Overview

Dataset statistics

Number of variables12
Number of observations341
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory35.8 KiB
Average record size in memory107.4 B

Variable types

Numeric11
Categorical1

Dataset

Description기초생활보장 장애인 연령별 수급자현황
Author경기복지재단(경기도장애인복지종합지원센터)
URLhttps://data.gg.go.kr/portal/data/service/selectServicePage.do?&infId=B4PIQYODUV0AU8076PVQ25441769&infSeq=1

Alerts

기준년도 is highly overall correlated with 80세이상수급자수(명)High correlation
총계(명) is highly overall correlated with 10세미만수급자수(명) and 8 other fieldsHigh correlation
10세미만수급자수(명) is highly overall correlated with 총계(명) and 8 other fieldsHigh correlation
10대수급자수(10세~19세)(명) is highly overall correlated with 총계(명) and 9 other fieldsHigh correlation
20대수급자수(20세~29세)(명) is highly overall correlated with 총계(명) and 9 other fieldsHigh correlation
30대수급자수(30세~39세)(명) is highly overall correlated with 총계(명) and 8 other fieldsHigh correlation
40대수급자수(40세~49세)(명) is highly overall correlated with 총계(명) and 9 other fieldsHigh correlation
50대수급자수(50세~59세)(명) is highly overall correlated with 총계(명) and 9 other fieldsHigh correlation
60대수급자수(60세~69세)(명) is highly overall correlated with 총계(명) and 8 other fieldsHigh correlation
70대수급자수(70세~79세)(명) is highly overall correlated with 총계(명) and 8 other fieldsHigh correlation
80세이상수급자수(명) is highly overall correlated with 기준년도 and 9 other fieldsHigh correlation
시군명 is highly overall correlated with 10대수급자수(10세~19세)(명) and 3 other fieldsHigh correlation

Reproduction

Analysis started2024-03-12 23:30:26.351011
Analysis finished2024-03-12 23:30:36.203458
Duration9.85 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
2024-03-13T08:30:36.244342image/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
2024-03-13T08:30:36.322742image/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

HIGH CORRELATION 

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

2024-03-13T08:30:36.429703image/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%

총계(명)
Real number (ℝ)

HIGH CORRELATION 

Distinct329
Distinct (%)96.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2353.3783
Minimum173
Maximum7535
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.1 KiB
2024-03-13T08:30:36.524786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum173
5-th percentile544
Q11133
median1744
Q33187
95-th percentile6082
Maximum7535
Range7362
Interquartile range (IQR)2054

Descriptive statistics

Standard deviation1693.115
Coefficient of variation (CV)0.71944023
Kurtosis0.5681915
Mean2353.3783
Median Absolute Deviation (MAD)823
Skewness1.1486214
Sum802502
Variance2866638.5
MonotonicityNot monotonic
2024-03-13T08:30:36.635262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1453 2
 
0.6%
700 2
 
0.6%
643 2
 
0.6%
937 2
 
0.6%
1506 2
 
0.6%
2146 2
 
0.6%
1242 2
 
0.6%
1396 2
 
0.6%
3034 2
 
0.6%
1743 2
 
0.6%
Other values (319) 321
94.1%
ValueCountFrequency (%)
173 1
0.3%
180 1
0.3%
186 1
0.3%
193 1
0.3%
199 1
0.3%
215 1
0.3%
217 2
0.6%
220 1
0.3%
237 1
0.3%
242 1
0.3%
ValueCountFrequency (%)
7535 1
0.3%
7360 1
0.3%
7206 1
0.3%
7047 1
0.3%
7037 1
0.3%
7006 1
0.3%
6968 1
0.3%
6807 1
0.3%
6738 1
0.3%
6666 1
0.3%

10세미만수급자수(명)
Real number (ℝ)

HIGH CORRELATION 

Distinct55
Distinct (%)16.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean17.038123
Minimum0
Maximum60
Zeros2
Zeros (%)0.6%
Negative0
Negative (%)0.0%
Memory size3.1 KiB
2024-03-13T08:30:36.740803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2
Q17
median13
Q324
95-th percentile42
Maximum60
Range60
Interquartile range (IQR)17

