Overview

Dataset statistics

Number of variables11
Number of observations54
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.2 KiB
Average record size in memory98.4 B

Variable types

Categorical3
Numeric8

Dataset

Description국립목포병원 입원 및 외래 수입금에 관련된 데이터로, 종별 구분, 연인원, 총진료비, 비급여총액, 본인부담금 등의 외래/입원 수입금 현황을 제공합니다.
URLhttps://www.data.go.kr/data/15052128/fileData.do

Alerts

건수 is highly overall correlated with 연인원 and 6 other fieldsHigh correlation
연인원 is highly overall correlated with 건수 and 6 other fieldsHigh correlation
총진료비 is highly overall correlated with 건수 and 6 other fieldsHigh correlation
급여총액 is highly overall correlated with 건수 and 6 other fieldsHigh correlation
비급여총액 is highly overall correlated with 건수 and 5 other fieldsHigh correlation
본인부담액 is highly overall correlated with 개인부담액High correlation
조합부담액 is highly overall correlated with 건수 and 6 other fieldsHigh correlation
개인부담액 is highly overall correlated with 본인부담액High correlation
종별 is highly overall correlated with 건수 and 5 other fieldsHigh correlation
구분 is highly overall correlated with 건수 and 4 other fieldsHigh correlation
총진료비 has unique valuesUnique
급여총액 has unique valuesUnique
개인부담액 has unique valuesUnique
비급여총액 has 9 (16.7%) zerosZeros
본인부담액 has 9 (16.7%) zerosZeros
조합부담액 has 6 (11.1%) zerosZeros

Reproduction

Analysis started2023-12-12 16:58:52.035426
Analysis finished2023-12-12 16:59:00.443821
Duration8.41 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

종별
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)5.6%
Missing0
Missing (%)0.0%
Memory size564.0 B
보험
18 
보호
18 
일반
18 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
보험 18
33.3%
보호 18
33.3%
일반 18
33.3%

Length

2023-12-13T01:59:00.524112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T01:59:00.613885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
보험 18
33.3%
보호 18
33.3%
일반 18
33.3%

구분
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)3.7%
Missing0
Missing (%)0.0%
Memory size564.0 B
외래
27 
입원
27 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
외래 27
50.0%
입원 27
50.0%

Length

2023-12-13T01:59:00.735422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T01:59:00.835011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
외래 27
50.0%
입원 27
50.0%

작업년월
Categorical

Distinct9
Distinct (%)16.7%
Missing0
Missing (%)0.0%
Memory size564.0 B
2021-04-01
6 
2021-05-01
6 
2021-06-01
6 
2021-07-01
6 
2021-08-01
6 
Other values (4)
24 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2021-04-01
2nd row2021-05-01
3rd row2021-06-01
4th row2021-07-01
5th row2021-08-01

Common Values

ValueCountFrequency (%)
2021-04-01 6
11.1%
2021-05-01 6
11.1%
2021-06-01 6
11.1%
2021-07-01 6
11.1%
2021-08-01 6
11.1%
2021-09-01 6
11.1%
2021-10-01 6
11.1%
2021-11-01 6
11.1%
2021-12-01 6
11.1%

Length

2023-12-13T01:59:00.928727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T01:59:01.035308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021-04-01 6
11.1%
2021-05-01 6
11.1%
2021-06-01 6
11.1%
2021-07-01 6
11.1%
2021-08-01 6
11.1%
2021-09-01 6
11.1%
2021-10-01 6
11.1%
2021-11-01 6
11.1%
2021-12-01 6
11.1%

건수
Real number (ℝ)

HIGH CORRELATION 

Distinct35
Distinct (%)64.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean45.518519
Minimum2
Maximum280
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size618.0 B
2023-12-13T01:59:01.171350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile4
Q17.25
median14
Q364.75
95-th percentile162.35
Maximum280
Range278
Interquartile range (IQR)57.5

Descriptive statistics

Standard deviation61.369509
Coefficient of variation (CV)1.3482317
Kurtosis4.7048749
Mean45.518519
Median Absolute Deviation (MAD)10
Skewness2.1363486
Sum2458
Variance3766.2166
MonotonicityNot monotonic
2023-12-13T01:59:01.295618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
5 4
 
