Overview

Dataset statistics

Number of variables18
Number of observations341
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory53.7 KiB
Average record size in memory161.4 B

Variable types

Numeric15
Categorical3

Dataset

Description연령별 장애수당 수급자 집계현황
Author경기복지재단(경기도장애인복지종합지원센터)
URLhttps://data.gg.go.kr/portal/data/service/selectServicePage.do?&infId=S4XNZEWR3IZILI0SRMQF25646207&infSeq=1

Alerts

18세미만기초생활수급자수(명) has constant value ""Constant
18세미만차상위계층수급자수(명) has constant value ""Constant
전체총계(명) is highly overall correlated with 18세이상64세이하총계(명) and 10 other fieldsHigh correlation
18세미만총계(명) is highly overall correlated with 18세미만시설수급자수(명)High correlation
18세이상64세이하총계(명) is highly overall correlated with 전체총계(명) and 9 other fieldsHigh correlation
65세이상총계(명) is highly overall correlated with 전체총계(명) and 9 other fieldsHigh correlation
기초생활수급자합계(명) is highly overall correlated with 전체총계(명) and 9 other fieldsHigh correlation
18세이상64세이하기초생활수급자수(명) is highly overall correlated with 전체총계(명) and 9 other fieldsHigh correlation
65세이상기초생활수급자수(명) is highly overall correlated with 전체총계(명) and 8 other fieldsHigh correlation
시설수급자합계(명) is highly overall correlated with 전체총계(명) and 4 other fieldsHigh correlation
18세미만시설수급자수(명) is highly overall correlated with 18세미만총계(명)High correlation
18세이상64세이하시설수급자수(명) is highly overall correlated with 시설수급자합계(명) and 2 other fieldsHigh correlation
65세이상시설수급자수(명) is highly overall correlated with 전체총계(명) and 9 other fieldsHigh correlation
차상위계층수급자합계(명) is highly overall correlated with 전체총계(명) and 9 other fieldsHigh correlation
18세이상64세이하차상위계층수급자수(명) is highly overall correlated with 전체총계(명) and 8 other fieldsHigh correlation
65세이상차상위계층수급자수(명) is highly overall correlated with 전체총계(명) and 9 other fieldsHigh correlation
시군명 is highly overall correlated with 전체총계(명) and 6 other fieldsHigh correlation
18세미만총계(명) has 332 (97.4%) zerosZeros
18세미만시설수급자수(명) has 332 (97.4%) zerosZeros
18세이상64세이하시설수급자수(명) has 25 (7.3%) zerosZeros

Reproduction

Analysis started2024-03-12 23:38:46.448137
Analysis finished2024-03-12 23:39:05.406881
Duration18.96 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

기준년도
Real number (ℝ)

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
2024-03-13T08:39:05.446742image/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
2024-03-13T08:39:05.527912image/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

2024-03-13T08:39:05.815158image/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%

전체총계(명)
Real number (ℝ)

HIGH CORRELATION 

Distinct325
Distinct (%)95.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1835.2581
Minimum165
Maximum6486
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.1 KiB
2024-03-13T08:39:05.909606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum165
5-th percentile533
Q1963
median1389
Q32511
95-th percentile4290
Maximum6486
Range6321
Interquartile range (IQR)1548

Descriptive statistics

Standard deviation1210.4573
Coefficient of variation (CV)0.65955702
Kurtosis0.27162912
Mean1835.2581
Median Absolute Deviation (MAD)574
Skewness1.0321241
Sum625823
Variance1465207
MonotonicityNot monotonic
2024-03-13T08:39:06.029286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
784 2
 
0.6%
1330 2
 
0.6%
1402 2
 
0.6%
1278 2
 
0.6%
179 2
 
0.6%
1001 2
 
0.6%
859 2
 
0.6%
783 2
 
0.6%
1196 2
 
0.6%
688 2
 
0.6%
Other values (315) 321
94.1%
ValueCountFrequency (%)
165 1
0.3%
166 1
0.3%
167 1
0.3%
169 1
0.3%
171 1
0.3%
175 1
0.3%
179 2
0.6%
195 1
0.3%
197 1
0.3%
211 1
0.3%
ValueCountFrequency (%)
6486 1
0.3%
4951 1
0.3%
4927 1
0.3%
4904 1
0.3%
4834 1
0.3%
4766 1
0.3%
4655 1
0.3%
4653 1
0.3%
4620 1
0.3%
4584 1
0.3%

18세미만총계(명)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct7
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.55718475
Minimum0
Maximum108
Zeros332
Zeros (%)97.4%
Negative0
Negative (%)0.0%
Memory size3.1 KiB
2024-03-13T08:39:06.130398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum108
Range108
Interquartile range (IQR)0

