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

Categorical4
Numeric6

Dataset

Description저소득장애인 의료비 지원 집계현황
Author경기복지재단(경기도장애인복지종합지원센터)
URLhttps://data.gg.go.kr/portal/data/service/selectServicePage.do?&infId=4413BQQ9LZWMTNI8LEJ226084122&infSeq=1

Alerts

전체지원건수(건) is highly overall correlated with 전체지원금액(원) and 4 other fieldsHigh correlation
전체지원금액(원) is highly overall correlated with 전체지원건수(건) and 4 other fieldsHigh correlation
의료비지원건수(건) is highly overall correlated with 전체지원건수(건) and 4 other fieldsHigh correlation
의료비지원금액(원) is highly overall correlated with 전체지원건수(건) and 4 other fieldsHigh correlation
보조기기지원건수(건) is highly overall correlated with 전체지원건수(건) and 4 other fieldsHigh correlation
보조기기지원금액(원) is highly overall correlated with 전체지원건수(건) and 4 other fieldsHigh correlation
보장구지원건수(건) is highly imbalanced (94.4%)Imbalance
보장구지원금액(원) is highly imbalanced (94.4%)Imbalance
전체지원건수(건) has 3 (1.9%) zerosZeros
전체지원금액(원) has 3 (1.9%) zerosZeros
의료비지원건수(건) has 41 (26.5%) zerosZeros
의료비지원금액(원) has 41 (26.5%) zerosZeros
보조기기지원건수(건) has 34 (21.9%) zerosZeros
보조기기지원금액(원) has 34 (21.9%) zerosZeros

Reproduction

Analysis started2023-12-10 22:58:59.924124
Analysis finished2023-12-10 22:59:03.502805
Duration3.58 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

2023-12-11T07:59:03.566128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:59:03.707329image/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

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

2023-12-11T07:59:03.827445image/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%

전체지원건수(건)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct64
Distinct (%)41.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean28.593548
Minimum0
Maximum237
Zeros3
Zeros (%)1.9%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2023-12-11T07:59:03.936453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile2
Q16.5
median17
Q335
95-th percentile105
Maximum237
Range237
Interquartile range (IQR)28.5

Descriptive statistics

Standard deviation36.224892
Coefficient of variation (CV)1.2668904
Kurtosis10.10189
Mean28.593548
Median Absolute Deviation (MAD)13
Skewness2.8467984
Sum4432
Variance1312.2428
MonotonicityNot monotonic
2023-12-11T07:59:04.067646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2 11
 
7.1%
4 8
 
5.2%
11 7
 
4.5%
13 6
 
3.9%
6 6
 
3.9%
12 6
 
3.9%
27 6
 
3.9%
8 6
 
3.9%
3 5
 
3.2%
23 5
 
3.2%
Other values (54) 89
57.4%
ValueCountFrequency (%)
0 3
 
1.9%
1 3
 
1.9%
2 11
7.1%
3 5
3.2%
4 8
5.2%
5 3
 
1.9%
6 6
3.9%
7 3
 
1.9%
8 6
3.9%
9 3
 
1.9%
ValueCountFrequency (%)
237 1
0.6%
185 1
0.6%
142 1
0.6%
140 1
0.6%
138 1
0.6%
137 1
0.6%
130 1
0.6%
119 1
0.6%
99 1
0.6%
96 1
0.6%

전체지원금액(원)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct151
Distinct (%)97.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean29336293
Minimum0
Maximum1.8901832 × 108
Zeros3
Zeros (%)1.9%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2023-12-11T07:59:04.202617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1500000
Q17711530
median15981420
Q339029265
95-th percentile97401246
Maximum1.8901832 × 108
Range1.8901832 × 108
Interquartile range (IQR)31317735

Descriptive statistics

Standard deviation33073737
Coefficient of variation (CV)1.1274
Kurtosis6.2506575
Mean29336293
Median Absolute Deviation (MAD)12606790
Skewness2.2506241
Sum4.5471254 × 109
Variance1.0938721 × 1015
MonotonicityNot monotonic
2023-12-11T07:59:04.370543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 3
 
