Overview

Dataset statistics

Number of variables11
Number of observations341
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory32.8 KiB
Average record size in memory98.4 B

Variable types

Numeric10
Categorical1

Dataset

Description기초생활보장 장애인 장애정도별 수급자현황
Author경기복지재단(경기도장애인복지종합지원센터)
URLhttps://data.gg.go.kr/portal/data/service/selectServicePage.do?&infId=RTQ7W2R8684T15BUSC6S25625605&infSeq=1

Alerts

기준년도 is highly overall correlated with 1급인원수(명) and 7 other fieldsHigh correlation
1급인원수(명) is highly overall correlated with 기준년도 and 7 other fieldsHigh correlation
2급인원수(명) is highly overall correlated with 기준년도 and 7 other fieldsHigh correlation
3급인원수(명) is highly overall correlated with 기준년도 and 7 other fieldsHigh correlation
4급인원수(명) is highly overall correlated with 기준년도 and 7 other fieldsHigh correlation
5급인원수(명) is highly overall correlated with 기준년도 and 7 other fieldsHigh correlation
6급인원수(명) is highly overall correlated with 기준년도 and 7 other fieldsHigh correlation
심한 장애인수급자수(명) is highly overall correlated with 기준년도 and 7 other fieldsHigh correlation
심하지 않은 장애인수급자수(명) is highly overall correlated with 기준년도 and 7 other fieldsHigh correlation
1급인원수(명) has 155 (45.5%) zerosZeros
2급인원수(명) has 155 (45.5%) zerosZeros
3급인원수(명) has 155 (45.5%) zerosZeros
4급인원수(명) has 155 (45.5%) zerosZeros
5급인원수(명) has 155 (45.5%) zerosZeros
6급인원수(명) has 155 (45.5%) zerosZeros
심한 장애인수급자수(명) has 186 (54.5%) zerosZeros
심하지 않은 장애인수급자수(명) has 186 (54.5%) zerosZeros

Reproduction

Analysis started2024-03-12 23:21:39.439212
Analysis finished2024-03-12 23:21:48.015078
Duration8.58 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

기준년도
Real number (ℝ)

HIGH CORRELATION 

Distinct11
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2018
Minimum2013
Maximum2023
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.1 KiB
2024-03-13T08:21:48.066233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2013
5-th percentile2013
Q12015
median2018
Q32021
95-th percentile2023
Maximum2023
Range10
Interquartile range (IQR)6

Descriptive statistics

Standard deviation3.1669247
Coefficient of variation (CV)0.0015693383
Kurtosis-1.2202754
Mean2018
Median Absolute Deviation (MAD)3
Skewness0
Sum688138
Variance10.029412
MonotonicityDecreasing
2024-03-13T08:21:48.155671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
2023 31
9.1%
2022 31
9.1%
2021 31
9.1%
2020 31
9.1%
2019 31
9.1%
2018 31
9.1%
2017 31
9.1%
2016 31
9.1%
2015 31
9.1%
2014 31
9.1%
ValueCountFrequency (%)
2013 31
9.1%
2014 31
9.1%
2015 31
9.1%
2016 31
9.1%
2017 31
9.1%
2018 31
9.1%
2019 31
9.1%
2020 31
9.1%
2021 31
9.1%
2022 31
9.1%
ValueCountFrequency (%)
2023 31
9.1%
2022 31
9.1%
2021 31
9.1%
2020 31
9.1%
2019 31
9.1%
2018 31
9.1%
2017 31
9.1%
2016 31
9.1%
2015 31
9.1%
2014 31
9.1%

시군명
Categorical

Distinct31
Distinct (%)9.1%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
가평군
 
11
고양시
 
11
과천시
 
11
광명시
 
11
광주시
 
11
Other values (26)
286 

Length

Max length4
Median length3
Mean length3.0967742
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row가평군
2nd row고양시
3rd row과천시
4th row광명시
5th row광주시

Common Values

ValueCountFrequency (%)
가평군 11
 
3.2%
고양시 11
 
3.2%
과천시 11
 
3.2%
광명시 11
 
3.2%
광주시 11
 
3.2%
구리시 11
 
3.2%
군포시 11
 
3.2%
김포시 11
 
3.2%
남양주시 11
 
3.2%
동두천시 11
 
3.2%
Other values (21) 231
67.7%

Length

2024-03-13T08:21:48.246757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
가평군 11
 
