Overview

Dataset statistics

Number of variables3
Number of observations300
Missing cells0
Missing cells (%)0.0%
Duplicate rows12
Duplicate rows (%)4.0%
Total size in memory7.2 KiB
Average record size in memory24.4 B

Variable types

Categorical2
Text1

Dataset

Description한국보훈복지의료공단에서 제공하는 요양병원EMR시스템 내의 요양병원관련 진료비계산 기초자료정보(적용일, 규정명, 계산규정명)입니다.
Author한국보훈복지의료공단
URLhttps://www.data.go.kr/data/15122415/fileData.do

Alerts

Dataset has 12 (4.0%) duplicate rowsDuplicates
적용일 is highly overall correlated with 규정명High correlation
규정명 is highly overall correlated with 적용일High correlation

Reproduction

Analysis started2023-12-12 05:40:27.957444
Analysis finished2023-12-12 05:40:28.261355
Duration0.3 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

적용일
Categorical

HIGH CORRELATION 

Distinct13
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
2014-01-01
106 
2018-01-01
95 
2019-01-01
30 
2014-04-01
21 
2020-01-01
16 
Other values (8)
32 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique1 ?
Unique (%)0.3%

Sample

1st row2005-01-01
2nd row2009-07-01
3rd row2009-07-01
4th row2014-01-01
5th row2014-01-01

Common Values

ValueCountFrequency (%)
2014-01-01 106
35.3%
2018-01-01 95
31.7%
2019-01-01 30
 
10.0%
2014-04-01 21
 
7.0%
2020-01-01 16
 
5.3%
2017-07-01 12
 
4.0%
2017-04-01 4
 
1.3%
2021-01-01 4
 
1.3%
2022-01-01 4
 
1.3%
2023-01-01 3
 
1.0%
Other values (3) 5
 
1.7%

Length

2023-12-12T14:40:28.355968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2014-01-01 106
35.3%
2018-01-01 95
31.7%
2019-01-01 30
 
10.0%
2014-04-01 21
 
7.0%
2020-01-01 16
 
5.3%
2017-07-01 12
 
4.0%
2017-04-01 4
 
1.3%
2021-01-01 4
 
1.3%
2022-01-01 4
 
1.3%
2023-01-01 3
 
1.0%
Other values (3) 5
 
1.7%

규정명
Categorical

HIGH CORRELATION 

Distinct19
Distinct (%)6.3%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
수납액 감액율
80 
입원료 코드
67 
조제료 코드
46 
비급여 감액율
43 
본인부담상한액
23 
Other values (14)
41 

Length

Max length15
Median length10
Mean length6.7233333
Min length4

Unique

Unique8 ?
Unique (%)2.7%

Sample

1st row인공신장 과목코드
2nd row보훈감면대상자 미수코드 설정
3rd row가산식대코드
4th row중환자실 병동코드
5th row심야 가산율

Common Values

ValueCountFrequency (%)
수납액 감액율 80
26.7%
입원료 코드 67
22.3%
조제료 코드 46
15.3%
비급여 감액율 43
14.3%
본인부담상한액 23
 
7.7%
치과 감액율 12
 
4.0%
보호정신과정액코드 7
 
2.3%
심야 가산율 6
 
2.0%
의사등급 3
 
1.0%
간호사등급 3
 
1.0%
Other values (9) 10
 
3.3%

Length

2023-12-12T14:40:28.499285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
감액율 135
23.9%
코드 113
20.0%
수납액 80
14.2%
입원료 67
11.9%
조제료 46
 
8.1%
비급여 43
 
7.6%
본인부담상한액 23
 
4.1%
치과 12
 
2.1%
보호정신과정액코드 7
 
1.2%
심야 6
 
1.1%
Other values (22) 33
 
5.8%

계산규정명
Text

Distinct200
Distinct (%)66.7%
Missing0
Missing (%)0.0%
Memory size2.5 KiB
2023-12-12T14:40:28.704826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length40
Median length30
Mean length12.346667
Min length2

Characters and Unicode

Total characters3704
Distinct characters175
Distinct categories9 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique165 ?
Unique (%)55.0%

Sample

1st row인공신장 과목코드
2nd row보훈감면대상자 % 감면
3rd row산모식 가산식대 수가코드
4th row중환자실 병동코드
5th row야간가산
ValueCountFrequency (%)
입원료(내소정 29
 
5.8%
입원료(일반 26
 
5.2%
본인부담상한액 23
 
4.6%
이상 18
 
3.6%
조제투약 17
 
3.4%
가루약 17
 
3.4%
0-6시 13
 
2.6%
입원료 13
 
2.6%
90 12
 
2.4%
100 12
 
2.4%
Other values (199) 318
63.9%
2023-12-12T14:40:29.105702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
298
 
8.0%
원 176
 
4.8%
) 138
 
3.7%
( 138
 
3.7%
료 125
 
3.4%
1 105
 
2.8%
일 94
 
2.5%
입 85
 
2.3%
약 83
 
2.2%
상 82
 
2.2%
Other values (165) 2380
64.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2576
69.5%
Decimal Number 367
 
