Overview

Dataset statistics

Number of variables8
Number of observations310
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory21.6 KiB
Average record size in memory71.4 B

Variable types

Numeric7
Categorical1

Dataset

Description장애연금 급여종류별 지급 집계현황
Author경기복지재단(경기도장애인복지종합지원센터)
URLhttps://data.gg.go.kr/portal/data/service/selectServicePage.do?&infId=ZFF516BCFT4RIB0EEL6X26263448&infSeq=1

Alerts

전체수급자수(명) is highly overall correlated with 전체지급액(원) and 5 other fieldsHigh correlation
전체지급액(원) is highly overall correlated with 전체수급자수(명) and 5 other fieldsHigh correlation
장애연금수급자수(명) is highly overall correlated with 전체수급자수(명) and 5 other fieldsHigh correlation
장애연금지급액(원) is highly overall correlated with 전체수급자수(명) and 5 other fieldsHigh correlation
일시금수급자수(명) is highly overall correlated with 전체수급자수(명) and 5 other fieldsHigh correlation
일시금지급액(원) is highly overall correlated with 전체수급자수(명) and 4 other fieldsHigh correlation
시군명 is highly overall correlated with 전체수급자수(명) and 4 other fieldsHigh correlation
전체지급액(원) has unique valuesUnique
장애연금지급액(원) has unique valuesUnique
일시금지급액(원) has unique valuesUnique

Reproduction

Analysis started2024-04-11 04:51:21.272323
Analysis finished2024-04-11 04:51:26.583582
Duration5.31 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

기준년도
Real number (ℝ)

Distinct10
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2017.5
Minimum2013
Maximum2022
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.9 KiB
2024-04-11T13:51:26.632869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2013
5-th percentile2013
Q12015
median2017.5
Q32020
95-th percentile2022
Maximum2022
Range9
Interquartile range (IQR)5

Descriptive statistics

Standard deviation2.8769253
Coefficient of variation (CV)0.0014259853
Kurtosis-1.2246126
Mean2017.5
Median Absolute Deviation (MAD)2.5
Skewness0
Sum625425
Variance8.276699
MonotonicityDecreasing
2024-04-11T13:51:26.762908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
2022 31
10.0%
2021 31
10.0%
2020 31
10.0%
2019 31
10.0%
2018 31
10.0%
2017 31
10.0%
2016 31
10.0%
2015 31
10.0%
2014 31
10.0%
2013 31
10.0%
ValueCountFrequency (%)
2013 31
10.0%
2014 31
10.0%
2015 31
10.0%
2016 31
10.0%
2017 31
10.0%
2018 31
10.0%
2019 31
10.0%
2020 31
10.0%
2021 31
10.0%
2022 31
10.0%
ValueCountFrequency (%)
2022 31
10.0%
2021 31
10.0%
2020 31
10.0%
2019 31
10.0%
2018 31
10.0%
2017 31
10.0%
2016 31
10.0%
2015 31
10.0%
2014 31
10.0%
2013 31
10.0%

시군명
Categorical

HIGH CORRELATION 

Distinct31
Distinct (%)10.0%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
가평군
 
10
고양시
 
10
과천시
 
10
광명시
 
10
광주시
 
10
Other values (26)
260 

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 10
 
3.2%
고양시 10
 
3.2%
과천시 10
 
3.2%
광명시 10
 
3.2%
광주시 10
 
3.2%
구리시 10
 
3.2%
군포시 10
 
3.2%
김포시 10
 
3.2%
남양주시 10
 
3.2%
동두천시 10
 
3.2%
Other values (21) 210
67.7%

Length

2024-04-11T13:51:26.858972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
가평군 10
 
3.2%
안양시 10
 
3.2%
하남시 10
 
3.2%
포천시 10
 
3.2%
평택시 10
 
3.2%
파주시 10
 
3.2%
이천시 10
 
3.2%
의정부시 10
 
3.2%
의왕시 10
 
3.2%
용인시 10
 
3.2%
Other values (21) 210
67.7%

전체수급자수(명)
Real number (ℝ)

HIGH CORRELATION 

Distinct268
Distinct (%)86.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean589.74194
Minimum40
Maximum2549
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.9 KiB
2024-04-11T13:51:27.002379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum40
5-th percentile80
Q1261.75
median449.5
Q3879.5
95-th percentile1322
Maximum2549
Range2509
Interquartile range (IQR)617.75

