Overview

Dataset statistics

Number of variables13
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.2 MiB
Average record size in memory123.0 B

Variable types

DateTime2
Numeric11

Dataset

Description컬럼명 구분 구축년월, 구축시도, 구축시군구, 선택기관, 추가선택기관, 선택한의원, 선택치과의원, 희귀난치성, 11개질환, 기타질환, 자발적참여자, 처리일자
Author국민건강보험공단
URLhttps://www.data.go.kr/data/15121267/fileData.do

Alerts

구축시도 is highly overall correlated with 구축시군구 and 1 other fieldsHigh correlation
구축시군구 is highly overall correlated with 구축시도 and 1 other fieldsHigh correlation
선택기관 is highly overall correlated with 추가선택기관 and 5 other fieldsHigh correlation
추가선택기관 is highly overall correlated with 선택기관 and 4 other fieldsHigh correlation
선택한의원 is highly overall correlated with 선택기관 and 3 other fieldsHigh correlation
선택치과의원 is highly overall correlated with 선택기관 and 3 other fieldsHigh correlation
희귀난치성 is highly overall correlated with 선택기관High correlation
11개질환 is highly overall correlated with 선택기관 and 2 other fieldsHigh correlation
기타질환 is highly overall correlated with 선택기관 and 4 other fieldsHigh correlation
읍면동 is highly overall correlated with 구축시도 and 1 other fieldsHigh correlation
자발적참여자 is highly skewed (γ1 = 28.48385362)Skewed
선택기관 has 307 (3.1%) zerosZeros
추가선택기관 has 1395 (14.0%) zerosZeros
선택한의원 has 2964 (29.6%) zerosZeros
선택치과의원 has 3012 (30.1%) zerosZeros
희귀난치성 has 6484 (64.8%) zerosZeros
11개질환 has 3748 (37.5%) zerosZeros
기타질환 has 428 (4.3%) zerosZeros
자발적참여자 has 5803 (58.0%) zerosZeros

Reproduction

Analysis started2023-12-12 19:32:30.064114
Analysis finished2023-12-12 19:32:52.787313
Duration22.72 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

Distinct7
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2023-01-01 00:00:00
Maximum2023-07-01 00:00:00
2023-12-13T04:32:52.853988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:32:52.970741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)

구축시도
Real number (ℝ)

HIGH CORRELATION 

Distinct18
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6367476.5
Minimum5691000
Maximum6530000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T04:32:53.076311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5691000
5-th percentile6110000
Q16280000
median6420000
Q36460000
95-th percentile6480000
Maximum6530000
Range839000
Interquartile range (IQR)180000

Descriptive statistics

Standard deviation131448.11
Coefficient of variation (CV)0.020643675
Kurtosis3.5263535
Mean6367476.5
Median Absolute Deviation (MAD)50000
Skewness-1.6365232
Sum6.3674765 × 1010
Variance1.7278606 × 1010
MonotonicityNot monotonic
2023-12-13T04:32:53.177866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
6410000 1582
15.8%
6110000 1183
11.8%
6470000 944
9.4%
6460000 876
8.8%
6480000 835
8.3%
6450000 661
 
6.6%
6440000 611
 
6.1%
6260000 558
 
5.6%
6420000 472
 
4.7%
6280000 462
 
4.6%
Other values (8) 1816
18.2%
ValueCountFrequency (%)
5691000 65
 
0.7%
6110000 1183
11.8%
6260000 558
 
5.6%
6270000 396
 
4.0%
6280000 462
 
4.6%
6290000 247
 
2.5%
6300000 243
 
2.4%
6310000 146
 
1.5%
6410000 1582
15.8%
6420000 472
 
4.7%
ValueCountFrequency (%)
6530000 152
 
1.5%
6500000 123
 
1.2%
6480000 835
8.3%
6470000 944
9.4%
6460000 876
8.8%
6450000 661
6.6%
6440000 611
 
6.1%
6430000 444
 
4.4%
6420000 472
 
4.7%
6410000 1582
15.8%

구축시군구
Real number (ℝ)

HIGH CORRELATION 

Distinct259
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4303074.5
Minimum3000000
Maximum6520000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T04:32:53.334785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3000000
5-th percentile3110000
Q13560000
median4261000
Q34980000
95-th percentile5670140
Maximum6520000
Range3520000
Interquartile range (IQR)1420000

