Overview

Dataset statistics

Number of variables9
Number of observations30
Missing cells1
Missing cells (%)0.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.4 KiB
Average record size in memory83.4 B

Variable types

Text1
Numeric7
Unsupported1

Dataset

Description기초수급자및차상위계층통계201712
Author전라북도
URLhttps://www.bigdatahub.go.kr/opendata/dataSet/detail.nm?contentId=37&rlik=49451aebf056b486&serviceId=202002

Alerts

합계(기초수급자수) is highly overall correlated with 일반수급자 and 5 other fieldsHigh correlation
일반수급자 is highly overall correlated with 합계(기초수급자수) and 5 other fieldsHigh correlation
소계(법정차상위) is highly overall correlated with 합계(기초수급자수) and 5 other fieldsHigh correlation
한부모가족 is highly overall correlated with 합계(기초수급자수) and 5 other fieldsHigh correlation
차상위본인부담경감대상자 is highly overall correlated with 합계(기초수급자수) and 5 other fieldsHigh correlation
차상위자활사업참여자 is highly overall correlated with 합계(기초수급자수) and 5 other fieldsHigh correlation
차상위장애인 is highly overall correlated with 합계(기초수급자수) and 5 other fieldsHigh correlation
시설수급자 has 1 (3.3%) missing valuesMissing
시군명 has unique valuesUnique
합계(기초수급자수) has unique valuesUnique
일반수급자 has unique valuesUnique
소계(법정차상위) has unique valuesUnique
차상위장애인 has unique valuesUnique
시설수급자 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-03-14 03:06:41.508168
Analysis finished2024-03-14 03:06:45.514192
Duration4.01 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군명
Text

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
2024-03-14T12:06:45.594671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length9.5
Min length7

Characters and Unicode

Total characters285
Distinct characters31
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique30 ?
Unique (%)100.0%

Sample

1st row 계(가구)
2nd row (인원)
3rd row 전주시 계(가구)
4th row전주시 (인원)
5th row 군산시 계(가구)
ValueCountFrequency (%)
계(가구 15
25.9%
인원 15
25.9%
전주시 2
 
3.4%
군산시 2
 
3.4%
익산시 2
 
3.4%
정읍시 2
 
3.4%
남원시 2
 
3.4%
김제시 2
 
3.4%
완주군 2
 
3.4%
진안군 2
 
3.4%
Other values (6) 12
20.7%
2024-03-14T12:06:45.838515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
66
23.2%
( 30
10.5%
) 30
10.5%
군 18
 
6.3%
원 17
 
6.0%
가 15
 
5.3%
구 15
 
5.3%
인 15
 
5.3%
계 15
 
5.3%
시 12
 
4.2%
Other values (21) 52
18.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 159
55.8%
Space Separator 66
23.2%
Open Punctuation 30
 
10.5%
Close Punctuation 30
 
10.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
군 18
11.3%
원 17
10.7%
가 15
 
9.4%
구 15
 
9.4%
인 15
 
9.4%
계 15
 
9.4%
시 12
 
7.5%
주 6
 
3.8%
안 4
 
2.5%
산 4
 
2.5%
Other values (18) 38
23.9%
Space Separator
ValueCountFrequency (%)
66
100.0%
Open Punctuation
ValueCountFrequency (%)
( 30
100.0%
Close Punctuation
ValueCountFrequency (%)
) 30
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 159
55.8%
Common 126
44.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
군 18
11.3%
원 17
10.7%
가 15
 
9.4%
구 15
 
9.4%
인 15
 
9.4%
계 15
 
9.4%
시 12
 
7.5%
주 6
 
3.8%
안 4
 
2.5%
산 4
 
2.5%
Other values (18) 38
23.9%
Common
ValueCountFrequency (%)
66
52.4%
( 30
23.8%
) 30
23.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 159
55.8%
ASCII 126
44.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
66
52.4%
( 30
23.8%
) 30
23.8%
Hangul
ValueCountFrequency (%)
군 18
11.3%
원 17
10.7%
가 15
 
9.4%
구 15
 
9.4%
인 15
 
9.4%
계 15
 
9.4%
시 12
 
7.5%
주 6
 
3.8%
안 4
 
2.5%
산 4
 
2.5%
Other values (18) 38
23.9%

합계(기초수급자수)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10235.067
Minimum812
Maximum89275
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2024-03-14T12:06:45.944926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum812
5-th percentile909.05
Q11265.5
median3480.5
Q38806.5
95-th percentile47284.65
Maximum89275
Range88463
Interquartile range (IQR)7541

