Overview

Dataset statistics

Number of variables7
Number of observations60
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.6 KiB
Average record size in memory61.1 B

Variable types

Categorical4
Numeric3

Dataset

Description서울특별시 구로구 0세 아동의 외래, 입원 전체 진료현황 및 다빈도 상병별 진료현황(진료인원, 총진료비, 공단부담금)1. 진료일 기준(한의분류, 약국 제외), 연말 기준(0세), 주민등록주소지 기준(서울특별시 구로구)2. 건강보험 급여실적(의료급여 제외)이며, 비급여 제외- 2023년 6월 심사분까지 반영3. 해당 질병통계 자료는 요양기관에서 환자진료 중 진단명이 확정되지 않은 상태에서의 호소, 증세 등에 따라일차진단명을 부여하고 청구한 내역 중 주진단명 기준으로 발췌한 것이므로 최종 확정된 질병과는 다를 수 있음※ 다빈도 주상병에는 질병 및 손상분류에 해당하지 않는 기타 코드(출생에 따른 입원) 등은 제외
Author국민건강보험공단
URLhttps://www.data.go.kr/data/15126553/fileData.do

Alerts

주상병명 is highly overall correlated with 진료형태 and 1 other fieldsHigh correlation
주상병코드 is highly overall correlated with 진료형태 and 1 other fieldsHigh correlation
진료인원(명) is highly overall correlated with 진료형태High correlation
총 진료비(천원) is highly overall correlated with 공단부담금(천원)High correlation
공단부담금(천원) is highly overall correlated with 총 진료비(천원)High correlation
진료형태 is highly overall correlated with 진료인원(명) and 2 other fieldsHigh correlation
총 진료비(천원) has unique valuesUnique
공단부담금(천원) has unique valuesUnique

Reproduction

Analysis started2024-03-14 12:35:22.969481
Analysis finished2024-03-14 12:35:25.373051
Duration2.4 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

진료년도
Categorical

Distinct5
Distinct (%)8.3%
Missing0
Missing (%)0.0%
Memory size608.0 B
2018년
12 
2019년
12 
2020년
12 
2021년
12 
2022년
12 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2018년
2nd row2018년
3rd row2019년
4th row2019년
5th row2020년

Common Values

ValueCountFrequency (%)
2018년 12
20.0%
2019년 12
20.0%
2020년 12
20.0%
2021년 12
20.0%
2022년 12
20.0%

Length

2024-03-14T21:35:25.612216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T21:35:25.944447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2018년 12
20.0%
2019년 12
20.0%
2020년 12
20.0%
2021년 12
20.0%
2022년 12
20.0%

진료형태
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size608.0 B
입원
30 
외래
30 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
입원 30
50.0%
외래 30
50.0%

Length

2024-03-14T21:35:26.379284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T21:35:26.761431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
입원 30
50.0%
외래 30
50.0%

주상병코드
Categorical

HIGH CORRELATION 

Distinct16
Distinct (%)26.7%
Missing0
Missing (%)0.0%
Memory size608.0 B
전체
10 
P59
7 
P07
5 
P22
5 
J00
5 
Other values (11)
28 

Length

Max length3
Median length3
Mean length2.8333333
Min length2

Unique

Unique5 ?
Unique (%)8.3%

Sample

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

Common Values

ValueCountFrequency (%)
전체 10
16.7%
P59 7
11.7%
P07 5
8.3%
P22 5
8.3%
J00 5
8.3%
J06 5
8.3%
J20 5
8.3%
J18 4
 
6.7%
J21 4
 
6.7%
A09 3
 
5.0%
Other values (6) 7
11.7%

Length

2024-03-14T21:35:27.113214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
전체 10
16.7%
p59 7
11.7%
p07 5
8.3%
p22 5
8.3%
j00 5
8.3%
j06 5
8.3%
j20 5
8.3%
j18 4
 
6.7%
j21 4
 
6.7%
a09 3
 
5.0%
Other values (6) 7
11.7%

주상병명
Categorical

HIGH CORRELATION 

Distinct16
Distinct (%)26.7%
Missing0
Missing (%)0.0%
Memory size608.0 B
전체
10 
기타및상세불명의원인으로인한신생아황달
7 
달리분류되지않은단기임신및저체중출산에관련된장애
5 
신생아의호흡곤란
5 
급성비인두염[감기]
5 
Other values (11)
28 