Descriptive statistics

Standard deviation826010.2
Coefficient of variation (CV)0.19195815
Kurtosis-0.87461553
Mean4303074.5
Median Absolute Deviation (MAD)701000
Skewness0.22662097
Sum4.3030745 × 1010
Variance6.8229285 × 1011
MonotonicityNot monotonic
2023-12-13T04:32:53.505626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3780000 133
 
1.3%
3740000 117
 
1.2%
4490000 109
 
1.1%
4050000 101
 
1.0%
4810000 83
 
0.8%
3830000 83
 
0.8%
3230000 82
 
0.8%
5110000 80
 
0.8%
3560000 78
 
0.8%
4820000 78
 
0.8%
Other values (249) 9056
90.6%
ValueCountFrequency (%)
3000000 42
0.4%
3010000 47
0.5%
3020000 48
0.5%
3030000 54
0.5%
3040000 33
0.3%
3050000 44
0.4%
3060000 45
0.4%
3070000 43
0.4%
3080000 43
0.4%
3090000 40
0.4%
ValueCountFrequency (%)
6520000 51
0.5%
6510000 72
0.7%
5735000 21
 
0.2%
5730000 31
0.3%
5725000 36
0.4%
5720000 29
0.3%
5700000 40
0.4%
5690000 65
0.7%
5680000 30
0.3%
5670206 30
0.3%

선택기관
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct312
Distinct (%)3.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.9033
Minimum0
Maximum790
Zeros307
Zeros (%)3.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T04:32:53.677468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q17
median20
Q350
95-th percentile121
Maximum790
Range790
Interquartile range (IQR)43

Descriptive statistics

Standard deviation55.857828
Coefficient of variation (CV)1.473693
Kurtosis48.022075
Mean37.9033
Median Absolute Deviation (MAD)16
Skewness5.3286012
Sum379033
Variance3120.097
MonotonicityNot monotonic
2023-12-13T04:32:53.812954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
7 361
 
3.6%
5 351
 
3.5%
3 347
 
3.5%
4 332
 
3.3%
2 308
 
3.1%
8 308
 
3.1%
0 307
 
3.1%
6 303
 
3.0%
1 278
 
2.8%
9 248
 
2.5%
Other values (302) 6857
68.6%
ValueCountFrequency (%)
0 307
3.1%
1 278
2.8%
2 308
3.1%
3 347
3.5%
4 332
3.3%
5 351
3.5%
6 303
3.0%
7 361
3.6%
8 308
3.1%
9 248
2.5%
ValueCountFrequency (%)
790 1
< 0.1%
781 1
< 0.1%
780 1
< 0.1%
755 1
< 0.1%
751 1
< 0.1%
744 1
< 0.1%
734 1
< 0.1%
733 1
< 0.1%
731 2
< 0.1%
730 1
< 0.1%

추가선택기관
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct171
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12.945
Minimum0
Maximum456
Zeros1395
Zeros (%)14.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T04:32:53.946326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median5
Q315
95-th percentile49
Maximum456
Range456
Interquartile range (IQR)14

Descriptive statistics

Standard deviation24.773243
Coefficient of variation (CV)1.9137306
Kurtosis71.680145
Mean12.945
Median Absolute Deviation (MAD)4
Skewness6.5533945
Sum129450
Variance613.71355
MonotonicityNot monotonic
2023-12-13T04:32:54.368570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 1395
14.0%
1 1265
 
12.7%
2 872
 
8.7%
3 734
 
7.3%
4 612
 
6.1%
5 478
 
4.8%
6 379
 
3.8%
7 306
 
3.1%
8 267
 
2.7%
10 262
 
2.6%
Other values (161) 3430
34.3%
ValueCountFrequency (%)
0 1395
14.0%
1 1265
12.7%
2 872
8.7%
3 734
7.3%
4 612
6.1%
5 478
 
4.8%
6 379
 
3.8%
7 306
 
3.1%
8 267
 
2.7%
9 231
 
2.3%
ValueCountFrequency (%)
456 1
< 0.1%
449 1
< 0.1%
435 1
< 0.1%
358 1
< 0.1%
354 1
< 0.1%
353 2
< 0.1%
326 1
< 0.1%
325 1
< 0.1%
324 1
< 0.1%
322 1
< 0.1%