Descriptive statistics

Standard deviation13.047707
Coefficient of variation (CV)0.76579486
Kurtosis0.45018527
Mean17.038123
Median Absolute Deviation (MAD)7
Skewness1.0560819
Sum5810
Variance170.24266
MonotonicityNot monotonic
2024-03-13T08:30:36.844504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
6 20
 
5.9%
10 19
 
5.6%
8 18
 
5.3%
7 17
 
5.0%
4 15
 
4.4%
11 15
 
4.4%
18 13
 
3.8%
15 13
 
3.8%
9 12
 
3.5%
12 11
 
3.2%
Other values (45) 188
55.1%
ValueCountFrequency (%)
0 2
 
0.6%
1 7
 
2.1%
2 10
2.9%
3 10
2.9%
4 15
4.4%
5 11
3.2%
6 20
5.9%
7 17
5.0%
8 18
5.3%
9 12
3.5%
ValueCountFrequency (%)
60 1
0.3%
59 1
0.3%
57 2
0.6%
55 1
0.3%
54 1
0.3%
53 1
0.3%
51 1
0.3%
47 1
0.3%
46 1
0.3%
45 1
0.3%

10대수급자수(10세~19세)(명)
Real number (ℝ)

HIGH CORRELATION 

Distinct137
Distinct (%)40.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean70.642229
Minimum2
Maximum233
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.1 KiB
2024-03-13T08:30:36.948768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile12
Q135
median58
Q391
95-th percentile177
Maximum233
Range231
Interquartile range (IQR)56

Descriptive statistics

Standard deviation49.981595
Coefficient of variation (CV)0.7075314
Kurtosis0.96248438
Mean70.642229
Median Absolute Deviation (MAD)26
Skewness1.1792454
Sum24089
Variance2498.1599
MonotonicityNot monotonic
2024-03-13T08:30:37.054094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35 9
 
2.6%
41 9
 
2.6%
42 8
 
2.3%
60 6
 
1.8%
16 6
 
1.8%
30 5
 
1.5%
36 5
 
1.5%
69 5
 
1.5%
38 5
 
1.5%
12 5
 
1.5%
Other values (127) 278
81.5%
ValueCountFrequency (%)
2 1
 
0.3%
3 1
 
0.3%
6 1
 
0.3%
8 3
0.9%
9 3
0.9%
10 1
 
0.3%
11 4
1.2%
12 5
1.5%
13 3
0.9%
14 1
 
0.3%
ValueCountFrequency (%)
233 1
0.3%
230 2
0.6%
223 1
0.3%
222 1
0.3%
221 1
0.3%
212 2
0.6%
207 1
0.3%
200 1
0.3%
199 1
0.3%
193 1
0.3%

20대수급자수(20세~29세)(명)
Real number (ℝ)

HIGH CORRELATION 

Distinct139
Distinct (%)40.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean73.865103
Minimum4
Maximum244
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.1 KiB
2024-03-13T08:30:37.206246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4
5-th percentile12
Q138
median59
Q399
95-th percentile188
Maximum244
Range240
Interquartile range (IQR)61

Descriptive statistics

Standard deviation52.450812
Coefficient of variation (CV)0.7100892
Kurtosis0.94575414
Mean73.865103
Median Absolute Deviation (MAD)26
Skewness1.2058917
Sum25188
Variance2751.0876
MonotonicityNot monotonic
2024-03-13T08:30:37.314456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
39 8
 
2.3%
59 8
 
2.3%
42 7
 
2.1%
66 7
 
2.1%
60 7
 
2.1%
40 6
 
1.8%
36 6
 
1.8%
81 5
 
1.5%
51 5
 
1.5%
47 5
 
1.5%
Other values (129) 277
81.2%
ValueCountFrequency (%)
4 4
1.2%
5 3
0.9%
6 4
1.2%
9 1
 
0.3%
10 3
0.9%
12 3
0.9%
13 1
 
0.3%
15 3
0.9%
16 3
0.9%
19 5
1.5%
ValueCountFrequency (%)
244 1
0.3%
230 2
0.6%
228 1
0.3%
224 1
0.3%
223 1
0.3%
221 1
0.3%
216 1
0.3%
208 2
0.6%
206 1
0.3%
205 2
0.6%

30대수급자수(30세~39세)(명)
Real number (ℝ)