3.2%
안양시 11
 
3.2%
하남시 11
 
3.2%
포천시 11
 
3.2%
평택시 11
 
3.2%
파주시 11
 
3.2%
이천시 11
 
3.2%
의정부시 11
 
3.2%
의왕시 11
 
3.2%
용인시 11
 
3.2%
Other values (21) 231
67.7%

합계(명)
Real number (ℝ)

Distinct328
Distinct (%)96.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2355.8211
Minimum173
Maximum7535
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.1 KiB
2024-03-13T08:21:48.355428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum173
5-th percentile544
Q11128
median1744
Q33186
95-th percentile6144
Maximum7535
Range7362
Interquartile range (IQR)2058

Descriptive statistics

Standard deviation1696.1036
Coefficient of variation (CV)0.71996282
Kurtosis0.57462891
Mean2355.8211
Median Absolute Deviation (MAD)820
Skewness1.150189
Sum803335
Variance2876767.5
MonotonicityNot monotonic
2024-03-13T08:21:48.470845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
850 2
 
0.6%
633 2
 
0.6%
1176 2
 
0.6%
1447 2
 
0.6%
1848 2
 
0.6%
1506 2
 
0.6%
2644 2
 
0.6%
1744 2
 
0.6%
937 2
 
0.6%
1128 2
 
0.6%
Other values (318) 321
94.1%
ValueCountFrequency (%)
173 1
0.3%
179 1
0.3%
186 1
0.3%
192 1
0.3%
198 1
0.3%
214 1
0.3%
217 1
0.3%
220 1
0.3%
221 1
0.3%
237 1
0.3%
ValueCountFrequency (%)
7535 1
0.3%
7360 1
0.3%
7206 1
0.3%
7047 1
0.3%
7034 1
0.3%
7006 1
0.3%
6968 1
0.3%
6807 1
0.3%
6797 1
0.3%
6738 1
0.3%

1급인원수(명)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct153
Distinct (%)44.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean148.71554
Minimum0
Maximum819
Zeros155
Zeros (%)45.5%
Negative0
Negative (%)0.0%
Memory size3.1 KiB
2024-03-13T08:21:48.587307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median77
Q3243
95-th percentile597
Maximum819
Range819
Interquartile range (IQR)243

Descriptive statistics

Standard deviation189.9668
Coefficient of variation (CV)1.2773837
Kurtosis1.2137916
Mean148.71554
Median Absolute Deviation (MAD)77
Skewness1.3692291
Sum50712
Variance36087.386
MonotonicityNot monotonic
2024-03-13T08:21:48.687713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 155
45.5%
20 4
 
1.2%
153 3
 
0.9%
180 3
 
0.9%
243 3
 
0.9%
156 3
 
0.9%
138 2
 
0.6%
270 2
 
0.6%
217 2
 
0.6%
155 2
 
0.6%
Other values (143) 162
47.5%
ValueCountFrequency (%)
0 155
45.5%
17 1
 
0.3%
20 4
 
1.2%
27 1
 
0.3%
60 1
 
0.3%
63 1
 
0.3%
65 1
 
0.3%
73 1
 
0.3%
74 2
 
0.6%
75 2
 
0.6%
ValueCountFrequency (%)
819 1
0.3%
768 1
0.3%
714 1
0.3%
706 1
0.3%
701 1
0.3%
681 1
0.3%
665 1
0.3%
659 1
0.3%
645 1
0.3%
639 1
0.3%

2급인원수(명)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct164
Distinct (%)48.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean241.76833
Minimum0
Maximum1303
Zeros155
Zeros (%)45.5%
Negative0
Negative (%)0.0%
Memory size3.1 KiB
2024-03-13T08:21:48.791579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median130
Q3373
95-th percentile978
Maximum1303
Range1303
Interquartile range (IQR)373