선택한의원
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct109
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.4423
Minimum0
Maximum174
Zeros2964
Zeros (%)29.6%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T04:32:54.529838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q38
95-th percentile26
Maximum174
Range174
Interquartile range (IQR)8

Descriptive statistics

Standard deviation12.362854
Coefficient of variation (CV)1.9190124
Kurtosis42.821201
Mean6.4423
Median Absolute Deviation (MAD)2
Skewness5.2862518
Sum64423
Variance152.84015
MonotonicityNot monotonic
2023-12-13T04:32:54.734981image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 2964
29.6%
1 1405
14.1%
2 860
 
8.6%
3 678
 
6.8%
4 505
 
5.1%
5 407
 
4.1%
6 357
 
3.6%
7 313
 
3.1%
8 246
 
2.5%
9 239
 
2.4%
Other values (99) 2026
20.3%
ValueCountFrequency (%)
0 2964
29.6%
1 1405
14.1%
2 860
 
8.6%
3 678
 
6.8%
4 505
 
5.1%
5 407
 
4.1%
6 357
 
3.6%
7 313
 
3.1%
8 246
 
2.5%
9 239
 
2.4%
ValueCountFrequency (%)
174 1
< 0.1%
172 1
< 0.1%
171 1
< 0.1%
170 1
< 0.1%
157 2
< 0.1%
155 1
< 0.1%
144 1
< 0.1%
143 1
< 0.1%
142 1
< 0.1%
135 1
< 0.1%

선택치과의원
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct117
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.8459
Minimum0
Maximum155
Zeros3012
Zeros (%)30.1%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T04:32:54.923403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median2
Q38
95-th percentile28
Maximum155
Range155
Interquartile range (IQR)8

Descriptive statistics

Standard deviation13.140282
Coefficient of variation (CV)1.9194383
Kurtosis29.560476
Mean6.8459
Median Absolute Deviation (MAD)2
Skewness4.6052219
Sum68459
Variance172.66702
MonotonicityNot monotonic
2023-12-13T04:32:55.205158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 3012
30.1%
1 1384
13.8%
2 872
 
8.7%
3 620
 
6.2%
4 463
 
4.6%
5 433
 
4.3%
6 345
 
3.5%
7 284
 
2.8%
8 270
 
2.7%
9 222
 
2.2%
Other values (107) 2095
20.9%
ValueCountFrequency (%)
0 3012
30.1%
1 1384
13.8%
2 872
 
8.7%
3 620
 
6.2%
4 463
 
4.6%
5 433
 
4.3%
6 345
 
3.5%
7 284
 
2.8%
8 270
 
2.7%
9 222
 
2.2%
ValueCountFrequency (%)
155 2
< 0.1%
153 2
< 0.1%
141 1
 
< 0.1%
140 1
 
< 0.1%
138 1
 
< 0.1%
122 1
 
< 0.1%
120 4
< 0.1%
119 2
< 0.1%
116 3
< 0.1%
112 1
 
< 0.1%

희귀난치성
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct36
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.9703
Minimum0
Maximum56
Zeros6484
Zeros (%)64.8%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T04:32:55.412677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile5
Maximum56
Range56
Interquartile range (IQR)1

Descriptive statistics

Standard deviation2.5146471
Coefficient of variation (CV)2.5916182
Kurtosis85.491326
Mean0.9703
Median Absolute Deviation (MAD)0
Skewness7.2614766
Sum9703
Variance6.3234503
MonotonicityNot monotonic
2023-12-13T04:32:55.598623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=36)
ValueCountFrequency (%)
0 6484
64.8%
1 1689
 
16.9%
2 695
 
7.0%
3 412
 
4.1%
4 219
 
2.2%
5 129
 
1.3%
6 96
 
1.0%
7 74
 
0.7%
8 51
 
0.5%
9 31
 
0.3%
Other values (26) 120
 
1.2%
ValueCountFrequency (%)
0 6484
64.8%
1 1689
 
16.9%
2 695
 
7.0%
3 412
 
4.1%
4 219
 
2.2%
5 129
 
1.3%
6 96
 
1.0%
7 74
 
0.7%
8 51
 
0.5%
9 31
 
0.3%
ValueCountFrequency (%)
56 1
 
< 0.1%
48 1
 
< 0.1%
38 3
< 0.1%
34 1
 
< 0.1%
33 1
 
< 0.1%
32 1
 
< 0.1%
30 1
 
< 0.1%
29 1
 
< 0.1%
28 3
< 0.1%
27 1
 
< 0.1%

11개질환
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct69
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.3751
Minimum0
Maximum111
Zeros3748
Zeros (%)37.5%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T04:32:55.828771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1
Q34
95-th percentile14
Maximum111
Range111
Interquartile range (IQR)4