1.9%
3000000 2
 
1.3%
1500000 2
 
1.3%
117645760 1
 
0.6%
48354580 1
 
0.6%
18602610 1
 
0.6%
118182140 1
 
0.6%
59511550 1
 
0.6%
179030770 1
 
0.6%
35144680 1
 
0.6%
Other values (141) 141
91.0%
ValueCountFrequency (%)
0 3
1.9%
735100 1
 
0.6%
969860 1
 
0.6%
977400 1
 
0.6%
1050000 1
 
0.6%
1500000 2
1.3%
1513190 1
 
0.6%
1542280 1
 
0.6%
1929280 1
 
0.6%
1985040 1
 
0.6%
ValueCountFrequency (%)
189018320 1
0.6%
179030770 1
0.6%
132291790 1
0.6%
123242280 1
0.6%
118182140 1
0.6%
117645760 1
0.6%
115334610 1
0.6%
101298650 1
0.6%
95730930 1
0.6%
95486380 1
0.6%

의료비지원건수(건)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct45
Distinct (%)29.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean15.651613
Minimum0
Maximum132
Zeros41
Zeros (%)26.5%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2023-12-11T07:59:04.507709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median6
Q316
95-th percentile80.8
Maximum132
Range132
Interquartile range (IQR)16

Descriptive statistics

Standard deviation26.415657
Coefficient of variation (CV)1.6877275
Kurtosis7.5848014
Mean15.651613
Median Absolute Deviation (MAD)6
Skewness2.758668
Sum2426
Variance697.78693
MonotonicityNot monotonic
2023-12-11T07:59:04.662848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
0 41
26.5%
3 12
 
7.7%
1 9
 
5.8%
4 7
 
4.5%
12 6
 
3.9%
14 5
 
3.2%
7 5
 
3.2%
15 4
 
2.6%
13 4
 
2.6%
6 4
 
2.6%
Other values (35) 58
37.4%
ValueCountFrequency (%)
0 41
26.5%
1 9
 
5.8%
2 4
 
2.6%
3 12
 
7.7%
4 7
 
4.5%
5 2
 
1.3%
6 4
 
2.6%
7 5
 
3.2%
8 4
 
2.6%
9 2
 
1.3%
ValueCountFrequency (%)
132 1
0.6%
128 1
0.6%
120 1
0.6%
110 1
0.6%
106 1
0.6%
100 1
0.6%
94 1
0.6%
85 1
0.6%
79 1
0.6%
77 1
0.6%

의료비지원금액(원)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct113
Distinct (%)72.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13424443
Minimum0
Maximum1.0635637 × 108
Zeros41
Zeros (%)26.5%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2023-12-11T07:59:04.825690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median5526870
Q315792990
95-th percentile58789021
Maximum1.0635637 × 108
Range1.0635637 × 108
Interquartile range (IQR)15792990

Descriptive statistics

Standard deviation20539683
Coefficient of variation (CV)1.5300212
Kurtosis6.9211982
Mean13424443
Median Absolute Deviation (MAD)5526870
Skewness2.5528899
Sum2.0807887 × 109
Variance4.2187859 × 1014
MonotonicityNot monotonic
2023-12-11T07:59:04.963006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 41
 
26.5%
1500000 3
 
1.9%
1819860 1
 
0.6%
26304030 1
 
0.6%
2491420 1
 
0.6%
14821600 1
 
0.6%
8664000 1
 
0.6%
26145600 1
 
0.6%
9394330 1
 
0.6%
7769270 1
 
0.6%
Other values (103) 103
66.5%
ValueCountFrequency (%)
0 41
26.5%
279000 1
 
0.6%
635100 1
 
0.6%
723220 1
 
0.6%
931860 1
 
0.6%
969860 1
 
0.6%
1190000 1
 
0.6%
1447400 1
 
0.6%
1458870 1
 
0.6%
1486360 1
 
0.6%
ValueCountFrequency (%)
106356370 1
0.6%
99994030 1
0.6%
93942810 1
0.6%
81922280 1
0.6%
80236580 1
0.6%
75236790 1
0.6%
74283140 1
0.6%
59045200 1
0.6%
58679230 1
0.6%
58146250 1
0.6%

보장구지원건수(건)
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
0
154 
3
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)0.6%