HIGH CORRELATION 

Distinct208
Distinct (%)61.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean151.45161
Minimum6
Maximum505
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.1 KiB
2024-03-13T08:30:37.418654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum6
5-th percentile29
Q174
median117
Q3218
95-th percentile384
Maximum505
Range499
Interquartile range (IQR)144

Descriptive statistics

Standard deviation108.90239
Coefficient of variation (CV)0.71905732
Kurtosis0.7421036
Mean151.45161
Median Absolute Deviation (MAD)57
Skewness1.1461042
Sum51645
Variance11859.731
MonotonicityNot monotonic
2024-03-13T08:30:37.530704image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
56 6
 
1.8%
87 5
 
1.5%
55 5
 
1.5%
30 5
 
1.5%
86 4
 
1.2%
129 4
 
1.2%
57 4
 
1.2%
104 4
 
1.2%
116 4
 
1.2%
53 4
 
1.2%
Other values (198) 296
86.8%
ValueCountFrequency (%)
6 1
 
0.3%
8 1
 
0.3%
9 1
 
0.3%
10 1
 
0.3%
11 1
 
0.3%
13 1
 
0.3%
20 1
 
0.3%
22 1
 
0.3%
23 1
 
0.3%
24 3
0.9%
ValueCountFrequency (%)
505 1
0.3%
504 1
0.3%
467 1
0.3%
466 1
0.3%
457 1
0.3%
456 2
0.6%
454 1
0.3%
453 1
0.3%
439 1
0.3%
427 1
0.3%

40대수급자수(40세~49세)(명)
Real number (ℝ)

HIGH CORRELATION 

Distinct267
Distinct (%)78.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean329.29326
Minimum14
Maximum893
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.1 KiB
2024-03-13T08:30:37.637275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum14
5-th percentile63
Q1160
median255
Q3434
95-th percentile779
Maximum893
Range879
Interquartile range (IQR)274

Descriptive statistics

Standard deviation224.43769
Coefficient of variation (CV)0.68157392
Kurtosis-0.27938355
Mean329.29326
Median Absolute Deviation (MAD)125
Skewness0.8695857
Sum112289
Variance50372.278
MonotonicityNot monotonic
2024-03-13T08:30:37.736955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
151 4
 
1.2%
155 4
 
1.2%
376 3
 
0.9%
209 3
 
0.9%
71 3
 
0.9%
168 3
 
0.9%
367 3
 
0.9%
197 3
 
0.9%
127 3
 
0.9%
199 2
 
0.6%
Other values (257) 310
90.9%
ValueCountFrequency (%)
14 2
0.6%
15 1
0.3%
16 2
0.6%
19 1
0.3%
21 1
0.3%
30 1
0.3%
31 1
0.3%
33 1
0.3%
40 1
0.3%
48 1
0.3%
ValueCountFrequency (%)
893 1
0.3%
859 1
0.3%
849 1
0.3%
848 1
0.3%
840 1
0.3%
839 1
0.3%
838 1
0.3%
826 1
0.3%
825 1
0.3%
818 1
0.3%

50대수급자수(50세~59세)(명)
Real number (ℝ)

HIGH CORRELATION 

Distinct279
Distinct (%)81.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean569.15249
Minimum33
Maximum1527
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.1 KiB
2024-03-13T08:30:37.834307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum33
5-th percentile134
Q1287
median432
Q3764
95-th percentile1403
Maximum1527
Range1494
Interquartile range (IQR)477

Descriptive statistics

Standard deviation397.52035
Coefficient of variation (CV)0.69844261
Kurtosis-0.14495875
Mean569.15249
Median Absolute Deviation (MAD)212
Skewness0.96638743
Sum194081
Variance158022.43
MonotonicityNot monotonic
2024-03-13T08:30:37.953301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
284 3
 
0.9%
413 3
 
0.9%
160 3
 
0.9%
447 3
 
0.9%
320 3
 
0.9%
339 3
 
0.9%
300 3
 
0.9%
443 3
 
0.9%
254 3
 
0.9%
393 2
 
0.6%
Other values (269) 312
91.5%
ValueCountFrequency (%)
33 1
0.3%
36 2
0.6%
38 1
0.3%
39 1
0.3%
40 2
0.6%
42 1
0.3%
45 1
0.3%
46 1
0.3%
51 1
0.3%
119 1
0.3%
ValueCountFrequency (%)
1527 1
0.3%
1507 1
0.3%
1484 1
0.3%
1469 1
0.3%
1454 1
0.3%
1452 1
0.3%
1446 1
0.3%
1443 1
0.3%
1440 1
0.3%
1431 1
0.3%