Descriptive statistics

Standard deviation6.8413946
Coefficient of variation (CV)2.0270198
Kurtosis59.393563
Mean3.3751
Median Absolute Deviation (MAD)1
Skewness6.0365298
Sum33751
Variance46.80468
MonotonicityNot monotonic
2023-12-13T04:32:56.022954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 3748
37.5%
1 1825
18.2%
2 1153
 
11.5%
3 689
 
6.9%
4 494
 
4.9%
5 325
 
3.2%
7 231
 
2.3%
6 229
 
2.3%
8 167
 
1.7%
10 158
 
1.6%
Other values (59) 981
 
9.8%
ValueCountFrequency (%)
0 3748
37.5%
1 1825
18.2%
2 1153
 
11.5%
3 689
 
6.9%
4 494
 
4.9%
5 325
 
3.2%
6 229
 
2.3%
7 231
 
2.3%
8 167
 
1.7%
9 140
 
1.4%
ValueCountFrequency (%)
111 1
 
< 0.1%
110 1
 
< 0.1%
109 1
 
< 0.1%
108 1
 
< 0.1%
95 1
 
< 0.1%
92 3
< 0.1%
91 1
 
< 0.1%
85 1
 
< 0.1%
84 2
< 0.1%
77 1
 
< 0.1%

기타질환
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct277
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean31.582
Minimum0
Maximum731
Zeros428
Zeros (%)4.3%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T04:32:56.217848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q16
median16
Q341
95-th percentile105
Maximum731
Range731
Interquartile range (IQR)35

Descriptive statistics

Standard deviation47.832841
Coefficient of variation (CV)1.5145602
Kurtosis54.208978
Mean31.582
Median Absolute Deviation (MAD)13
Skewness5.5978584
Sum315820
Variance2287.9807
MonotonicityNot monotonic
2023-12-13T04:32:56.411134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4 441
 
4.4%
0 428
 
4.3%
3 419
 
4.2%
2 405
 
4.0%
5 386
 
3.9%
1 374
 
3.7%
6 372
 
3.7%
7 336
 
3.4%
8 302
 
3.0%
9 280
 
2.8%
Other values (267) 6257
62.6%
ValueCountFrequency (%)
0 428
4.3%
1 374
3.7%
2 405
4.0%
3 419
4.2%
4 441
4.4%
5 386
3.9%
6 372
3.7%
7 336
3.4%
8 302
3.0%
9 280
2.8%
ValueCountFrequency (%)
731 1
 
< 0.1%
723 1
 
< 0.1%
721 1
 
< 0.1%
657 3
< 0.1%
656 1
 
< 0.1%
653 1
 
< 0.1%
648 1
 
< 0.1%
642 1
 
< 0.1%
632 1
 
< 0.1%
582 2
< 0.1%

자발적참여자
Real number (ℝ)

SKEWED  ZEROS 

Distinct76
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.9761
Minimum0
Maximum544
Zeros5803
Zeros (%)58.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T04:32:56.624973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile6
Maximum544
Range544
Interquartile range (IQR)1

Descriptive statistics

Standard deviation11.038112
Coefficient of variation (CV)5.5858063
Kurtosis1156.3171
Mean1.9761
Median Absolute Deviation (MAD)0
Skewness28.483854
Sum19761
Variance121.83991
MonotonicityNot monotonic
2023-12-13T04:32:56.816792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 5803
58.0%
1 1887
 
18.9%
2 852
 
8.5%
3 444
 
4.4%
4 227
 
2.3%
5 191
 
1.9%
6 128
 
1.3%
7 66
 
0.7%
8 55
 
0.5%
9 28
 
0.3%
Other values (66) 319
 
3.2%
ValueCountFrequency (%)
0 5803
58.0%
1 1887
 
18.9%
2 852
 
8.5%
3 444
 
4.4%
4 227
 
2.3%
5 191
 
1.9%
6 128
 
1.3%
7 66
 
0.7%
8 55
 
0.5%
9 28
 
0.3%
ValueCountFrequency (%)
544 1
< 0.1%
454 1
< 0.1%
445 1
< 0.1%
177 1
< 0.1%
172 1
< 0.1%
169 1
< 0.1%
155 1
< 0.1%
145 1
< 0.1%
137 1
< 0.1%
117 1
< 0.1%
Distinct7
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
Minimum2023-02-01 00:00:00
Maximum2023-08-01 00:00:00
2023-12-13T04:32:56.960247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:32:57.098166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)