Sample

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

Common Values

ValueCountFrequency (%)
0 154
99.4%
3 1
 
0.6%

Length

2023-12-11T07:59:05.097102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:59:05.465651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 154
99.4%
3 1
 
0.6%

보장구지원금액(원)
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
0
154 
153030
 
1

Length

Max length6
Median length1
Mean length1.0322581
Min length1

Unique

Unique1 ?
Unique (%)0.6%

Sample

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

Common Values

ValueCountFrequency (%)
0 154
99.4%
153030 1
 
0.6%

Length

2023-12-11T07:59:05.571955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T07:59:05.670852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 154
99.4%
153030 1
 
0.6%

보조기기지원건수(건)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct36
Distinct (%)23.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10.335484
Minimum0
Maximum105
Zeros34
Zeros (%)21.9%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2023-12-11T07:59:05.764040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median6
Q315
95-th percentile32
Maximum105
Range105
Interquartile range (IQR)14

Descriptive statistics

Standard deviation13.428153
Coefficient of variation (CV)1.2992283
Kurtosis16.058815
Mean10.335484
Median Absolute Deviation (MAD)6
Skewness3.0874437
Sum1602
Variance180.31529
MonotonicityNot monotonic
2023-12-11T07:59:05.878656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=36)
ValueCountFrequency (%)
0 34
21.9%
4 13
 
8.4%
1 9
 
5.8%
8 9
 
5.8%
3 8
 
5.2%
6 7
 
4.5%
2 6
 
3.9%
20 5
 
3.2%
15 5
 
3.2%
7 5
 
3.2%
Other values (26) 54
34.8%
ValueCountFrequency (%)
0 34
21.9%
1 9
 
5.8%
2 6
 
3.9%
3 8
 
5.2%
4 13
 
8.4%
5 4
 
2.6%
6 7
 
4.5%
7 5
 
3.2%
8 9
 
5.8%
9 3
 
1.9%
ValueCountFrequency (%)
105 1
 
0.6%
57 1
 
0.6%
46 2
1.3%
40 1
 
0.6%
36 1
 
0.6%
34 1
 
0.6%
32 2
1.3%
31 2
1.3%
30 3
1.9%
29 1
 
0.6%

보조기기지원금액(원)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct109
Distinct (%)70.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13505534
Minimum0
Maximum89024290
Zeros34
Zeros (%)21.9%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2023-12-11T07:59:06.056500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11325000
median7500000
Q320432050
95-th percentile43551100
Maximum89024290
Range89024290
Interquartile range (IQR)19107050

Descriptive statistics

Standard deviation16298115
Coefficient of variation (CV)1.2067731
Kurtosis4.0761216
Mean13505534
Median Absolute Deviation (MAD)7500000
Skewness1.8723345
Sum2.0933577 × 109
Variance2.6562855 × 1014
MonotonicityNot monotonic
2023-12-11T07:59:06.181583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 34
 
21.9%
1500000 4
 
2.6%
4500000 4
 
2.6%
6000000 3
 
1.9%
3000000 3
 
1.9%
10500000 2
 
1.3%
15305000 2
 
1.3%
7500000 2
 
1.3%
20298100 1
 
0.6%
13490000 1
 
0.6%
Other values (99) 99
63.9%
ValueCountFrequency (%)
0 34
21.9%
100000 1
 
0.6%
440000 1
 
0.6%
900000 1
 
0.6%
1050000 1
 
0.6%
1150000 1
 
0.6%
1500000 4
 
2.6%
1553000 1
 
0.6%
1880000 1
 
0.6%
2360000 1
 
0.6%
ValueCountFrequency (%)
89024290 1
0.6%
72674400 1
0.6%
64900700 1
0.6%
63178000 1
0.6%
57055000 1
0.6%
56540000 1
0.6%
50956000 1
0.6%
43899000 1
0.6%
43402000 1
0.6%
42332000 1
0.6%

