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

Numeric13
Categorical5

Dataset

Description연령별 장애아동수당 수급자 집계현황
Author경기복지재단(경기도장애인복지종합지원센터)
URLhttps://data.gg.go.kr/portal/data/service/selectServicePage.do?&infId=XAXEHLVZQSWKIR9SW77M25701717&infSeq=1

Alerts

전체총계(명) is highly overall correlated with 18세미만총계(명) and 10 other fieldsHigh correlation
18세미만총계(명) is highly overall correlated with 전체총계(명) and 10 other fieldsHigh correlation
18세이상20세이하총계(명) is highly overall correlated with 전체총계(명) and 10 other fieldsHigh correlation
기초생활수급자합계(명) is highly overall correlated with 전체총계(명) and 8 other fieldsHigh correlation
18세미만기초생활수급자수(명) is highly overall correlated with 전체총계(명) and 8 other fieldsHigh correlation
18세이상20세이하기초생활수급자수(명) is highly overall correlated with 전체총계(명) and 7 other fieldsHigh correlation
시설수급자합계(명) is highly overall correlated with 전체총계(명) and 4 other fieldsHigh correlation
18세미만시설수급자수(명) is highly overall correlated with 전체총계(명) and 4 other fieldsHigh correlation
18세이상20세이하시설수급자수(명) is highly overall correlated with 18세이상20세이하총계(명) and 2 other fieldsHigh correlation
차상위계층수급자합계(명) is highly overall correlated with 전체총계(명) and 8 other fieldsHigh correlation
18세미만차상위계층수급자수(명) is highly overall correlated with 전체총계(명) and 8 other fieldsHigh correlation
18세이상20세이하차상위계층수급자수(명) is highly overall correlated with 전체총계(명) and 7 other fieldsHigh correlation
시군명 is highly overall correlated with 전체총계(명) and 5 other fieldsHigh correlation
20세초과총계(명) is highly overall correlated with 20세초과기초생활수급자수(명) and 1 other fieldsHigh correlation
20세초과기초생활수급자수(명) is highly overall correlated with 20세초과총계(명)High correlation
20세초과시설수급자수(명) is highly overall correlated with 20세초과총계(명)High correlation
20세초과총계(명) is highly imbalanced (78.1%)Imbalance
20세초과기초생활수급자수(명) is highly imbalanced (89.8%)Imbalance
20세초과시설수급자수(명) is highly imbalanced (86.6%)Imbalance
20세초과차상위계층수급자수(명) is highly imbalanced (92.7%)Imbalance
18세이상20세이하총계(명) has 4 (1.2%) zerosZeros
18세이상20세이하기초생활수급자수(명) has 10 (2.9%) zerosZeros
시설수급자합계(명) has 66 (19.4%) zerosZeros
18세미만시설수급자수(명) has 76 (22.3%) zerosZeros
18세이상20세이하시설수급자수(명) has 149 (43.7%) zerosZeros
18세이상20세이하차상위계층수급자수(명) has 28 (8.2%) zerosZeros

Reproduction

Analysis started2024-03-23 02:50:26.145149
Analysis finished2024-03-23 02:51:11.891959
Duration45.75 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
2024-03-23T02:51:12.044741image/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
2024-03-23T02:51:12.415855image/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

2024-03-23T02:51:12.814796image/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 

Distinct186
Distinct (%)54.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean111.75367
Minimum8
Maximum359
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.1 KiB
2024-03-23T02:51:13.196654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum8
5-th percentile22
Q152
median97
Q3156
95-th percentile263
Maximum359
Range351
Interquartile range (IQR)104

Descriptive statistics

Standard deviation73.964167
Coefficient of variation (CV)0.66185003
Kurtosis0.46659071
Mean111.75367
Median Absolute Deviation (MAD)50
Skewness0.9358538
Sum38108
Variance5470.698
MonotonicityNot monotonic
2024-03-23T02:51:13.704959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
52 7
 
2.1%
56 5
 
1.5%
45 5
 
1.5%
27 5
 
1.5%
97 4
 
1.2%
21 4
 
1.2%
22 4
 
1.2%
51 4
 
1.2%
102 4
 
1.2%
46 4
 
1.2%
Other values (176) 295
86.5%
ValueCountFrequency (%)
8 2
0.6%
9 1
 
0.3%
10 1
 
0.3%
11 2
0.6%
12 2
0.6%
13 2
0.6%
20 3
0.9%
21 4
1.2%
22 4
1.2%
23 1
 
0.3%
ValueCountFrequency (%)
359 1
0.3%
337 1
0.3%
331 1
0.3%
328 1
0.3%
322 1
0.3%
317 1
0.3%
311 1
0.3%
306 1
0.3%
296 2
0.6%
278 1
0.3%