Length

Max length24
Median length18
Mean length11.133333
Min length2

Unique

Unique5 ?
Unique (%)8.3%

Sample

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

Common Values

ValueCountFrequency (%)
전체 10
16.7%
기타및상세불명의원인으로인한신생아황달 7
11.7%
달리분류되지않은단기임신및저체중출산에관련된장애 5
8.3%
신생아의호흡곤란 5
8.3%
급성비인두염[감기] 5
8.3%
다발성및상세불명부위의급성상기도감염 5
8.3%
급성기관지염 5
8.3%
상세불명병원체의폐렴 4
 
6.7%
급성세기관지염 4
 
6.7%
감염성및상세불명기원의기타위장염및결장염 3
 
5.0%
Other values (6) 7
11.7%

Length

2024-03-14T21:35:27.508905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
전체 10
16.7%
기타및상세불명의원인으로인한신생아황달 7
11.7%
달리분류되지않은단기임신및저체중출산에관련된장애 5
8.3%
신생아의호흡곤란 5
8.3%
급성비인두염[감기 5
8.3%
다발성및상세불명부위의급성상기도감염 5
8.3%
급성기관지염 5
8.3%
상세불명병원체의폐렴 4
 
6.7%
급성세기관지염 4
 
6.7%
감염성및상세불명기원의기타위장염및결장염 3
 
5.0%
Other values (6) 7
11.7%

진료인원(명)
Real number (ℝ)

HIGH CORRELATION 

Distinct57
Distinct (%)95.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean643.45
Minimum22
Maximum2825
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size668.0 B
2024-03-14T21:35:27.882192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum22
5-th percentile33.75
Q187.75
median315
Q3696.75
95-th percentile2552.1
Maximum2825
Range2803
Interquartile range (IQR)609

Descriptive statistics

Standard deviation824.48656
Coefficient of variation (CV)1.281353
Kurtosis1.1727551
Mean643.45
Median Absolute Deviation (MAD)246.5
Skewness1.6028369
Sum38607
Variance679778.08
MonotonicityNot monotonic
2024-03-14T21:35:28.267231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
70 2
 
3.3%
62 2
 
3.3%
800 2
 
3.3%
2825 1
 
1.7%
332 1
 
1.7%
273 1
 
1.7%
456 1
 
1.7%
422 1
 
1.7%
281 1
 
1.7%
293 1
 
1.7%
Other values (47) 47
78.3%
ValueCountFrequency (%)
22 1
1.7%
28 1
1.7%
29 1
1.7%
34 1
1.7%
42 1
1.7%
44 1
1.7%
57 1
1.7%
62 2
3.3%
63 1
1.7%
67 1
1.7%
ValueCountFrequency (%)
2825 1
1.7%
2702 1
1.7%
2668 1
1.7%
2546 1
1.7%
2378 1
1.7%
2253 1
1.7%
2178 1
1.7%
2146 1
1.7%
2035 1
1.7%
1998 1
1.7%

총 진료비(천원)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct60
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean705495.15
Minimum7341
Maximum5698013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size668.0 B
2024-03-14T21:35:28.612712image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7341
5-th percentile10751.9
Q119941.25
median66820.5
Q3602117.25
95-th percentile5086478
Maximum5698013
Range5690672
Interquartile range (IQR)582176

Descriptive statistics

Standard deviation1459244.3
Coefficient of variation (CV)2.0683974
Kurtosis5.9064532
Mean705495.15
Median Absolute Deviation (MAD)50816.5
Skewness2.6332507
Sum42329709
Variance2.1293939 × 1012
MonotonicityNot monotonic
2024-03-14T21:35:28.963977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4946925 1
 
1.7%
68619 1
 
1.7%
567937 1
 
1.7%
110266 1
 
1.7%
7341 1
 
1.7%
14586 1
 
1.7%
32022 1
 
1.7%
10857 1
 
1.7%
14979 1
 
1.7%
21253 1
 
1.7%
Other values (50) 50
83.3%
ValueCountFrequency (%)
7341 1
1.7%
7848 1
1.7%
8755 1
1.7%
10857 1
1.7%
10888 1
1.7%
11568 1
1.7%
12463 1
1.7%
13347 1
1.7%
14586 1
1.7%
14979 1
1.7%
ValueCountFrequency (%)
5698013 1
1.7%
5285722 1
1.7%
5255237 1
1.7%
5077596 1
1.7%
4946925 1
1.7%
1833903 1
1.7%
1760237 1
1.7%
1601049 1
1.7%
1415220 1
1.7%
1240176 1
1.7%

