Overview

Dataset statistics

Number of variables8
Number of observations31
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.2 KiB
Average record size in memory71.3 B

Variable types

Categorical6
Text2

Alerts

단위 has constant value ""Constant
규격명 is highly overall correlated with 적용시작일자 and 3 other fieldsHigh correlation
적용시작일자 is highly overall correlated with 투여경로명 and 3 other fieldsHigh correlation
투여경로명 is highly overall correlated with 적용시작일자 and 3 other fieldsHigh correlation
급여구분명 is highly overall correlated with 적용시작일자 and 3 other fieldsHigh correlation
개당산출단가 is highly overall correlated with 적용시작일자 and 3 other fieldsHigh correlation
약품코드 has unique valuesUnique

Reproduction

Analysis started2023-12-10 12:00:43.119755
Analysis finished2023-12-10 12:00:43.806556
Duration0.69 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

적용시작일자
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)16.1%
Missing0
Missing (%)0.0%
Memory size380.0 B
20100101
19 
20160401
9 
20170401
 
1
20130301
 
1
20130401
 
1

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique3 ?
Unique (%)9.7%

Sample

1st row20170401
2nd row20130301
3rd row20130401
4th row20160401
5th row20160401

Common Values

ValueCountFrequency (%)
20100101 19
61.3%
20160401 9
29.0%
20170401 1
 
3.2%
20130301 1
 
3.2%
20130401 1
 
3.2%

Length

2023-12-10T21:00:43.884277image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T21:00:44.035081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20100101 19
61.3%
20160401 9
29.0%
20170401 1
 
3.2%
20130301 1
 
3.2%
20130401 1
 
3.2%

투여경로명
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)6.5%
Missing0
Missing (%)0.0%
Memory size380.0 B
<NA>
17 
내복
14 

Length

Max length4
Median length4
Mean length3.0967742
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 17
54.8%
내복 14
45.2%

Length

2023-12-10T21:00:44.239887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T21:00:44.391155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 17
54.8%
내복 14
45.2%

품목명
Text

Distinct29
Distinct (%)93.5%
Missing0
Missing (%)0.0%
Memory size380.0 B
2023-12-10T21:00:44.609790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length8
Mean length7.6774194
Min length5

Characters and Unicode

Total characters238
Distinct characters42
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique27 ?
Unique (%)87.1%

Sample

1st row신텍스치자엑스산
2nd row정우치자엑스산
3rd row기화치자엑스산
4th row한신치자엑스산
5th row한풍치자엑스산
ValueCountFrequency (%)
치자엑스산 18
37.5%
경방치자엑스산 2
 
4.2%
정우치자엑스산 2
 
4.2%
한중 1
 
2.1%
신텍스치자엑스산 1
 
2.1%
천일 1
 
2.1%
중경 1
 
2.1%
삼영 1
 
2.1%
태양 1
 
2.1%
삼익 1
 
2.1%
Other values (19) 19
39.6%
2023-12-10T21:00:45.032127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
스 33
13.9%
치 31
13.0%
자 31
13.0%
엑 31
13.0%
산 31
13.0%
17
 
7.1%
한 6
 
2.5%
경 4
 
1.7%
신 4
 
1.7%
삼 3
 
1.3%
Other values (32) 47
19.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 221
92.9%
Space Separator 17
 
7.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
스 33
14.9%
치 31
14.0%
자 31
14.0%
엑 31
14.0%
산 31
14.0%
한 6
 
2.7%
경 4
 
1.8%
신 4
 
1.8%
삼 3
 
1.4%
중 3
 
1.4%
Other values (31) 44
19.9%
Space Separator
ValueCountFrequency (%)
17
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 221
92.9%
Common 17
 
7.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
스 33
14.9%
치 31
14.0%
자 31
14.0%
엑 31
14.0%
산 31
14.0%
한 6
 