Descriptive statistics

Standard deviation313.09534
Coefficient of variation (CV)1.2950221
Kurtosis1.1669939
Mean241.76833
Median Absolute Deviation (MAD)130
Skewness1.3906408
Sum82443
Variance98028.69
MonotonicityNot monotonic
2024-03-13T08:21:48.909700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 155
45.5%
40 3
 
0.9%
224 3
 
0.9%
251 2
 
0.6%
141 2
 
0.6%
232 2
 
0.6%
597 2
 
0.6%
237 2
 
0.6%
493 2
 
0.6%
246 2
 
0.6%
Other values (154) 166
48.7%
ValueCountFrequency (%)
0 155
45.5%
38 1
 
0.3%
39 1
 
0.3%
40 3
 
0.9%
42 1
 
0.3%
98 1
 
0.3%
103 1
 
0.3%
112 1
 
0.3%
118 1
 
0.3%
119 1
 
0.3%
ValueCountFrequency (%)
1303 1
0.3%
1180 1
0.3%
1172 1
0.3%
1153 1
0.3%
1143 1
0.3%
1104 1
0.3%
1102 1
0.3%
1086 1
0.3%
1082 1
0.3%
1069 1
0.3%

3급인원수(명)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct166
Distinct (%)48.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean296.37243
Minimum0
Maximum1543
Zeros155
Zeros (%)45.5%
Negative0
Negative (%)0.0%
Memory size3.1 KiB
2024-03-13T08:21:49.011167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median166
Q3450
95-th percentile1199
Maximum1543
Range1543
Interquartile range (IQR)450

Descriptive statistics

Standard deviation386.99598
Coefficient of variation (CV)1.3057759
Kurtosis1.3765507
Mean296.37243
Median Absolute Deviation (MAD)166
Skewness1.4453916
Sum101063
Variance149765.89
MonotonicityNot monotonic
2024-03-13T08:21:49.148435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 155
45.5%
166 3
 
0.9%
202 3
 
0.9%
350 3
 
0.9%
325 3
 
0.9%
417 2
 
0.6%
860 2
 
0.6%
144 2
 
0.6%
282 2
 
0.6%
289 2
 
0.6%
Other values (156) 164
48.1%
ValueCountFrequency (%)
0 155
45.5%
49 1
 
0.3%
53 1
 
0.3%
54 2
 
0.6%
60 1
 
0.3%
69 1
 
0.3%
127 1
 
0.3%
136 1
 
0.3%
143 1
 
0.3%
144 2
 
0.6%
ValueCountFrequency (%)
1543 1
0.3%
1527 1
0.3%
1521 1
0.3%
1442 1
0.3%
1417 1
0.3%
1411 1
0.3%
1388 1
0.3%
1379 1
0.3%
1360 1
0.3%
1358 1
0.3%

4급인원수(명)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct149
Distinct (%)43.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean125.78299
Minimum0
Maximum799
Zeros155
Zeros (%)45.5%
Negative0
Negative (%)0.0%
Memory size3.1 KiB
2024-03-13T08:21:49.262345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median75
Q3186
95-th percentile516
Maximum799
Range799
Interquartile range (IQR)186

Descriptive statistics

Standard deviation167.99377
Coefficient of variation (CV)1.3355841
Kurtosis1.8627353
Mean125.78299
Median Absolute Deviation (MAD)75
Skewness1.5552989
Sum42892
Variance28221.906
MonotonicityNot monotonic
2024-03-13T08:21:49.567868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 155
45.5%
85 4
 
1.2%
83 3
 
0.9%
516 3
 
0.9%
153 3
 
0.9%
93 3
 
0.9%
178 3
 
0.9%
168 3
 
0.9%
195 2
 
0.6%
169 2
 
0.6%
Other values (139) 160
46.9%
ValueCountFrequency (%)
0 155
45.5%
21 1
 
0.3%
22 1
 
0.3%
24 1
 
0.3%
25 1
 
0.3%
26 1
 
0.3%
28 1
 
0.3%
41 1
 
0.3%
43 1
 
0.3%
50 1
 
0.3%
ValueCountFrequency (%)
799 1
0.3%
693 1
0.3%
646 1
0.3%
636 1
0.3%
630 1
0.3%
621 1
0.3%
611 1
0.3%
605 1
0.3%
601 1
0.3%
583 1
0.3%