60대수급자수(60세~69세)(명)
Real number (ℝ)

HIGH CORRELATION 

Distinct292
Distinct (%)85.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean492.08504
Minimum25
Maximum1895
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.1 KiB
2024-03-13T08:30:38.091395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum25
5-th percentile101
Q1211
median373
Q3635
95-th percentile1348
Maximum1895
Range1870
Interquartile range (IQR)424

Descriptive statistics

Standard deviation390.27036
Coefficient of variation (CV)0.79309535
Kurtosis1.9299109
Mean492.08504
Median Absolute Deviation (MAD)181
Skewness1.4889129
Sum167801
Variance152310.95
MonotonicityNot monotonic
2024-03-13T08:30:38.228030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
192 3
 
0.9%
333 3
 
0.9%
346 3
 
0.9%
231 3
 
0.9%
203 3
 
0.9%
256 2
 
0.6%
110 2
 
0.6%
515 2
 
0.6%
186 2
 
0.6%
391 2
 
0.6%
Other values (282) 316
92.7%
ValueCountFrequency (%)
25 1
0.3%
30 1
0.3%
37 2
0.6%
39 1
0.3%
42 1
0.3%
43 1
0.3%
45 1
0.3%
46 1
0.3%
48 1
0.3%
51 1
0.3%
ValueCountFrequency (%)
1895 1
0.3%
1859 1
0.3%
1834 1
0.3%
1750 1
0.3%
1737 1
0.3%
1712 1
0.3%
1698 1
0.3%
1660 1
0.3%
1596 1
0.3%
1585 1
0.3%

70대수급자수(70세~79세)(명)
Real number (ℝ)

HIGH CORRELATION 

Distinct262
Distinct (%)76.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean369.3607
Minimum31
Maximum1308
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.1 KiB
2024-03-13T08:30:38.363746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum31
5-th percentile84
Q1176
median266
Q3510
95-th percentile986
Maximum1308
Range1277
Interquartile range (IQR)334

Descriptive statistics

Standard deviation271.89581
Coefficient of variation (CV)0.73612544
Kurtosis0.95142402
Mean369.3607
Median Absolute Deviation (MAD)125
Skewness1.2624639
Sum125952
Variance73927.331
MonotonicityNot monotonic
2024-03-13T08:30:38.472056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
176 5
 
1.5%
136 4
 
1.2%
160 4
 
1.2%
143 4
 
1.2%
281 4
 
1.2%
217 4
 
1.2%
189 3
 
0.9%
161 3
 
0.9%
230 3
 
0.9%
271 3
 
0.9%
Other values (252) 304
89.1%
ValueCountFrequency (%)
31 1
 
0.3%
39 1
 
0.3%
40 1
 
0.3%
41 1
 
0.3%
45 2
0.6%
46 2
0.6%
48 2
0.6%
49 1
 
0.3%
72 1
 
0.3%
77 3
0.9%
ValueCountFrequency (%)
1308 1
0.3%
1216 1
0.3%
1189 1
0.3%
1168 1
0.3%
1144 1
0.3%
1121 1
0.3%
1109 1
0.3%
1101 1
0.3%
1074 1
0.3%
1073 1
0.3%

80세이상수급자수(명)
Real number (ℝ)

HIGH CORRELATION 

Distinct250
Distinct (%)73.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean280.48974
Minimum17
Maximum1462
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.1 KiB
2024-03-13T08:30:38.578257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum17
5-th percentile43
Q194
median183
Q3342
95-th percentile925
Maximum1462
Range1445
Interquartile range (IQR)248

Descriptive statistics

Standard deviation275.90112
Coefficient of variation (CV)0.98364069
Kurtosis3.4069149
Mean280.48974
Median Absolute Deviation (MAD)105
Skewness1.8709623
Sum95647
Variance76121.427
MonotonicityNot monotonic
2024-03-13T08:30:38.882319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
79 6
 