읍면동
Real number (ℝ)

HIGH CORRELATION 

Distinct3817
Distinct (%)38.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4349425.2
Minimum3000000
Maximum6520044
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2023-12-13T04:32:57.282205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3000000
5-th percentile3110038
Q13560082
median4350019.5
Q35060036.2
95-th percentile5670151
Maximum6520044
Range3520044
Interquartile range (IQR)1499954.2

Descriptive statistics

Standard deviation854476.45
Coefficient of variation (CV)0.19645733
Kurtosis-1.0222298
Mean4349425.2
Median Absolute Deviation (MAD)739999.5
Skewness0.1578933
Sum4.3494252 × 1010
Variance7.3013 × 1011
MonotonicityNot monotonic
2023-12-13T04:32:57.479584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
5690145 6
 
0.1%
3260052 6
 
0.1%
4020036 6
 
0.1%
4730032 6
 
0.1%
3760011 6
 
0.1%
3230057 6
 
0.1%
3810057 6
 
0.1%
3310044 6
 
0.1%
3990366 6
 
0.1%
4390066 6
 
0.1%
Other values (3807) 9940
99.4%
ValueCountFrequency (%)
3000000 4
< 0.1%
3000042 1
 
< 0.1%
3000043 2
< 0.1%
3000044 2
< 0.1%
3000045 2
< 0.1%
3000046 2
< 0.1%
3000047 4
< 0.1%
3000049 3
< 0.1%
3000053 1
 
< 0.1%
3000054 4
< 0.1%
ValueCountFrequency (%)
6520044 1
 
< 0.1%
6520043 4
< 0.1%
6520042 4
< 0.1%
6520041 3
< 0.1%
6520040 4
< 0.1%
6520039 4
< 0.1%
6520038 4
< 0.1%
6520037 3
< 0.1%
6520036 3
< 0.1%
6520035 2
< 0.1%