2.7%
경 4
 
1.8%
신 4
 
1.8%
삼 3
 
1.4%
중 3
 
1.4%
Other values (31) 44
19.9%
Common
ValueCountFrequency (%)
17
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 221
92.9%
ASCII 17
 
7.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
스 33
14.9%
치 31
14.0%
자 31
14.0%
엑 31
14.0%
산 31
14.0%
한 6
 
2.7%
경 4
 
1.8%
신 4
 
1.8%
삼 3
 
1.4%
중 3
 
1.4%
Other values (31) 44
19.9%
ASCII
ValueCountFrequency (%)
17
100.0%

약품코드
Text

UNIQUE 

Distinct31
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size380.0 B
2023-12-10T21:00:45.293960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length9
Mean length8.9354839
Min length8

Characters and Unicode

Total characters277
Distinct characters12
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique31 ?
Unique (%)100.0%

Sample

1st row623003060
2nd row651002520
3rd row652802620
4th row655004950
5th row658103780
ValueCountFrequency (%)
623003060 1
 
3.2%
h00059003 1
 
3.2%
h00059022 1
 
3.2%
h00059021 1
 
3.2%
h00059017 1
 
3.2%
h00059016 1
 
3.2%
h00059015 1
 
3.2%
h00059014 1
 
3.2%
h00059013 1
 
3.2%
h00059012 1
 
3.2%
Other values (21) 21
67.7%
2023-12-10T21:00:45.690927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 115
41.5%
5 28
 
10.1%
9 26
 
9.4%
6 23
 
8.3%
2 20
 
7.2%
H 17
 
6.1%
1 16
 
5.8%
3 10
 
3.6%
4 10
 
3.6%
8 5
 
1.8%
Other values (2) 7
 
2.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 258
93.1%
Uppercase Letter 19
 
6.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 115
44.6%
5 28
 
10.9%
9 26
 
10.1%
6 23
 
8.9%
2 20
 
7.8%
1 16
 
6.2%
3 10
 
3.9%
4 10
 
3.9%
8 5
 
1.9%
7 5
 
1.9%
Uppercase Letter
ValueCountFrequency (%)
H 17
89.5%
A 2
 
10.5%

Most occurring scripts

ValueCountFrequency (%)
Common 258
93.1%
Latin 19
 
6.9%

Most frequent character per script

Common
ValueCountFrequency (%)
0 115
44.6%
5 28
 
10.9%
9 26
 
10.1%
6 23
 
8.9%
2 20
 
7.8%
1 16
 
6.2%
3 10
 
3.9%
4 10
 
3.9%
8 5
 
1.9%
7 5
 
1.9%
Latin
ValueCountFrequency (%)
H 17
89.5%
A 2
 
10.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 277
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 115
41.5%
5 28
 
10.1%
9 26
 
9.4%
6 23
 
8.3%
2 20
 
7.2%
H 17
 
6.1%
1 16
 
5.8%
3 10
 
3.6%
4 10
 
3.6%
8 5
 
1.8%
Other values (2) 7
 
2.5%

규격명
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)9.7%
Missing0
Missing (%)0.0%
Memory size380.0 B
1.0
23 
0.7
7 
1.4
 
1

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique1 ?
Unique (%)3.2%

Sample

1st row0.7
2nd row1.0
3rd row1.0
4th row0.7
5th row0.7

Common Values

ValueCountFrequency (%)
1.0 23
74.2%
0.7 7
 
22.6%
1.4 1
 
3.2%

Length

2023-12-10T21:00:45.830009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T21:00:45.920104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1.0 23
74.2%
0.7 7
 
22.6%
1.4 1
 
3.2%

급여구분명
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)6.5%
Missing0
Missing (%)0.0%
Memory size380.0 B
삭제
21 
급여
10 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row급여
2nd row삭제
3rd row삭제
4th row급여
5th row급여

Common Values

ValueCountFrequency (%)
삭제 21
67.7%
급여 10
32.3%

Length

2023-12-10T21:00:46.037039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T21:00:46.162794image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
삭제 21
67.7%
급여 10
32.3%

