Overview

Dataset statistics

Number of variables6
Number of observations10000
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory605.5 KiB
Average record size in memory62.0 B

Variable types

Numeric5
Categorical1

Dataset

Description환경성질환(천식) 의료이용정보1. 사례정의 : 상병코드 AND 약제­ J45 천식 , - J46 천식지속상태- 호흡기내과 전문의의 자문을 거쳐 선정된 천식 관련 흡입제 및 경구제, 단일제제 및 복합제(주성분 약 270 여종)를 반영2. 구축방법○ 전체 청구상병 테이블(주상병(=1상병) 및 주상병 이외의 모든 부상병 포함)에서 해당 상병코드가 포함된 모든 청구건 추출○ 해당 상병코드로 진단 받은 모든 청구건을 중복제거 후 진료에피소드로 묶고, 건수를 산출함.- 각 청구건의 날짜 간격이 42일 이내인 경우 하나의 진료에피소드로 구축함.- 방법론 참조 : 국립환경과학원 '국민건강보험공단 빅데이터를 이용한 가습기살균제 건강피해 규명 연구(II)'(2020),'가습기살균제 호흡기계 건강피해 통합 판정체계 구축 연구'(2021)○ 2006년 1월~2022년 12월까지 주·부상병 조건의 진료에피소드 건수- 하나의 진료에피소드에 포함된 여러 청구건들 중에서 해당 상병코드가 주상병 또는 제2상병으로 1회 이상 청구된 경우임.○ 2006년 1월~2022년 12월까지 "외래 및 입원"과 "입원"의 진료에피소드 건수- "입원" 진료에피소드는 하나의 진료에피소드에 포함된 여러 청구건들 중 하나 이상의 입원 청구건이 포함된 경우임.○ 시군구, 요양개시년월, 입원/외래, 성별, 연령군별 진료에피소드 건수를 산출함.3. 레이아웃○ 요양개시년월 ○ 주소(시도) ○ 주소(시군구) ○ 성별(1 : 남자, 2 : 여자)○ 연령군(0 : 0-5세, 1 : 6-11세, 2 : 12-17세, 3 : 18-44세, 4 : 45-64세, 5 : ≥65세)○ 진료에피소드건수- 외래 및 입원 주·부상병 조건의 진료에피소드 건수(시트명: 외래입원주부상병)- 입원 주·부상병 조건의 진료에피소드 건수(시트명: 입원주부상병)
Author국민건강보험공단
URLhttps://www.data.go.kr/data/15104806/fileData.do

Alerts

주소(시도) is highly overall correlated with 주소(시군구)High correlation
주소(시군구) is highly overall correlated with 주소(시도)High correlation
연령군 has 1726 (17.3%) zerosZeros

Reproduction

Analysis started2024-03-14 18:24:27.815770
Analysis finished2024-03-14 18:24:36.485862
Duration8.67 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

요양개시연월
Real number (ℝ)

Distinct34
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean200698.14
Minimum200601
Maximum200810
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-15T03:24:36.605291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum200601
5-th percentile200602
Q1200609
median200705
Q3200801
95-th percentile200808
Maximum200810
Range209
Interquartile range (IQR)192

Descriptive statistics

Standard deviation78.886927
Coefficient of variation (CV)0.00039306258
Kurtosis-1.395721
Mean200698.14
Median Absolute Deviation (MAD)96
Skewness0.13521427
Sum2.0069814 × 109
Variance6223.1473
MonotonicityNot monotonic
2024-03-15T03:24:36.824956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
200610 334
 
3.3%
200706 330
 
3.3%
200705 329
 
3.3%
200808 323
 
3.2%
200609 319
 
3.2%
200712 315
 
3.1%
200701 311
 
3.1%
200709 311
 
3.1%
200710 309
 
3.1%
200608 305
 
3.0%
Other values (24) 6814
68.1%
ValueCountFrequency (%)
200601 293
2.9%
200602 289
2.9%
200603 293
2.9%
200604 275
2.8%
200605 297
3.0%
200606 301
3.0%
200607 302
3.0%
200608 305
3.0%
200609 319
3.2%
200610 334
3.3%
ValueCountFrequency (%)
200810 140
1.4%
200809 300
3.0%
200808 323
3.2%
200807 293
2.9%
200806 291
2.9%
200805 305
3.0%
200804 262
2.6%
200803 281
2.8%
200802 283
2.8%
200801 294
2.9%