Descriptive statistics

Standard deviation6.5219392
Coefficient of variation (CV)11.705165
Kurtosis229.06666
Mean0.55718475
Median Absolute Deviation (MAD)0
Skewness14.692084
Sum190
Variance42.535691
MonotonicityNot monotonic
2024-03-13T08:39:06.215706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0 332
97.4%
1 3
 
0.9%
6 2
 
0.6%
52 1
 
0.3%
5 1
 
0.3%
10 1
 
0.3%
108 1
 
0.3%
ValueCountFrequency (%)
0 332
97.4%
1 3
 
0.9%
5 1
 
0.3%
6 2
 
0.6%
10 1
 
0.3%
52 1
 
0.3%
108 1
 
0.3%
ValueCountFrequency (%)
108 1
 
0.3%
52 1
 
0.3%
10 1
 
0.3%
6 2
 
0.6%
5 1
 
0.3%
1 3
 
0.9%
0 332
97.4%

18세이상64세이하총계(명)
Real number (ℝ)

HIGH CORRELATION 

Distinct286
Distinct (%)83.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean868.90909
Minimum49
Maximum2599
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.1 KiB
2024-03-13T08:39:06.339139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum49
5-th percentile223
Q1455
median652
Q31110
95-th percentile2064
Maximum2599
Range2550
Interquartile range (IQR)655

Descriptive statistics

Standard deviation580.18092
Coefficient of variation (CV)0.66771188
Kurtosis-0.13824396
Mean868.90909
Median Absolute Deviation (MAD)295
Skewness0.96342029
Sum296298
Variance336609.9
MonotonicityNot monotonic
2024-03-13T08:39:06.450862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
246 4
 
1.2%
520 4
 
1.2%
698 3
 
0.9%
574 3
 
0.9%
455 3
 
0.9%
222 3
 
0.9%
543 3
 
0.9%
441 3
 
0.9%
431 2
 
0.6%
580 2
 
0.6%
Other values (276) 311
91.2%
ValueCountFrequency (%)
49 1
0.3%
55 2
0.6%
58 1
0.3%
60 1
0.3%
62 1
0.3%
66 1
0.3%
74 1
0.3%
76 1
0.3%
78 1
0.3%
94 1
0.3%
ValueCountFrequency (%)
2599 1
0.3%
2134 1
0.3%
2129 1
0.3%
2115 1
0.3%
2108 1
0.3%
2099 1
0.3%
2098 1
0.3%
2097 1
0.3%
2090 1
0.3%
2083 1
0.3%

65세이상총계(명)
Real number (ℝ)

HIGH CORRELATION 

Distinct300
Distinct (%)88.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean965.79179
Minimum105
Maximum3887
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.1 KiB
2024-03-13T08:39:06.556670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum105
5-th percentile279
Q1484
median721
Q31343
95-th percentile2422
Maximum3887
Range3782
Interquartile range (IQR)859

Descriptive statistics

Standard deviation671.95673
Coefficient of variation (CV)0.69575735
Kurtosis1.3948226
Mean965.79179
Median Absolute Deviation (MAD)306
Skewness1.30324
Sum329335
Variance451525.85
MonotonicityNot monotonic
2024-03-13T08:39:06.687316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
688 3
 
0.9%
487 3
 
0.9%
869 3
 
0.9%
434 3
 
0.9%
614 3
 
0.9%
686 3
 
0.9%
117 3
 
0.9%
473 2
 
0.6%
780 2
 
0.6%
1234 2
 
0.6%
Other values (290) 314
92.1%
ValueCountFrequency (%)
105 1
 
0.3%
107 1
 
0.3%
110 1
 
0.3%
111 2
0.6%
113 1
 
0.3%
117 3
0.9%
118 1
 
0.3%
121 1
 
0.3%
218 1
 
0.3%
223 1
 
0.3%
ValueCountFrequency (%)
3887 1
0.3%
3141 1
0.3%
3049 1
0.3%
2980 1
0.3%
2872 1
0.3%
2752 1
0.3%
2709 1
0.3%
2706 1
0.3%
2696 1
0.3%
2622 1
0.3%

기초생활수급자합계(명)
Real number (ℝ)

HIGH CORRELATION 

Distinct306
Distinct (%)89.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1201.607
Minimum89
Maximum5117
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.1 KiB
2024-03-13T08:39:06.803946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum89
5-th percentile322
Q1604
median901
Q31610
95-th percentile2861
Maximum5117
Range5028
Interquartile range (IQR)1006

Descriptive statistics

Standard deviation847.724
Coefficient of variation (CV)0.70549187
Kurtosis1.1204271
Mean1201.607
Median Absolute Deviation (MAD)419
Skewness1.209511
Sum409748
Variance718635.98
MonotonicityNot monotonic
2024-03-13T08:39:06.941161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1000 4
 
