Overview

Dataset statistics

Number of variables7
Number of observations36
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.3 KiB
Average record size in memory64.7 B

Variable types

Categorical3
Numeric4

Dataset

Description국립목포병원 진료비 청구 현황에 관련된 데이터로, 보험유형, 내원, 진료비 총액, 본인부담 등의 진료비 청구 현황을 제공합니다.
URLhttps://www.data.go.kr/data/3048709/fileData.do

Alerts

인원(청구건수) is highly overall correlated with 본인부담액(B) and 1 other fieldsHigh correlation
요양급여총액(A=B+C+D) is highly overall correlated with 본인부담액(B) and 2 other fieldsHigh correlation
본인부담액(B) is highly overall correlated with 인원(청구건수) and 3 other fieldsHigh correlation
청구액(D) is highly overall correlated with 요양급여총액(A=B+C+D) and 1 other fieldsHigh correlation
서식 is highly overall correlated with 인원(청구건수) and 2 other fieldsHigh correlation
장애인비용(C) is highly imbalanced (81.7%)Imbalance
요양급여총액(A=B+C+D) has unique valuesUnique
본인부담액(B) has unique valuesUnique
청구액(D) has unique valuesUnique

Reproduction

Analysis started2023-12-12 01:37:00.960913
Analysis finished2023-12-12 01:37:04.026375
Duration3.07 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

진료년월
Categorical

Distinct9
Distinct (%)25.0%
Missing0
Missing (%)0.0%
Memory size420.0 B
4월
4 
5월
4 
6월
4 
7월
4 
8월
4 
Other values (4)
16 

Length

Max length3
Median length2
Mean length2.3333333
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row4월
2nd row4월
3rd row4월
4th row4월
5th row5월

Common Values

ValueCountFrequency (%)
4월 4
11.1%
5월 4
11.1%
6월 4
11.1%
7월 4
11.1%
8월 4
11.1%
9월 4
11.1%
10월 4
11.1%
11월 4
11.1%
12월 4
11.1%

Length

2023-12-12T10:37:04.124172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T10:37:04.333056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
4월 4
11.1%
5월 4
11.1%
6월 4
11.1%
7월 4
11.1%
8월 4
11.1%
9월 4
11.1%
10월 4
11.1%
11월 4
11.1%
12월 4
11.1%

서식
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)11.1%
Missing0
Missing (%)0.0%
Memory size420.0 B
건강보험외래
9 
건강보험입원
9 
의료급여외래
9 
의료급여입원
9 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row건강보험외래
2nd row건강보험입원
3rd row의료급여외래
4th row의료급여입원
5th row건강보험외래

Common Values

ValueCountFrequency (%)
건강보험외래 9
25.0%
건강보험입원 9
25.0%
의료급여외래 9
25.0%
의료급여입원 9
25.0%

Length

2023-12-12T10:37:04.533894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T10:37:04.678340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
건강보험외래 9
25.0%
건강보험입원 9
25.0%
의료급여외래 9
25.0%
의료급여입원 9
25.0%

인원(청구건수)
Real number (ℝ)

HIGH CORRELATION 

Distinct27
Distinct (%)75.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean51.5
Minimum7
Maximum164
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size456.0 B
2023-12-12T10:37:04.832424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7
5-th percentile8
Q114
median36.5
Q375
95-th percentile117.25
Maximum164
Range157
Interquartile range (IQR)61

Descriptive statistics

Standard deviation41.227938
Coefficient of variation (CV)0.80054248
Kurtosis-0.08629998
Mean51.5
Median Absolute Deviation (MAD)27.5
Skewness0.83991248
Sum1854
Variance1699.7429
MonotonicityNot monotonic
2023-12-12T10:37:05.030855image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
112 2
 
5.6%
8 2
 
5.6%
96 2
 
5.6%
14 2
 
5.6%
9 2
 
5.6%
13 2
 
5.6%
65 2
 
5.6%
58 2
 
5.6%
25 2
 
5.6%
87 1
 
2.8%
Other values (17) 17
47.2%
ValueCountFrequency (%)
7 1
2.8%
8 2
5.6%
9 2
5.6%
11 1
2.8%
13 2
5.6%
14 2
5.6%
15 1
2.8%
25 2
5.6%
27 1
2.8%
28 1
2.8%
ValueCountFrequency (%)
164 1
2.8%
118 1
2.8%
117 1
2.8%
112 2
5.6%
97 1
2.8%
96 2
5.6%
87 1
2.8%
71 1
2.8%
69 1
2.8%
67 1
2.8%

