Overview

Dataset statistics

Number of variables13
Number of observations341
Missing cells1
Missing cells (%)< 0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory38.8 KiB
Average record size in memory116.4 B

Variable types

Numeric11
Categorical2

Dataset

Description장애정도별 장애수당 수급자 집계현황
Author경기복지재단(경기도장애인복지종합지원센터)
URLhttps://data.gg.go.kr/portal/data/service/selectServicePage.do?&infId=I3KZOXLDEHZXGR0ENX5225657609&infSeq=1

Alerts

기준년도 is highly overall correlated with 3급경증수급자수(명) and 5 other fieldsHigh correlation
합계(명) is highly overall correlated with 시군명High correlation
2급중증수급자수(명) is highly overall correlated with 3급경증수급자수(명) and 3 other fieldsHigh correlation
3급경증수급자수(명) is highly overall correlated with 기준년도 and 7 other fieldsHigh correlation
4급경증수급자수(명) is highly overall correlated with 기준년도 and 6 other fieldsHigh correlation
5급경증수급자수(명) is highly overall correlated with 기준년도 and 6 other fieldsHigh correlation
6급경증수급자수(명) is highly overall correlated with 기준년도 and 6 other fieldsHigh correlation
심한장애(중증)수급자수(명) is highly overall correlated with 기준년도 and 5 other fieldsHigh correlation
심하지않은장애(경증)수급자수(명) is highly overall correlated with 기준년도 and 5 other fieldsHigh correlation
시군명 is highly overall correlated with 합계(명) and 1 other fieldsHigh correlation
3급중증수급자수(명) is highly imbalanced (63.2%)Imbalance
1급중증수급자수(명) has 307 (90.0%) zerosZeros
2급중증수급자수(명) has 260 (76.2%) zerosZeros
3급경증수급자수(명) has 124 (36.4%) zerosZeros
4급경증수급자수(명) has 124 (36.4%) zerosZeros
5급경증수급자수(명) has 124 (36.4%) zerosZeros
6급경증수급자수(명) has 124 (36.4%) zerosZeros
해당없음수급자수(명) has 285 (83.6%) zerosZeros
심한장애(중증)수급자수(명) has 247 (72.4%) zerosZeros
심하지않은장애(경증)수급자수(명) has 227 (66.6%) zerosZeros

Reproduction

Analysis started2024-04-11 04:52:18.117374
Analysis finished2024-04-11 04:52:29.683830
Duration11.57 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

기준년도
Real number (ℝ)

HIGH CORRELATION 

Distinct11
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2018
Minimum2013
Maximum2023
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.1 KiB
2024-04-11T13:52:29.735960image/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
2024-04-11T13:52:29.846200image/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

2024-04-11T13:52:29.956314image/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%

합계(명)
Real number (ℝ)

HIGH CORRELATION 

Distinct322
Distinct (%)94.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1858.6481
Minimum165
Maximum5799
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.1 KiB
2024-04-11T13:52:30.068124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum165
5-th percentile525
Q1974
median1400
Q32598
95-th percentile4288
Maximum5799
Range5634
Interquartile range (IQR)1624

Descriptive statistics

Standard deviation1227.4212
Coefficient of variation (CV)0.66038385
Kurtosis0.15415882
Mean1858.6481
Median Absolute Deviation (MAD)584
Skewness1.0138967
Sum633799
Variance1506562.8
MonotonicityNot monotonic
2024-04-11T13:52:30.182398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
787 2
 
0.6%
612 2
 
0.6%
1124 2
 
0.6%
1104 2
 
0.6%
1060 2
 
0.6%
2014 2
 
0.6%
859 2
 
0.6%
1278 2
 
0.6%
858 2
 
0.6%
1086 2
 
0.6%
Other values (312) 321
94.1%
ValueCountFrequency (%)
165 1
0.3%
166 1
0.3%
167 1
0.3%
169 1
0.3%
174 1
0.3%
179 2
0.6%
195 1
0.3%
197 1
0.3%
211 1
0.3%
213 1
0.3%
ValueCountFrequency (%)
5799 1
0.3%
5634 1
0.3%
5100 1
0.3%
4990 1
0.3%
4943 1
0.3%
4927 1
0.3%
4904 1
0.3%
4872 1
0.3%
4834 1
0.3%
4766 1
0.3%

1급중증수급자수(명)
Real number (ℝ)

