Overview

Dataset statistics

Number of variables10
Number of observations155
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory13.6 KiB
Average record size in memory89.9 B

Variable types

Categorical3
Numeric7

Dataset

Description장애인복지신문 보급 집계현황
Author경기복지재단(경기도장애인복지종합지원센터)
URLhttps://data.gg.go.kr/portal/data/service/selectServicePage.do?&infId=0EMF8OGVS224X91KZKIA26248187&infSeq=1

Alerts

기타 has constant value ""Constant
총계(가구수) is highly overall correlated with 시군명High correlation
1급2급가구수(1급~2급) is highly overall correlated with 3급가구수 and 2 other fieldsHigh correlation
3급가구수 is highly overall correlated with 1급2급가구수(1급~2급) and 2 other fieldsHigh correlation
4급5급6급가구수(4급~6급) is highly overall correlated with 1급2급가구수(1급~2급) and 1 other fieldsHigh correlation
장애의정도가심하지않은장애 is highly overall correlated with 1급2급가구수(1급~2급) and 1 other fieldsHigh correlation
시군명 is highly overall correlated with 총계(가구수)High correlation
총계(가구수) has 33 (21.3%) zerosZeros
1급2급가구수(1급~2급) has 124 (80.0%) zerosZeros
3급가구수 has 124 (80.0%) zerosZeros
4급5급6급가구수(4급~6급) has 137 (88.4%) zerosZeros
장애의정도가심하지않은장애 has 45 (29.0%) zerosZeros
장애의정도가심한장애 has 69 (44.5%) zerosZeros
시설 has 116 (74.8%) zerosZeros

Reproduction

Analysis started2024-03-12 23:54:07.826883
Analysis finished2024-03-12 23:54:12.479957
Duration4.65 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

기준년도
Categorical

Distinct5
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2022
31 
2021
31 
2020
31 
2019
31 
2018
31 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2022
2nd row2022
3rd row2022
4th row2022
5th row2022

Common Values

ValueCountFrequency (%)
2022 31
20.0%
2021 31
20.0%
2020 31
20.0%
2019 31
20.0%
2018 31
20.0%

Length

2024-03-13T08:54:12.532114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T08:54:12.614707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022 31
20.0%
2021 31
20.0%
2020 31
20.0%
2019 31
20.0%
2018 31
20.0%

시군명
Categorical

HIGH CORRELATION 

Distinct31
Distinct (%)20.0%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
가평군
 
5
고양시
 
5
과천시
 
5
광명시
 
5
광주시
 
5
Other values (26)
130 

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 5
 
3.2%
고양시 5
 
3.2%
과천시 5
 
3.2%
광명시 5
 
3.2%
광주시 5
 
3.2%
구리시 5
 
3.2%
군포시 5
 
3.2%
김포시 5
 
3.2%
남양주시 5
 
3.2%
동두천시 5
 
3.2%
Other values (21) 105
67.7%

Length

2024-03-13T08:54:12.713980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
가평군 5
 
3.2%
안양시 5
 
3.2%
하남시 5
 
3.2%
포천시 5
 
3.2%
평택시 5
 
3.2%
파주시 5
 
3.2%
이천시 5
 
3.2%
의정부시 5
 
3.2%
의왕시 5
 
3.2%
용인시 5
 
3.2%
Other values (21) 105
67.7%

총계(가구수)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct116
Distinct (%)74.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean738.49032
Minimum0
Maximum5882
Zeros33
Zeros (%)21.3%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2024-03-13T08:54:12.808986image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q1221.5
median531
Q3913.5
95-th percentile1848.4
Maximum5882
Range5882
Interquartile range (IQR)692

Descriptive statistics

Standard deviation973.68336
Coefficient of variation (CV)1.3184782
Kurtosis16.417231
Mean738.49032
Median Absolute Deviation (MAD)362
Skewness3.647415
Sum114466
Variance948059.28
MonotonicityNot monotonic
2024-03-13T08:54:12.919304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 33
 
21.3%
541 3
 
1.9%
300 3
 
1.9%
341 2
 
1.3%
1190 2
 
1.3%
322 2
 
1.3%
1548 1
 
0.6%
842 1
 
0.6%
304 1
 
0.6%
250 1
 
0.6%
Other values (106) 106
68.4%
ValueCountFrequency (%)
0 33
21.3%
141 1
 
0.6%
160 1
 
0.6%
169 1
 
0.6%
176 1
 
0.6%
203 1
 
0.6%
220 1
 
0.6%
223 1
 
0.6%
225 1
 
0.6%
250 1
 
0.6%
ValueCountFrequency (%)
5882 1
0.6%
5850 1
0.6%
5830 1
0.6%
5465 1
0.6%
2644 1
0.6%
2064 1
0.6%
2029 1
0.6%
1868 1
0.6%
1840 1
0.6%
1800 1
0.6%