7.4%
4 4
 
7.4%
9 4
 
7.4%
10 4
 
7.4%
7 3
 
5.6%
67 2
 
3.7%
117 2
 
3.7%
12 2
 
3.7%
6 2
 
3.7%
15 2
 
3.7%
Other values (25) 25
46.3%
ValueCountFrequency (%)
2 1
 
1.9%
4 4
7.4%
5 4
7.4%
6 2
3.7%
7 3
5.6%
8 1
 
1.9%
9 4
7.4%
10 4
7.4%
11 1
 
1.9%
12 2
3.7%
ValueCountFrequency (%)
280 1
1.9%
245 1
1.9%
176 1
1.9%
155 1
1.9%
137 1
1.9%
129 1
1.9%
117 2
3.7%
111 1
1.9%
73 1
1.9%
71 1
1.9%

연인원
Real number (ℝ)

HIGH CORRELATION 

Distinct35
Distinct (%)64.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean45.518519
Minimum2
Maximum280
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size618.0 B
2023-12-13T01:59:01.414569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile4
Q17.25
median14
Q364.75
95-th percentile162.35
Maximum280
Range278
Interquartile range (IQR)57.5

Descriptive statistics

Standard deviation61.369509
Coefficient of variation (CV)1.3482317
Kurtosis4.7048749
Mean45.518519
Median Absolute Deviation (MAD)10
Skewness2.1363486
Sum2458
Variance3766.2166
MonotonicityNot monotonic
2023-12-13T01:59:01.520855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
5 4
 
7.4%
4 4
 
7.4%
9 4
 
7.4%
10 4
 
7.4%
7 3
 
5.6%
67 2
 
3.7%
117 2
 
3.7%
12 2
 
3.7%
6 2
 
3.7%
15 2
 
3.7%
Other values (25) 25
46.3%
ValueCountFrequency (%)
2 1
 
1.9%
4 4
7.4%
5 4
7.4%
6 2
3.7%
7 3
5.6%
8 1
 
1.9%
9 4
7.4%
10 4
7.4%
11 1
 
1.9%
12 2
3.7%
ValueCountFrequency (%)
280 1
1.9%
245 1
1.9%
176 1
1.9%
155 1
1.9%
137 1
1.9%
129 1
1.9%
117 2
3.7%
111 1
1.9%
73 1
1.9%
71 1
1.9%

총진료비
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct54
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean65828831
Minimum189280
Maximum2.9151149 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size618.0 B
2023-12-13T01:59:01.637661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum189280
5-th percentile339034
Q11058617.5
median22376870
Q31.0561443 × 108
95-th percentile2.6224355 × 108
Maximum2.9151149 × 108
Range2.9132221 × 108
Interquartile range (IQR)1.0455582 × 108

Descriptive statistics

Standard deviation90551736
Coefficient of variation (CV)1.3755635
Kurtosis0.63120725
Mean65828831
Median Absolute Deviation (MAD)21801045
Skewness1.408275
Sum3.5547569 × 109
Variance8.1996168 × 1015
MonotonicityNot monotonic
2023-12-13T01:59:01.781306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
23989390 1
 
1.9%
389510 1
 
1.9%
117520040 1
 
1.9%
140310520 1
 
1.9%
131852840 1
 
1.9%
106971070 1
 
1.9%
115186160 1
 
1.9%
101544520 1
 
1.9%
401370 1
 
1.9%
189280 1
 
1.9%
Other values (44) 44
81.5%
ValueCountFrequency (%)
189280 1
1.9%
272880 1
1.9%
288360 1
1.9%
366320 1
1.9%
389510 1
1.9%
401370 1
1.9%
419640 1
1.9%
520470 1
1.9%
562020 1
1.9%
589630 1
1.9%
ValueCountFrequency (%)
291511490 1
1.9%
282920720 1
1.9%
277794870 1
1.9%
253869760 1
1.9%
252298750 1
1.9%
246770910 1
1.9%
237175520 1
1.9%
187727220 1
1.9%
185714020 1
1.9%
140310520 1
1.9%

급여총액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct54
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean65768646
Minimum187280
Maximum2.9142739 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size618.0 B
2023-12-13T01:59:01.910427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum187280
5-th percentile335784
Q11058617.5
median22376870
Q31.0556048 × 108
95-th percentile2.6214616 × 108
Maximum2.9142739 × 108
Range2.9124011 × 108
Interquartile range (IQR)1.0450186 × 108

Descriptive statistics

Standard deviation90531442
Coefficient of variation (CV)1.3765137
Kurtosis0.63143847
Mean65768646
Median Absolute Deviation (MAD)21833595
Skewness1.4084175
Sum3.5515069 × 109
Variance8.195942 × 1015
MonotonicityNot monotonic
2023-12-13T01:59:02.037678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
23864790 1
 