1.2%
408 3
 
0.9%
89 3
 
0.9%
735 3
 
0.9%
401 2
 
0.6%
389 2
 
0.6%
480 2
 
0.6%
1286 2
 
0.6%
747 2
 
0.6%
760 2
 
0.6%
Other values (296) 316
92.7%
ValueCountFrequency (%)
89 3
0.9%
94 1
 
0.3%
95 1
 
0.3%
103 1
 
0.3%
107 1
 
0.3%
109 1
 
0.3%
117 1
 
0.3%
119 1
 
0.3%
138 1
 
0.3%
240 1
 
0.3%
ValueCountFrequency (%)
5117 1
0.3%
3712 1
0.3%
3601 1
0.3%
3458 1
0.3%
3333 1
0.3%
3332 1
0.3%
3275 1
0.3%
3246 1
0.3%
3231 1
0.3%
3179 1
0.3%
Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
0
341 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 341
100.0%

Length

2024-03-13T08:39:07.056310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T08:39:07.136602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 341
100.0%

18세이상64세이하기초생활수급자수(명)
Real number (ℝ)

HIGH CORRELATION 

Distinct288
Distinct (%)84.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean679.41935
Minimum36
Maximum2323
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.1 KiB
2024-03-13T08:39:07.233313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36
5-th percentile167
Q1355
median506
Q3915
95-th percentile1689
Maximum2323
Range2287
Interquartile range (IQR)560

Descriptive statistics

Standard deviation472.67272
Coefficient of variation (CV)0.69570099
Kurtosis0.091380788
Mean679.41935
Median Absolute Deviation (MAD)240
Skewness1.0196942
Sum231682
Variance223419.5
MonotonicityNot monotonic
2024-03-13T08:39:07.349131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
570 4
 
1.2%
465 3
 
0.9%
458 3
 
0.9%
401 3
 
0.9%
355 3
 
0.9%
404 2
 
0.6%
389 2
 
0.6%
1710 2
 
0.6%
1699 2
 
0.6%
499 2
 
0.6%
Other values (278) 315
92.4%
ValueCountFrequency (%)
36 1
0.3%
37 2
0.6%
41 1
0.3%
42 1
0.3%
45 1
0.3%
49 1
0.3%
56 1
0.3%
57 1
0.3%
60 1
0.3%
74 1
0.3%
ValueCountFrequency (%)
2323 1
0.3%
1744 1
0.3%
1739 1
0.3%
1737 1
0.3%
1733 1
0.3%
1729 2
0.6%
1725 1
0.3%
1721 1
0.3%
1718 1
0.3%
1710 2
0.6%

65세이상기초생활수급자수(명)
Real number (ℝ)

HIGH CORRELATION 

Distinct286
Distinct (%)83.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean522.18768
Minimum47
Maximum2794
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.1 KiB
2024-03-13T08:39:07.460535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum47
5-th percentile119
Q1250
median382
Q3722
95-th percentile1327
Maximum2794
Range2747
Interquartile range (IQR)472

Descriptive statistics

Standard deviation401.32275
Coefficient of variation (CV)0.7685412
Kurtosis3.9136381
Mean522.18768
Median Absolute Deviation (MAD)174
Skewness1.7113464
Sum178066
Variance161059.95
MonotonicityNot monotonic
2024-03-13T08:39:07.564307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
307 3
 
0.9%
270 3
 
0.9%
192 3
 
0.9%
297 3
 
0.9%
206 3
 
0.9%
1653 2
 
0.6%
331 2
 
0.6%
248 2
 
0.6%
329 2
 
0.6%
243 2
 
0.6%
Other values (276) 316
92.7%
ValueCountFrequency (%)
47 1
0.3%
48 1
0.3%
49 1
0.3%
52 1
0.3%
53 1
0.3%
58 2
0.6%
59 1
0.3%
60 1
0.3%
64 1
0.3%
67 1
0.3%
ValueCountFrequency (%)
2794 1
0.3%
2099 1
0.3%
1868 1
0.3%
1814 1
0.3%
1758 1
0.3%
1721 1
0.3%
1653 2
0.6%
1607 1
0.3%
1521 1
0.3%
1501 1
0.3%

시설수급자합계(명)
Real number (ℝ)

HIGH CORRELATION 

Distinct159
Distinct (%)46.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean76.01173
Minimum0
Maximum507
Zeros1
Zeros (%)0.3%
Negative0
Negative (%)0.0%
Memory size3.1 KiB
2024-03-13T08:39:07.674862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile12
Q125
median49
Q3108
95-th percentile221
Maximum507
Range507
Interquartile range (IQR)83