ZEROS 

Distinct10
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.52492669
Minimum0
Maximum78
Zeros307
Zeros (%)90.0%
Negative0
Negative (%)0.0%
Memory size3.1 KiB
2024-04-11T13:52:30.281153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1
Maximum78
Range78
Interquartile range (IQR)0

Descriptive statistics

Standard deviation4.6104224
Coefficient of variation (CV)8.7829834
Kurtosis239.87116
Mean0.52492669
Median Absolute Deviation (MAD)0
Skewness14.79968
Sum179
Variance21.255994
MonotonicityNot monotonic
2024-04-11T13:52:30.379981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
0 307
90.0%
1 22
 
6.5%
2 4
 
1.2%
5 2
 
0.6%
28 1
 
0.3%
6 1
 
0.3%
16 1
 
0.3%
78 1
 
0.3%
8 1
 
0.3%
3 1
 
0.3%
ValueCountFrequency (%)
0 307
90.0%
1 22
 
6.5%
2 4
 
1.2%
3 1
 
0.3%
5 2
 
0.6%
6 1
 
0.3%
8 1
 
0.3%
16 1
 
0.3%
28 1
 
0.3%
78 1
 
0.3%
ValueCountFrequency (%)
78 1
 
0.3%
28 1
 
0.3%
16 1
 
0.3%
8 1
 
0.3%
6 1
 
0.3%
5 2
 
0.6%
3 1
 
0.3%
2 4
 
1.2%
1 22
 
6.5%
0 307
90.0%

2급중증수급자수(명)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct9
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.4516129
Minimum0
Maximum17
Zeros260
Zeros (%)76.2%
Negative0
Negative (%)0.0%
Memory size3.1 KiB
2024-04-11T13:52:30.472848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile2
Maximum17
Range17
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.3937377
Coefficient of variation (CV)3.0861335
Kurtosis73.270313
Mean0.4516129
Median Absolute Deviation (MAD)0
Skewness7.4044412
Sum154
Variance1.9425047
MonotonicityNot monotonic
2024-04-11T13:52:30.563783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
0 260
76.2%
1 55
 
16.1%
2 12
 
3.5%
3 7
 
2.1%
4 2
 
0.6%
5 2
 
0.6%
12 1
 
0.3%
17 1
 
0.3%
7 1
 
0.3%
ValueCountFrequency (%)
0 260
76.2%
1 55
 
16.1%
2 12
 
3.5%
3 7
 
2.1%
4 2
 
0.6%
5 2
 
0.6%
7 1
 
0.3%
12 1
 
0.3%
17 1
 
0.3%
ValueCountFrequency (%)
17 1
 
0.3%
12 1
 
0.3%
7 1
 
0.3%
5 2
 
0.6%
4 2
 
0.6%
3 7
 
2.1%
2 12
 
3.5%
1 55
 
16.1%
0 260
76.2%

3급중증수급자수(명)
Categorical

IMBALANCE 

Distinct4
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size2.8 KiB
0
290 
1
41 
2
 
8
3
 
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 (%)
0 290
85.0%
1 41
 
12.0%
2 8
 
2.3%
3 2
 
0.6%

Length

2024-04-11T13:52:30.668459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-11T13:52:30.757746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 290
85.0%
1 41
 
12.0%
2 8
 
2.3%
3 2
 
0.6%

3급경증수급자수(명)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct196
Distinct (%)57.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean412.26393
Minimum0
Maximum1626
Zeros124
Zeros (%)36.4%
Negative0
Negative (%)0.0%
Memory size3.1 KiB
2024-04-11T13:52:30.867080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median349
Q3639
95-th percentile1394
Maximum1626
Range1626
Interquartile range (IQR)639

Descriptive statistics

Standard deviation448.54962
Coefficient of variation (CV)1.0880157
Kurtosis0.21689276
Mean412.26393
Median Absolute Deviation (MAD)349
Skewness1.0438668
Sum140582
Variance201196.77
MonotonicityNot monotonic
2024-04-11T13:52:31.005989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 124
36.4%
304 3
 
0.9%
415 2
 
0.6%
830 2
 
0.6%
258 2
 
0.6%
373 2
 
0.6%
306 2
 
0.6%
331 2
 
0.6%
738 2
 
0.6%
179 2
 
0.6%
Other values (186) 198
58.1%
ValueCountFrequency (%)
0 124
36.4%
50 1
 
0.3%
51 1
 
0.3%
56 1
 
0.3%
62 1
 
0.3%
65 1
 
0.3%
66 1
 
0.3%
71 1
 
0.3%
169 1
 
0.3%
173 1
 
0.3%
ValueCountFrequency (%)
1626 1
0.3%
1601 1
0.3%
1579 1
0.3%
1576 1
0.3%
1557 1
0.3%
1534 1
0.3%
1533 1
0.3%
1520 1
0.3%
1519 1
0.3%
1515 1
0.3%