1.9%
381510 1
 
1.9%
117481140 1
 
1.9%
140249920 1
 
1.9%
131813040 1
 
1.9%
106909470 1
 
1.9%
115133560 1
 
1.9%
101513520 1
 
1.9%
390070 1
 
1.9%
187280 1
 
1.9%
Other values (44) 44
81.5%
ValueCountFrequency (%)
187280 1
1.9%
272880 1
1.9%
288360 1
1.9%
361320 1
1.9%
381510 1
1.9%
390070 1
1.9%
410240 1
1.9%
504470 1
1.9%
522020 1
1.9%
564530 1
1.9%
ValueCountFrequency (%)
291427390 1
1.9%
282853280 1
1.9%
277719970 1
1.9%
253760260 1
1.9%
252208450 1
1.9%
246514620 1
1.9%
237094230 1
1.9%
187652620 1
1.9%
185617520 1
1.9%
140249920 1
1.9%

비급여총액
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct45
Distinct (%)83.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean60185.37
Minimum0
Maximum256290
Zeros9
Zeros (%)16.7%
Negative0
Negative (%)0.0%
Memory size618.0 B
2023-12-13T01:59:02.182723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q110325
median33200
Q383397.5
95-th percentile212125
Maximum256290
Range256290
Interquartile range (IQR)73072.5

Descriptive statistics

Standard deviation68452.355
Coefficient of variation (CV)1.1373587
Kurtosis1.0531103
Mean60185.37
Median Absolute Deviation (MAD)32200
Skewness1.3898524
Sum3250010
Variance4.6857248 × 109
MonotonicityNot monotonic
2023-12-13T01:59:02.300840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
0 9
 
16.7%
16000 2
 
3.7%
124600 1
 
1.9%
31000 1
 
1.9%
15000 1
 
1.9%
136400 1
 
1.9%
26200 1
 
1.9%
38900 1
 
1.9%
60600 1
 
1.9%
39800 1
 
1.9%
Other values (35) 35
64.8%
ValueCountFrequency (%)
0 9
16.7%
2000 1
 
1.9%
5000 1
 
1.9%
8000 1
 
1.9%
9400 1
 
1.9%
10100 1
 
1.9%
11000 1
 
1.9%
11300 1
 
1.9%
15000 1
 
1.9%
16000 2
 
3.7%
ValueCountFrequency (%)
256290 1
1.9%
229800 1
1.9%
213100 1
1.9%
211600 1
1.9%
196600 1
1.9%
196300 1
1.9%
142490 1
1.9%
136400 1
1.9%
131100 1
1.9%
124600 1
1.9%

본인부담액
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct45
Distinct (%)83.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1205605.4
Minimum0
Maximum10796570
Zeros9
Zeros (%)16.7%
Negative0
Negative (%)0.0%
Memory size618.0 B
2023-12-13T01:59:02.424525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q113570
median331200
Q31110530
95-th percentile6282115
Maximum10796570
Range10796570
Interquartile range (IQR)1096960

Descriptive statistics

Standard deviation2274335
Coefficient of variation (CV)1.8864672
Kurtosis8.192292
Mean1205605.4
Median Absolute Deviation (MAD)320420
Skewness2.8339354
Sum65102690
Variance5.1725997 × 1012
MonotonicityNot monotonic
2023-12-13T01:59:02.560090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
0 9
 
16.7%
10780 2
 
3.7%
272880 1
 
1.9%
89970 1
 
1.9%
390070 1
 
1.9%
187280 1
 
1.9%
361320 1
 
1.9%
1032680 1
 
1.9%
410240 1
 
1.9%
381510 1
 
1.9%
Other values (35) 35
64.8%
ValueCountFrequency (%)
0 9
16.7%
7500 1
 
1.9%
9000 1
 
1.9%
10780 2
 
3.7%
13500 1
 
1.9%
13780 1
 
1.9%
15280 1
 
1.9%
17070 1
 
1.9%
89970 1
 
1.9%
96000 1
 
1.9%
ValueCountFrequency (%)
10796570 1
1.9%
9113590 1
1.9%
7420200 1
1.9%
5669300 1
1.9%
3566800 1
1.9%
3542600 1
1.9%
3265300 1
1.9%
2836740 1
1.9%
2007700 1
1.9%
1851740 1
1.9%