주소(시도)
Real number (ℝ)

HIGH CORRELATION 

Distinct17
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.6399
Minimum11
Maximum50
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-15T03:24:37.091970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum11
5-th percentile11
Q129
median42
Q346
95-th percentile48
Maximum50
Range39
Interquartile range (IQR)17

Descriptive statistics

Standard deviation11.251439
Coefficient of variation (CV)0.2989232
Kurtosis0.46853526
Mean37.6399
Median Absolute Deviation (MAD)4
Skewness-1.2701968
Sum376399
Variance126.59489
MonotonicityNot monotonic
2024-03-15T03:24:37.499110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
41 1684
16.8%
11 1007
10.1%
47 967
9.7%
46 885
8.8%
48 824
8.2%
42 751
7.5%
26 653
 
6.5%
45 620
 
6.2%
44 592
 
5.9%
43 573
 
5.7%
Other values (7) 1444
14.4%
ValueCountFrequency (%)
11 1007
10.1%
26 653
 
6.5%
27 319
 
3.2%
28 374
 
3.7%
29 220
 
2.2%
30 186
 
1.9%
31 225
 
2.2%
36 40
 
0.4%
41 1684
16.8%
42 751
7.5%
ValueCountFrequency (%)
50 80
 
0.8%
48 824
8.2%
47 967
9.7%
46 885
8.8%
45 620
 
6.2%
44 592
 
5.9%
43 573
 
5.7%
42 751
7.5%
41 1684
16.8%
36 40
 
0.4%

주소(시군구)
Real number (ℝ)

HIGH CORRELATION 

Distinct250
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean38076.137
Minimum11110
Maximum50130
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-15T03:24:37.840925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum11110
5-th percentile11410
Q129170
median42720
Q346720
95-th percentile48330
Maximum50130
Range39020
Interquartile range (IQR)17550

Descriptive statistics

Standard deviation11313.165
Coefficient of variation (CV)0.29711957
Kurtosis0.41699844
Mean38076.137
Median Absolute Deviation (MAD)4170
Skewness-1.2521278
Sum3.8076137 × 108
Variance1.2798771 × 108
MonotonicityNot monotonic
2024-03-15T03:24:38.131613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
41820 57
 
0.6%
41133 55
 
0.5%
11170 55
 
0.5%
46170 55
 
0.5%
46910 51
 
0.5%
42810 51
 
0.5%
26380 51
 
0.5%
29155 51
 
0.5%
41111 51
 
0.5%
42830 51
 
0.5%
Other values (240) 9472
94.7%
ValueCountFrequency (%)
11110 40
0.4%
11140 40
0.4%
11170 55
0.5%
11200 43
0.4%
11215 26
0.3%
11230 35
0.4%
11260 39
0.4%
11290 42
0.4%
11305 38
0.4%
11320 33
0.3%
ValueCountFrequency (%)
50130 31
0.3%
50110 49
0.5%
48890 43
0.4%
48880 41
0.4%
48870 44
0.4%
48860 45
0.4%
48850 42
0.4%
48840 36
0.4%
48820 28
0.3%
48740 39
0.4%

성별
Categorical

Distinct2
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
1
5099 
2
4901 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row2
5th row1

Common Values

ValueCountFrequency (%)
1 5099
51.0%
2 4901
49.0%

Length

2024-03-15T03:24:38.379971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T03:24:38.688548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 5099
51.0%
2 4901
49.0%

연령군
Real number (ℝ)

ZEROS 

Distinct6
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.4978
Minimum0
Maximum5
Zeros1726
Zeros (%)17.3%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-15T03:24:38.968678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median3
Q34
95-th percentile5
Maximum5
Range5
Interquartile range (IQR)3

Descriptive statistics

Standard deviation1.7154852
Coefficient of variation (CV)0.68679846
Kurtosis-1.2739057
Mean2.4978
Median Absolute Deviation (MAD)1
Skewness-0.0084464285
Sum24978
Variance2.9428894
MonotonicityNot monotonic
2024-03-15T03:24:39.183539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 1726
17.3%
3 1676
16.8%
4 1671
16.7%
5 1671
16.7%
2 1655
16.6%
1 1601
16.0%
ValueCountFrequency (%)
0 1726
17.3%
1 1601
16.0%
2 1655
16.6%
3 1676
16.8%
4 1671
16.7%
5 1671
16.7%
ValueCountFrequency (%)
5 1671
16.7%
4 1671
16.7%
3 1676
16.8%
2 1655
16.6%
1 1601
16.0%
0 1726
17.3%