18세미만총계(명)
Real number (ℝ)

HIGH CORRELATION 

Distinct172
Distinct (%)50.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean94.774194
Minimum7
Maximum306
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.1 KiB
2024-03-23T02:51:14.203468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7
5-th percentile17
Q144
median83
Q3132
95-th percentile213
Maximum306
Range299
Interquartile range (IQR)88

Descriptive statistics

Standard deviation63.226428
Coefficient of variation (CV)0.66712705
Kurtosis0.4527102
Mean94.774194
Median Absolute Deviation (MAD)41
Skewness0.93524666
Sum32318
Variance3997.5812
MonotonicityNot monotonic
2024-03-23T02:51:14.629791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
42 7
 
2.1%
41 7
 
2.1%
57 6
 
1.8%
45 6
 
1.8%
17 5
 
1.5%
23 5
 
1.5%
85 5
 
1.5%
44 5
 
1.5%
67 4
 
1.2%
25 4
 
1.2%
Other values (162) 287
84.2%
ValueCountFrequency (%)
7 1
 
0.3%
8 3
0.9%
9 2
 
0.6%
10 1
 
0.3%
11 1
 
0.3%
12 2
 
0.6%
15 1
 
0.3%
16 2
 
0.6%
17 5
1.5%
18 3
0.9%
ValueCountFrequency (%)
306 1
0.3%
288 1
0.3%
286 1
0.3%
273 1
0.3%
266 1
0.3%
263 1
0.3%
257 1
0.3%
255 1
0.3%
254 1
0.3%
253 1
0.3%

18세이상20세이하총계(명)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct54
Distinct (%)15.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean16.909091
Minimum0
Maximum74
Zeros4
Zeros (%)1.2%
Negative0
Negative (%)0.0%
Memory size3.1 KiB
2024-03-23T02:51:14.937954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2
Q17
median14
Q322
95-th percentile44
Maximum74
Range74
Interquartile range (IQR)15

Descriptive statistics

Standard deviation12.904876
Coefficient of variation (CV)0.7631916
Kurtosis1.9838713
Mean16.909091
Median Absolute Deviation (MAD)7
Skewness1.3301096
Sum5766
Variance166.53583
MonotonicityNot monotonic
2024-03-23T02:51:15.406468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5 17
 
5.0%
4 17
 
5.0%
11 16
 
4.7%
14 15
 
4.4%
18 13
 
3.8%
10 13
 
3.8%
7 13
 
3.8%
15 12
 
3.5%
12 12
 
3.5%
2 12
 
3.5%
Other values (44) 201
58.9%
ValueCountFrequency (%)
0 4
 
1.2%
1 6
 
1.8%
2 12
3.5%
3 10
2.9%
4 17
5.0%
5 17
5.0%
6 10
2.9%
7 13
3.8%
8 9
2.6%
9 11
3.2%
ValueCountFrequency (%)
74 1
0.3%
64 1
0.3%
59 1
0.3%
57 1
0.3%
56 1
0.3%
55 1
0.3%
54 1
0.3%
53 2
0.6%
52 1
0.3%
49 2
0.6%

20세초과총계(명)
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
0
323 
1
 
12
2
 
6

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 (%)
0 323
94.7%
1 12
 
3.5%
2 6
 
1.8%

Length

2024-03-23T02:51:15.836326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-23T02:51:16.158130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 323
94.7%
1 12
 
3.5%
2 6
 
1.8%

기초생활수급자합계(명)
Real number (ℝ)

HIGH CORRELATION 

Distinct116
Distinct (%)34.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean54.175953
Minimum4
Maximum183
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.1 KiB
2024-03-23T02:51:16.370066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4
5-th percentile10
Q127
median42
Q368
95-th percentile142
Maximum183
Range179
Interquartile range (IQR)41

Descriptive statistics

Standard deviation38.831667
Coefficient of variation (CV)0.71676943
Kurtosis1.175306
Mean54.175953
Median Absolute Deviation (MAD)18
Skewness1.2804418
Sum18474
Variance1507.8984
MonotonicityNot monotonic
2024-03-23T02:51:16.638091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35 9
 
2.6%
41 9
 
2.6%
21 8
 
2.3%
24 7
 
2.1%
51 7
 
2.1%
20 7
 
2.1%
31 7
 
2.1%
34 7
 
2.1%
56 7
 
2.1%
39 6
 
1.8%
Other values (106) 267
78.3%
ValueCountFrequency (%)
4 5
1.5%
5 3
0.9%
7 4
1.2%
8 1
 