Descriptive statistics

Standard deviation427.01312
Coefficient of variation (CV)0.72406776
Kurtosis0.35420515
Mean589.74194
Median Absolute Deviation (MAD)263.5
Skewness0.86528275
Sum182820
Variance182340.21
MonotonicityNot monotonic
2024-04-11T13:51:27.134377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
209 3
 
1.0%
181 3
 
1.0%
268 3
 
1.0%
293 3
 
1.0%
361 2
 
0.6%
203 2
 
0.6%
292 2
 
0.6%
121 2
 
0.6%
153 2
 
0.6%
78 2
 
0.6%
Other values (258) 286
92.3%
ValueCountFrequency (%)
40 1
0.3%
45 1
0.3%
48 1
0.3%
49 1
0.3%
52 1
0.3%
53 1
0.3%
62 1
0.3%
65 1
0.3%
67 2
0.6%
77 2
0.6%
ValueCountFrequency (%)
2549 1
0.3%
1574 1
0.3%
1567 1
0.3%
1551 1
0.3%
1549 1
0.3%
1526 1
0.3%
1455 1
0.3%
1429 1
0.3%
1428 1
0.3%
1419 1
0.3%

전체지급액(원)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct310
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3098310.9
Minimum299328
Maximum12491013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.9 KiB
2024-04-11T13:51:27.252266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum299328
5-th percentile405654.85
Q11268150
median2328613
Q34675573
95-th percentile7283968.1
Maximum12491013
Range12191685
Interquartile range (IQR)3407423

Descriptive statistics

Standard deviation2326076.6
Coefficient of variation (CV)0.75075635
Kurtosis0.13112223
Mean3098310.9
Median Absolute Deviation (MAD)1391131
Skewness0.90815775
Sum9.6047637 × 108
Variance5.4106322 × 1012
MonotonicityNot monotonic
2024-04-11T13:51:27.374584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
633463 1
 
0.3%
817908 1
 
0.3%
2981367 1
 
0.3%
1412228 1
 
0.3%
3146114 1
 
0.3%
970401 1
 
0.3%
5752049 1
 
0.3%
1521212 1
 
0.3%
307373 1
 
0.3%
889305 1
 
0.3%
Other values (300) 300
96.8%
ValueCountFrequency (%)
299328 1
0.3%
307373 1
0.3%
317520 1
0.3%
319031 1
0.3%
335298 1
0.3%
335519 1
0.3%
339890 1
0.3%
343657 1
0.3%
347813 1
0.3%
359626 1
0.3%
ValueCountFrequency (%)
12491013 1
0.3%
9105562 1
0.3%
8925627 1
0.3%
8884979 1
0.3%
8708521 1
0.3%
8652139 1
0.3%
8542829 1
0.3%
8416819 1
0.3%
8383433 1
0.3%
8158732 1
0.3%

장애연금수급자수(명)
Real number (ℝ)

HIGH CORRELATION 

Distinct270
Distinct (%)87.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean566.61613
Minimum38
Maximum2439
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.9 KiB
2024-04-11T13:51:27.485271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum38
5-th percentile77
Q1254.25
median433
Q3846.5
95-th percentile1277.3
Maximum2439
Range2401
Interquartile range (IQR)592.25

Descriptive statistics

Standard deviation409.25986
Coefficient of variation (CV)0.7222877
Kurtosis0.33779322
Mean566.61613
Median Absolute Deviation (MAD)253.5
Skewness0.86279849
Sum175651
Variance167493.64
MonotonicityNot monotonic
2024-04-11T13:51:27.620716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
77 5
 
1.6%
114 3
 
1.0%
297 3
 
1.0%
463 2
 
0.6%
288 2
 
0.6%
180 2
 
0.6%
1508 2
 
0.6%
293 2
 
0.6%
703 2
 
0.6%
262 2
 
0.6%
Other values (260) 285
91.9%
ValueCountFrequency (%)
38 1
0.3%
44 1
0.3%
46 1
0.3%
47 1
0.3%
51 1
0.3%
52 1
0.3%
61 1
0.3%
62 1
0.3%
63 1
0.3%
64 1
0.3%
ValueCountFrequency (%)
2439 1
0.3%
1508 2
0.6%
1492 1
0.3%
1480 1
0.3%
1458 1
0.3%
1402 1
0.3%
1384 1
0.3%
1361 1
0.3%
1356 1
0.3%
1354 1
0.3%