1.8%
103 4
 
1.2%
152 4
 
1.2%
81 4
 
1.2%
60 4
 
1.2%
191 3
 
0.9%
72 3
 
0.9%
43 3
 
0.9%
71 3
 
0.9%
56 3
 
0.9%
Other values (240) 304
89.1%
ValueCountFrequency (%)
17 1
0.3%
18 1
0.3%
19 2
0.6%
21 1
0.3%
24 1
0.3%
31 1
0.3%
33 1
0.3%
34 1
0.3%
36 2
0.6%
39 1
0.3%
ValueCountFrequency (%)
1462 1
0.3%
1404 1
0.3%
1278 1
0.3%
1265 1
0.3%
1238 1
0.3%
1221 1
0.3%
1135 1
0.3%
1132 1
0.3%
1106 1
0.3%
1089 1
0.3%

Interactions

2024-03-13T08:30:34.861336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:30:26.741086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:30:27.465125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:30:28.251008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:30:29.080523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:30:29.834634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:30:30.625357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:30:31.540028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:30:32.249149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:30:33.095594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:30:33.862871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:30:35.005434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:30:26.800896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:30:27.531335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:30:28.336007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:30:29.145147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:30:29.897057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:30:30.687133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:30:31.603579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:30:32.327092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:30:33.160365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:30:33.935085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:30:35.093057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:30:26.869036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:30:27.603225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:30:28.418067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:30:29.218229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:30:29.965511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:30:30.756639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:30:31.671857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:30:32.410762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:30:33.232393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:30:34.009291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:30:35.162164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:30:26.932459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:30:27.676668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:30:28.488956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:30:29.283756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:30:30.034862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:30:31.015451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:30:31.737953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:30:32.502443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:30:33.302543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:30:34.076229image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:30:35.226152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:30:26.992642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:30:27.741319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:30:28.554740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:30:29.344255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:30:30.094275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:30:31.075037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:30:31.796665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:30:32.576791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:30:33.366108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:30:34.144743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:30:35.292868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:30:27.055474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:30:27.809685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:30:28.636950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:30:29.412747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:30:30.156779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:30:31.138379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:30:31.858327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:30:32.657342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:30:33.434816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:30:34.250835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:30:35.358226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:30:27.123694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:30:27.874881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:30:28.703547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:30:29.476736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:30:30.225187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:30:31.200894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:30:31.922334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:30:32.733682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:30:33.501214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:30:34.348074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:30:35.629965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:30:27.187180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:30:27.940272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:30:28.779209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:30:29.539342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:30:30.288917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:30:31.260523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:30:31.979871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:30:32.803880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:30:33.567415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:30:34.436308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:30:35.702070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:30:27.258302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:30:28.014168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:30:28.859248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:30:29.609108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:30:30.375295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:30:31.331908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:30:32.050734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:30:32.879142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:30:33.646318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:30:34.537094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:30:35.777063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:30:27.326429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:30:28.087044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:30:28.936962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:30:29.691340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:30:30.462194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:30:31.400113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:30:32.117208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:30:32.952340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:30:33.720803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:30:34.627537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:30:35.891742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:30:27.395848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:30:28.163073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:30:29.007324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:30:29.766397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:30:30.553817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:30:31.468601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:30:32.184045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:30:33.021450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:30:33.789737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:30:34.711043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-13T08:30:38.978138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기준년도시군명총계(명)10세미만수급자수(명)10대수급자수(10세~19세)(명)20대수급자수(20세~29세)(명)30대수급자수(30세~39세)(명)40대수급자수(40세~49세)(명)50대수급자수(50세~59세)(명)60대수급자수(60세~69세)(명)70대수급자수(70세~79세)(명)80세이상수급자수(명)
기준년도1.0000.0000.3240.0000.0000.0000.0000.0000.0000.3150.2550.524
시군명0.0001.0000.8140.8300.9280.8960.8530.9440.9200.6670.7870.325
총계(명)0.3240.8141.0000.8460.9000.9510.9530.9020.9200.9540.9620.898
10세미만수급자수(명)0.0000.8300.8461.0000.8980.8540.8340.8190.8390.8410.8760.784
10대수급자수(10세~19세)(명)0.0000.9280.9000.8981.0000.9210.8910.9180.9380.8420.8550.728
20대수급자수(20세~29세)(명)0.0000.8960.9510.8540.9211.0000.9330.9200.9350.9040.9260.810
30대수급자수(30세~39세)(명)0.0000.8530.9530.8340.8910.9331.0000.9020.9070.9180.9220.863
40대수급자수(40세~49세)(명)0.0000.9440.9020.8190.9180.9200.9021.0000.9560.8410.8590.745
50대수급자수(50세~59세)(명)0.0000.9200.9200.8390.9380.9350.9070.9561.0000.8640.8710.687
60대수급자수(60세~69세)(명)0.3150.6670.9540.8410.8420.9040.9180.8410.8641.0000.9650.890
70대수급자수(70세~79세)(명)0.2550.7870.9620.8760.8550.9260.9220.8590.8710.9651.0000.878
80세이상수급자수(명)0.5240.3250.8980.7840.7280.8100.8630.7450.6870.8900.8781.000
2024-03-13T08:30:39.097644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기준년도총계(명)10세미만수급자수(명)10대수급자수(10세~19세)(명)20대수급자수(20세~29세)(명)30대수급자수(30세~39세)(명)40대수급자수(40세~49세)(명)50대수급자수(50세~59세)(명)60대수급자수(60세~69세)(명)70대수급자수(70세~79세)(명)80세이상수급자수(명)시군명
기준년도1.0000.2940.2620.1480.2280.230-0.0400.1010.4510.3700.6430.000
총계(명)0.2941.0000.8700.9430.9720.9720.9290.9700.9770.9810.8890.436
10세미만수급자수(명)0.2620.8701.0000.8690.8540.8560.8160.8510.8490.8490.7720.465
10대수급자수(10세~19세)(명)0.1480.9430.8691.0000.9430.9300.9320.9540.8940.8930.7660.645
20대수급자수(20세~29세)(명)0.2280.9720.8540.9431.0000.9580.9270.9570.9380.9380.8300.552
30대수급자수(30세~39세)(명)0.2300.9720.8560.9300.9581.0000.9360.9510.9290.9340.8370.491
40대수급자수(40세~49세)(명)-0.0400.9290.8160.9320.9270.9361.0000.9730.8410.8740.6840.691
50대수급자수(50세~59세)(명)0.1010.9700.8510.9540.9570.9510.9731.0000.9130.9290.7740.625
60대수급자수(60세~69세)(명)0.4510.9770.8490.8940.9380.9290.8410.9131.0000.9790.9440.294
70대수급자수(70세~79세)(명)0.3700.9810.8490.8930.9380.9340.8740.9290.9791.0000.9210.403
80세이상수급자수(명)0.6430.8890.7720.7660.8300.8370.6840.7740.9440.9211.0000.115
시군명0.0000.4360.4650.6450.5520.4910.6910.6250.2940.4030.1151.000