Descriptive statistics

Standard deviation70.576532
Coefficient of variation (CV)0.92849528
Kurtosis4.5567287
Mean76.01173
Median Absolute Deviation (MAD)30
Skewness1.7835061
Sum25920
Variance4981.0469
MonotonicityNot monotonic
2024-03-13T08:39:07.783450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
21 8
 
2.3%
24 7
 
2.1%
16 7
 
2.1%
34 7
 
2.1%
31 7
 
2.1%
22 7
 
2.1%
26 7
 
2.1%
12 6
 
1.8%
38 6
 
1.8%
23 6
 
1.8%
Other values (149) 273
80.1%
ValueCountFrequency (%)
0 1
 
0.3%
1 2
0.6%
4 1
 
0.3%
5 2
0.6%
6 1
 
0.3%
7 2
0.6%
8 2
0.6%
9 2
0.6%
10 1
 
0.3%
11 3
0.9%
ValueCountFrequency (%)
507 1
0.3%
306 1
0.3%
302 1
0.3%
299 1
0.3%
295 1
0.3%
278 1
0.3%
273 1
0.3%
270 1
0.3%
262 1
0.3%
259 1
0.3%

18세미만시설수급자수(명)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct7
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.55718475
Minimum0
Maximum108
Zeros332
Zeros (%)97.4%
Negative0
Negative (%)0.0%
Memory size3.1 KiB
2024-03-13T08:39:07.875716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile0
Maximum108
Range108
Interquartile range (IQR)0

Descriptive statistics

Standard deviation6.5219392
Coefficient of variation (CV)11.705165
Kurtosis229.06666
Mean0.55718475
Median Absolute Deviation (MAD)0
Skewness14.692084
Sum190
Variance42.535691
MonotonicityNot monotonic
2024-03-13T08:39:07.974076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0 332
97.4%
1 3
 
0.9%
6 2
 
0.6%
52 1
 
0.3%
5 1
 
0.3%
10 1
 
0.3%
108 1
 
0.3%
ValueCountFrequency (%)
0 332
97.4%
1 3
 
0.9%
5 1
 
0.3%
6 2
 
0.6%
10 1
 
0.3%
52 1
 
0.3%
108 1
 
0.3%
ValueCountFrequency (%)
108 1
 
0.3%
52 1
 
0.3%
10 1
 
0.3%
6 2
 
0.6%
5 1
 
0.3%
1 3
 
0.9%
0 332
97.4%

18세이상64세이하시설수급자수(명)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct74
Distinct (%)21.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean23.671554
Minimum0
Maximum188
Zeros25
Zeros (%)7.3%
Negative0
Negative (%)0.0%
Memory size3.1 KiB
2024-03-13T08:39:08.074799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q14
median10
Q323
95-th percentile92
Maximum188
Range188
Interquartile range (IQR)19

Descriptive statistics

Standard deviation34.905975
Coefficient of variation (CV)1.4745958
Kurtosis6.295105
Mean23.671554
Median Absolute Deviation (MAD)7
Skewness2.4194248
Sum8072
Variance1218.4271
MonotonicityNot monotonic
2024-03-13T08:39:08.190732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 25
 
7.3%
2 21
 
6.2%
1 19
 
5.6%
3 19
 
5.6%
4 18
 
5.3%
5 18
 
5.3%
12 15
 
4.4%
6 12
 
3.5%
8 12
 
3.5%
9 12
 
3.5%
Other values (64) 170
49.9%
ValueCountFrequency (%)
0 25
7.3%
1 19
5.6%
2 21
6.2%
3 19
5.6%
4 18
5.3%
5 18
5.3%
6 12
3.5%
7 11
3.2%
8 12
3.5%
9 12
3.5%
ValueCountFrequency (%)
188 1
0.3%
186 2
0.6%
179 1
0.3%
166 1
0.3%
154 1
0.3%
141 1
0.3%
132 1
0.3%
130 1
0.3%
127 1
0.3%
118 1
0.3%

65세이상시설수급자수(명)
Real number (ℝ)

HIGH CORRELATION 

Distinct123
Distinct (%)36.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean51.782991
Minimum0
Maximum375
Zeros2
Zeros (%)0.6%
Negative0
Negative (%)0.0%
Memory size3.1 KiB
2024-03-13T08:39:08.319085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile10
Q120
median36
Q373
95-th percentile138
Maximum375
Range375
Interquartile range (IQR)53

Descriptive statistics

Standard deviation45.867711
Coefficient of variation (CV)0.88576789
Kurtosis7.5572558
Mean51.782991
Median Absolute Deviation (MAD)19
Skewness2.0272508
Sum17658
Variance2103.8469
MonotonicityNot monotonic
2024-03-13T08:39:08.435415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
21 12
 