Descriptive statistics

Standard deviation19312.975
Coefficient of variation (CV)1.8869418
Kurtosis11.209218
Mean10235.067
Median Absolute Deviation (MAD)2368
Skewness3.3102505
Sum307052
Variance3.72991 × 108
MonotonicityNot monotonic
2024-03-14T12:06:46.048567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
64251 1
 
3.3%
964 1
 
3.3%
2956 1
 
3.3%
2195 1
 
3.3%
2579 1
 
3.3%
2136 1
 
3.3%
1255 1
 
3.3%
936 1
 
3.3%
1581 1
 
3.3%
1157 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
812 1
3.3%
887 1
3.3%
936 1
3.3%
964 1
3.3%
1068 1
3.3%
1157 1
3.3%
1206 1
3.3%
1255 1
3.3%
1297 1
3.3%
1581 1
3.3%
ValueCountFrequency (%)
89275 1
3.3%
64251 1
3.3%
26548 1
3.3%
17510 1
3.3%
14863 1
3.3%
12672 1
3.3%
11251 1
3.3%
9344 1
3.3%
7194 1
3.3%
6807 1
3.3%

일반수급자
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9877.4667
Minimum753
Maximum89275
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2024-03-14T12:06:46.147757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum753
5-th percentile848.85
Q11265.5
median3139.5
Q38216.25
95-th percentile44334.45
Maximum89275
Range88522
Interquartile range (IQR)6950.75

Descriptive statistics

Standard deviation18828.771
Coefficient of variation (CV)1.9062348
Kurtosis12.076303
Mean9877.4667
Median Absolute Deviation (MAD)2070.5
Skewness3.3957572
Sum296324
Variance3.5452262 × 108
MonotonicityNot monotonic
2024-03-14T12:06:46.246671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
58887 1
 
3.3%
862 1
 
3.3%
2956 1
 
3.3%
2138 1
 
3.3%
2579 1
 
3.3%
1904 1
 
3.3%
1255 1
 
3.3%
843 1
 
3.3%
1581 1
 
3.3%
1070 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
753 1
3.3%
843 1
3.3%
856 1
3.3%
862 1
3.3%
1068 1
3.3%
1070 1
3.3%
1206 1
3.3%
1255 1
3.3%
1297 1
3.3%
1581 1
3.3%
ValueCountFrequency (%)
89275 1
3.3%
58887 1
3.3%
26548 1
3.3%
16565 1
3.3%
14863 1
3.3%
12672 1
3.3%
9765 1
3.3%
8557 1
3.3%
7194 1
3.3%
6807 1
3.3%

시설수급자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1
Missing (%)3.3%
Memory size372.0 B

소계(법정차상위)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4630.5333
Minimum384
Maximum46049
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2024-03-14T12:06:46.346643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum384
5-th percentile401
Q1643.5
median2039.5
Q33459
95-th percentile18579.6
Maximum46049
Range45665
Interquartile range (IQR)2815.5

Descriptive statistics

Standard deviation9075.6308
Coefficient of variation (CV)1.9599537
Kurtosis15.888574
Mean4630.5333
Median Absolute Deviation (MAD)1428.5
Skewness3.8211584
Sum138916
Variance82367074
MonotonicityNot monotonic
2024-03-14T12:06:46.441792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
23409 1
 
3.3%
456 1
 
3.3%
1997 1
 
3.3%
1255 1
 
3.3%
2449 1
 
3.3%
1571 1
 
3.3%
618 1
 
3.3%
412 1
 
3.3%
953 1
 
3.3%
604 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
384 1
3.3%
392 1
3.3%
412 1
3.3%
456 1
3.3%
570 1
3.3%
603 1
3.3%
604 1
3.3%
618 1
3.3%
720 1
3.3%
953 1
3.3%
ValueCountFrequency (%)
46049 1
3.3%
23409 1
3.3%
12677 1
3.3%
7172 1
3.3%
5994 1
3.3%
4981 1
3.3%
3996 1
3.3%
3499 1
3.3%
3339 1
3.3%
2944 1
3.3%

한부모가족
Real number (ℝ)

HIGH CORRELATION 

Distinct28
Distinct (%)93.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean686.93333
Minimum13
Maximum8322
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2024-03-14T12:06:46.537260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum13
5-th percentile18.7
Q165.75
median118
Q3416
95-th percentile2597.45
Maximum8322
Range8309
Interquartile range (IQR)350.25

Descriptive statistics

Standard deviation1599.9512
Coefficient of variation (CV)2.3291215
Kurtosis18.921943
Mean686.93333
Median Absolute Deviation (MAD)99
Skewness4.1309974
Sum20608
Variance2559843.7
MonotonicityNot monotonic
2024-03-14T12:06:46.628472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
24 2
 