0.3%
9 4
1.2%
10 1
 
0.3%
11 2
 
0.6%
12 5
1.5%
13 2
 
0.6%
14 4
1.2%
ValueCountFrequency (%)
183 1
0.3%
182 1
0.3%
181 1
0.3%
175 1
0.3%
173 1
0.3%
167 1
0.3%
159 1
0.3%
157 1
0.3%
152 1
0.3%
151 1
0.3%

18세미만기초생활수급자수(명)
Real number (ℝ)

HIGH CORRELATION 

Distinct99
Distinct (%)29.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean44.771261
Minimum3
Maximum154
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.1 KiB
2024-03-23T02:51:17.015525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile8
Q123
median35
Q356
95-th percentile107
Maximum154
Range151
Interquartile range (IQR)33

Descriptive statistics

Standard deviation32.356387
Coefficient of variation (CV)0.72270439
Kurtosis1.3383594
Mean44.771261
Median Absolute Deviation (MAD)15
Skewness1.309087
Sum15267
Variance1046.9358
MonotonicityNot monotonic
2024-03-23T02:51:17.441580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
32 12
 
3.5%
33 11
 
3.2%
24 11
 
3.2%
23 10
 
2.9%
20 10
 
2.9%
15 9
 
2.6%
29 9
 
2.6%
56 9
 
2.6%
27 7
 
2.1%
26 7
 
2.1%
Other values (89) 246
72.1%
ValueCountFrequency (%)
3 3
0.9%
4 4
1.2%
5 2
 
0.6%
6 4
1.2%
7 1
 
0.3%
8 4
1.2%
9 4
1.2%
10 4
1.2%
11 3
0.9%
12 5
1.5%
ValueCountFrequency (%)
154 1
0.3%
153 1
0.3%
149 1
0.3%
148 1
0.3%
146 1
0.3%
143 2
0.6%
141 1
0.3%
140 1
0.3%
132 1
0.3%
128 1
0.3%

18세이상20세이하기초생활수급자수(명)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct36
Distinct (%)10.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9.3782991
Minimum0
Maximum45
Zeros10
Zeros (%)2.9%
Negative0
Negative (%)0.0%
Memory size3.1 KiB
2024-03-23T02:51:17.801630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q14
median7
Q313
95-th percentile27
Maximum45
Range45
Interquartile range (IQR)9

Descriptive statistics

Standard deviation8.0308595
Coefficient of variation (CV)0.85632367
Kurtosis2.8721266
Mean9.3782991
Median Absolute Deviation (MAD)4
Skewness1.5972079
Sum3198
Variance64.494704
MonotonicityNot monotonic
2024-03-23T02:51:18.077549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=36)
ValueCountFrequency (%)
4 31
 
9.1%
6 30
 
8.8%
2 24
 
7.0%
3 23
 
6.7%
5 22
 
6.5%
1 20
 
5.9%
7 19
 
5.6%
8 18
 
5.3%
11 17
 
5.0%
13 16
 
4.7%
Other values (26) 121
35.5%
ValueCountFrequency (%)
0 10
 
2.9%
1 20
5.9%
2 24
7.0%
3 23
6.7%
4 31
9.1%
5 22
6.5%
6 30
8.8%
7 19
5.6%
8 18
5.3%
9 13
3.8%
ValueCountFrequency (%)
45 1
 
0.3%
44 1
 
0.3%
36 3
0.9%
33 2
0.6%
32 2
0.6%
31 1
 
0.3%
30 3
0.9%
29 1
 
0.3%
28 3
0.9%
27 2
0.6%

20세초과기초생활수급자수(명)
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
0
334 
1
 
5
2
 
2

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 (%)
0 334
97.9%
1 5
 
1.5%
2 2
 
0.6%

Length

2024-03-23T02:51:18.456228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-23T02:51:18.802046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 334
97.9%
1 5
 
1.5%
2 2
 
0.6%

시설수급자합계(명)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct58
Distinct (%)17.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12.894428
Minimum0
Maximum121
Zeros66
Zeros (%)19.4%
Negative0
Negative (%)0.0%
Memory size3.1 KiB
2024-03-23T02:51:19.149596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median6
Q314
95-th percentile53
Maximum121
Range121
Interquartile range (IQR)13