3.5%
20 11
 
3.2%
19 10
 
2.9%
17 10
 
2.9%
28 9
 
2.6%
22 8
 
2.3%
31 8
 
2.3%
14 8
 
2.3%
24 8
 
2.3%
10 7
 
2.1%
Other values (113) 250
73.3%
ValueCountFrequency (%)
0 2
 
0.6%
1 1
 
0.3%
2 2
 
0.6%
5 3
0.9%
6 4
1.2%
8 2
 
0.6%
9 3
0.9%
10 7
2.1%
11 6
1.8%
12 3
0.9%
ValueCountFrequency (%)
375 1
0.3%
244 1
0.3%
189 1
0.3%
186 1
0.3%
183 1
0.3%
178 1
0.3%
171 1
0.3%
160 1
0.3%
159 1
0.3%
151 1
0.3%

차상위계층수급자합계(명)
Real number (ℝ)

HIGH CORRELATION 

Distinct285
Distinct (%)83.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean557.6393
Minimum0
Maximum1481
Zeros1
Zeros (%)0.3%
Negative0
Negative (%)0.0%
Memory size3.1 KiB
2024-03-13T08:39:08.543433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile162
Q1284
median419
Q3761
95-th percentile1239
Maximum1481
Range1481
Interquartile range (IQR)477

Descriptive statistics

Standard deviation355.11453
Coefficient of variation (CV)0.63681763
Kurtosis-0.424763
Mean557.6393
Median Absolute Deviation (MAD)186
Skewness0.82559626
Sum190155
Variance126106.33
MonotonicityNot monotonic
2024-03-13T08:39:08.650253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
394 5
 
1.5%
268 3
 
0.9%
266 3
 
0.9%
324 3
 
0.9%
263 3
 
0.9%
330 3
 
0.9%
272 3
 
0.9%
406 3
 
0.9%
354 3
 
0.9%
455 2
 
0.6%
Other values (275) 310
90.9%
ValueCountFrequency (%)
0 1
0.3%
53 1
0.3%
54 1
0.3%
56 1
0.3%
58 2
0.6%
60 1
0.3%
61 1
0.3%
62 1
0.3%
64 1
0.3%
70 2
0.6%
ValueCountFrequency (%)
1481 1
0.3%
1472 1
0.3%
1406 2
0.6%
1372 1
0.3%
1355 1
0.3%
1346 1
0.3%
1343 1
0.3%
1341 1
0.3%
1307 2
0.6%
1293 1
0.3%
Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
0
341 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 341
100.0%

Length

2024-03-13T08:39:08.751073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T08:39:08.830624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 341
100.0%

18세이상64세이하차상위계층수급자수(명)
Real number (ℝ)

HIGH CORRELATION 

Distinct208
Distinct (%)61.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean165.81818
Minimum0
Maximum618
Zeros1
Zeros (%)0.3%
Negative0
Negative (%)0.0%
Memory size3.1 KiB
2024-03-13T08:39:08.918609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile30
Q180
median129
Q3222
95-th percentile384
Maximum618
Range618
Interquartile range (IQR)142

Descriptive statistics

Standard deviation116.54861
Coefficient of variation (CV)0.70286991
Kurtosis0.38020395
Mean165.81818
Median Absolute Deviation (MAD)64
Skewness1.0192601
Sum56544
Variance13583.579
MonotonicityNot monotonic
2024-03-13T08:39:09.022845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
123 7
 
2.1%
88 5
 
1.5%
132 5
 
1.5%
380 4
 
1.2%
76 4
 
1.2%
65 4
 
1.2%
194 4
 
1.2%
134 4
 
1.2%
101 4
 
1.2%
75 4
 
1.2%
Other values (198) 296
86.8%
ValueCountFrequency (%)
0 1
 
0.3%
2 1
 
0.3%
13 1
 
0.3%
16 2
0.6%
17 2
0.6%
18 3
0.9%
19 1
 
0.3%
20 1
 
0.3%
21 1
 
0.3%
23 2
0.6%
ValueCountFrequency (%)
618 1
0.3%
545 1
0.3%
483 1
0.3%
479 1
0.3%
470 1
0.3%
434 1
0.3%
430 1
0.3%
416 1
0.3%
409 2
0.6%
407 1
0.3%

65세이상차상위계층수급자수(명)
Real number (ℝ)

HIGH CORRELATION 

Distinct263
Distinct (%)77.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean391.82111
Minimum0
Maximum1138
Zeros1
Zeros (%)0.3%
Negative0
Negative (%)0.0%
Memory size3.1 KiB
2024-03-13T08:39:09.409735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile116
Q1202
median305
Q3545
95-th percentile922
Maximum1138
Range1138
Interquartile range (IQR)343