1급2급가구수(1급~2급)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct32
Distinct (%)20.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean97.187097
Minimum0
Maximum1964
Zeros124
Zeros (%)80.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2024-03-13T08:54:13.030209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile569.9
Maximum1964
Range1964
Interquartile range (IQR)0

Descriptive statistics

Standard deviation251.84183
Coefficient of variation (CV)2.5913094
Kurtosis20.863683
Mean97.187097
Median Absolute Deviation (MAD)0
Skewness3.9118461
Sum15064
Variance63424.309
MonotonicityNot monotonic
2024-03-13T08:54:13.128722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
0 124
80.0%
358 1
 
0.6%
557 1
 
0.6%
331 1
 
0.6%
705 1
 
0.6%
547 1
 
0.6%
757 1
 
0.6%
251 1
 
0.6%
817 1
 
0.6%
173 1
 
0.6%
Other values (22) 22
 
14.2%
ValueCountFrequency (%)
0 124
80.0%
134 1
 
0.6%
149 1
 
0.6%
159 1
 
0.6%
164 1
 
0.6%
173 1
 
0.6%
209 1
 
0.6%
237 1
 
0.6%
251 1
 
0.6%
255 1
 
0.6%
ValueCountFrequency (%)
1964 1
0.6%
974 1
0.6%
895 1
0.6%
817 1
0.6%
773 1
0.6%
757 1
0.6%
705 1
0.6%
600 1
0.6%
557 1
0.6%
547 1
0.6%

3급가구수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct31
Distinct (%)20.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean59.225806
Minimum0
Maximum1368
Zeros124
Zeros (%)80.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2024-03-13T08:54:13.228812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile398.8
Maximum1368
Range1368
Interquartile range (IQR)0

Descriptive statistics

Standard deviation170.636
Coefficient of variation (CV)2.8811089
Kurtosis25.221463
Mean59.225806
Median Absolute Deviation (MAD)0
Skewness4.4283851
Sum9180
Variance29116.643
MonotonicityNot monotonic
2024-03-13T08:54:13.320524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
0 124
80.0%
151 2
 
1.3%
424 1
 
0.6%
183 1
 
0.6%
193 1
 
0.6%
248 1
 
0.6%
433 1
 
0.6%
100 1
 
0.6%
639 1
 
0.6%
110 1
 
0.6%
Other values (21) 21
 
13.5%
ValueCountFrequency (%)
0 124
80.0%
14 1
 
0.6%
26 1
 
0.6%
45 1
 
0.6%
69 1
 
0.6%
85 1
 
0.6%
100 1
 
0.6%
108 1
 
0.6%
110 1
 
0.6%
144 1
 
0.6%
ValueCountFrequency (%)
1368 1
0.6%
771 1
0.6%
639 1
0.6%
603 1
0.6%
548 1
0.6%
485 1
0.6%
433 1
0.6%
424 1
0.6%
388 1
0.6%
381 1
0.6%

4급5급6급가구수(4급~6급)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct19
Distinct (%)12.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean41.503226
Minimum0
Maximum2133
Zeros137
Zeros (%)88.4%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2024-03-13T08:54:13.417578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile234.7
Maximum2133
Range2133
Interquartile range (IQR)0

Descriptive statistics

Standard deviation198.38476
Coefficient of variation (CV)4.779984
Kurtosis82.095127
Mean41.503226
Median Absolute Deviation (MAD)0
Skewness8.3057011
Sum6433
Variance39356.511
MonotonicityNot monotonic
2024-03-13T08:54:13.511531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
0 137
88.4%
547 1
 
0.6%
6 1
 
0.6%
139 1
 
0.6%
448 1
 
0.6%
226 1
 
0.6%
225 1
 
0.6%
365 1
 
0.6%
45 1
 
0.6%
284 1
 
0.6%
Other values (9) 9
 
5.8%
ValueCountFrequency (%)
0 137
88.4%
6 1
 
0.6%
19 1
 
0.6%
45 1
 
0.6%
91 1
 
0.6%
123 1
 
0.6%
127 1
 
0.6%
139 1
 
0.6%
141 1
 
0.6%
225 1
 
0.6%
ValueCountFrequency (%)
2133 1
0.6%
739 1
0.6%
547 1
0.6%
520 1
0.6%
448 1
0.6%
365 1
0.6%
284 1
0.6%
255 1
0.6%
226 1
0.6%
225 1
0.6%