6.7%
95 2
 
6.7%
1982 1
 
3.3%
329 1
 
3.3%
180 1
 
3.3%
39 1
 
3.3%
258 1
 
3.3%
62 1
 
3.3%
88 1
 
3.3%
16 1
 
3.3%
Other values (18) 18
60.0%
ValueCountFrequency (%)
13 1
3.3%
16 1
3.3%
22 1
3.3%
24 2
6.7%
39 1
3.3%
55 1
3.3%
62 1
3.3%
77 1
3.3%
79 1
3.3%
88 1
3.3%
ValueCountFrequency (%)
8322 1
3.3%
3101 1
3.3%
1982 1
3.3%
1649 1
3.3%
1127 1
3.3%
716 1
3.3%
548 1
3.3%
423 1
3.3%
395 1
3.3%
329 1
3.3%

차상위본인부담경감대상자
Real number (ℝ)

HIGH CORRELATION 

Distinct29
Distinct (%)96.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2474
Minimum110
Maximum25646
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2024-03-14T12:06:46.732740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum110
5-th percentile139.75
Q1303
median1198.5
Q31990
95-th percentile9506.05
Maximum25646
Range25536
Interquartile range (IQR)1687

Descriptive statistics

Standard deviation4966.5779
Coefficient of variation (CV)2.0075093
Kurtosis17.271917
Mean2474
Median Absolute Deviation (MAD)931.5
Skewness3.9579105
Sum74220
Variance24666896
MonotonicityNot monotonic
2024-03-14T12:06:46.828707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
170 2
 
6.7%
11464 1
 
3.3%
25646 1
 
3.3%
1231 1
 
3.3%
738 1
 
3.3%
1382 1
 
3.3%
832 1
 
3.3%
270 1
 
3.3%
444 1
 
3.3%
220 1
 
3.3%
Other values (19) 19
63.3%
ValueCountFrequency (%)
110 1
3.3%
115 1
3.3%
170 2
6.7%
200 1
3.3%
220 1
3.3%
223 1
3.3%
270 1
3.3%
402 1
3.3%
444 1
3.3%
580 1
3.3%
ValueCountFrequency (%)
25646 1
3.3%
11464 1
3.3%
7113 1
3.3%
3888 1
3.3%
3330 1
3.3%
2422 1
3.3%
2272 1
3.3%
2133 1
3.3%
1561 1
3.3%
1456 1
3.3%

차상위자활사업참여자
Real number (ℝ)

HIGH CORRELATION 

Distinct28
Distinct (%)93.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean128.06667
Minimum5
Maximum1102
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2024-03-14T12:06:46.927498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5
5-th percentile12.45
Q132.75
median58
Q388.5
95-th percentile569.25
Maximum1102
Range1097
Interquartile range (IQR)55.75

Descriptive statistics

Standard deviation236.33494
Coefficient of variation (CV)1.8454055
Kurtosis12.021758
Mean128.06667
Median Absolute Deviation (MAD)26
Skewness3.4738426
Sum3842
Variance55854.202
MonotonicityNot monotonic
2024-03-14T12:06:47.080328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)
ValueCountFrequency (%)
32 2
 
6.7%
61 2
 
6.7%
819 1
 
3.3%
12 1
 
3.3%
57 1
 
3.3%
35 1
 
3.3%
90 1
 
3.3%
67 1
 
3.3%
13 1
 
3.3%
5 1
 
3.3%
Other values (18) 18
60.0%
ValueCountFrequency (%)
5 1
3.3%
12 1
3.3%
13 1
3.3%
19 1
3.3%
27 1
3.3%
28 1
3.3%
32 2
6.7%
35 1
3.3%
44 1
3.3%
45 1
3.3%
ValueCountFrequency (%)
1102 1
3.3%
819 1
3.3%
264 1
3.3%
214 1
3.3%
151 1
3.3%
125 1
3.3%
112 1
3.3%
90 1
3.3%
84 1
3.3%
80 1
3.3%

차상위장애인
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1341.5333
Minimum208
Maximum10979
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2024-03-14T12:06:47.216060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum208
5-th percentile217.7
Q1289
median615.5
Q31119.25
95-th percentile6018.75
Maximum10979
Range10771
Interquartile range (IQR)830.25

Descriptive statistics

Standard deviation2434.7706
Coefficient of variation (CV)1.8149162
Kurtosis11.570423
Mean1341.5333
Median Absolute Deviation (MAD)353
Skewness3.4663473
Sum40246
Variance5928107.6
MonotonicityNot monotonic
2024-03-14T12:06:47.330220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
9144 1
 