Descriptive statistics

Standard deviation259.13717
Coefficient of variation (CV)0.66136601
Kurtosis0.1252339
Mean391.82111
Median Absolute Deviation (MAD)137
Skewness1.0023482
Sum133611
Variance67152.071
MonotonicityNot monotonic
2024-03-13T08:39:09.523975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
207 4
 
1.2%
249 3
 
0.9%
262 3
 
0.9%
565 3
 
0.9%
324 3
 
0.9%
173 3
 
0.9%
576 3
 
0.9%
168 3
 
0.9%
454 3
 
0.9%
267 3
 
0.9%
Other values (253) 310
90.9%
ValueCountFrequency (%)
0 1
0.3%
34 1
0.3%
35 1
0.3%
40 1
0.3%
41 1
0.3%
42 2
0.6%
43 1
0.3%
44 1
0.3%
47 1
0.3%
51 1
0.3%
ValueCountFrequency (%)
1138 1
0.3%
1115 1
0.3%
1105 1
0.3%
1086 1
0.3%
1059 1
0.3%
1041 1
0.3%
1026 1
0.3%
1011 1
0.3%
990 2
0.6%
988 1
0.3%

Interactions

2024-03-13T08:39:03.944588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:38:47.024825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:38:48.072584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:38:49.195841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:38:50.448289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:38:51.865413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:38:53.083698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:38:54.199383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:38:55.327313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:38:56.677522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:38:57.877992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:38:58.978957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:39:00.229153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:39:01.630754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:39:02.802668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:39:04.012081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:38:47.084835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:38:48.154669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:38:49.261254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:38:50.519721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:38:51.950771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:38:53.157055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:38:54.264637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:38:55.392953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:38:56.746242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:38:57.942126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:38:59.062569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:39:00.296465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:39:01.711481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:39:02.894125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:39:04.081859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:38:47.151073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:38:48.236390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:38:49.333174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:38:50.609421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:38:52.033919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:38:53.230446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:38:54.351140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:38:55.459321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:38:56.821752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:38:58.012575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:38:59.148369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:39:00.367092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:39:01.796904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:39:02.971221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:39:04.157459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:38:47.216578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:38:48.304300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:38:49.406963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:38:50.682501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:38:52.107189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:38:53.305813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:38:54.430415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:38:55.533880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:38:56.896735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:38:58.085848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:38:59.231906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:39:00.435928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:39:01.887911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:39:03.046024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:39:04.236916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:38:47.280377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:38:48.369851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:38:49.490528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:38:50.771582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:38:52.196398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:38:53.377550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:38:54.498088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:38:55.612026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:38:56.996133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:38:58.151216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:38:59.328257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:39:00.503739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:39:01.973622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:39:03.124730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:39:04.328712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:38:47.352725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:38:48.443608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:38:49.614700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:38:50.859238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:38:52.284570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:38:53.466113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:38:54.578101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:38:55.683949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:38:57.075118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:38:58.226431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:38:59.442892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:39:00.585323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:39:02.066145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:39:03.206736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:39:04.409066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:38:47.415497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:38:48.524642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:38:49.701008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:38:50.951621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:38:52.356733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:38:53.532837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:38:54.651420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:38:55.748366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:38:57.146609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:38:58.291318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:38:59.538576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:39:00.668087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:39:02.137001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:39:03.281179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:39:04.473716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:38:47.475498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:38:48.601422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:38:49.783223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:38:51.042356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:38:52.430046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:38:53.599587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:38:54.712835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:38:55.809423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:38:57.218095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:38:58.364747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:38:59.618079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:39:00.751412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:39:02.208979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:39:03.350632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:39:04.543751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:38:47.544950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:38:48.680680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:38:49.855186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:38:51.140181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:38:52.514721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:38:53.678914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:38:54.779381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:38:55.875829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:38:57.298692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:38:58.437131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:38:59.689687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:39:00.828628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:39:02.284512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:39:03