Interactions

2023-12-13T04:32:50.851835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:32:34.517606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:32:35.859589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:32:37.747059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:32:39.351769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:32:40.888248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:32:42.486263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:32:44.161514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:32:45.752764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:32:47.573770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:32:49.222657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:32:50.973228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:32:34.615834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:32:35.983460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:32:37.871522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:32:39.487927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:32:41.016307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:32:42.645653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:32:44.312906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:32:45.874338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:32:47.716547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:32:49.361579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:32:51.104733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:32:34.722415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:32:36.128294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:32:38.031355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:32:39.626363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:32:41.164296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:32:42.816292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:32:44.448230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:32:46.010893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:32:47.861277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:32:49.533983image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:32:51.236169image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:32:34.822841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:32:36.271059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:32:38.185547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:32:39.755436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:32:41.284437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:32:42.976098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:32:44.604920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:32:46.149133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:32:48.020290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:32:49.689772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:32:51.376786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:32:34.912211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:32:36.396707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:32:38.320273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:32:39.877589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:32:41.443411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:32:43.116036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:32:44.711921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:32:46.595968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:32:48.152609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:32:49.826835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:32:51.546480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:32:35.024753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:32:36.547108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:32:38.461310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:32:40.009839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:32:41.588844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:32:43.257406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:32:44.875655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:32:46.748973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:32:48.296753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:32:49.967540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:32:51.716947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:32:35.159783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:32:36.706158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:32:38.608049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:32:40.161035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:32:41.730774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:32:43.409593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:32:45.017269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:32:46.892645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:32:48.439644image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:32:50.111287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:32:51.856476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:32:35.293829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:32:36.834101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:32:38.750031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:32:40.293692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:32:41.866440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:32:43.573698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:32:45.151096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:32:47.015158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:32:48.587521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:32:50.252963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:32:51.997866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:32:35.432009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:32:36.962427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:32:38.886894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:32:40.435078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:32:42.017441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:32:43.714127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:32:45.284499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:32:47.131991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:32:48.748133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:32:50.380111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:32:52.114931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:32:35.584295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:32:37.111437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:32:39.053244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:32:40.590799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:32:42.176110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:32:43.857781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:32:45.420987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:32:47.286038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:32:48.920242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:32:50.531926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:32:52.238026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:32:35.706561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:32:37.582900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:32:39.193079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:32:40.738763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:32:42.336742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:32:43.996308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:32:45.588028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:32:47.421560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:32:49.074900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T04:32:50.678905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T04:32:57.612209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구축년월구축시도구축시군구선택기관추가선택기관선택한의원선택치과의원희귀난치성11개질환기타질환자발적참여자처리일자읍면동
구축년월1.0000.0110.0100.0000.0000.0000.0000.0000.0000.0000.0001.0000.012
구축시도0.0111.0000.8800.3020.1380.3040.3180.1100.2060.3210.0470.0110.880
구축시군구0.0100.8801.0000.2040.1660.2040.2310.1810.1520.2140.1050.0101.000
선택기관0.0000.3020.2041.0000.7860.8930.8510.4970.7890.9780.5200.0000.202
추가선택기관0.0000.1380.1660.7861.0000.7620.7540.3270.6720.8180.3560.0000.167
선택한의원0.0000.3040.2040.8930.7621.0000.9500.4640.7700.8890.2500.0000.205
선택치과의원0.0000.3180.2310.8510.7540.9501.0000.3340.7090.8850.1380.0000.232
희귀난치성0.0000.1100.1810.4970.3270.4640.3341.0000.4310.4520.1210.0000.190
11개질환0.0000.2060.1520.7890.6720.7700.7090.4311.0000.7590.4040.0000.157
기타질환0.0000.3210.2140.9780.8180.8890.8850.4520.7591.0000.0350.0000.212
자발적참여자0.0000.0470.1050.5200.3560.2500.1380.1210.4040.0351.0000.0000.110
처리일자1.0000.0110.0100.0000.0000.0000.0000.0000.0000.0000.0001.0000.012
읍면동0.0120.8801.0000.2020.1670.2050.2320.1900.1570.2120.1100.0121.000
2023-12-13T04:32:57.807706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구축시도구축시군구선택기관추가선택기관선택한의원선택치과의원희귀난치성11개질환기타질환자발적참여자읍면동
구축시도1.0000.879-0.316-0.307-0.335-0.345-0.202-0.233-0.316-0.0410.834
구축시군구0.8791.000-0.334-0.324-0.357-0.361-0.231-0.230-0.335-0.0280.954
선택기관-0.316-0.3341.0000.8310.7300.7080.5260.6760.9700.438-0.315
추가선택기관-0.307-0.3240.8311.0000.7510.7580.4910.5460.7880.465-0.279
선택한의원-0.335-0.3570.7300.7511.0000.8840.4120.4320.7160.364-0.323
선택치과의원-0.345-0.3610.7080.7580.8841.0000.4020.4390.6870.377-0.324
희귀난치성-0.202-0.2310.5260.4910.4120.4021.0000.4340.4960.194-0.219
11개질환-0.233-0.2300.6760.5460.4320.4390.4341.0000.6120.252-0.208
기타질환-0.316-0.3350.9700.7880.7160.6870.4960.6121.0000.346-0.337
자발적참여자-0.041-0.0280.4380.4650.3640.3770.1940.2520.3461.000-0.004
읍면동0.8340.954-0.315-0.279-0.323-0.324-0.219-0.208-0.337-0.0041.000

Missing values

2023-12-13T04:32:52.435771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T04:32:52.702518image/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

구축년월구축시도구축시군구선택기관추가선택기관선택한의원선택치과의원희귀난치성11개질환기타질환자발적참여자처리일자읍면동
2642023-0161100003140000100000102023-02-013140043
79552023-036110000315000015854001502023-04-013150056
11442023-016300000365000063321013165422023-02-013650037
95072023-0364100005540000500000502023-04-015540303
199182023-0662700003430000652651025672023-07-013430028
173462023-056420000425000012120007502023-06-014250000
202042023-06629000035900001443525702023-07-013590023
270692023-0765300004301000331102102023-08-014301043
191902023-065691000569000013423011112023-07-015690184
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195542023-0661100003200000461821044112023-07-013200164
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53012023-0264100003910000521101312023-03-013910344
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135622023-0464200004300000111100102023-05-014300022
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