장애연금지급액(원)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct310
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2737815.1
Minimum268922
Maximum10998058
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.9 KiB
2024-04-11T13:51:27.747511image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum268922
5-th percentile359669.25
Q11151247.2
median2053774
Q34034165.2
95-th percentile6441277.9
Maximum10998058
Range10729136
Interquartile range (IQR)2882918

Descriptive statistics

Standard deviation2037653
Coefficient of variation (CV)0.74426245
Kurtosis0.10999302
Mean2737815.1
Median Absolute Deviation (MAD)1194864
Skewness0.89956105
Sum8.487227 × 108
Variance4.1520298 × 1012
MonotonicityNot monotonic
2024-04-11T13:51:27.858883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
574649 1
 
0.3%
753586 1
 
0.3%
2628372 1
 
0.3%
1324216 1
 
0.3%
2682356 1
 
0.3%
829625 1
 
0.3%
5073915 1
 
0.3%
1315327 1
 
0.3%
302551 1
 
0.3%
864683 1
 
0.3%
Other values (300) 300
96.8%
ValueCountFrequency (%)
268922 1
0.3%
270163 1
0.3%
282971 1
0.3%
294242 1
0.3%
301371 1
0.3%
302551 1
0.3%
305252 1
0.3%
308107 1
0.3%
316216 1
0.3%
317520 1
0.3%
ValueCountFrequency (%)
10998058 1
0.3%
7908369 1
0.3%
7894287 1
0.3%
7813359 1
0.3%
7649367 1
0.3%
7456611 1
0.3%
7436064 1
0.3%
7271532 1
0.3%
7271101 1
0.3%
7174040 1
0.3%

일시금수급자수(명)
Real number (ℝ)

HIGH CORRELATION 

Distinct71
Distinct (%)22.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean23.125806
Minimum0
Maximum110
Zeros1
Zeros (%)0.3%
Negative0
Negative (%)0.0%
Memory size2.9 KiB
2024-04-11T13:51:28.109421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2
Q18
median18
Q335
95-th percentile59
Maximum110
Range110
Interquartile range (IQR)27

Descriptive statistics

Standard deviation18.66864
Coefficient of variation (CV)0.80726437
Kurtosis0.83453564
Mean23.125806
Median Absolute Deviation (MAD)12
Skewness1.0174535
Sum7169
Variance348.5181
MonotonicityNot monotonic
2024-04-11T13:51:28.212080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4 17
 
5.5%
9 15
 
4.8%
10 14
 
4.5%
21 11
 
3.5%
7 11
 
3.5%
5 11
 
3.5%
2 11
 
3.5%
16 9
 
2.9%
17 9
 
2.9%
3 9
 
2.9%
Other values (61) 193
62.3%
ValueCountFrequency (%)
0 1
 
0.3%
1 7
2.3%
2 11
3.5%
3 9
2.9%
4 17
5.5%
5 11
3.5%
6 6
 
1.9%
7 11
3.5%
8 6
 
1.9%
9 15
4.8%
ValueCountFrequency (%)
110 1
0.3%
74 1
0.3%
71 1
0.3%
68 1
0.3%
67 1
0.3%
66 1
0.3%
65 2
0.6%
64 2
0.6%
63 1
0.3%
62 1
0.3%

일시금지급액(원)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct310
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean359527.95
Minimum0
Maximum1492955
Zeros1
Zeros (%)0.3%
Negative0
Negative (%)0.0%
Memory size2.9 KiB
2024-04-11T13:51:28.328684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile33907.75
Q1114784.25
median273933
Q3542348.5
95-th percentile964186.9
Maximum1492955
Range1492955
Interquartile range (IQR)427564.25

Descriptive statistics

Standard deviation303852.38
Coefficient of variation (CV)0.84514258
Kurtosis0.59609304
Mean359527.95
Median Absolute Deviation (MAD)188240.5
Skewness1.0655596
Sum1.1145366 × 108
Variance9.2326267 × 1010
MonotonicityNot monotonic
2024-04-11T13:51:28.443130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
58814 1
 