.419879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:39:04.610824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:38:47.620355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:38:48.759059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:38:49.929537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:38:51.217438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:38:52.587561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:38:53.748885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:38:54.861724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:38:55.952195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:38:57.374463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:38:58.508727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:38:59.757687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:39:00.911117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:39:02.357753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:39:03.488025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:39:04.680552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:38:47.695030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:38:48.834416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:38:50.010962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:38:51.292565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:38:52.660935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:38:53.816103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:38:54.930693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:38:56.033500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:38:57.440897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:38:58.580036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:38:59.838818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:39:01.237200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:39:02.424155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:39:03.556016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:39:04.756309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:38:47.768634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:38:48.909997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:38:50.095811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:38:51.382619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:38:52.740561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:38:53.890641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:38:55.004315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:38:56.119521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:38:57.558938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:38:58.652296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:38:59.919755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:39:01.312443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:39:02.501542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:39:03.632991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:39:04.839195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:38:47.852184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:38:48.982395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:38:50.204393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:38:51.456482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:38:52.820221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:38:53.967055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:38:55.096561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:38:56.193151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:38:57.639648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:38:58.743811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:38:59.994593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:39:01.387322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:39:02.577374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:39:03.707198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:39:04.913096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:38:47.932843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:38:49.055457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:38:50.280383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:38:51.723486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:38:52.912947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:38:54.040692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:38:55.178777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:38:56.531737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:38:57.728890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:38:58.820647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:39:00.083145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:39:01.470933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:39:02.651337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:39:03.792379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:39:04.990999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:38:48.002318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:38:49.127128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:38:50.377002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:38:51.790953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:38:52.994382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:38:54.122119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:38:55.256059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:38:56.604876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:38:57.805637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:38:58.896506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:39:00.160921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:39:01.549021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:39:02.721390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:39:03.870935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-13T08:39:09.614077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기준년도시군명전체총계(명)18세미만총계(명)18세이상64세이하총계(명)65세이상총계(명)기초생활수급자합계(명)18세이상64세이하기초생활수급자수(명)65세이상기초생활수급자수(명)시설수급자합계(명)18세미만시설수급자수(명)18세이상64세이하시설수급자수(명)65세이상시설수급자수(명)차상위계층수급자합계(명)18세이상64세이하차상위계층수급자수(명)65세이상차상위계층수급자수(명)
기준년도1.0000.0000.144NaN0.0000.3620.1510.0000.2280.000NaN0.0000.0820.0000.0000.228
시군명0.0001.0000.8650.0340.9470.7210.8490.9430.7010.8360.0340.8940.7110.9000.8670.842
전체총계(명)0.1440.8651.0000.0000.8740.8940.9740.9470.9580.4560.0000.4010.5780.8340.7620.777
18세미만총계(명)NaN0.0340.0001.0000.3800.0000.0000.5420.0000.2471.0000.0000.0000.1010.0000.000
18세이상64세이하총계(명)0.0000.9470.8740.3801.0000.9050.8640.9420.7860.4740.3800.5700.5790.8750.9060.827
65세이상총계(명)0.3620.7210.8940.0000.9051.0000.8860.7960.9140.5140.0000.4830.7650.9100.8020.910
기초생활수급자합계(명)0.1510.8490.9740.0000.8640.8861.0000.9570.9760.3840.0000.2940.5370.7640.7500.723
18세이상64세이하기초생활수급자수(명)0.0000.9430.9470.5420.9420.7960.9571.0000.9040.4780.5420.5270.5440.7570.7930.687
65세이상기초생활수급자수(명)0.2280.7010.9580.0000.7860.9140.9760.9041.0000.4100.0000.2840.6100.7340.6340.736
시설수급자합계(명)0.0000.8360.4560.2470.4740.5140.3840.4780.4101.0000.2470.8180.9280.4870.4850.517
18세미만시설수급자수(명)NaN0.0340.0001.0000.3800.0000.0000.5420.0000.2471.0000.0000.0000.1010.0000.000
18세이상64세이하시설수급자수(명)0.0000.8940.4010.0000.5700.4830.2940.5270.2840.8180.0001.0000.6640.6090.5260.608
65세이상시설수급자수(명)0.0820.7110.5780.0000.5790.7650.5370.5440.6100.9280.0000.6641.0000.5610.4310.620
차상위계층수급자합계(명)0.0000.9000.8340.1010.8750.9100.7640.7570.7340.4870.1010.6090.5611.0000.8700.961
18세이상64세이하차상위계층수급자수(명)0.0000.8670.7620.0000.9060.8020.7500.7930.6340.4850.0000.5260.4310.8701.0000.813
65세이상차상위계층수급자수(명)0.2280.8420.7770.0000.8270.9100.7230.6870.7360.5170.0000.6080.6200.9610.8131.000
2024-03-13T08:39:09.760447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기준년도전체총계(명)18세미만총계(명)18세이상64세이하총계(명)65세이상총계(명)기초생활수급자합계(명)18세이상64세이하기초생활수급자수(명)65세이상기초생활수급자수(명)시설수급자합계(명)18세미만시설수급자수(명)18세이상64세이하시설수급자수(명)65세이상시설수급자수(명)차상위계층수급자합계(명)18세이상64세이하차상위계층수급자수(명)65세이상차상위계층수급자수(명)시군명
기준년도1.0000.198-0.255-0.0000.3660.2040.0650.3640.157-0.2550.0330.2510.162-0.2150.3220.000
전체총계(명)0.1981.000-0.0550.9700.9770.9900.9750.9600.538-0.0550.3010.6630.9690.8700.9510.532
18세미만총계(명)-0.255-0.0551.000-0.031-0.094-0.056-0.038-0.0930.0221.0000.020-0.070-0.0370.048-0.0800.000
18세이상64세이하총계(명)-0.0000.970-0.0311.0000.9040.9640.9890.8910.497-0.0310.2850.6050.9410.9320.8850.701
65세이상총계(명)0.3660.977-0.0940.9041.0000.9650.9200.9800.545-0.0940.3010.6840.9490.7760.9690.337
기초생활수급자합계(명)0.2040.990-0.0560.9640.9651.0000.9830.9720.465-0.0560.2250.6050.9410.8500.9220.506
18세이상64세이하기초생활수급자수(명)0.0650.975-0.0380.9890.9200.9831.0000.9180.449-0.0380.2200.5800.9350.8980.8920.709
65세이상기초생활수급자수(명)0.3640.960-0.0930.8910.9800.9720.9181.0000.462-0.0930.2150.6170.9020.7480.9160.336
시설수급자합계(명)0.1570.5380.0220.4970.5450.4650.4490.4621.0000.0220.8750.9240.4980.4150.5170.497
18세미만시설수급자수(명)-0.255-0.0551.000-0.031-0.094-0.056-0.038-0.0930.0221.0000.020-0.070-0.0370.048-0.0800.000
18세이상64세이하시설수급자수(명)0.0330.3010.0200.2850.3010.2250.2200.2150.8750.0201.0000.6800.2940.2540.3080.566
65세이상시설수급자수(명)0.2510.663-0.0700.6050.6840.6050.5800.6170.924-0.0700.6801.0000.6060.4870.6320.356
차상위계층수급자합계(명)0.1620.969-0.0370.9410.9490.9410.9350.9020.498-0.0370.2940.6061.0000.9000.9790.578
18세이상64세이하차상위계층수급자수(명)-0.2150.8700.0480.9320.7760.8500.8980.7480.4150.0480.2540.4870.9001.0000.8030.514
65세이상차상위계층수급자수(명)0.3220.951-0.0800.8850.9690.9220.8920.9160.517-0.0800.3080.6320.9790.8031.0000.474
시군명0.0000.5320.0000.7010.3370.5060.7090.3360.4970.0000.5660.3560.5780.5140.4741.000