장애의정도가심하지않은장애
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct102
Distinct (%)65.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean439.69677
Minimum0
Maximum3486
Zeros45
Zeros (%)29.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2024-03-13T08:54:13.607077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median300
Q3597
95-th percentile1291
Maximum3486
Range3486
Interquartile range (IQR)597

Descriptive statistics

Standard deviation583.57936
Coefficient of variation (CV)1.3272314
Kurtosis12.881148
Mean439.69677
Median Absolute Deviation (MAD)300
Skewness3.0547748
Sum68153
Variance340564.87
MonotonicityNot monotonic
2024-03-13T08:54:13.713713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 45
29.0%
3486 3
 
1.9%
470 2
 
1.3%
285 2
 
1.3%
1 2
 
1.3%
219 2
 
1.3%
1291 2
 
1.3%
300 2
 
1.3%
935 2
 
1.3%
973 1
 
0.6%
Other values (92) 92
59.4%
ValueCountFrequency (%)
0 45
29.0%
1 2
 
1.3%
2 1
 
0.6%
48 1
 
0.6%
84 1
 
0.6%
89 1
 
0.6%
109 1
 
0.6%
115 1
 
0.6%
128 1
 
0.6%
153 1
 
0.6%
ValueCountFrequency (%)
3486 3
1.9%
2124 1
 
0.6%
1484 1
 
0.6%
1322 1
 
0.6%
1294 1
 
0.6%
1291 2
1.3%
1190 1
 
0.6%
1163 1
 
0.6%
1158 1
 
0.6%
1155 1
 
0.6%

장애의정도가심한장애
Real number (ℝ)

ZEROS 

Distinct78
Distinct (%)50.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean239.06452
Minimum0
Maximum3456
Zeros69
Zeros (%)44.5%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2024-03-13T08:54:13.821666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median54
Q3289.5
95-th percentile961.9
Maximum3456
Range3456
Interquartile range (IQR)289.5

Descriptive statistics

Standard deviation455.27952
Coefficient of variation (CV)1.9044211
Kurtosis20.164987
Mean239.06452
Median Absolute Deviation (MAD)54
Skewness3.9203984
Sum37055
Variance207279.44
MonotonicityNot monotonic
2024-03-13T08:54:13.925789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 69
44.5%
92 3
 
1.9%
72 2
 
1.3%
286 2
 
1.3%
270 2
 
1.3%
120 2
 
1.3%
175 2
 
1.3%
181 2
 
1.3%
345 2
 
1.3%
51 1
 
0.6%
Other values (68) 68
43.9%
ValueCountFrequency (%)
0 69
44.5%
2 1
 
0.6%
8 1
 
0.6%
25 1
 
0.6%
30 1
 
0.6%
35 1
 
0.6%
42 1
 
0.6%
46 1
 
0.6%
51 1
 
0.6%
54 1
 
0.6%
ValueCountFrequency (%)
3456 1
0.6%
2146 1
0.6%
2114 1
0.6%
2096 1
0.6%
1180 1
0.6%
1098 1
0.6%
1004 1
0.6%
992 1
0.6%
949 1
0.6%
920 1
0.6%

시설
Real number (ℝ)

ZEROS 

Distinct29
Distinct (%)18.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean33.264516
Minimum0
Maximum656
Zeros116
Zeros (%)74.8%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2024-03-13T08:54:14.050565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile250
Maximum656
Range656
Interquartile range (IQR)1

Descriptive statistics

Standard deviation94.686295
Coefficient of variation (CV)2.8464654
Kurtosis15.864152
Mean33.264516
Median Absolute Deviation (MAD)0
Skewness3.7127747
Sum5156
Variance8965.4945
MonotonicityNot monotonic
2024-03-13T08:54:14.186384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
0 116
74.8%
10 4
 
2.6%
250 3
 
1.9%
6 2
 
1.3%
86 2
 
1.3%
4 2
 
1.3%
2 2
 
1.3%
75 2
 
1.3%
72 2
 
1.3%
300 1
 
0.6%
Other values (19) 19
 
12.3%
ValueCountFrequency (%)
0 116
74.8%
2 2
 
1.3%
3 1
 
0.6%
4 2
 
1.3%
6 2
 
1.3%
7 1
 
0.6%
9 1
 
0.6%
10 4
 
2.6%
12 1
 
0.6%
26 1
 
0.6%
ValueCountFrequency (%)
656 1
 
0.6%
402 1
 
0.6%
386 1
 
0.6%
371 1
 
0.6%
367 1
 
0.6%
300 1
 
0.6%
250 3
1.9%
223 1
 
0.6%
214 1
 
0.6%
190 1
 
0.6%

기타
Categorical

CONSTANT 

Distinct1
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
0
155 

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 (%)
0 155
100.0%

Length

2024-03-13T08:54:14.518395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T08:54:14.592958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 155
100.0%