Descriptive statistics

Standard deviation18.891813
Coefficient of variation (CV)1.4651144
Kurtosis8.320036
Mean12.894428
Median Absolute Deviation (MAD)6
Skewness2.5778718
Sum4397
Variance356.90059
MonotonicityNot monotonic
2024-03-23T02:51:19.597389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 66
19.4%
1 28
 
8.2%
2 24
 
7.0%
6 20
 
5.9%
11 17
 
5.0%
3 16
 
4.7%
4 16
 
4.7%
5 14
 
4.1%
12 12
 
3.5%
10 10
 
2.9%
Other values (48) 118
34.6%
ValueCountFrequency (%)
0 66
19.4%
1 28
8.2%
2 24
 
7.0%
3 16
 
4.7%
4 16
 
4.7%
5 14
 
4.1%
6 20
 
5.9%
7 9
 
2.6%
8 6
 
1.8%
9 8
 
2.3%
ValueCountFrequency (%)
121 1
 
0.3%
118 1
 
0.3%
110 1
 
0.3%
86 1
 
0.3%
68 1
 
0.3%
67 2
0.6%
66 1
 
0.3%
64 1
 
0.3%
62 1
 
0.3%
60 3
0.9%

18세미만시설수급자수(명)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct55
Distinct (%)16.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10.601173
Minimum0
Maximum112
Zeros76
Zeros (%)22.3%
Negative0
Negative (%)0.0%
Memory size3.1 KiB
2024-03-23T02:51:20.301053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median5
Q311
95-th percentile45
Maximum112
Range112
Interquartile range (IQR)10

Descriptive statistics

Standard deviation16.237734
Coefficient of variation (CV)1.5316922
Kurtosis9.342711
Mean10.601173
Median Absolute Deviation (MAD)5
Skewness2.7103058
Sum3615
Variance263.664
MonotonicityNot monotonic
2024-03-23T02:51:20.738345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 76
22.3%
1 31
 
9.1%
2 27
 
7.9%
4 21
 
6.2%
5 19
 
5.6%
8 15
 
4.4%
6 14
 
4.1%
3 13
 
3.8%
10 13
 
3.8%
9 13
 
3.8%
Other values (45) 99
29.0%
ValueCountFrequency (%)
0 76
22.3%
1 31
9.1%
2 27
 
7.9%
3 13
 
3.8%
4 21
 
6.2%
5 19
 
5.6%
6 14
 
4.1%
7 11
 
3.2%
8 15
 
4.4%
9 13
 
3.8%
ValueCountFrequency (%)
112 1
0.3%
102 1
0.3%
87 1
0.3%
74 1
0.3%
65 1
0.3%
59 1
0.3%
57 1
0.3%
56 1
0.3%
54 1
0.3%
53 2
0.6%

18세이상20세이하시설수급자수(명)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct17
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.2580645
Minimum0
Maximum23
Zeros149
Zeros (%)43.7%
Negative0
Negative (%)0.0%
Memory size3.1 KiB
2024-03-23T02:51:21.117867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q33
95-th percentile9
Maximum23
Range23
Interquartile range (IQR)3

Descriptive statistics

Standard deviation3.3127607
Coefficient of variation (CV)1.4670797
Kurtosis6.198809
Mean2.2580645
Median Absolute Deviation (MAD)1
Skewness2.1855942
Sum770
Variance10.974383
MonotonicityNot monotonic
2024-03-23T02:51:21.459358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
0 149
43.7%
1 51
 
15.0%
2 42
 
12.3%
3 18
 
5.3%
4 17
 
5.0%
5 17
 
5.0%
6 11
 
3.2%
8 7
 
2.1%
7 7
 
2.1%
11 5
 
1.5%
Other values (7) 17
 
5.0%
ValueCountFrequency (%)
0 149
43.7%
1 51
 
15.0%
2 42
 
12.3%
3 18
 
5.3%
4 17
 
5.0%
5 17
 
5.0%
6 11
 
3.2%
7 7
 
2.1%
8 7
 
2.1%
9 5
 
1.5%
ValueCountFrequency (%)
23 1
 
0.3%
16 1
 
0.3%
14 1
 
0.3%
13 2
 
0.6%
12 4
1.2%
11 5
1.5%
10 3
0.9%
9 5
1.5%
8 7
2.1%
7 7
2.1%

20세초과시설수급자수(명)
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
0
331 
1
 
8
2
 
2

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 (%)
0 331
97.1%
1 8
 
2.3%
2 2
 
0.6%

Length

2024-03-23T02:51:21.763670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-23T02:51:21.984132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 331
97.1%
1 8
 
2.3%
2 2
 
0.6%

차상위계층수급자합계(명)
Real number (ℝ)