5급인원수(명)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct143
Distinct (%)41.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean121.35191
Minimum0
Maximum806
Zeros155
Zeros (%)45.5%
Negative0
Negative (%)0.0%
Memory size3.1 KiB
2024-03-13T08:21:49.690682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median78
Q3175
95-th percentile477
Maximum806
Range806
Interquartile range (IQR)175

Descriptive statistics

Standard deviation161.65881
Coefficient of variation (CV)1.3321489
Kurtosis2.3402262
Mean121.35191
Median Absolute Deviation (MAD)78
Skewness1.619108
Sum41381
Variance26133.57
MonotonicityNot monotonic
2024-03-13T08:21:49.803720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 155
45.5%
166 4
 
1.2%
108 3
 
0.9%
160 3
 
0.9%
84 3
 
0.9%
98 3
 
0.9%
99 3
 
0.9%
67 3
 
0.9%
138 3
 
0.9%
126 3
 
0.9%
Other values (133) 158
46.3%
ValueCountFrequency (%)
0 155
45.5%
20 1
 
0.3%
21 1
 
0.3%
22 1
 
0.3%
24 1
 
0.3%
27 1
 
0.3%
30 1
 
0.3%
48 1
 
0.3%
52 1
 
0.3%
54 1
 
0.3%
ValueCountFrequency (%)
806 1
0.3%
760 1
0.3%
693 1
0.3%
621 1
0.3%
596 1
0.3%
588 1
0.3%
579 1
0.3%
571 1
0.3%
570 1
0.3%
554 1
0.3%

6급인원수(명)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct141
Distinct (%)41.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean117.78592
Minimum0
Maximum800
Zeros155
Zeros (%)45.5%
Negative0
Negative (%)0.0%
Memory size3.1 KiB
2024-03-13T08:21:49.911574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median59
Q3172
95-th percentile488
Maximum800
Range800
Interquartile range (IQR)172

Descriptive statistics

Standard deviation158.27832
Coefficient of variation (CV)1.3437796
Kurtosis2.1558462
Mean117.78592
Median Absolute Deviation (MAD)59
Skewness1.5985596
Sum40165
Variance25052.028
MonotonicityNot monotonic
2024-03-13T08:21:50.018004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 155
45.5%
184 4
 
1.2%
123 4
 
1.2%
112 3
 
0.9%
151 3
 
0.9%
24 3
 
0.9%
172 3
 
0.9%
103 3
 
0.9%
84 3
 
0.9%
366 3
 
0.9%
Other values (131) 157
46.0%
ValueCountFrequency (%)
0 155
45.5%
22 1
 
0.3%
24 3
 
0.9%
26 1
 
0.3%
30 1
 
0.3%
33 1
 
0.3%
34 1
 
0.3%
43 1
 
0.3%
51 1
 
0.3%
55 1
 
0.3%
ValueCountFrequency (%)
800 1
0.3%
649 1
0.3%
646 1
0.3%
627 1
0.3%
620 1
0.3%
600 1
0.3%
589 1
0.3%
566 1
0.3%
541 1
0.3%
524 1
0.3%

심한 장애인수급자수(명)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct149
Distinct (%)43.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean761.02346
Minimum0
Maximum4210
Zeros186
Zeros (%)54.5%
Negative0
Negative (%)0.0%
Memory size3.1 KiB
2024-03-13T08:21:50.126896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31201
95-th percentile3608
Maximum4210
Range4210
Interquartile range (IQR)1201

Descriptive statistics

Standard deviation1120.339
Coefficient of variation (CV)1.4721478
Kurtosis1.4544968
Mean761.02346
Median Absolute Deviation (MAD)0
Skewness1.5354472
Sum259509
Variance1255159.4
MonotonicityNot monotonic
2024-03-13T08:21:50.231353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 186
54.5%
895 2
 