Missing values

2024-03-13T08:30:36.022708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-13T08:30:36.150992image/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

기준년도시군명총계(명)10세미만수급자수(명)10대수급자수(10세~19세)(명)20대수급자수(20세~29세)(명)30대수급자수(30세~39세)(명)40대수급자수(40세~49세)(명)50대수급자수(50세~59세)(명)60대수급자수(60세~69세)(명)70대수급자수(70세~79세)(명)80세이상수급자수(명)
02023가평군860618244566142192176191
12023고양시7360401572165046751401173711681462
22023과천시242094241933514557
32023광명시220795260151225386547393384
42023광주시2110267181175243410437336331
52023구리시1570143442101133286425289246
62023군포시2373184265136188425623413463
72023김포시3068287690182315498707586586
82023남양주시551739138132337548953126710141089
92023동두천시16867356083142330421281327
기준년도시군명총계(명)10세미만수급자수(명)10대수급자수(10세~19세)(명)20대수급자수(20세~29세)(명)30대수급자수(30세~39세)(명)40대수급자수(40세~49세)(명)50대수급자수(50세~59세)(명)60대수급자수(60세~69세)(명)70대수급자수(70세~79세)(명)80세이상수급자수(명)
3312013오산시70882930641761851057239
3322013용인시166986660131367447247230113
3332013의왕시478112123897119698743
3342013의정부시2618147991165507784449382147
3352013이천시1006532308523126115314465
3362013파주시1990115850136403536310341145
3372013평택시225345779188421667370343124
3382013포천시14526436911030240223521768
3392013하남시63372121571301701077743
3402013화성시136513374612331637819018577