HIGH CORRELATION 

Distinct108
Distinct (%)31.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean44.683284
Minimum0
Maximum170
Zeros1
Zeros (%)0.3%
Negative0
Negative (%)0.0%
Memory size3.1 KiB
2024-03-23T02:51:22.297301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile9
Q121
median36
Q362
95-th percentile106
Maximum170
Range170
Interquartile range (IQR)41

Descriptive statistics

Standard deviation32.750743
Coefficient of variation (CV)0.7329529
Kurtosis1.1536817
Mean44.683284
Median Absolute Deviation (MAD)19
Skewness1.1787464
Sum15237
Variance1072.6112
MonotonicityNot monotonic
2024-03-23T02:51:22.715599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
12 10
 
2.9%
21 10
 
2.9%
23 10
 
2.9%
42 8
 
2.3%
24 8
 
2.3%
16 8
 
2.3%
22 8
 
2.3%
15 8
 
2.3%
14 7
 
2.1%
20 7
 
2.1%
Other values (98) 257
75.4%
ValueCountFrequency (%)
0 1
 
0.3%
3 2
 
0.6%
4 1
 
0.3%
5 2
 
0.6%
6 5
1.5%
7 3
0.9%
8 2
 
0.6%
9 6
1.8%
10 6
1.8%
11 5
1.5%
ValueCountFrequency (%)
170 1
0.3%
168 1
0.3%
164 1
0.3%
147 1
0.3%
136 2
0.6%
126 1
0.3%
125 1
0.3%
124 1
0.3%
123 1
0.3%
122 1
0.3%

18세미만차상위계층수급자수(명)
Real number (ℝ)

HIGH CORRELATION 

Distinct100
Distinct (%)29.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean39.40176
Minimum0
Maximum158
Zeros1
Zeros (%)0.3%
Negative0
Negative (%)0.0%
Memory size3.1 KiB
2024-03-23T02:51:23.160954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile7
Q118
median30
Q355
95-th percentile95
Maximum158
Range158
Interquartile range (IQR)37

Descriptive statistics

Standard deviation29.196492
Coefficient of variation (CV)0.74099464
Kurtosis1.163853
Mean39.40176
Median Absolute Deviation (MAD)17
Skewness1.1740364
Sum13436
Variance852.43517
MonotonicityNot monotonic
2024-03-23T02:51:23.767842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
8 11
 
3.2%
28 11
 
3.2%
19 10
 
2.9%
21 9
 
2.6%
22 9
 
2.6%
23 9
 
2.6%
29 8
 
2.3%
18 7
 
2.1%
17 7
 
2.1%
34 7
 
2.1%
Other values (90) 253
74.2%
ValueCountFrequency (%)
0 1
 
0.3%
3 2
 
0.6%
4 3
 
0.9%
5 4
 
1.2%
6 6
1.8%
7 3
 
0.9%
8 11
3.2%
9 6
1.8%
10 5
1.5%
11 6
1.8%
ValueCountFrequency (%)
158 1
0.3%
143 2
0.6%
133 1
0.3%
120 2
0.6%
112 1
0.3%
109 1
0.3%
108 1
0.3%
106 2
0.6%
105 1
0.3%
104 1
0.3%

18세이상20세이하차상위계층수급자수(명)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct24
Distinct (%)7.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.2727273
Minimum0
Maximum27
Zeros28
Zeros (%)8.2%
Negative0
Negative (%)0.0%
Memory size3.1 KiB
2024-03-23T02:51:24.191337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median4
Q37
95-th percentile16
Maximum27
Range27
Interquartile range (IQR)5

Descriptive statistics

Standard deviation4.5939975
Coefficient of variation (CV)0.87127538
Kurtosis2.484835
Mean5.2727273
Median Absolute Deviation (MAD)2
Skewness1.4868129
Sum1798
Variance21.104813
MonotonicityNot monotonic
2024-03-23T02:51:24.854188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
3 44
12.9%
2 40
11.7%
1 36
10.6%
4 35
10.3%
5 31
9.1%
6 30
8.8%
0 28
8.2%
7 23
6.7%
8 17
 
5.0%
16 8
 
2.3%
Other values (14) 49
14.4%
ValueCountFrequency (%)
0 28
8.2%
1 36
10.6%
2 40
11.7%
3 44
12.9%
4 35
10.3%
5 31
9.1%
6 30
8.8%
7 23
6.7%
8 17
 