0.3%
64322 1
 
0.3%
352995 1
 
0.3%
88012 1
 
0.3%
463758 1
 
0.3%
140776 1
 
0.3%
678134 1
 
0.3%
205885 1
 
0.3%
4822 1
 
0.3%
24622 1
 
0.3%
Other values (300) 300
96.8%
ValueCountFrequency (%)
0 1
0.3%
4822 1
0.3%
10444 1
0.3%
12976 1
0.3%
13616 1
0.3%
17982 1
0.3%
18514 1
0.3%
19569 1
0.3%
20076 1
0.3%
22015 1
0.3%
ValueCountFrequency (%)
1492955 1
0.3%
1448915 1
0.3%
1211275 1
0.3%
1197839 1
0.3%
1145718 1
0.3%
1123475 1
0.3%
1111901 1
0.3%
1086218 1
0.3%
1017258 1
0.3%
1007443 1
0.3%

Interactions

2024-04-11T13:51:25.894487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:51:22.634847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:51:23.256827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:51:23.743718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:51:24.234049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:51:24.728795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:51:25.227168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:51:25.993778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:51:22.738175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:51:23.320124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:51:23.808166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:51:24.296129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:51:24.794505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:51:25.295336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:51:26.072770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:51:22.920305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:51:23.387096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:51:23.874787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:51:24.359207image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:51:24.866306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:51:25.364264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:51:26.143647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:51:22.990741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:51:23.458495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:51:23.944769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:51:24.430019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:51:24.941634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:51:25.434529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:51:26.210862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:51:23.053921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:51:23.520814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:51:24.012405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:51:24.491765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:51:25.014578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:51:25.500531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:51:26.280926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:51:23.116730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:51:23.590534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:51:24.082869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:51:24.561765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:51:25.084770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:51:25.565247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:51:26.350398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:51:23.182875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:51:23.667942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:51:24.149890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:51:24.633791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:51:25.149160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:51:25.630710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-11T13:51:28.526037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기준년도시군명전체수급자수(명)전체지급액(원)장애연금수급자수(명)장애연금지급액(원)일시금수급자수(명)일시금지급액(원)
기준년도1.0000.0000.0000.0000.0000.0000.0000.000
시군명0.0001.0000.9300.8900.9350.8970.8400.779
전체수급자수(명)0.0000.9301.0000.9301.0000.9430.9490.812
전체지급액(원)0.0000.8900.9301.0000.9290.9960.8680.850
장애연금수급자수(명)0.0000.9351.0000.9291.0000.9450.9450.804
장애연금지급액(원)0.0000.8970.9430.9960.9451.0000.8530.817
일시금수급자수(명)0.0000.8400.9490.8680.9450.8531.0000.868
일시금지급액(원)0.0000.7790.8120.8500.8040.8170.8681.000
2024-04-11T13:51:28.620499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기준년도전체수급자수(명)전체지급액(원)장애연금수급자수(명)장애연금지급액(원)일시금수급자수(명)일시금지급액(원)시군명
기준년도1.0000.0710.1420.0710.1380.0570.1670.000
전체수급자수(명)0.0711.0000.9911.0000.9930.9620.9460.677
전체지급액(원)0.1420.9911.0000.9900.9990.9630.9650.576
장애연금수급자수(명)0.0711.0000.9901.0000.9930.9570.9420.689
장애연금지급액(원)0.1380.9930.9990.9931.0000.9540.9530.590
일시금수급자수(명)0.0570.9620.9630.9570.9541.0000.9820.504
일시금지급액(원)0.1670.9460.9650.9420.9530.9821.0000.393
시군명0.0000.6770.5760.6890.5900.5040.3931.000

Missing values

2024-04-11T13:51:26.446224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-11T13:51:26.542159image/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

기준년도시군명전체수급자수(명)전체지급액(원)장애연금수급자수(명)장애연금지급액(원)일시금수급자수(명)일시금지급액(원)
02022가평군126633463122574649458814
12022고양시1387854282913327456611551086218
22022과천시4531903144294242124789
32022광명시4632764157442236369221400465
42022광주시5753008825559274863716260188
52022구리시2681476206258127545910200747
62022군포시3962472909375200220621470703
72022김포시6363701886615333605121365835
82022남양주시109261302291054547429338655936
92022동두천시163802929159745344457585
기준년도시군명전체수급자수(명)전체지급액(원)장애연금수급자수(명)장애연금지급액(원)일시금수급자수(명)일시금지급액(원)
3002013오산시27712529572711177899675058
3012013용인시9845130518941456497743565541
3022013의왕시18192875417177637110152383
3032013의정부시6323192797602274358330449214
3042013이천시3051374058288117906717194991
3052013파주시6073089383570255964537529738
3062013평택시7023130746681283100521299741
3072013포천시27412322672691147222585045
3082013하남시195106245518586580210196653
3092013화성시7333526063703310389530422168