0.6%
2393 2
 
0.6%
1132 2
 
0.6%
793 2
 
0.6%
1201 2
 
0.6%
771 2
 
0.6%
781 2
 
0.6%
1664 1
 
0.3%
1027 1
 
0.3%
Other values (139) 139
40.8%
ValueCountFrequency (%)
0 186
54.5%
127 1
 
0.3%
130 1
 
0.3%
133 1
 
0.3%
139 1
 
0.3%
141 1
 
0.3%
386 1
 
0.3%
394 1
 
0.3%
398 1
 
0.3%
399 1
 
0.3%
ValueCountFrequency (%)
4210 1
0.3%
4116 1
0.3%
4106 1
0.3%
4058 1
0.3%
4044 1
0.3%
4043 1
0.3%
3952 1
0.3%
3948 1
0.3%
3904 1
0.3%
3818 1
0.3%

심하지 않은 장애인수급자수(명)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct151
Distinct (%)44.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean543.02053
Minimum0
Maximum3419
Zeros186
Zeros (%)54.5%
Negative0
Negative (%)0.0%
Memory size3.1 KiB
2024-03-13T08:21:50.330873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q3794
95-th percentile2497
Maximum3419
Range3419
Interquartile range (IQR)794

Descriptive statistics

Standard deviation819.46917
Coefficient of variation (CV)1.5090943
Kurtosis1.9078103
Mean543.02053
Median Absolute Deviation (MAD)0
Skewness1.6457008
Sum185170
Variance671529.71
MonotonicityNot monotonic
2024-03-13T08:21:50.445428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 186
54.5%
1276 2
 
0.6%
448 2
 
0.6%
331 2
 
0.6%
563 2
 
0.6%
680 2
 
0.6%
389 1
 
0.3%
2234 1
 
0.3%
1054 1
 
0.3%
1830 1
 
0.3%
Other values (141) 141
41.3%
ValueCountFrequency (%)
0 186
54.5%
87 1
 
0.3%
90 1
 
0.3%
91 1
 
0.3%
96 1
 
0.3%
103 1
 
0.3%
282 1
 
0.3%
296 1
 
0.3%
311 1
 
0.3%
317 1
 
0.3%
ValueCountFrequency (%)
3419 1
0.3%
3199 1
0.3%
3162 1
0.3%
3150 1
0.3%
3143 1
0.3%
2992 1
0.3%
2976 1
0.3%
2963 1
0.3%
2920 1
0.3%
2862 1
0.3%