5.0%
9 7
 
2.1%
ValueCountFrequency (%)
27 1
 
0.3%
22 1
 
0.3%
21 1
 
0.3%
20 2
 
0.6%
19 1
 
0.3%
18 1
 
0.3%
17 3
 
0.9%
16 8
2.3%
15 3
 
0.9%
14 6
1.8%
Distinct2
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
0
338 
1
 
3

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 (%)
0 338
99.1%
1 3
 
0.9%

Length

2024-03-23T02:51:25.939683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-23T02:51:26.636038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 338
99.1%
1 3
 
0.9%

Interactions

2024-03-23T02:51:07.893994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:50:28.207833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:50:31.894714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:50:34.796576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:50:37.729687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:50:40.738696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:50:44.309593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:50:47.492656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:50:50.682647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:50:54.071107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:50:57.600165image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:51:00.749055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:51:04.266367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:51:08.145449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:50:28.361371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:50:32.155072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:50:34.998838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:50:37.943895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:50:40.995934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:50:44.564586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:50:47.745749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:50:50.977902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:50:54.315984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:50:57.841811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:51:01.000287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:51:04.501465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:51:08.418655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:50:28.623760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:50:32.412722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:50:35.268978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:50:38.159964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:50:41.268693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:50:44.834565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:50:47.973469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:50:51.258660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:50:54.770731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:50:58.101148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:51:01.270403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:51:04.791911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:51:08.645030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:50:28.918775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:50:32.655721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:50:35.534916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:50:38.331818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:50:41.549973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:50:45.136445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:50:48.138560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:50:51.512714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:50:55.022922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:50:58.286206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:51:01.539154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:51:05.063752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:51:08.860821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:50:29.207833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:50:32.960725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:50:35.799418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:50:38.513788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:50:41.827846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:50:45.382204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:50:48.383971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:50:51.784706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:50:55.285719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:50:58.453369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:51:01.776209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:51:05.360848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:51:09.136811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:50:29.555564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:50:33.150226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:50:36.066611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:50:38.713383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:50:42.092718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:50:45.606058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:50:48.607411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:50:52.104703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:50:55.558589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:50:58.677130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:51:01.977687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:51:05.658995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:51:09.314607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:50:29.827057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:50:33.429159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:50:36.328266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:50:38.998416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:50:42.372741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:50:45.791342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:50:48.781157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:50:52.401281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:50:55.831425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:50:58.891472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:51:02.264566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:51:05.955935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:51:09.466353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:50:30.187351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:50:33.626331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:50:36.577031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:50:39.250619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:50:42.626084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:50:45.953777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:50:48.956769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:50:52.662268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:50:56.074211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:50:59.139072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:51:02.512786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:51:06.219527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:51:09.829963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:50:30.448719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:50:33.795551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:50:36.794901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:50:39.522680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:50:42.891910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:50:46.193554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:50:49.247152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:50:52.924722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:50:56.326265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:50:59.406139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:51:02.882599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:51:06.571379