Overview

Dataset statistics

Number of variables5
Number of observations5013
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory200.8 KiB
Average record size in memory41.0 B

Variable types

Categorical4
Numeric1

Dataset

Description1. 진료일기준(한의분류 제외, 약국 제외), 연령(연말기준)2. 건강보험 급여실적(의료급여 제외)이며, 비급여는 제외- 2023년 6월 지급분까지 반영3. 아래 질병통계 자료는 요양기관에서 환자진료 중 진단명이 확정되지 않은 상태에서의 호소, 증세 등에 따라 일차진단명을 부여하고 청구한 내역 중 주진단명 및 제1부상병 기준으로 발췌한 것이므로 최종 확정된 질병과는 다를 수 있음<주상병코드 및 제1부상병코드는 KOICD 질병분류정보센터(https://www.koicd.kr) 참조>※ 2023.12.5. 발췌 데이터로서, 민원인의 제공 신청에 따른 제공 건
Author국민건강보험공단
URLhttps://www.data.go.kr/data/15125352/fileData.do

Reproduction

Analysis started2023-12-12 20:06:55.958966
Analysis finished2023-12-12 20:06:56.712308
Duration0.75 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

진료년도
Categorical

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size39.3 KiB
2021년
838 
2022년
837 
2017년
836 
2020년
835 
2018년
834 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2017년
2nd row2017년
3rd row2017년
4th row2017년
5th row2017년

Common Values

ValueCountFrequency (%)
2021년 838
16.7%
2022년 837
16.7%
2017년 836
16.7%
2020년 835
16.7%
2018년 834
16.6%
2019년 833
16.6%

Length

2023-12-13T05:06:56.798903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:06:56.932898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021년 838
16.7%
2022년 837
16.7%
2017년 836
16.7%
2020년 835
16.7%
2018년 834
16.6%
2019년 833
16.6%

성별
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size39.3 KiB
남자
2508 
여자
2505 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
남자 2508
50.0%
여자 2505
50.0%

Length

2023-12-13T05:06:57.075719image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T05:06:57.185246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
남자 2508
50.0%
여자 2505
50.0%

주부상병코드
Categorical

Distinct21
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size39.3 KiB
S00/S01/S03/S09/S10/S11/S13/S19
 
240
S02/S04/S05/S06/S12/S15/S16
 
240
S07/S08/S14/S17/S18
 
240
S20/S21/S23/S27/S29/S30/S31/S33/S39
 
240
S22/S24/S25/S32/S34/S35/S36
 
240
Other values (16)
3813 

Length

Max length43
Median length35
Mean length21.340315
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowS00/S01/S03/S09/S10/S11/S13/S19
2nd rowS00/S01/S03/S09/S10/S11/S13/S19
3rd rowS00/S01/S03/S09/S10/S11/S13/S19
4th rowS00/S01/S03/S09/S10/S11/S13/S19
5th rowS00/S01/S03/S09/S10/S11/S13/S19

Common Values

ValueCountFrequency (%)
S00/S01/S03/S09/S10/S11/S13/S19 240
 
4.8%
S02/S04/S05/S06/S12/S15/S16 240
 
4.8%
S07/S08/S14/S17/S18 240
 
4.8%
S20/S21/S23/S27/S29/S30/S31/S33/S39 240
 
4.8%
S22/S24/S25/S32/S34/S35/S36 240
 
4.8%
S40/S41/S43/S49/S50/S51/S53/S59 240
 
4.8%
S60/S61/S63/S69 240
 
4.8%
S62/S64/S65/S66 240
 
4.8%
S42/S44/S45/S46/S52/S54/S55/S56 240
 
4.8%
S67/S68 240
 
4.8%
Other values (11) 2613
52.1%

Length

2023-12-13T05:06:57.314205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
s00/s01/s03/s09/s10/s11/s13/s19 240
 
4.8%
s42/s44/s45/s46/s52/s54/s55/s56 240
 
4.8%
t00/t01/t03/t06/t07/t09/t11/t13/t14/t20~t35 240
 
4.8%
s92/s94/s95/s96 240
 
4.8%
s90/s91/s93/s99 240
 
4.8%
s72/s74/s75/s76/s82/s84/s85/s86 240
 
4.8%
s02/s04/s05/s06/s12/s15/s16 240
 
4.8%
s67/s68 240
 
4.8%
s70/s71/s73/s79/s80/s81/s83/s89 240
 
4.8%
s62/s64/s65/s66 240
 
4.8%
Other values (11) 2613
52.1%

연령
Categorical

Distinct20
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size39.3 KiB
계
 
252
45~49세
 
252
85세 이상
 
252
1~4세
 
252
5~9세
 
252
Other values (15)
3753 

Length

Max length6
Median length6
Mean length5.3680431
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row계
2nd row0세
3rd row1~4세
4th row5~9세
5th row10~14세