4급경증수급자수(명)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct173
Distinct (%)50.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean217.81818
Minimum0
Maximum950
Zeros124
Zeros (%)36.4%
Negative0
Negative (%)0.0%
Memory size3.1 KiB
2024-04-11T13:52:31.313681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median162
Q3310
95-th percentile754
Maximum950
Range950
Interquartile range (IQR)310

Descriptive statistics

Standard deviation242.65376
Coefficient of variation (CV)1.1140198
Kurtosis0.48512917
Mean217.81818
Median Absolute Deviation (MAD)162
Skewness1.1488568
Sum74276
Variance58880.849
MonotonicityNot monotonic
2024-04-11T13:52:31.423556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 124
36.4%
162 4
 
1.2%
127 3
 
0.9%
254 3
 
0.9%
272 3
 
0.9%
380 3
 
0.9%
280 3
 
0.9%
153 3
 
0.9%
161 3
 
0.9%
129 2
 
0.6%
Other values (163) 190
55.7%
ValueCountFrequency (%)
0 124
36.4%
37 1
 
0.3%
38 1
 
0.3%
40 2
 
0.6%
42 1
 
0.3%
43 1
 
0.3%
44 1
 
0.3%
83 2
 
0.6%
96 1
 
0.3%
100 1
 
0.3%
ValueCountFrequency (%)
950 1
0.3%
913 1
0.3%
902 1
0.3%
864 1
0.3%
844 1
0.3%
836 1
0.3%
828 1
0.3%
817 1
0.3%
812 1
0.3%
807 1
0.3%

5급경증수급자수(명)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct172
Distinct (%)50.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean222.56012
Minimum0
Maximum1043
Zeros124
Zeros (%)36.4%
Negative0
Negative (%)0.0%
Memory size3.1 KiB
2024-04-11T13:52:31.535864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median165
Q3320
95-th percentile770
Maximum1043
Range1043
Interquartile range (IQR)320

Descriptive statistics

Standard deviation248.3557
Coefficient of variation (CV)1.1159039
Kurtosis0.64641031
Mean222.56012
Median Absolute Deviation (MAD)165
Skewness1.180741
Sum75893
Variance61680.553
MonotonicityNot monotonic
2024-04-11T13:52:31.654205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 124
36.4%
213 6
 
1.8%
255 3
 
0.9%
121 3
 
0.9%
163 3
 
0.9%
277 3
 
0.9%
186 3
 
0.9%
412 3
 
0.9%
152 3
 
0.9%
276 2
 
0.6%
Other values (162) 188
55.1%
ValueCountFrequency (%)
0 124
36.4%
37 1
 
0.3%
40 2
 
0.6%
43 1
 
0.3%
44 1
 
0.3%
46 1
 
0.3%
47 1
 
0.3%
97 1
 
0.3%
100 1
 
0.3%
104 1
 
0.3%
ValueCountFrequency (%)
1043 1
0.3%
961 1
0.3%
919 1
0.3%
905 1
0.3%
887 1
0.3%
879 1
0.3%
877 1
0.3%
875 1
0.3%
856 1
0.3%
837 1
0.3%

6급경증수급자수(명)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct184
Distinct (%)54.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean206.26393
Minimum0
Maximum894
Zeros124
Zeros (%)36.4%
Negative0
Negative (%)0.0%
Memory size3.1 KiB
2024-04-11T13:52:31.776750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median157
Q3297
95-th percentile742
Maximum894
Range894
Interquartile range (IQR)297

Descriptive statistics

Standard deviation232.23299
Coefficient of variation (CV)1.1259021
Kurtosis0.51455409
Mean206.26393
Median Absolute Deviation (MAD)157
Skewness1.1720238
Sum70336
Variance53932.16
MonotonicityNot monotonic
2024-04-11T13:52:31.895824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 124
36.4%
323 3
 
