.5%
311539 1
0.5%
306117 1
0.5%
303157 1
0.5%

등록장애인여성수(명)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct204
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean63277.24
Minimum1483
Maximum237209
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2024-04-14T12:19:34.377468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1483
5-th percentile5093.9
Q130151.75
median53125
Q372329.75
95-th percentile204346.05
Maximum237209
Range235726
Interquartile range (IQR)42178

Descriptive statistics

Standard deviation52684.898
Coefficient of variation (CV)0.83260423
Kurtosis2.9296221
Mean63277.24
Median Absolute Deviation (MAD)21959
Skewness1.8218464
Sum12908557
Variance2.7756985 × 109
MonotonicityNot monotonic
2024-04-14T12:19:34.488261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
42348 1
 
0.5%
47318 1
 
0.5%
66078 1
 
0.5%
59325 1
 
0.5%
15456 1
 
0.5%
53558 1
 
0.5%
40405 1
 
0.5%
40883 1
 
0.5%
206765 1
 
0.5%
75052 1
 
0.5%
Other values (194) 194
95.1%
ValueCountFrequency (%)
1483 1
0.5%
2940 1
0.5%
3002 1
0.5%
3283 1
0.5%
3754 1
0.5%
4058 1
0.5%
4375 1
0.5%
4655 1
0.5%
4870 1
0.5%
4982 1
0.5%
ValueCountFrequency (%)
237209 1
0.5%
236840 1
0.5%
234577 1
0.5%
231022 1
0.5%
227006 1
0.5%
221503 1
0.5%
215405 1
0.5%
210898 1
0.5%
206765 1
0.5%
205173 1
0.5%

등록장애인비율(%)
Real number (ℝ)

HIGH CORRELATION 

Distinct43
Distinct (%)21.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.4014706
Minimum3.3
Maximum7.6
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2024-04-14T12:19:34.589362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.3
5-th percentile4
Q14.6
median5.3
Q36.2
95-th percentile7.5
Maximum7.6
Range4.3
Interquartile range (IQR)1.6

Descriptive statistics

Standard deviation1.0918632
Coefficient of variation (CV)0.20214185
Kurtosis-0.77765925
Mean5.4014706
Median Absolute Deviation (MAD)0.8
Skewness0.36450618
Sum1101.9
Variance1.1921653
MonotonicityNot monotonic
2024-04-14T12:19:34.691258image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
4.7 16
 
7.8%
4.8 13
 
6.4%
5.4 12
 
5.9%
4.6 9
 
4.4%
4.2 9
 
4.4%
4.1 9
 
4.4%
6.1 8
 
3.9%
4.3 7
 
3.4%
5.0 7
 
3.4%
5.3 7
 
3.4%
Other values (33) 107
52.5%
ValueCountFrequency (%)
3.3 1
 
0.5%
3.4 2
 
1.0%
3.5 2
 
1.0%
3.6 1
 
0.5%
3.7 1
 
0.5%
3.8 1
 
0.5%
3.9 2
 
1.0%
4.0 6
2.9%
4.1 9
4.4%
4.2 9
4.4%
ValueCountFrequency (%)
7.6 6
2.9%
7.5 6
2.9%
7.4 3
1.5%
7.3 1
 
0.5%
7.2 1
 
0.5%
7.1 2
 
1.0%
7.0 6
2.9%
6.9 3
1.5%
6.7 1
 
0.5%
6.6 4
2.0%

등록장애인남성비율(%)
Real number (ℝ)

HIGH CORRELATION 

Distinct46
Distinct (%)22.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.0480392
Minimum0.1
Maximum8.2
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2024-04-14T12:19:34.801732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.1
5-th percentile4.2
Q15.2
median5.9
Q37
95-th percentile8
Maximum8.2
Range8.1
Interquartile range (IQR)1.8

Descriptive statistics

Standard deviation1.2258489
Coefficient of variation (CV)0.20268534
Kurtosis1.6793851
Mean6.0480392
Median Absolute Deviation (MAD)0.9
Skewness-0.51221928
Sum1233.8
Variance1.5027055
MonotonicityNot monotonic
2024-04-14T12:19:35.090420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=46)
ValueCountFrequency (%)
5.5 12
 
5.9%
5.0 11
 
5.4%
6.9 10
 
4.9%
5.6 9
 
4.4%
5.8 9
 
4.4%
5.9 9
 
4.4%
6.0 8
 
3.9%
7.1 7
 
3.4%
4.9 7
 
3.4%
6.8 6
 
2.9%
Other values (36) 116
56.9%
ValueCountFrequency (%)
0.1 1
 
0.5%
2.8 1
 
0.5%
3.4 1
 
0.5%
3.5 2
1.0%
4.0 2
1.0%
4.1 2
1.0%
4.2 3
1.5%
4.3 1
 
0.5%
4.4 2
1.0%
4.5 1
 
0.5%
ValueCountFrequency (%)
8.2 3
1.5%
8.1 5
2.5%
8.0 5
2.5%
7.9 2
 
1.0%
7.8 4
2.0%
7.7 4
2.0%
7.6 6
2.9%
7.5 4
2.0%
7.4 5
2.5%
7.2 2
 
1.0%

등록장애인여성비율(%)
Real number (ℝ)