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:51:10.051383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:50:30.744030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:50:34.010596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:50:36.956996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:50:39.690220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:50:43.173475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:50:46.457387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:50:49.481323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:50:53.210589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:50:56.568621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:50:59.656696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:51:03.158372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:51:06.809633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:51:10.260029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:50:30.976961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:50:34.243267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:50:37.113325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:50:39.886550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:50:43.469909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:50:46.664288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:50:49.784108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:50:53.423238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:50:56.828452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:50:59.893617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:51:03.471786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:51:07.071264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:51:10.429459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:50:31.233816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:50:34.447149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:50:37.298785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:50:40.353045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:50:43.747003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:50:46.949659image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:50:50.109978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:50:53.648063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:50:57.083824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:51:00.155148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:51:03.658023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:51:07.360271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:51:10.613695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:50:31.565088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:50:34.630387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:50:37.491004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:50:40.570040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:50:44.047998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:50:47.207241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:50:50.397512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:50:53.904455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:50:57.351744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:51:00.501278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:51:04.010297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T02:51:07.653392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-23T02:51:27.167545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기준년도시군명전체총계(명)18세미만총계(명)18세이상20세이하총계(명)20세초과총계(명)기초생활수급자합계(명)18세미만기초생활수급자수(명)18세이상20세이하기초생활수급자수(명)20세초과기초생활수급자수(명)시설수급자합계(명)18세미만시설수급자수(명)18세이상20세이하시설수급자수(명)20세초과시설수급자수(명)차상위계층수급자합계(명)18세미만차상위계층수급자수(명)18세이상20세이하차상위계층수급자수(명)20세초과차상위계층수급자수(명)
기준년도1.0000.0000.0000.0000.2910.4120.0000.0000.1800.2660.0000.0000.0000.3210.0000.0000.1970.000
시군명0.0001.0000.9150.9200.7400.2020.9050.9160.7210.0000.7780.7280.6300.3090.8980.8900.6390.291
전체총계(명)0.0000.9151.0000.9890.8610.3040.9430.9350.7100.1580.4760.4620.3670.2410.9150.9130.8130.086
18세미만총계(명)0.0000.9200.9891.0000.8080.2720.9260.9450.6530.2370.4770.4580.3140.2530.9240.9330.7840.036
18세이상20세이하총계(명)0.2910.7400.8610.8081.0000.3770.8580.7780.8640.1550.3500.2690.4240.4410.7860.7600.9150.154
20세초과총계(명)0.4120.2020.3040.2720.3771.0000.1300.3170.3510.8640.5200.5160.4150.9030.2220.1490.3390.241
기초생활수급자합계(명)0.0000.9050.9430.9260.8580.1301.0000.9710.7330.2660.3590.3340.3390.1790.8850.8630.7790.149
18세미만기초생활수급자수(명)0.0000.9160.9350.9450.7780.3170.9711.0000.6820.5090.3560.3210.2670.2090.8790.8820.7250.000
18세이상20세이하기초생활수급자수(명)0.1800.7210.7100.6530.8640.3510.7330.6821.0000.3620.2370.2180.2180.3580.5840.5580.6990.000
20세초과기초생활수급자수(명)0.2660.0000.1580.2370.1550.8640.2660.5090.3621.0000.1430.1950.0000.2110.1830.1000.1050.000
시설수급자합계(명)0.0000.7780.4760.4770.3500.5200.3590.3560.2370.1431.0000.9410.8660.6170.2750.2580.1890.101
18세미만시설수급자수(명)0.0000.7280.4620.4580.2690.5160.3340.3210.2180.1950.9411.0000.7880.6250.2500.2290.0000.000
18세이상20세이하시설수급자수(명)0.0000.6300.3670.3140.4240.4150.3390.2670.2180.0000.8660.7881.0000.6220.0000.0000.1890.000
20세초과시설수급자수(명)0.3210.3090.2410.2530.4410.9030.1790.2090.3580.2110.6170.6250.6221.0000.0000.0780.3740.107
차상위계층수급자합계(명)0.0000.8980.9150.9240.7860.2220.8850.8790.5840.1830.2750.2500.0000.0001.0000.9930.8200.285
18세미만차상위계층수급자수(명)0.0000.8900.9130.9330.7600.1490.8630.8820.5580.1000.2580.2290.0000.0780.9931.0000.7920.278
18세이상20세이하차상위계층수급자수(명)0.1970.6390.8130.7840.9150.3390.7790.7250.6990.1050.1890.0000.1890.3740.8200.7921.0000.118
20세초과차상위계층수급자수(명)0.0000.2910.0860.0360.1540.2410.1490.0000.0000.0000.1010.0000.0000.1070.2850.2780.1181.000
2024-03-23T02:51:27.637680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
20세초과총계(명)20세초과기초생활수급자수(명)20세초과차상위계층수급자수(명)20세초과시설수급자수(명)시군명
20세초과총계(명)1.0000.5530.3920.6210.097
20세초과기초생활수급자수(명)0.5531.0000.0000.0660.000
20세초과차상위계층수급자수(명)0.3920.0001.0000.1770.236
20세초과시설수급자수(명)0.6210.0660.1771.0000.156
시군명0.0970.0000.2360.1561.000
2024-03-23T02:51:27.929436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기준년도전체총계(명)18세미만총계(명)18세이상20세이하총계(명)기초생활수급자합계(명)18세미만기초생활수급자수(명)18세이상20세이하기초생활수급자수(명)시설수급자합계(명)18세미만시설수급자수(명)18세이상20세이하시설수급자수(명)차상위계층수급자합계(명)18세미만차상위계층수급자수(명)18세이상20세이하차상위계층수급자수(명)시군명20세초과총계(명)20세초과기초생활수급자수(명)20세초과시설수급자수(명)20세초과차상위계층수급자수(명)
기준년도1.000-0.066-0.042-0.221-0.102-0.077-0.215-0.078-0.057-0.1910.0180.029-0.0970.0000.1920.0850.1400.000
전체총계(명)-0.0661.0000.9950.8570.9550.9490.7730.5600.5510.4360.9070.8990.7320.6120.1890.0930.1460.065
18세미만총계(명)-0.0420.9951.0000.8070.9470.9510.7250.5490.5460.4020.9110.9080.6960.6240.1670.1430.1540.025
18세이상20세이하총계(명)-0.2210.8570.8071.0000.8420.7870.9200.5510.5140.5670.7360.7030.8020.3550.2420.0910.2920.117
기초생활수급자합계(명)-0.1020.9550.9470.8421.0000.9910.8190.4200.4070.3410.8960.8880.7360.5880.0760.1630.1060.113
18세미만기초생활수급자수(명)-0.0770.9490.9510.7870.9911.0000.7430.4070.3960.3210.9000.8940.7210.6130.1980.3510.1260.000
18세이상20세이하기초생활수급자수(명)-0.2150.7730.7250.9200.8190.7431.0000.3920.3710.3630.6910.6730.6760.3610.1790.1930.1800.023
시설수급자합계(명)-0.0780.5600.5490.5510.4200.4070.3921.0000.9850.7910.3450.3360.2900.4230.3830.0900.4830.074
18세미만시설수급자수(명)-0.0570.5510.5460.5140.4070.3960.3710.9851.0000.6950.3430.3360.2710.3600.2630.0850.3410.000
18세이상20세이하시설수급자수(명)-0.1910.4360.4020.5670.3410.3210.3630.7910.6951.0000.2340.2190.2630.2920.2890.0000.4890.000
차상위계층수급자합계(명)0.0180.9070.9110.7360.8960.9000.6910.3450.3430.2341.0000.9950.7700.5650.1430.1210.0000.221
18세미만차상위계층수급자수(명)0.0290.8990.9080.7030.8880.8940.6730.3360.3360.2190.9951.0000.7120.5480.0890.0620.0470.211
18세이상20세이하차상위계층수급자수(명)-0.0970.7320.6960.8020.7360.7210.6760.2900.2710.2630.7700.7121.0000.2740.2140.0610.2400.089
시군명0.0000.6120.6240.3550.5880.6130.3610.4230.3600.2920.5650.5480.2741.0000.0970.0000.1560.236
20세초과총계(명)0.1920.1890.1670.2420.0760.1980.1790.3830.2630.2890.1430.0890.2140.0971.0000.5530.6210.392
20세초과기초생활수급자수(명)0.0850.0930.1430.0910.1630.3510.1930.0900.0850.0000.1210.0620.0610.0000.5531.0000.0660.000
20세초과시설수급자수(명)0.1400.1460.1540.2920.1060.1260.1800.4830.3410.4890.0000.0470.2400.1560.6210.0661.0000.177
20세초과차상위계층수급자수(명)0.0000.0650.0250.1170.1130.0000.0230.0740.0000.0000.2210.2110.0890.2360.3920.0000.1771.000