개당산출단가
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)12.9%
Missing0
Missing (%)0.0%
Memory size380.0 B
31.0
18 
56.0
10 
0.0
2 
44.29
 
1

Length

Max length5
Median length4
Mean length3.9677419
Min length3

Unique

Unique1 ?
Unique (%)3.2%

Sample

1st row56.0
2nd row0.0
3rd row0.0
4th row56.0
5th row56.0

Common Values

ValueCountFrequency (%)
31.0 18
58.1%
56.0 10
32.3%
0.0 2
 
6.5%
44.29 1
 
3.2%

Length

2023-12-10T21:00:46.341833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T21:00:46.537103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
31.0 18
58.1%
56.0 10
32.3%
0.0 2
 
6.5%
44.29 1
 
3.2%

단위
Categorical

CONSTANT 

Distinct1
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size380.0 B
g
31 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
g 31
100.0%

Length

2023-12-10T21:00:46.679175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T21:00:46.820067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
g 31
100.0%

Correlations

2023-12-10T21:00:46.909860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
적용시작일자품목명약품코드규격명급여구분명개당산출단가
적용시작일자1.0000.0001.0000.5861.0000.819
품목명0.0001.0001.0000.3550.0000.000
약품코드1.0001.0001.0001.0001.0001.000
규격명0.5860.3551.0001.0000.5740.541
급여구분명1.0000.0001.0000.5741.0001.000
개당산출단가0.8190.0001.0000.5411.0001.000
2023-12-10T21:00:47.088309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
규격명적용시작일자투여경로명급여구분명개당산출단가
규격명1.0000.5131.0000.8290.533
적용시작일자0.5131.0001.0000.9470.770
투여경로명1.0001.0001.0001.0001.000
급여구분명0.8290.9471.0001.0000.965
개당산출단가0.5330.7701.0000.9651.000
2023-12-10T21:00:47.220048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
적용시작일자투여경로명규격명급여구분명개당산출단가
적용시작일자1.0001.0000.5130.9470.770
투여경로명1.0001.0001.0001.0001.000
규격명0.5131.0001.0000.8290.533
급여구분명0.9471.0000.8291.0000.965
개당산출단가0.7701.0000.5330.9651.000

Missing values

2023-12-10T21:00:43.613971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T21:00:43.742220image/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

적용시작일자투여경로명품목명약품코드규격명급여구분명개당산출단가단위
020170401내복신텍스치자엑스산6230030600.7급여56.0g
120130301내복정우치자엑스산6510025201.0삭제0.0g
220130401내복기화치자엑스산6528026201.0삭제0.0g
320160401내복한신치자엑스산6550049500.7급여56.0g
420160401내복한풍치자엑스산6581037800.7급여56.0g
520160401내복동의치자엑스산6612006401.0급여56.0g
620160401내복경방치자엑스산6613019200.7급여56.0g
720160401내복인스팜치자엑스산6624044400.7급여56.0g
820160401내복한중치자엑스산6627032300.7급여56.0g
920160401내복아이월드치자엑스산6696019301.4급여56.0g
적용시작일자투여경로명품목명약품코드규격명급여구분명개당산출단가단위
2120100101<NA>경진 치자엑스산H000590091.0삭제31.0g
2220100101<NA>보문 치자엑스산H000590121.0삭제31.0g
2320100101<NA>남창 치자엑스산H000590131.0삭제31.0g
2420100101<NA>신화 치자엑스산H000590141.0삭제31.0g
2520100101<NA>원광 치자엑스산H000590151.0삭제31.0g
2620100101<NA>삼익 치자엑스산H000590161.0삭제31.0g
2720100101<NA>태양 치자엑스산H000590171.0삭제31.0g
2820100101<NA>삼영 치자엑스산H000590211.0삭제31.0g
2920100101<NA>중경 치자엑스산H000590221.0삭제31.0g
3020100101<NA>한풍 치자엑스산H000590231.0삭제31.0g