HIGH CORRELATION 

Distinct45
Distinct (%)22.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.6083333
Minimum0.1
Maximum7.2
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2024-04-14T12:19:35.214015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.1
5-th percentile3.3
Q13.8
median4.3
Q35.4
95-th percentile6.985
Maximum7.2
Range7.1
Interquartile range (IQR)1.6

Descriptive statistics

Standard deviation1.1665195
Coefficient of variation (CV)0.25313261
Kurtosis0.34599331
Mean4.6083333
Median Absolute Deviation (MAD)0.9
Skewness0.28490135
Sum940.1
Variance1.3607677
MonotonicityNot monotonic
2024-04-14T12:19:35.320106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
4.1 19
 
9.3%
3.4 14
 
6.9%
3.3 11
 
5.4%
4.9 11
 
5.4%
5.2 11
 
5.4%
5.4 11
 
5.4%
3.9 10
 
4.9%
3.8 9
 
4.4%
5.6 7
 
3.4%
4.2 7
 
3.4%
Other values (35) 94
46.1%
ValueCountFrequency (%)
0.1 1
 
0.5%
2.6 1
 
0.5%
2.7 2
 
1.0%
2.8 2
 
1.0%
3.0 1
 
0.5%
3.1 1
 
0.5%
3.2 1
 
0.5%
3.3 11
5.4%
3.4 14
6.9%
3.5 5
 
2.5%
ValueCountFrequency (%)
7.2 2
 
1.0%
7.1 5
2.5%
7.0 4
2.0%
6.9 1
 
0.5%
6.8 1
 
0.5%
6.7 3
1.5%
6.6 1
 
0.5%
6.5 1
 
0.5%
6.4 5
2.5%
6.3 1
 
0.5%

Interactions

2024-04-14T12:19:31.789296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-14T12:19:24.606607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-14T12:19:25.493062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-14T12:19:26.224875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-14T12:19:27.012100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-14T12:19:28.002669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-14T12:19:28.738859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-14T12:19:29.488575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-14T12:19:30.214531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-14T12:19:31.029820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-14T12:19:31.860744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-14T12:19:24.714078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-14T12:19:25.565232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-14T12:19:26.293765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-14T12:19:27.101193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-14T12:19:28.088310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-14T12:19:28.808908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-14T12:19:29.558155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-14T12:19:30.428610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-14T12:19:31.103807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-14T12:19:31.938832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-14T12:19:24.916419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-14T12:19:25.640842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-14T12:19:26.375736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-14T12:19:27.204382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-14T12:19:28.167755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-14T12:19:28.890635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-14T12:19:29.634255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-14T12:19:30.496644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-14T12:19:31.183923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-14T12:19:32.014763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-14T12:19:24.990263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-14T12:19:25.717466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-14T12:19:26.447531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-14T12:19:27.301192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-14T12:19:28.239867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-14T12:19:28.967405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-14T12:19:29.703917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-14T12:19:30.566831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-14T12:19:31.261260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-14T12:19:32.089076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-14T12:19:25.064038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-14T12:19:25.793367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-14T12:19:26.527393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-14T12:19:27.399421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-14T12:19:28.315186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-14T12:19:29.043704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-14T12:19:29.772883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-14T12:19:30.636354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-14T12:19:31.341818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-14T12:19:32.161385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-14T12:19:25.135155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-14T12:19:25.865844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-14T12:19:26.603523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-14T12:19:27.480071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-14T12:19:28.382846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-14T12:19:29.116132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-14T12:19:29.837703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-14T12:19:30.703330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-14T12:19:31.416811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-14T12:19:32.235008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-14T12:19:25.207349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-14T12:19:25.940588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-14T12:19:26.681571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-14T12:19:27.704999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