요양급여총액(A=B+C+D)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct36
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean87725270
Minimum450810
Maximum2.8352209 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size456.0 B
2023-12-12T10:37:05.198195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum450810
5-th percentile547752.5
Q18809842.5
median41866570
Q31.3749273 × 108
95-th percentile2.7592728 × 108
Maximum2.8352209 × 108
Range2.8307128 × 108
Interquartile range (IQR)1.2868289 × 108

Descriptive statistics

Standard deviation96326613
Coefficient of variation (CV)1.0980486
Kurtosis-0.59921041
Mean87725270
Median Absolute Deviation (MAD)41220500
Skewness0.90207545
Sum3.1581097 × 109
Variance9.2788165 × 1015
MonotonicityNot monotonic
2023-12-12T10:37:05.359032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=36)
ValueCountFrequency (%)
34091580 1
 
2.8%
127675270 1
 
2.8%
273556370 1
 
2.8%
3991530 1
 
2.8%
125549680 1
 
2.8%
10314490 1
 
2.8%
283522090 1
 
2.8%
4295900 1
 
2.8%
106311640 1
 
2.8%
32599500 1
 
2.8%
Other values (26) 26
72.2%
ValueCountFrequency (%)
450810 1
2.8%
487790 1
2.8%
567740 1
2.8%
724400 1
2.8%
798440 1
2.8%
1091960 1
2.8%
3991530 1
2.8%
4255510 1
2.8%
4295900 1
2.8%
10314490 1
2.8%
ValueCountFrequency (%)
283522090 1
2.8%
283040030 1
2.8%
273556370 1
2.8%
240914300 1
2.8%
240326870 1
2.8%
232657770 1
2.8%
224726210 1
2.8%
170319060 1
2.8%
166945110 1
2.8%
127675270 1
2.8%

본인부담액(B)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct36
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3610034.4
Minimum7500
Maximum12696200
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size456.0 B
2023-12-12T10:37:05.567140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7500
5-th percentile10335
Q1648260
median1777400
Q34809355
95-th percentile12169905
Maximum12696200
Range12688700
Interquartile range (IQR)4161095

Descriptive statistics

Standard deviation4304452.5
Coefficient of variation (CV)1.1923577
Kurtosis-0.26309466
Mean3610034.4
Median Absolute Deviation (MAD)1703510
Skewness1.1679511
Sum1.2996124 × 108
Variance1.8528312 × 1013
MonotonicityNot monotonic
2023-12-12T10:37:05.749840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=36)
ValueCountFrequency (%)
3764800 1
 
2.8%
2042860 1
 
2.8%
11721200 1
 
2.8%
10780 1
 
2.8%
2196030 1
 
2.8%
1643500 1
 
2.8%
12117460 1
 
2.8%
117890 1
 
2.8%
1829430 1
 
2.8%
3072200 1
 
2.8%
Other values (26) 26
72.2%
ValueCountFrequency (%)
7500 1
2.8%
9000 1
2.8%
10780 1
2.8%
12000 1
2.8%
15280 1
2.8%
22760 1
2.8%
25210 1
2.8%
29890 1
2.8%
117890 1
2.8%
825050 1
2.8%
ValueCountFrequency (%)
12696200 1
2.8%
12327240 1
2.8%
12117460 1
2.8%
11721200 1
2.8%
10346490 1
2.8%
10084870 1
2.8%
10005480 1
2.8%
8803130 1
2.8%
7943020 1
2.8%
3764800 1
2.8%

장애인비용(C)
Categorical

IMBALANCE 

Distinct2
Distinct (%)5.6%
Missing0
Missing (%)0.0%
Memory size420.0 B
0
35 
10100
 
1

Length

Max length5
Median length1
Mean length1.1111111
Min length1

Unique

Unique1 ?
Unique (%)2.8%

Sample

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

Common Values

ValueCountFrequency (%)
0 35
97.2%
10100 1
 
2.8%

Length

2023-12-12T10:37:05.953090image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T10:37:06.089823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 35
97.2%
10100 1
 
2.8%

청구액(D)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct36
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.5508718 × 108
Minimum438810
Maximum1.1228218 × 1010
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size456.0 B
2023-12-12T10:37:06.201744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum438810
5-th percentile539127.5
Q17563300
median39571645
Q31.3397483 × 108
95-th percentile8.3549908 × 108
Maximum1.1228218 × 1010
Range1.1227779 × 1010
Interquartile range (IQR)1.2641153 × 108