진료에피소드 건수
Real number (ℝ)

Distinct629
Distinct (%)6.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean108.9983
Minimum1
Maximum1359
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-15T03:24:39.417454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile5
Q124
median64
Q3146
95-th percentile372
Maximum1359
Range1358
Interquartile range (IQR)122

Descriptive statistics

Standard deviation127.85697
Coefficient of variation (CV)1.173018
Kurtosis9.0750615
Mean108.9983
Median Absolute Deviation (MAD)48
Skewness2.4779571
Sum1089983
Variance16347.405
MonotonicityNot monotonic
2024-03-15T03:24:39.835665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
2 139
 
1.4%
3 124
 
1.2%
6 123
 
1.2%
14 122
 
1.2%
9 121
 
1.2%
4 118
 
1.2%
7 115
 
1.1%
5 114
 
1.1%
10 114
 
1.1%
15 107
 
1.1%
Other values (619) 8803
88.0%
ValueCountFrequency (%)
1 94
0.9%
2 139
1.4%
3 124
1.2%
4 118
1.2%
5 114
1.1%
6 123
1.2%
7 115
1.1%
8 104
1.0%
9 121
1.2%
10 114
1.1%
ValueCountFrequency (%)
1359 1
< 0.1%
1301 1
< 0.1%
1210 1
< 0.1%
1126 1
< 0.1%
1092 1
< 0.1%
1070 1
< 0.1%
1018 1
< 0.1%
934 1
< 0.1%
930 1
< 0.1%
929 1
< 0.1%

Interactions

2024-03-15T03:24:34.308795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T03:24:28.222037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T03:24:29.925131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T03:24:31.823192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T03:24:33.096290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T03:24:34.555634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T03:24:28.491336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T03:24:30.204031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T03:24:32.162954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T03:24:33.356441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T03:24:34.921977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T03:24:29.051343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T03:24:30.628630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T03:24:32.374390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T03:24:33.634897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T03:24:35.479359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T03:24:29.346127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T03:24:31.013208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T03:24:32.567250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T03:24:33.932297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T03:24:35.762390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T03:24:29.624949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T03:24:31.454276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T03:24:32.810833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T03:24:34.133429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-15T03:24:40.120359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
요양개시연월주소(시도)주소(시군구)성별연령군진료에피소드 건수
요양개시연월1.0000.0430.0320.0000.0000.000
주소(시도)0.0431.0000.9990.0000.0000.253
주소(시군구)0.0320.9991.0000.0120.0000.280
성별0.0000.0000.0121.0000.0000.146
연령군0.0000.0000.0000.0001.0000.347
진료에피소드 건수0.0000.2530.2800.1460.3471.000
2024-03-15T03:24:40.303154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
요양개시연월주소(시도)주소(시군구)연령군진료에피소드 건수성별
요양개시연월1.000-0.017-0.0160.006-0.0000.000
주소(시도)-0.0171.0000.995-0.005-0.3490.000
주소(시군구)-0.0160.9951.000-0.006-0.3740.009
연령군0.006-0.005-0.0061.000-0.0700.000
진료에피소드 건수-0.000-0.349-0.374-0.0701.0000.112
성별0.0000.0000.0090.0000.1121.000

Missing values

2024-03-15T03:24:36.124686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-15T03:24:36.407541image/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

요양개시연월주소(시도)주소(시군구)성별연령군진료에피소드 건수
2852520061043431501451
87962006034848720139
97227200809444413110306
74056200801474717021129
6710120071142427201317
49601200705444427010220
5505720070741418201319
48906200705414139023312
894262008064848860235
942262008084343770228
요양개시연월주소(시도)주소(시군구)성별연령군진료에피소드 건수
3479020061244448252055
9875120081026261401457
84259200805292914025169
1629820060641418201131
205812006074747940254
56731200708111126025135
9663520080941414101558
7509520080227271701581
9662920080941413902595
78747200803414141020357