-14T12:19:28.457686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-14T12:19:29.193897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-14T12:19:29.921595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-14T12:19:30.770603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-14T12:19:31.494121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-14T12:19:32.300651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-14T12:19:25.273582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-14T12:19:26.004871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-14T12:19:26.748517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-14T12:19:27.769819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-14T12:19:28.519724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-14T12:19:29.261392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-14T12:19:30.001449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-14T12:19:30.830659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-14T12:19:31.562683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-14T12:19:32.366903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-14T12:19:25.342527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-14T12:19:26.070769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-14T12:19:26.820544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-14T12:19:27.845410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-14T12:19:28.585199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-14T12:19:29.329676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-14T12:19:30.069129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-14T12:19:30.889283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-14T12:19:31.632671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-14T12:19:32.443402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-14T12:19:25.420002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-14T12:19:26.148413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-14T12:19:26.918092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-14T12:19:27.919963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-14T12:19:28.661615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-14T12:19:29.409000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-14T12:19:30.143629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-14T12:19:30.958124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-14T12:19:31.712589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-14T12:19:35.405208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기준년도시도명주민등록인구수(명)주민등록남성인구수(명)주민등록여성인구수(명)등록장애인수(명)등록장애인남성수(명)등록장애인여성수(명)등록장애인비율(%)등록장애인남성비율(%)등록장애인여성비율(%)
기준년도1.0000.0000.0000.0000.0000.0000.0000.0000.0000.1420.000
시도명0.0001.0000.9340.9370.9650.9520.9440.9530.9320.8520.936
주민등록인구수(명)0.0000.9341.0000.9970.9810.9670.9690.8860.7270.6000.649
주민등록남성인구수(명)0.0000.9370.9971.0000.9760.9650.9720.9030.7180.6080.657
주민등록여성인구수(명)0.0000.9650.9810.9761.0000.9100.9100.9200.7440.6050.683
등록장애인수(명)0.0000.9520.9670.9650.9101.0000.9950.9730.7710.5350.688
등록장애인남성수(명)0.0000.9440.9690.9720.9100.9951.0000.9460.7570.5310.639
등록장애인여성수(명)0.0000.9530.8860.9030.9200.9730.9461.0000.7440.5400.686
등록장애인비율(%)0.0000.9320.7270.7180.7440.7710.7570.7441.0000.8570.945
등록장애인남성비율(%)0.1420.8520.6000.6080.6050.5350.5310.5400.8571.0000.954
등록장애인여성비율(%)0.0000.9360.6490.6570.6830.6880.6390.6860.9450.9541.000
2024-04-14T12:19:35.524182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기준년도주민등록인구수(명)주민등록남성인구수(명)주민등록여성인구수(명)등록장애인수(명)등록장애인남성수(명)등록장애인여성수(명)등록장애인비율(%)등록장애인남성비율(%)등록장애인여성비율(%)시도명
기준년도1.000-0.027-0.025-0.0260.0580.0500.0550.0740.0000.0730.000
주민등록인구수(명)-0.0271.0001.0001.0000.9560.9750.927-0.091-0.029-0.1450.760
주민등록남성인구수(명)-0.0251.0001.0000.9990.9580.9760.927-0.089-0.027-0.1440.769
주민등록여성인구수(명)-0.0261.0000.9991.0000.9550.9740.926-0.094-0.030-0.1470.846
등록장애인수(명)0.0580.9560.9580.9551.0000.9910.9890.0650.1050.0170.811
등록장애인남성수(명)0.0500.9750.9760.9740.9911.0000.9670.0080.055-0.0430.788
등록장애인여성수(명)0.0550.9270.9270.9260.9890.9671.0000.1150.1480.0760.785
등록장애인비율(%)0.074-0.091-0.089-0.0940.0650.0080.1151.0000.9280.9890.713
등록장애인남성비율(%)0.000-0.029-0.027-0.0300.1050.0550.1480.9281.0000.9100.561
등록장애인여성비율(%)0.073-0.145-0.144-0.1470.017-0.0430.0760.9890.9101.0000.739
시도명0.0000.7600.7690.8460.8110.7880.7850.7130.5610.7391.000

Missing values

2024-04-14T12:19:32.550250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-14T12:19:32.672272image/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

기준년도시도명주민등록인구수(명)주민등록남성인구수(명)주민등록여성인구수(명)등록장애인수(명)등록장애인남성수(명)등록장애인여성수(명)등록장애인비율(%)등록장애인남성비율(%)등록장애인여성비율(%)
02023강원152780776844975935810052058172423486.67.65.6
12023경기13630821685589567749265864213492122372094.35.13.5
22023경남325115816369871614171188825109456793695.86.74.9
32023경북255432412902981264026178341100045782967.07.86.2
42023광주14192377008967183416931439427298874.95.64.2
52023대구23749601166803120815713052075407551135.56.54.6
62023대전14422167192927229247144041823296175.05.84.1
72023부산329336216054311687931175467103165723025.36.44.3
82023서울9386034454003148460033897952258451639504.25.03.4
92023세종38652519252419400112944785150933.34.12.6
기준년도시도명주민등록인구수(명)주민등록남성인구수(명)주민등록여성인구수(명)등록장애인수(명)등록장애인남성수(명)등록장애인여성수(명)등록장애인비율(%)등록장애인남성비율(%)등록장애인여성비율(%)
1942012부산353848417544791784005170743101764689794.85.83.9
1952012서울10195318504133651539824075282375381699904.04.73.3
1962012세종11311757633554847081414129406.37.25.3
1972012울산11472565904245568324898229829191534.35.13.4
1982012인천28439811431593141238813346781204522634.75.73.7
1992012전남190961895435495526414578878066677227.68.27.1
2002012전북187334193338693995513305472490605647.17.86.4
2012012제주5837132922132915003240517616147895.66.05.1
2022012충남20287771026812100196512487272284525886.27.05.2
2032012충북15656287892867763429413754138399996.06.95.2