Common Values

ValueCountFrequency (%)
계 252
 
5.0%
45~49세 252
 
5.0%
85세 이상 252
 
5.0%
1~4세 252
 
5.0%
5~9세 252
 
5.0%
10~14세 252
 
5.0%
15~19세 252
 
5.0%
20~24세 252
 
5.0%
25~29세 252
 
5.0%
30~34세 252
 
5.0%
Other values (10) 2493
49.7%

Length

2023-12-13T05:06:57.484187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
계 252
 
4.8%
35~39세 252
 
4.8%
80~84세 252
 
4.8%
75~79세 252
 
4.8%
70~74세 252
 
4.8%
65~69세 252
 
4.8%
60~64세 252
 
4.8%
55~59세 252
 
4.8%
50~54세 252
 
4.8%
40~44세 252
 
4.8%
Other values (11) 2745
52.1%

진료인원(명)
Real number (ℝ)

Distinct3849
Distinct (%)76.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean51662.1
Minimum1
Maximum2054141
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size44.2 KiB
2023-12-13T05:06:57.687049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile23
Q1349
median9999
Q343640
95-th percentile140226.8
Maximum2054141
Range2054140
Interquartile range (IQR)43291

Descriptive statistics

Standard deviation174520.12
Coefficient of variation (CV)3.3781074
Kurtosis63.401334
Mean51662.1
Median Absolute Deviation (MAD)9940
Skewness7.5078606
Sum2.5898211 × 108
Variance3.0457273 × 1010
MonotonicityNot monotonic
2023-12-13T05:06:57.846976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
21 20
 
0.4%
1 17
 
0.3%
18 16
 
0.3%
22 16
 
0.3%
17 16
 
0.3%
20 15
 
0.3%
31 14
 
0.3%
23 13
 
0.3%
2 13
 
0.3%
37 13
 
0.3%
Other values (3839) 4860
96.9%
ValueCountFrequency (%)
1 17
0.3%
2 13
0.3%
3 11
0.2%
4 10
0.2%
5 5
 
0.1%
6 9
0.2%
7 9
0.2%
8 9
0.2%
9 5
 
0.1%
10 6
 
0.1%
ValueCountFrequency (%)
2054141 1
< 0.1%
2049428 1
< 0.1%
2038714 1
< 0.1%
1993723 1
< 0.1%
1981921 1
< 0.1%
1980857 1
< 0.1%
1968604 1
< 0.1%
1963652 1
< 0.1%
1918403 1
< 0.1%
1899871 1
< 0.1%

Interactions

2023-12-13T05:06:56.355901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T05:06:57.940753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
진료년도성별주부상병코드연령진료인원(명)
진료년도1.0000.0000.0000.0000.000
성별0.0001.0000.0000.0000.000
주부상병코드0.0000.0001.0000.0000.381
연령0.0000.0000.0001.0000.543
진료인원(명)0.0000.0000.3810.5431.000
2023-12-13T05:06:58.062012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연령진료년도성별주부상병코드
연령1.0000.0000.0000.000
진료년도0.0001.0000.0000.000
성별0.0000.0001.0000.000
주부상병코드0.0000.0000.0001.000
2023-12-13T05:06:58.453552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
진료인원(명)진료년도성별주부상병코드연령
진료인원(명)1.0000.0000.0000.1570.248
진료년도0.0001.0000.0000.0000.000
성별0.0000.0001.0000.0000.000
주부상병코드0.1570.0000.0001.0000.000
연령0.2480.0000.0000.0001.000

Missing values

2023-12-13T05:06:56.510950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T05:06:56.642615image/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

진료년도성별주부상병코드연령진료인원(명)
02017년남자S00/S01/S03/S09/S10/S11/S13/S19계1380602
12017년남자S00/S01/S03/S09/S10/S11/S13/S190세5195
22017년남자S00/S01/S03/S09/S10/S11/S13/S191~4세130400
32017년남자S00/S01/S03/S09/S10/S11/S13/S195~9세117896
42017년남자S00/S01/S03/S09/S10/S11/S13/S1910~14세78365
52017년남자S00/S01/S03/S09/S10/S11/S13/S1915~19세79403
62017년남자S00/S01/S03/S09/S10/S11/S13/S1920~24세71235
72017년남자S00/S01/S03/S09/S10/S11/S13/S1925~29세87021
82017년남자S00/S01/S03/S09/S10/S11/S13/S1930~34세84975
92017년남자S00/S01/S03/S09/S10/S11/S13/S1935~39세97863
진료년도성별주부상병코드연령진료인원(명)
50032022년여자T04/T0540~44세15
50042022년여자T04/T0545~49세14
50052022년여자T04/T0550~54세26
50062022년여자T04/T0555~59세17
50072022년여자T04/T0560~64세23
50082022년여자T04/T0565~69세19
50092022년여자T04/T0570~74세21
50102022년여자T04/T0575~79세14
50112022년여자T04/T0580~84세12
50122022년여자T04/T0585세 이상8