3.3%
208 1
 
3.3%
529 1
 
3.3%
443 1
 
3.3%
719 1
 
3.3%
610 1
 
3.3%
247 1
 
3.3%
221 1
 
3.3%
384 1
 
3.3%
328 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
208 1
3.3%
215 1
3.3%
221 1
3.3%
236 1
3.3%
239 1
3.3%
247 1
3.3%
261 1
3.3%
276 1
3.3%
328 1
3.3%
384 1
3.3%
ValueCountFrequency (%)
10979 1
3.3%
9144 1
3.3%
2199 1
3.3%
1779 1
3.3%
1484 1
3.3%
1425 1
3.3%
1230 1
3.3%
1170 1
3.3%
967 1
3.3%
910 1
3.3%

Interactions

2024-03-14T12:06:44.761830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T12:06:41.712372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T12:06:42.165920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T12:06:42.933152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T12:06:43.385136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T12:06:43.860450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T12:06:44.327523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T12:06:44.871551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T12:06:41.786772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T12:06:42.222973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T12:06:42.991400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T12:06:43.463006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T12:06:43.923898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T12:06:44.388388image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T12:06:44.980460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T12:06:41.844588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T12:06:42.289070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T12:06:43.055376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T12:06:43.533853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T12:06:44.000122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T12:06:44.445682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T12:06:45.053233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T12:06:41.906682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T12:06:42.349461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T12:06:43.122227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T12:06:43.601940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T12:06:44.069265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T12:06:44.506073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T12:06:45.132572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T12:06:41.964220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T12:06:42.410423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T12:06:43.193424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T12:06:43.667015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T12:06:44.140971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T12:06:44.563693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T12:06:45.210698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T12:06:42.034805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T12:06:42.783950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T12:06:43.255158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T12:06:43.730086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T12:06:44.202711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T12:06:44.624089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T12:06:45.279516image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T12:06:42.100565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T12:06:42.858587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T12:06:43.321097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T12:06:43.792677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T12:06:44.265794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T12:06:44.694864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-14T12:06:47.425494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군명합계(기초수급자수)일반수급자소계(법정차상위)한부모가족차상위본인부담경감대상자차상위자활사업참여자차상위장애인
시군명1.0001.0001.0001.0001.0001.0001.0001.000
합계(기초수급자수)1.0001.0001.0000.9990.9970.9970.9990.937
일반수급자1.0001.0001.0000.9990.9970.9970.9990.937
소계(법정차상위)1.0000.9990.9991.0000.9990.9990.9961.000
한부모가족1.0000.9970.9970.9991.0001.0000.9910.928
차상위본인부담경감대상자1.0000.9970.9970.9991.0001.0000.9910.928
차상위자활사업참여자1.0000.9990.9990.9960.9910.9911.0000.901
차상위장애인1.0000.9370.9371.0000.9280.9280.9011.000
2024-03-14T12:06:47.773841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
합계(기초수급자수)일반수급자소계(법정차상위)한부모가족차상위본인부담경감대상자차상위자활사업참여자차상위장애인
합계(기초수급자수)1.0000.9990.9710.9150.9590.8900.975
일반수급자0.9991.0000.9710.9190.9600.8980.974
소계(법정차상위)0.9710.9711.0000.9310.9930.9060.968
한부모가족0.9150.9190.9311.0000.9120.8730.907
차상위본인부담경감대상자0.9590.9600.9930.9121.0000.8830.943
차상위자활사업참여자0.8900.8980.9060.8730.8831.0000.909
차상위장애인0.9750.9740.9680.9070.9430.9091.000

Missing values

2024-03-14T12:06:45.366060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T12:06:45.469034image/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

시군명합계(기초수급자수)일반수급자시설수급자소계(법정차상위)한부모가족차상위본인부담경감대상자차상위자활사업참여자차상위장애인
0계(가구)64251588875364234091982114648199144
1(인원)8927589275NaN46049832225646110210979
2전주시 계(가구)1751016565945498171622722141779
3전주시 (인원)2654826548-12677310171132642199
4군산시 계(가구)9344855778729442381456801170
5군산시 (인원)1267212672-5994112733301121425
6익산시 계(가구)1125197651486333942315611251230
7익산시 (인원)1486314863-7172164938881511484
8정읍시 계(가구)519648573392379140137445820
9정읍시 (인원)71947194-3996548242259967
시군명합계(기초수급자수)일반수급자시설수급자소계(법정차상위)한부모가족차상위본인부담경감대상자차상위자활사업참여자차상위장애인
20장수군 계(가구)887856313842211532215
21장수군 (인원)12971297-6039520047261
22임실군 계(가구)11571070876042422032328
23임실군 (인원)15811581-9537744448384
24순창군 계(가구)93684393412161705221
25순창군 (인원)12551255-6188827013247
26고창군 계(가구)2136190423215716283267610
27고창군 (인원)25792579-2449258138290719
28부안군 계(가구)219521385712553973835443
29부안군 (인원)29562956-1997180123157529