0.9%
742 3
 
0.9%
272 3
 
0.9%
157 3
 
0.9%
127 2
 
0.6%
255 2
 
0.6%
246 2
 
0.6%
228 2
 
0.6%
297 2
 
0.6%
Other values (174) 195
57.2%
ValueCountFrequency (%)
0 124
36.4%
36 1
 
0.3%
39 1
 
0.3%
40 1
 
0.3%
41 1
 
0.3%
47 1
 
0.3%
48 1
 
0.3%
50 1
 
0.3%
77 1
 
0.3%
82 1
 
0.3%
ValueCountFrequency (%)
894 1
0.3%
881 1
0.3%
822 1
0.3%
810 1
0.3%
806 1
0.3%
798 1
0.3%
796 1
0.3%
793 1
0.3%
784 1
0.3%
775 1
0.3%

해당없음수급자수(명)
Real number (ℝ)

ZEROS 

Distinct17
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.97067449
Minimum0
Maximum35
Zeros285
Zeros (%)83.6%
Negative0
Negative (%)0.0%
Memory size3.1 KiB
2024-04-11T13:52:31.990506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile5
Maximum35
Range35
Interquartile range (IQR)0

Descriptive statistics

Standard deviation3.9510634
Coefficient of variation (CV)4.0704309
Kurtosis36.477033
Mean0.97067449
Median Absolute Deviation (MAD)0
Skewness5.7424431
Sum331
Variance15.610902
MonotonicityNot monotonic
2024-04-11T13:52:32.086374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
0 285
83.6%
1 30
 
8.8%
5 3
 
0.9%
3 3
 
0.9%
4 3
 
0.9%
14 2
 
0.6%
8 2
 
0.6%
7 2
 
0.6%
9 2
 
0.6%
21 2
 
0.6%
Other values (7) 7
 
2.1%
ValueCountFrequency (%)
0 285
83.6%
1 30
 
8.8%
3 3
 
0.9%
4 3
 
0.9%
5 3
 
0.9%
6 1
 
0.3%
7 2
 
0.6%
8 2
 
0.6%
9 2
 
0.6%
10 1
 
0.3%
ValueCountFrequency (%)
35 1
0.3%
29 1
0.3%
28 1
0.3%
24 1
0.3%
21 2
0.6%
15 1
0.3%
14 2
0.6%
10 1
0.3%
9 2
0.6%
8 2
0.6%

심한장애(중증)수급자수(명)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct40
Distinct (%)11.8%
Missing1
Missing (%)0.3%
Infinite0
Infinite (%)0.0%
Mean217.49412
Minimum0
Maximum5790
Zeros247
Zeros (%)72.4%
Negative0
Negative (%)0.0%
Memory size3.1 KiB
2024-04-11T13:52:32.229909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile1611.05
Maximum5790
Range5790
Interquartile range (IQR)1

Descriptive statistics

Standard deviation824.54195
Coefficient of variation (CV)3.7911
Kurtosis21.913796
Mean217.49412
Median Absolute Deviation (MAD)0
Skewness4.5396506
Sum73948
Variance679869.42
MonotonicityNot monotonic
2024-04-11T13:52:32.336743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)
ValueCountFrequency (%)
0 247
72.4%
2 24
 
7.0%
1 18
 
5.3%
4 8
 
2.3%
3 6
 
1.8%
5 3
 
0.9%
4208 1
 
0.3%
2598 1
 
0.3%
1735 1
 
0.3%
1313 1
 
0.3%
Other values (30) 30
 
8.8%
ValueCountFrequency (%)
0 247
72.4%
1 18
 
5.3%
2 24
 
7.0%
3 6
 
1.8%
4 8
 
2.3%
5 3
 
0.9%
6 1
 
0.3%
7 1
 
0.3%
51 1
 
0.3%
212 1
 
0.3%
ValueCountFrequency (%)
5790 1
0.3%
5631 1
0.3%
4990 1
0.3%
4869 1
0.3%
4208 1
0.3%
4053 1
0.3%
4039 1
0.3%
3159 1
0.3%
3109 1
0.3%
2884 1
0.3%

심하지않은장애(경증)수급자수(명)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct98
Distinct (%)28.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean311.41642
Minimum0
Maximum3171
Zeros227
Zeros (%)66.6%
Negative0
Negative (%)0.0%
Memory size3.1 KiB
2024-04-11T13:52:32.449314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q3398
95-th percentile1741
Maximum3171
Range3171
Interquartile range (IQR)398

Descriptive statistics

Standard deviation662.58926
Coefficient of variation (CV)2.1276632
Kurtosis6.43595
Mean311.41642
Median Absolute Deviation (MAD)0
Skewness2.5617987
Sum106193
Variance439024.53
MonotonicityNot monotonic
2024-04-11T13:52:32.586457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 227
66.6%
1 9
 