Missing values

2024-03-23T02:51:10.869944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-23T02:51:11.585290image/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)18세이상20세이하총계(명)20세초과총계(명)기초생활수급자합계(명)18세미만기초생활수급자수(명)18세이상20세이하기초생활수급자수(명)20세초과기초생활수급자수(명)시설수급자합계(명)18세미만시설수급자수(명)18세이상20세이하시설수급자수(명)20세초과시설수급자수(명)차상위계층수급자합계(명)18세미만차상위계층수급자수(명)18세이상20세이하차상위계층수급자수(명)20세초과차상위계층수급자수(명)
02023가평군2924501612401100121110
12023고양시2101892109281110282710908190
22023과천시8710431000004400
32023광명시52421002420400000282260
42023광주시1089117040337010820585080
52023구리시4139202624200000151500
62023군포시6362102827104400313100
72023김포시1159817063521101010514650
82023남양주시167146210736310000009483110
92023동두천시4843502421303300211920
기준년도시군명전체총계(명)18세미만총계(명)18세이상20세이하총계(명)20세초과총계(명)기초생활수급자합계(명)18세미만기초생활수급자수(명)18세이상20세이하기초생활수급자수(명)20세초과기초생활수급자수(명)시설수급자합계(명)18세미만시설수급자수(명)18세이상20세이하시설수급자수(명)20세초과시설수급자수(명)차상위계층수급자합계(명)18세미만차상위계층수급자수(명)18세이상20세이하차상위계층수급자수(명)20세초과차상위계층수급자수(명)
3312013오산시59461303124706330221930
3322013용인시1891691916967206653121544950
3332013의왕시2826201212000000161420
3342013의정부시1651491609483110121110595540
3352013이천시5649703125602200232210
3362013파주시15112229064501401210207562130
3372013평택시160141181565060675791373430
3382013포천시13010228048351305443110282440
3392013하남시4543202220200000232300
3402013화성시115103120454320241860464240