Descriptive statistics

Standard deviation1.8934563 × 109
Coefficient of variation (CV)4.1606452
Kurtosis32.321597
Mean4.5508718 × 108
Median Absolute Deviation (MAD)38942680
Skewness5.6023072
Sum1.6383138 × 1010
Variance3.5851766 × 1018
MonotonicityNot monotonic
2023-12-12T10:37:06.730074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=36)
ValueCountFrequency (%)
30326780 1
 
2.8%
125632410 1
 
2.8%
261835170 1
 
2.8%
3980750 1
 
2.8%
123353650 1
 
2.8%
8670990 1
 
2.8%
271404630 1
 
2.8%
4178010 1
 
2.8%
104482210 1
 
2.8%
29527300 1
 
2.8%
Other values (26) 26
72.2%
ValueCountFrequency (%)
438810 1
2.8%
480290 1
2.8%
558740 1
2.8%
699190 1
2.8%
775680 1
2.8%
1062070 1
2.8%
3980750 1
2.8%
4178010 1
2.8%
4240230 1
2.8%
8670990 1
2.8%
ValueCountFrequency (%)
11228218100 1
2.8%
2527782430 1
2.8%
271404630 1
2.8%
270712790 1
2.8%
261835170 1
2.8%
229980380 1
2.8%
222572900 1
2.8%
214720730 1
2.8%
159002090 1
2.8%
125632410 1
2.8%

Interactions

2023-12-12T10:37:03.202831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:37:01.371531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:37:02.092856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:37:02.648392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:37:03.338106image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:37:01.553269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:37:02.227366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:37:02.808018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:37:03.447261image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:37:01.723763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:37:02.360672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:37:02.930401image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:37:03.564003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:37:01.924501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:37:02.510459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T10:37:03.065418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T10:37:06.865501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
진료년월서식인원(청구건수)요양급여총액(A=B+C+D)본인부담액(B)장애인비용(C)청구액(D)
진료년월1.0000.0000.0000.0000.0000.0900.000
서식0.0001.0000.9490.8820.8230.0770.000
인원(청구건수)0.0000.9491.0000.7780.8800.0900.977
요양급여총액(A=B+C+D)0.0000.8820.7781.0000.8540.0000.218
본인부담액(B)0.0000.8230.8800.8541.0000.0000.000
장애인비용(C)0.0900.0770.0900.0000.0001.0000.000
청구액(D)0.0000.0000.9770.2180.0000.0001.000
2023-12-12T10:37:07.067373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
서식장애인비용(C)진료년월
서식1.0000.0000.000
장애인비용(C)0.0001.0000.000
진료년월0.0000.0001.000
2023-12-12T10:37:07.263604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
인원(청구건수)요양급여총액(A=B+C+D)본인부담액(B)청구액(D)진료년월서식장애인비용(C)
인원(청구건수)1.0000.4170.7260.4810.0000.8430.000
요양급여총액(A=B+C+D)0.4171.0000.8580.9250.0000.6780.000
본인부담액(B)0.7260.8581.0000.8100.0000.7000.000
청구액(D)0.4810.9250.8101.0000.0000.0000.000
진료년월0.0000.0000.0000.0001.0000.0000.000
서식0.8430.6780.7000.0000.0001.0000.000
장애인비용(C)0.0000.0000.0000.0000.0000.0001.000

Missing values

2023-12-12T10:37:03.758437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T10:37:03.954023image/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

진료년월서식인원(청구건수)요양급여총액(A=B+C+D)본인부담액(B)장애인비용(C)청구액(D)
04월건강보험외래164340915803764800030326780
14월건강보험입원7124091430012696200011228218100
24월의료급여외래1110919602989001062070
34월의료급여입원27713293101326830070002480
45월건강보험외래118129275901909900011017690
55월건강보험입원401703190608803130016515930
65월의료급여외래8450810120000438810
75월의료급여입원15664961101053240065442870
86월건강보험외래112172042701744200015460070
96월건강보험입원4216694511079430200159002090
진료년월서식인원(청구건수)요양급여총액(A=B+C+D)본인부담액(B)장애인비용(C)청구액(D)
2610월의료급여외래14429590011789004178010
2710월의료급여입원2810631164018294300104482210
2811월건강보험외래117325995003072200029527300
2911월건강보험입원58240326870103464900229980380
3011월의료급여외래8724400252100699190
3111월의료급여입원2510773139017191100106012280
3212월건강보험외래11229652230186980002527782430
3312월건강보험입원58232657770100848700222572900
3412월의료급여외래1342555101528004240230
3512월의료급여입원25967236601624800095098860