조합부담액
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct48
Distinct (%)88.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean64563041
Minimum-20
Maximum2.9089043 × 108
Zeros6
Zeros (%)11.1%
Negative3
Negative (%)5.6%
Memory size618.0 B
2023-12-13T01:59:02.676770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-20
5-th percentile-3.5
Q1748070
median18331090
Q31.0556048 × 108
95-th percentile2.6165683 × 108
Maximum2.9089043 × 108
Range2.9089045 × 108
Interquartile range (IQR)1.0481241 × 108

Descriptive statistics

Standard deviation90959957
Coefficient of variation (CV)1.4088549
Kurtosis0.61277626
Mean64563041
Median Absolute Deviation (MAD)18083355
Skewness1.4079562
Sum3.4864042 × 109
Variance8.2737137 × 1015
MonotonicityNot monotonic
2023-12-13T01:59:02.802626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=48)
ValueCountFrequency (%)
0 6
 
11.1%
-10 2
 
3.7%
645920 1
 
1.9%
75340250 1
 
1.9%
78913550 1
 
1.9%
66459450 1
 
1.9%
117481140 1
 
1.9%
140249920 1
 
1.9%
131813040 1
 
1.9%
106909470 1
 
1.9%
Other values (38) 38
70.4%
ValueCountFrequency (%)
-20 1
 
1.9%
-10 2
 
3.7%
0 6
11.1%
495470 1
 
1.9%
508520 1
 
1.9%
549250 1
 
1.9%
645920 1
 
1.9%
722840 1
 
1.9%
823760 1
 
1.9%
3989780 1
 
1.9%
ValueCountFrequency (%)
290890430 1
1.9%
282326240 1
1.9%
277203810 1
1.9%
253285380 1
1.9%
251784130 1
1.9%
246048060 1
1.9%
236649110 1
1.9%
187333580 1
1.9%
185301040 1
1.9%
140249920 1
1.9%

개인부담액
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct54
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1265790.7
Minimum16000
Maximum10796570
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size618.0 B
2023-12-13T01:59:02.922104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum16000
5-th percentile25780
Q155275
median377915
Q31110530
95-th percentile6470501.5
Maximum10796570
Range10780570
Interquartile range (IQR)1055255

Descriptive statistics

Standard deviation2292387.4
Coefficient of variation (CV)1.8110319
Kurtosis7.7498046
Mean1265790.7
Median Absolute Deviation (MAD)334575
Skewness2.7662109
Sum68352700
Variance5.2550399 × 1012
MonotonicityNot monotonic
2023-12-13T01:59:03.066991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3691400 1
 
1.9%
389510 1
 
1.9%
38900 1
 
1.9%
60600 1
 
1.9%
39800 1
 
1.9%
61600 1
 
1.9%
52600 1
 
1.9%
31000 1
 
1.9%
401370 1
 
1.9%
189280 1
 
1.9%
Other values (44) 44
81.5%
ValueCountFrequency (%)
16000 1
1.9%
21780 1
1.9%
25000 1
1.9%
26200 1
1.9%
27480 1
1.9%
31000 1
1.9%
38070 1
1.9%
38900 1
1.9%
39800 1
1.9%
40380 1
1.9%
ValueCountFrequency (%)
10796570 1
1.9%
9140390 1
1.9%
7562690 1
1.9%
5882400 1
1.9%
3772400 1
1.9%
3691400 1
1.9%
3461900 1
1.9%
2836740 1
1.9%
2065600 1
1.9%
1975000 1
1.9%