2.6%
3 4
 
1.2%
2 4
 
1.2%
444 2
 
0.6%
450 2
 
0.6%
721 2
 
0.6%
898 1
 
0.3%
3034 1
 
0.3%
2870 1
 
0.3%
Other values (88) 88
 
25.8%
ValueCountFrequency (%)
0 227
66.6%
1 9
 
2.6%
2 4
 
1.2%
3 4
 
1.2%
4 1
 
0.3%
6 1
 
0.3%
7 1
 
0.3%
9 1
 
0.3%
50 1
 
0.3%
113 1
 
0.3%
ValueCountFrequency (%)
3171 1
0.3%
3142 1
0.3%
3133 1
0.3%
3034 1
0.3%
2987 1
0.3%
2975 1
0.3%
2920 1
0.3%
2870 1
0.3%
2684 1
0.3%
2617 1
0.3%

Interactions

2024-04-11T13:52:28.377066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:52:19.659529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:52:20.579985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:52:21.383004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:52:22.314126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:52:23.307295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:52:24.176953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:52:24.934551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:52:25.908452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:52:26.724001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:52:27.549696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:52:28.609795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:52:19.893781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:52:20.648974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:52:21.465436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:52:22.384719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:52:23.375458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:52:24.238011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:52:25.008945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:52:25.970982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:52:26.791045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:52:27.630917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:52:28.682013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:52:19.959691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:52:20.716630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:52:21.542623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:52:22.461131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:52:23.459518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:52:24.305702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:52:25.076159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:52:26.047179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:52:26.865467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:52:27.727916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:52:28.767329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:52:20.032823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:52:20.790930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:52:21.638801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:52:22.538892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:52:23.550918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:52:24.382548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:52:25.153826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:52:26.140131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:52:26.954381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:52:27.801824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:52:28.861488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:52:20.102632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:52:20.863860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:52:21.761897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:52:22.620381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:52:23.631767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:52:24.451652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:52:25.244718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:52:26.209791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:52:27.038621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:52:27.877088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:52:28.947771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:52:20.174797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:52:20.939692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:52:21.886388image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:52:22.852683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:52:23.710397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:52:24.523000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:52:25.341084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:52:26.282915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:52:27.117051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:52:27.952720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:52:29.013070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:52:20.236337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:52:21.001712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:52:21.954193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:52:22.917568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:52:23.778396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:52:24.585037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:52:25.412169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:52:26.349450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:52:27.182542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:52:28.019799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:52:29.083349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:52:20.300224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:52:21.070969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:52:22.021427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:52:22.988214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:52:23.847852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:52:24.666361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:52:25.641412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:52:26.418329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:52:27.251237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:52:28.089882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:52:29.147633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:52:20.361070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:52:21.144149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:52:22.087670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:52:23.052646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:52:23.933030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:52:24.726880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:52:25.701917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:52:26.482220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:52:27.314792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:52:28.162074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:52:29.222693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:52:20.430464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:52:21.218794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:52:22.163000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:52:23.132025image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:52:24.015308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:52:24.794580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:52:25.772121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:52:26.573118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:52:27.389699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:52:28.235505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:52:29.306264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:52:20.506732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:52:21.290096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:52:22.235887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:52:23.214369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:52:24.097481image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:52:24.863090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:52:25.840947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:52:26.649301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:52:27.464428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-11T13:52:28.306509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-11T13:52:32.670114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기준년도시군명합계(명)1급중증수급자수(명)2급중증수급자수(명)3급중증수급자수(명)3급경증수급자수(명)4급경증수급자수(명)5급경증수급자수(명)6급경증수급자수(명)해당없음수급자수(명)심한장애(중증)수급자수(명)심하지않은장애(경증)수급자수(명)
기준년도1.0000.0000.244NaN0.3660.2540.7270.7190.7340.7220.5350.6910.750
시군명0.0001.0000.8590.0340.0720.2430.8600.8070.7740.8030.0000.0000.369
합계(명)0.2440.8591.0000.0000.0000.1500.8940.8740.8720.8940.1510.8480.770
1급중증수급자수(명)NaN0.0340.0001.0000.9310.5170.2870.3520.2150.2730.0000.0000.000
2급중증수급자수(명)0.3660.0720.0000.9311.0000.6180.3790.3840.3390.3500.4600.0000.000
3급중증수급자수(명)0.2540.2430.1500.5170.6181.0000.4200.5020.4320.4980.0000.0000.000
3급경증수급자수(명)0.7270.8600.8940.2870.3790.4201.0000.9610.9550.9600.3600.0000.538
4급경증수급자수(명)0.7190.8070.8740.3520.3840.5020.9611.0000.9710.9700.3990.0000.530
5급경증수급자수(명)0.7340.7740.8720.2150.3390.4320.9550.9711.0000.9730.3770.0000.525
6급경증수급자수(명)0.7220.8030.8940.2730.3500.4980.9600.9700.9731.0000.4080.0000.521
해당없음수급자수(명)0.5350.0000.1510.0000.4600.0000.3600.3990.3770.4081.0000.0000.000
심한장애(중증)수급자수(명)0.6910.0000.8480.0000.0000.0000.0000.0000.0000.0000.0001.0000.000
심하지않은장애(경증)수급자수(명)0.7500.3690.7700.0000.0000.0000.5380.5300.5250.5210.0000.0001.000
2024-04-11T13:52:32.789311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
3급중증수급자수(명)시군명
3급중증수급자수(명)1.0000.122
시군명0.1221.000
2024-04-11T13:52:32.864115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기준년도합계(명)1급중증수급자수(명)2급중증수급자수(명)3급경증수급자수(명)4급경증수급자수(명)5급경증수급자수(명)6급경증수급자수(명)해당없음수급자수(명)심한장애(중증)수급자수(명)심하지않은장애(경증)수급자수(명)시군명3급중증수급자수(명)
기준년도1.0000.203-0.230-0.364-0.689-0.681-0.674-0.673-0.2160.6220.8080.0000.151
합계(명)0.2031.0000.1080.2220.2340.2360.2360.2330.0750.3040.2610.5010.091
1급중증수급자수(명)-0.2300.1081.0000.1890.3200.3190.3130.3120.027-0.201-0.2290.0000.444
2급중증수급자수(명)-0.3640.2220.1891.0000.5620.5490.5530.5500.351-0.335-0.3820.0260.447
3급경증수급자수(명)-0.6890.2340.3200.5621.0000.9930.9910.9880.381-0.684-0.7790.5020.261
4급경증수급자수(명)-0.6810.2360.3190.5490.9931.0000.9970.9950.367-0.684-0.7790.4260.321
5급경증수급자수(명)-0.6740.2360.3130.5530.9910.9971.0000.9970.371-0.684-0.7790.3880.269
6급경증수급자수(명)-0.6730.2330.3120.5500.9880.9950.9971.0000.373-0.684-0.7790.4220.318
해당없음수급자수(명)-0.2160.0750.0270.3510.3810.3670.3710.3731.000-0.267-0.3040.0000.000
심한장애(중증)수급자수(명)0.6220.304-0.201-0.335-0.684-0.684-0.684-0.684-0.2671.0000.6700.0000.000
심하지않은장애(경증)수급자수(명)0.8080.261-0.229-0.382-0.779-0.779-0.779-0.779-0.3040.6701.0000.1330.000
시군명0.0000.5010.0000.0260.5020.4260.3880.4220.0000.0000.1331.0000.122
3급중증수급자수(명)0.1510.0910.4440.4470.2610.3210.2690.3180.0000.0000.0000.1221.000