Interactions

2024-03-13T08:21:47.044873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:21:39.779565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:21:40.464736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:21:41.198065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:21:42.107851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:21:43.091804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:21:43.914109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:21:44.667942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:21:45.458053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:21:46.392072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:21:47.110789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:21:39.837784image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:21:40.530897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:21:41.264255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:21:42.189894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:21:43.188995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:21:43.994266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:21:44.734136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:21:45.524901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:21:46.452471image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:21:47.182340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:21:39.907360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:21:40.599227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:21:41.332137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:21:42.281551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:21:43.295839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:21:44.067561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:21:44.804993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:21:45.595359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:21:46.517911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:21:47.246934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:21:39.970755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:21:40.663464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:21:41.387139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:21:42.368704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:21:43.370417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:21:44.133994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:21:44.868366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:21:45.665267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:21:46.577101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:21:47.324310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:21:40.035021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:21:40.736094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:21:41.450241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:21:42.458493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:21:43.449646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:21:44.202970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:21:44.937237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:21:45.732645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:21:46.641598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:21:47.415689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:21:40.103979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:21:40.830621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:21:41.522414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:21:42.556211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:21:43.529402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:21:44.293016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:21:45.012442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:21:45.806906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:21:46.711001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:21:47.516254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:21:40.180802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:21:40.912192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:21:41.596217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:21:42.649259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:21:43.616334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:21:44.375185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:21:45.088362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:21:45.884618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:21:46.778359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:21:47.593287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:21:40.256299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:21:40.986460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:21:41.665246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:21:42.741472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:21:43.692037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:21:44.454841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:21:45.197283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:21:45.960961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:21:46.849103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:21:47.670762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:21:40.326188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:21:41.058114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:21:41.734040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:21:42.831134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:21:43.766593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:21:44.530346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:21:45.311532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:21:46.034354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:21:46.919197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:21:47.736297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:21:40.393202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:21:41.121303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:21:42.013302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:21:42.952458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:21:43.833534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:21:44.596020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:21:45.383675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:21:46.317490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:21:46.977111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-13T08:21:50.529913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기준년도시군명합계(명)1급인원수(명)2급인원수(명)3급인원수(명)4급인원수(명)5급인원수(명)6급인원수(명)심한 장애인수급자수(명)심하지 않은 장애인수급자수(명)
기준년도1.0000.0000.3190.7280.7190.7290.7230.7110.7040.6900.720
시군명0.0001.0000.8150.7610.7600.7490.7520.6800.6170.7750.626
합계(명)0.3190.8151.0000.8270.8950.8820.8760.8200.8570.9150.932
1급인원수(명)0.7280.7610.8271.0000.9630.9570.9550.9540.9370.6180.611
2급인원수(명)0.7190.7600.8950.9631.0000.9820.9790.9520.9540.6180.611
3급인원수(명)0.7290.7490.8820.9570.9821.0000.9760.9650.9530.6290.622
4급인원수(명)0.7230.7520.8760.9550.9790.9761.0000.9720.9710.6180.611
5급인원수(명)0.7110.6800.8200.9540.9520.9650.9721.0000.9760.6070.600
6급인원수(명)0.7040.6170.8570.9370.9540.9530.9710.9761.0000.5840.576
심한 장애인수급자수(명)0.6900.7750.9150.6180.6180.6290.6180.6070.5841.0000.958
심하지 않은 장애인수급자수(명)0.7200.6260.9320.6110.6110.6220.6110.6000.5760.9581.000
2024-03-13T08:21:50.647518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기준년도합계(명)1급인원수(명)2급인원수(명)3급인원수(명)4급인원수(명)5급인원수(명)6급인원수(명)심한 장애인수급자수(명)심하지 않은 장애인수급자수(명)시군명
기준년도1.0000.296-0.768-0.765-0.757-0.759-0.750-0.7450.8270.8340.000
합계(명)0.2961.0000.0510.0560.0560.0540.0530.0520.4670.4670.437
1급인원수(명)-0.7680.0511.0000.9970.9940.9920.9910.989-0.854-0.8540.375
2급인원수(명)-0.7650.0560.9971.0000.9970.9960.9940.994-0.854-0.8540.374
3급인원수(명)-0.7570.0560.9940.9971.0000.9970.9960.995-0.854-0.8540.363
4급인원수(명)-0.7590.0540.9920.9960.9971.0000.9970.995-0.854-0.8540.366
5급인원수(명)-0.7500.0530.9910.9940.9960.9971.0000.998-0.854-0.8540.303
6급인원수(명)-0.7450.0520.9890.9940.9950.9950.9981.000-0.854-0.8540.262
심한 장애인수급자수(명)0.8270.467-0.854-0.854-0.854-0.854-0.854-0.8541.0000.9980.390
심하지 않은 장애인수급자수(명)0.8340.467-0.854-0.854-0.854-0.854-0.854-0.8540.9981.0000.265
시군명0.0000.4370.3750.3740.3630.3660.3030.2620.3900.2651.000

Missing values

2024-03-13T08:21:47.835593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-13T08:21:47.960407image/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

기준년도시군명합계(명)1급인원수(명)2급인원수(명)3급인원수(명)4급인원수(명)5급인원수(명)6급인원수(명)심한 장애인수급자수(명)심하지 않은 장애인수급자수(명)
02023가평군860000000471389
12023고양시736000000042103150
22023과천시242000000139103
32023광명시22070000001304903
42023광주시21100000001228882
52023구리시1570000000824746
62023군포시237300000013261047
72023김포시306800000016601408
82023남양주시551700000030202497
92023동두천시1686000000916770
기준년도시군명합계(명)1급인원수(명)2급인원수(명)3급인원수(명)4급인원수(명)5급인원수(명)6급인원수(명)심한 장애인수급자수(명)심하지 않은 장애인수급자수(명)
3312013오산시7089817920486786300
3322013용인시166928443947416216114900
3332013의왕시4788612813643523300
3342013의정부시261838360572132928729300
3352013이천시100613823730310611810400
3362013파주시199031249353126420318700
3372013평택시225331353564724724326800
3382013포천시145224336738916313915100
3392013하남시63311414716683675600
3402013화성시136523034039314613312300