9.9%
Space Separator 298
 
8.0%
Close Punctuation 140
 
3.8%
Open Punctuation 140
 
3.8%
Other Punctuation 103
 
2.8%
Dash Punctuation 69
 
1.9%
Connector Punctuation 6
 
0.2%
Math Symbol 5
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
원 176
 
6.8%
료 125
 
4.9%
일 94
 
3.6%
입 85
 
3.3%
약 83
 
3.2%
상 82
 
3.2%
자 75
 
2.9%
내 70
 
2.7%
가 69
 
2.7%
족 69
 
2.7%
Other values (141) 1648
64.0%
Decimal Number
ValueCountFrequency (%)
1 105
28.6%
0 81
22.1%
9 29
 
7.9%
5 29
 
7.9%
2 27
 
7.4%
4 25
 
6.8%
6 25
 
6.8%
8 21
 
5.7%
3 13
 
3.5%
7 12
 
3.3%
Other Punctuation
ValueCountFrequency (%)
% 48
46.6%
/ 42
40.8%
, 5
 
4.9%
· 3
 
2.9%
. 3
 
2.9%
: 2
 
1.9%
Close Punctuation
ValueCountFrequency (%)
) 138
98.6%
] 2
 
1.4%
Open Punctuation
ValueCountFrequency (%)
( 138
98.6%
[ 2
 
1.4%
Space Separator
ValueCountFrequency (%)
298
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 69
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 6
100.0%
Math Symbol
ValueCountFrequency (%)
~ 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2576
69.5%
Common 1128
30.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
원 176
 
6.8%
료 125
 
4.9%
일 94
 
3.6%
입 85
 
3.3%
약 83
 
3.2%
상 82
 
3.2%
자 75
 
2.9%
내 70
 
2.7%
가 69
 
2.7%
족 69
 
2.7%
Other values (141) 1648
64.0%
Common
ValueCountFrequency (%)
298
26.4%
) 138
12.2%
( 138
12.2%
1 105
 
9.3%
0 81
 
7.2%
- 69
 
6.1%
% 48
 
4.3%
/ 42
 
3.7%
9 29
 
2.6%
5 29
 
2.6%
Other values (14) 151
13.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2576
69.5%
ASCII 1125
30.4%
None 3
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
298
26.5%
) 138
12.3%
( 138
12.3%
1 105
 
9.3%
0 81
 
7.2%
- 69
 
6.1%
% 48
 
4.3%
/ 42
 
3.7%
9 29
 
2.6%
5 29
 
2.6%
Other values (13) 148
13.2%
Hangul
ValueCountFrequency (%)
원 176
 
6.8%
료 125
 
4.9%
일 94
 
3.6%
입 85
 
3.3%
약 83
 
3.2%
상 82
 
3.2%
자 75
 
2.9%
내 70
 
2.7%
가 69
 
2.7%
족 69
 
2.7%
Other values (141) 1648
64.0%
None
ValueCountFrequency (%)
· 3
100.0%

Correlations

2023-12-12T14:40:29.207555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
적용일규정명
적용일1.0000.916
규정명0.9161.000
2023-12-12T14:40:29.303083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
적용일규정명
적용일1.0000.623
규정명0.6231.000
2023-12-12T14:40:29.464880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
적용일규정명
적용일1.0000.623
규정명0.6231.000

Missing values

2023-12-12T14:40:28.141431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T14:40:28.226176image/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

적용일규정명계산규정명
02005-01-01인공신장 과목코드인공신장 과목코드
12009-07-01보훈감면대상자 미수코드 설정보훈감면대상자 % 감면
22009-07-01가산식대코드산모식 가산식대 수가코드
32014-01-01중환자실 병동코드중환자실 병동코드
42014-01-01심야 가산율야간가산
52014-01-01심야 가산율휴일가산
62014-01-01심야 가산율평일응급
72014-01-01심야 가산율부수술
82014-01-01심야 가산율부수술야간
92014-01-01심야 가산율부수술휴일
적용일규정명계산규정명
2902021-01-01본인부담상한액본인부담상한액
2912021-01-01본인부담상한액본인부담상한액
2922021-01-01본인부담상한액본인부담상한액
2932022-01-01본인부담상한액본인부담상한액
2942022-01-01본인부담상한액본인부담상한액
2952022-01-01본인부담상한액본인부담상한액
2962022-01-01본인부담상한액본인부담상한액
2972023-01-01본인부담상한액본인부담상한액
2982023-01-01본인부담상한액본인부담상한액
2992023-01-01본인부담상한액본인부담상한액

Duplicate rows

Most frequently occurring

적용일규정명계산규정명# duplicates
02014-01-01보호정신과정액코드보호 정신과 정액 수가코드7
62018-01-01본인부담상한액본인부담상한액4
72019-01-01본인부담상한액본인부담상한액4
82020-01-01본인부담상한액본인부담상한액4
92021-01-01본인부담상한액본인부담상한액4
102022-01-01본인부담상한액본인부담상한액4
22014-01-01치과 감액율기타3
32014-01-01치과 감액율본인(배우자,자녀)3
42014-01-01치과 감액율직계가족3
52014-01-01치과 감액율협력병원/지인3