Missing values

2024-04-11T13:52:29.441201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-11T13:52:29.609957image/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

기준년도시군명합계(명)1급중증수급자수(명)2급중증수급자수(명)3급중증수급자수(명)3급경증수급자수(명)4급경증수급자수(명)5급경증수급자수(명)6급경증수급자수(명)해당없음수급자수(명)심한장애(중증)수급자수(명)심하지않은장애(경증)수급자수(명)
02023가평군845000000000398
12023고양시49430000000041750
22023과천시16700000000150
32023광명시1400000000000493
42023광주시1464000000000509
52023구리시1067000000000340
62023군포시1622000000000551
72023김포시2082000000001668
82023남양주시41190000000021271
92023동두천시1416000000001496
기준년도시군명합계(명)1급중증수급자수(명)2급중증수급자수(명)3급중증수급자수(명)3급경증수급자수(명)4급경증수급자수(명)5급경증수급자수(명)6급경증수급자수(명)해당없음수급자수(명)심한장애(중증)수급자수(명)심하지않은장애(경증)수급자수(명)
3312013오산시671001313125123109000
3322013용인시1531011708274285261100
3332013의왕시4480001798310482000
3342013의정부시2271011872481465451000
3352013이천시1021011410215223171000
3362013파주시1757870654412353323000
3372013평택시1953000775364397417000
3382013포천시1294000483272277262000
3392013하남시665000242150159114000
3402013화성시1453312686259262240000