공단부담금(천원)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct60
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean687162.5
Minimum6893
Maximum5580765
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size668.0 B
2024-03-14T21:35:29.204375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum6893
5-th percentile10148.25
Q116673.5
median60356.5
Q3566251.5
95-th percentile5001683.5
Maximum5580765
Range5573872
Interquartile range (IQR)549578

Descriptive statistics

Standard deviation1435868.8
Coefficient of variation (CV)2.0895622
Kurtosis5.8905925
Mean687162.5
Median Absolute Deviation (MAD)47203
Skewness2.6328538
Sum41229750
Variance2.0617192 × 1012
MonotonicityNot monotonic
2024-03-14T21:35:29.444440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
4850493 1
 
1.7%
58444 1
 
1.7%
564371 1
 
1.7%
109354 1
 
1.7%
6893 1
 
1.7%
13619 1
 
1.7%
30328 1
 
1.7%
10250 1
 
1.7%
13095 1
 
1.7%
18217 1
 
1.7%
Other values (50) 50
83.3%
ValueCountFrequency (%)
6893 1
1.7%
7345 1
1.7%
8215 1
1.7%
10250 1
1.7%
10315 1
1.7%
10932 1
1.7%
11778 1
1.7%
12522 1
1.7%
13095 1
1.7%
13212 1
1.7%
ValueCountFrequency (%)
5580765 1
1.7%
5205743 1
1.7%
5171534 1
1.7%
4992744 1
1.7%
4850493 1
1.7%
1819553 1
1.7%
1747497 1
1.7%
1588673 1
1.7%
1408147 1
1.7%
1235089 1
1.7%

Interactions

2024-03-14T21:35:24.420473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:35:23.375048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:35:23.994781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:35:24.560513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:35:23.613158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:35:24.135740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:35:24.704160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:35:23.851521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T21:35:24.276047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-14T21:35:29.868483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
진료년도진료형태주상병코드주상병명진료인원(명)총 진료비(천원)공단부담금(천원)
진료년도1.0000.0000.0000.0000.0000.0000.000
진료형태0.0001.0000.9060.9060.6640.4860.635
주상병코드0.0000.9061.0001.0000.7220.6930.783
주상병명0.0000.9061.0001.0000.7220.6930.783
진료인원(명)0.0000.6640.7220.7221.0000.5240.427
총 진료비(천원)0.0000.4860.6930.6930.5241.0000.997
공단부담금(천원)0.0000.6350.7830.7830.4270.9971.000
2024-03-14T21:35:30.056476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
주상병명주상병코드진료년도진료형태
주상병명1.0001.0000.0000.664
주상병코드1.0001.0000.0000.664
진료년도0.0000.0001.0000.000
진료형태0.6640.6640.0001.000
2024-03-14T21:35:30.220468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
진료인원(명)총 진료비(천원)공단부담금(천원)진료년도진료형태주상병코드주상병명
진료인원(명)1.0000.1280.1170.0000.6850.3930.393
총 진료비(천원)0.1281.0000.9960.0000.3430.3810.381
공단부담금(천원)0.1170.9961.0000.0000.4520.4730.473
진료년도0.0000.0000.0001.0000.0000.0000.000
진료형태0.6850.3430.4520.0001.0000.6640.664
주상병코드0.3930.3810.4730.0000.6641.0001.000
주상병명0.3930.3810.4730.0000.6641.0001.000

Missing values

2024-03-14T21:35:24.949580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T21:35:25.226589image/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

진료년도진료형태주상병코드주상병명진료인원(명)총 진료비(천원)공단부담금(천원)
02018년입원전체전체282549469254850493
12018년외래전체전체2668615396438757
22019년입원전체전체270256980135580765
32019년외래전체전체2546674309600936
42020년입원전체전체237852857225205743
52020년외래전체전체2178455427407026
62021년입원전체전체225350775964992744
72021년외래전체전체2146597691535800
82022년입원전체전체203552552375171534
92022년외래전체전체1998620909553489
진료년도진료형태주상병코드주상병명진료인원(명)총 진료비(천원)공단부담금(천원)
502022년입원J21급성세기관지염293773034077
512022년입원P07달리분류되지않은단기임신및저체중출산에관련된장애9118339031819553
522022년입원P22신생아의호흡곤란180795924790466
532022년입원P59기타및상세불명의원인으로인한신생아황달57106226104869
542022년입원R50기타및원인미상의열423435829813
552022년외래A09감염성및상세불명기원의기타위장염및결장염3341944717668
562022년외래J00급성비인두염[감기]32287558215
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