Interactions

2024-03-13T08:54:11.727355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:54:08.084401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:54:08.560640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:54:09.174459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:54:09.998492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:54:10.723261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:54:11.209461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:54:11.830006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:54:08.148089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:54:08.628107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:54:09.270530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:54:10.063329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:54:10.791995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:54:11.277896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:54:11.954065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:54:08.221085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:54:08.700507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:54:09.376666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:54:10.132571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:54:10.866654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:54:11.351837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:54:12.031748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:54:08.288938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:54:08.786506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:54:09.501935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:54:10.212874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:54:10.937094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:54:11.430096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:54:12.101320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:54:08.352632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:54:08.865596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:54:09.662858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:54:10.283991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:54:11.001307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:54:11.491591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:54:12.169722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:54:08.424003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:54:08.965186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:54:09.800576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:54:10.585222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:54:11.072170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:54:11.564824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:54:12.239282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:54:08.493324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:54:09.072374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:54:09.907899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:54:10.656194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:54:11.142460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T08:54:11.640283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-13T08:54:14.643473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기준년도시군명총계(가구수)1급2급가구수(1급~2급)3급가구수4급5급6급가구수(4급~6급)장애의정도가심하지않은장애장애의정도가심한장애시설
기준년도1.0000.0000.2610.5560.5300.5090.4050.3690.000
시군명0.0001.0000.8820.0000.0000.0000.7720.6030.783
총계(가구수)0.2610.8821.0000.6600.5220.4080.5720.7780.761
1급2급가구수(1급~2급)0.5560.0000.6601.0000.8640.7450.0000.0000.000
3급가구수0.5300.0000.5220.8641.0000.7780.0000.0000.000
4급5급6급가구수(4급~6급)0.5090.0000.4080.7450.7781.0000.0000.0000.000
장애의정도가심하지않은장애0.4050.7720.5720.0000.0000.0001.0000.7920.627
장애의정도가심한장애0.3690.6030.7780.0000.0000.0000.7921.0000.624
시설0.0000.7830.7610.0000.0000.0000.6270.6241.000
2024-03-13T08:54:14.734796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기준년도시군명
기준년도1.0000.000
시군명0.0001.000
2024-03-13T08:54:14.811521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
총계(가구수)1급2급가구수(1급~2급)3급가구수4급5급6급가구수(4급~6급)장애의정도가심하지않은장애장애의정도가심한장애시설기준년도시군명
총계(가구수)1.0000.2750.2790.3000.0830.2180.1600.1790.577
1급2급가구수(1급~2급)0.2751.0000.9970.732-0.617-0.499-0.2840.4170.000
3급가구수0.2790.9971.0000.758-0.617-0.499-0.2840.3730.000
4급5급6급가구수(4급~6급)0.3000.7320.7581.000-0.450-0.364-0.2070.2100.000
장애의정도가심하지않은장애0.083-0.617-0.617-0.4501.0000.2820.4220.2710.416
장애의정도가심한장애0.218-0.499-0.499-0.3640.2821.0000.4410.2590.286
시설0.160-0.284-0.284-0.2070.4220.4411.0000.0000.408
기준년도0.1790.4170.3730.2100.2710.2590.0001.0000.000
시군명0.5770.0000.0000.0000.4160.2860.4080.0001.000

Missing values

2024-03-13T08:54:12.328682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-13T08:54:12.436488image/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

기준년도시군명총계(가구수)1급2급가구수(1급~2급)3급가구수4급5급6급가구수(4급~6급)장애의정도가심하지않은장애장애의정도가심한장애시설기타
02022가평군2500002400100
12022고양시18000001294435710
22022과천시1690001155400
32022광명시846000564272100
42022광주시5470004836400
52022구리시6940001701383860
62022군포시5760002272491000
72022김포시355000355000
82022남양주시113500079034500
92022동두천시275000275000
기준년도시군명총계(가구수)1급2급가구수(1급~2급)3급가구수4급5급6급가구수(4급~6급)장애의정도가심하지않은장애장애의정도가심한장애시설기타
1452018오산시3222378500000
1462018용인시13715353884480000
1472018의왕시4221731101390000
1482018의정부시145681763900000
1492018이천시35125110000000
1502018파주시119075743300000
1512018평택시79554724800000
1522018포천시89870519300000
1532018하남시51433118300000
1542018화성시98755742460000