Interactions

2023-12-11T07:59:02.737403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:00.275595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:00.886366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:01.418658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:01.830916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:02.277538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:02.811310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:00.332664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:01.017572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:01.483489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:01.901163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:02.343747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:02.890369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:00.621280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:01.098338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:01.555270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:01.990272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:02.421557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:02.982233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:00.683682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:01.188594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:01.623801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:02.064761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:02.504827image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:03.058933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:00.750427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:01.279710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:01.695032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:02.142666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:02.582803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:03.144307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:00.813154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:01.351472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:01.765116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:02.208883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T07:59:02.654016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T07:59:06.268445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기준년도시군명전체지원건수(건)전체지원금액(원)의료비지원건수(건)의료비지원금액(원)보장구지원건수(건)보장구지원금액(원)보조기기지원건수(건)보조기기지원금액(원)
기준년도1.0000.0000.1680.0000.2390.3060.0110.0110.1980.549
시군명0.0001.0000.6840.8290.7270.7640.0460.0460.6790.615
전체지원건수(건)0.1680.6841.0000.9680.8780.8810.2720.2720.8660.861
전체지원금액(원)0.0000.8290.9681.0000.8600.8950.3710.3710.8090.852
의료비지원건수(건)0.2390.7270.8780.8601.0000.9680.0000.0000.7420.826
의료비지원금액(원)0.3060.7640.8810.8950.9681.0000.0000.0000.7750.869
보장구지원건수(건)0.0110.0460.2720.3710.0000.0001.0000.6980.1710.255
보장구지원금액(원)0.0110.0460.2720.3710.0000.0000.6981.0000.1710.255
보조기기지원건수(건)0.1980.6790.8660.8090.7420.7750.1710.1711.0000.932
보조기기지원금액(원)0.5490.6150.8610.8520.8260.8690.2550.2550.9321.000
2023-12-11T07:59:06.382850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군명보장구지원건수(건)기준년도보장구지원금액(원)
시군명1.0000.0000.0000.000
보장구지원건수(건)0.0001.0000.0000.492
기준년도0.0000.0001.0000.000
보장구지원금액(원)0.0000.4920.0001.000
2023-12-11T07:59:06.475623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
전체지원건수(건)전체지원금액(원)의료비지원건수(건)의료비지원금액(원)보조기기지원건수(건)보조기기지원금액(원)기준년도시군명보장구지원건수(건)보장구지원금액(원)
전체지원건수(건)1.0000.9770.8090.8070.7430.7390.1010.3160.2000.200
전체지원금액(원)0.9771.0000.7950.8200.7970.8030.0000.4640.2730.273
의료비지원건수(건)0.8090.7951.0000.9790.8100.8110.0980.3250.0000.000
의료비지원금액(원)0.8070.8200.9791.0000.8340.8360.1280.3600.0000.000
보조기기지원건수(건)0.7430.7970.8100.8341.0000.9920.1230.3170.1970.197
보조기기지원금액(원)0.7390.8030.8110.8360.9921.0000.2540.2440.1900.190
기준년도0.1010.0000.0980.1280.1230.2541.0000.0000.0000.000
시군명0.3160.4640.3250.3600.3170.2440.0001.0000.0000.000
보장구지원건수(건)0.2000.2730.0000.0000.1970.1900.0000.0001.0000.492
보장구지원금액(원)0.2000.2730.0000.0000.1970.1900.0000.0000.4921.000

Missing values

2023-12-11T07:59:03.290979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T07:59:03.450311image/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

기준년도시군명전체지원건수(건)전체지원금액(원)의료비지원건수(건)의료비지원금액(원)보장구지원건수(건)보장구지원금액(원)보조기기지원건수(건)보조기기지원금액(원)
02022가평군22047480000000
12022고양시1617960150000000
22022과천시2977400000000
32022광명시33500000000000
42022광주시1014055110000000
52022구리시43057450000000
62022군포시45361000000000
72022김포시1415443220000000
82022남양주시2319751770000000
92022동두천시98742200000000
기준년도시군명전체지원건수(건)전체지원금액(원)의료비지원건수(건)의료비지원금액(원)보장구지원건수(건)보장구지원금액(원)보조기기지원건수(건)보조기기지원금액(원)
1452018오산시1215360440668884400068472000
1462018용인시334681000046000000002940810000
1472018의왕시131317849032497490001010681000
1482018의정부시344897881079280810002739698000
1492018이천시513092112047256211200045300000
1502018파주시29282092501412904250001515305000
1512018평택시46413579902620791990002020566000
1522018포천시1511717590953705900066347000
1532018하남시54773210332202100021553000
1542018화성시5159000000242284697031530302436000000