Interactions

2023-12-13T01:58:58.604623image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:58:52.446306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:58:53.357620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:58:54.029790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:58:54.621524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:58:55.353075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:58:55.980479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:58:57.003243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:58:58.829875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:58:52.512492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:58:53.435393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:58:54.103900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:58:54.698513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:58:55.441441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:58:56.106885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:58:57.139941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:58:58.966724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:58:52.892980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:58:53.515755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:58:54.173385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:58:54.786790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:58:55.508822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:58:56.234811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:58:57.317520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:58:59.116001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:58:52.966949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:58:53.599908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:58:54.249264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:58:54.903738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:58:55.586304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:58:56.368279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:58:57.612091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:58:59.270696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:58:53.039759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:58:53.687347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:58:54.325976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:58:54.992605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:58:55.659826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:58:56.486220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:58:57.822915image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:58:59.399759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:58:53.113620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:58:53.801600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:58:54.395468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:58:55.068019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:58:55.730825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:58:56.612085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:58:57.994832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:58:59.517341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:58:53.192369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:58:53.876496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:58:54.471102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:58:55.144988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:58:55.812999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:58:56.705535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:58:58.152831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:58:59.622881image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:58:53.284213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:58:53.957651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:58:54.545964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:58:55.245235image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:58:55.895210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:58:56.849770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T01:58:58.441873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T01:59:03.180062image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
종별구분작업년월건수연인원총진료비급여총액비급여총액본인부담액조합부담액개인부담액
종별1.0000.0000.0000.8970.8970.6710.6710.8950.4380.6610.427
구분0.0001.0000.0000.5580.5580.8280.8280.4750.4150.8410.406
작업년월0.0000.0001.0000.0000.0000.0000.0000.0000.0000.0000.000
건수0.8970.5580.0001.0001.0000.7140.7140.9150.7890.7360.788
연인원0.8970.5580.0001.0001.0000.7140.7140.9150.7890.7360.788
총진료비0.6710.8280.0000.7140.7141.0001.0000.5840.0001.0000.000
급여총액0.6710.8280.0000.7140.7141.0001.0000.5840.0001.0000.000
비급여총액0.8950.4750.0000.9150.9150.5840.5841.0000.4550.5930.446
본인부담액0.4380.4150.0000.7890.7890.0000.0000.4551.0000.0001.000
조합부담액0.6610.8410.0000.7360.7361.0001.0000.5930.0001.0000.000
개인부담액0.4270.4060.0000.7880.7880.0000.0000.4461.0000.0001.000
2023-12-13T01:59:03.346575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
종별작업년월구분
종별1.0000.0000.000
작업년월0.0001.0000.000
구분0.0000.0001.000
2023-12-13T01:59:03.445234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
건수연인원총진료비급여총액비급여총액본인부담액조합부담액개인부담액종별구분작업년월
건수1.0001.0000.6260.6260.9230.2910.6160.3710.5920.5200.000
연인원1.0001.0000.6260.6260.9230.2910.6160.3710.5920.5200.000
총진료비0.6260.6261.0001.0000.5780.0370.9800.1600.5270.6140.000
급여총액0.6260.6261.0001.0000.5780.0370.9800.1600.5270.6140.000
비급여총액0.9230.9230.5780.5781.0000.2380.5920.3400.5900.4400.000
본인부담액0.2910.2910.0370.0370.2381.000-0.0280.9620.2910.2890.000
조합부담액0.6160.6160.9800.9800.592-0.0281.0000.0880.5100.6200.000
개인부담액0.3710.3710.1600.1600.3400.9620.0881.0000.2910.2890.000
종별0.5920.5920.5270.5270.5900.2910.5100.2911.0000.0000.000
구분0.5200.5200.6140.6140.4400.2890.6200.2890.0001.0000.000
작업년월0.0000.0000.0000.0000.0000.0000.0000.0000.0000.0001.000

Missing values

2023-12-13T01:59:00.207667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T01:59:00.375463image/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

종별구분작업년월건수연인원총진료비급여총액비급여총액본인부담액조합부담액개인부담액
0보험외래2021-04-0117617623989390238647901246003566800202979903691400
1보험외래2021-05-0128028025083070249405801424907420200175203807562690
2보험외래2021-06-0111711712546360124152601311001707400107078601838500
3보험외래2021-07-01111111119423701188447057900200770098767702065600
4보험외래2021-08-0112912915424710152131102116001763400134497101975000
5보험외래2021-09-0111711714011190138148901963001739100120757901935400
6보험외래2021-10-0124524515178400149486002298003542600114060003772400
7보험외래2021-11-0115515533865310336687101966003265300304034103461900
8보험외래2021-12-0113713731427760312146602131005669300255453605882400
9보험입원2021-04-017373246770910246514620256290466560246048060722850
종별구분작업년월건수연인원총진료비급여총액비급여총액본인부담액조합부담액개인부담액
44일반외래2021-12-01771136460113646001136480-201136480
45일반입원2021-04-0110102160503021569630354001851740197178901887140
46일반입원2021-05-014414756850147467501010014400014602750154100
47일반입원2021-06-012294831009483100096000938710096000
48일반입원2021-07-014421857370218573700107965701106080010796570
49일반입원2021-08-01992828219028255390268009113590191418009140390
50일반입원2021-09-0166253913402539134002836740225546002836740
51일반입원2021-10-01662289637022896370024480022651570244800
52일반입원2021-11-0110103016916030169160033440029834760334400
53일반입원2021-12-01111125736130257058303030032800025377830358300