Missing values

2024-03-13T08:39:05.107903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-13T08:39:05.331348image/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

기준년도시군명전체총계(명)18세미만총계(명)18세이상64세이하총계(명)65세이상총계(명)기초생활수급자합계(명)18세미만기초생활수급자수(명)18세이상64세이하기초생활수급자수(명)65세이상기초생활수급자수(명)시설수급자합계(명)18세미만시설수급자수(명)18세이상64세이하시설수급자수(명)65세이상시설수급자수(명)차상위계층수급자합계(명)18세미만차상위계층수급자수(명)18세이상64세이하차상위계층수급자수(명)65세이상차상위계층수급자수(명)
02023가평군845031752847401872872080107101163023140
12023고양시49510181031413275014611814270081189140602681138
22023과천시1670491181030366780085601343
32023광명시1400053186910250453572210219354076278
42023광주시1464057489094604684783803354800103377
52023구리시106704306377870363424160214264065199
62023군포시16260574105211520484668680860406082324
72023김포시2085071113741382058779567017506360107529
82023남양주시41200136827522554011051449273029244129302341059
92023동두천시14160527889882040148114004595394081313
기준년도시군명전체총계(명)18세미만총계(명)18세이상64세이하총계(명)65세이상총계(명)기초생활수급자합계(명)18세미만기초생활수급자수(명)18세이상64세이하기초생활수급자수(명)65세이상기초생활수급자수(명)시설수급자합계(명)18세미만시설수급자수(명)18세이상64세이하시설수급자수(명)65세이상시설수급자수(명)차상위계층수급자합계(명)18세미만차상위계층수급자수(명)18세이상64세이하차상위계층수급자수(명)65세이상차상위계층수급자수(명)
3312013오산시67104312404010284117720666198081117
3322013용인시15310844687896057232493054395420218324
3332013의왕시4851241243251015893381037196083113
3342013의정부시2277613109611556010055516465536570300357
3352013이천시10211540480603039021351118323670132235
3362013파주시17510884867110906314783709286050244361
3372013평택시1953011158381338085548335016195800244336
3382013포천시1294069859679105062854807414550185270
3392013하남시6280328300346020713910102810120161
3402013화성시1453081963474504902551590106535490223326