Overview

Dataset statistics

Number of variables3
Number of observations31
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory907.0 B
Average record size in memory29.3 B

Variable types

Text2
Categorical1

Dataset

Description건강보험심사평가원 보건의료빅데이터개방시스템(opendata.hira.or.kr)에서 서비스하는 의료이용지도의 의료자원대비 인구정보
Author건강보험심사평가원
URLhttps://www.data.go.kr/data/15067455/fileData.do

Alerts

의료자원구분코드 has unique valuesUnique
의료자원구분코드명 has unique valuesUnique

Reproduction

Analysis started2023-12-12 15:59:20.627709
Analysis finished2023-12-12 15:59:20.935476
Duration0.31 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

의료자원구분코드
Text

UNIQUE 

Distinct31
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size380.0 B
2023-12-13T00:59:21.080926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters93
Distinct characters14
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 rowM12
2nd rowM13
3rd rowM00
4th rowM01
5th rowM02
ValueCountFrequency (%)
m12 1
 
3.2%
o02 1
 
3.2%
e02 1
 
3.2%
e01 1
 
3.2%
e00 1
 
3.2%
f03 1
 
3.2%
f02 1
 
3.2%
f01 1
 
3.2%
f00 1
 
3.2%
o08 1
 
3.2%
Other values (21) 21
67.7%
2023-12-13T00:59:21.499093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 31
33.3%
M 15
16.1%
1 10
 
10.8%
O 9
 
9.7%
2 5
 
5.4%
3 4
 
4.3%
F 4
 
4.3%
4 3
 
3.2%
E 3
 
3.2%
5 2
 
2.2%
Other values (4) 7
 
7.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 62
66.7%
Uppercase Letter 31
33.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 31
50.0%
1 10
 
16.1%
2 5
 
8.1%
3 4
 
6.5%
4 3
 
4.8%
5 2
 
3.2%
6 2
 
3.2%
7 2
 
3.2%
8 2
 
3.2%
9 1
 
1.6%
Uppercase Letter
ValueCountFrequency (%)
M 15
48.4%
O 9
29.0%
F 4
 
12.9%
E 3
 
9.7%

Most occurring scripts

ValueCountFrequency (%)
Common 62
66.7%
Latin 31
33.3%

Most frequent character per script

Common
ValueCountFrequency (%)
0 31
50.0%
1 10
 
16.1%
2 5
 
8.1%
3 4
 
6.5%
4 3
 
4.8%
5 2
 
3.2%
6 2
 
3.2%
7 2
 
3.2%
8 2
 
3.2%
9 1
 
1.6%
Latin
ValueCountFrequency (%)
M 15
48.4%
O 9
29.0%
F 4
 
12.9%
E 3
 
9.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 93
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 31
33.3%
M 15
16.1%
1 10
 
10.8%
O 9
 
9.7%
2 5
 
5.4%
3 4
 
4.3%
F 4
 
4.3%
4 3
 
3.2%
E 3
 
3.2%
5 2
 
2.2%
Other values (4) 7
 
7.5%

의료자원구분코드명
Text

UNIQUE 

Distinct31
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size380.0 B
2023-12-13T00:59:21.760058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length7
Mean length4.0322581
Min length2

Characters and Unicode

Total characters125
Distinct characters50
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

Unique31 ?
Unique (%)100.0%

Sample

1st row산부인과인력
2nd row요양병원인력
3rd row의사
4th row치과의사
5th row한의사
ValueCountFrequency (%)
산부인과인력 1
 
3.2%
병원 1
 
3.2%
pet 1
 
3.2%
mri 1
 
3.2%
ct 1
 
3.2%
요양병원 1
 
3.2%
분만실보유산부인과 1
 
3.2%
소아청소년과의원 1
 
3.2%
병상 1
 
3.2%
약국 1
 
3.2%
Other values (21) 21
67.7%
2023-12-13T00:59:22.183813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
사 13
 
10.4%
원 11
 
8.8%
병 9
 
7.2%
의 9
 
7.2%
과 7
 
5.6%
인 5
 
4.0%
치 5
 
4.0%
산 4
 
3.2%
한 3
 
2.4%
부 3
 
2.4%
Other values (40) 56
44.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 117
93.6%
Uppercase Letter 8
 
6.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 13
 
11.1%
원 11
 
9.4%
병 9
 
7.7%
의 9
 
7.7%
과 7
 
6.0%
인 5
 
4.3%
치 5
 
4.3%
산 4
 
3.4%
한 3
 
2.6%
부 3
 
2.6%
Other values (33) 48
41.0%
Uppercase Letter
ValueCountFrequency (%)
T 2
25.0%
M 1
12.5%
C 1
12.5%
R 1
12.5%
I 1
12.5%
P 1
12.5%
E 1
12.5%

Most occurring scripts

ValueCountFrequency (%)
Hangul 117
93.6%
Latin 8
 
6.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 13
 
11.1%
원 11
 
9.4%
병 9
 
7.7%
의 9
 
7.7%
과 7
 
6.0%
인 5
 
4.3%
치 5
 
4.3%
산 4
 
3.4%
한 3
 
2.6%
부 3
 
2.6%
Other values (33) 48
41.0%
Latin
ValueCountFrequency (%)
T 2
25.0%
M 1
12.5%
C 1
12.5%
R 1
12.5%
I 1
12.5%
P 1
12.5%
E 1
12.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 117
93.6%
ASCII 8
 
6.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
사 13
 
11.1%
원 11
 
9.4%
병 9
 
7.7%
의 9
 
7.7%
과 7
 
6.0%
인 5
 
4.3%
치 5
 
4.3%
산 4
 
3.4%
한 3
 
2.6%
부 3
 
2.6%
Other values (33) 48
41.0%
ASCII
ValueCountFrequency (%)
T 2
25.0%
M 1
12.5%
C 1
12.5%
R 1
12.5%
I 1
12.5%
P 1
12.5%
E 1
12.5%

인구대비기준수
Categorical

Distinct5
Distinct (%)16.1%
Missing0
Missing (%)0.0%
Memory size380.0 B
100000
13 
10000
10 
1000000
6 
10000000
 
1
1000
 
1

Length

Max length8
Median length7
Mean length5.8709677
Min length4

Unique

Unique2 ?
Unique (%)6.5%

Sample

1st row10000
2nd row10000
3rd row10000
4th row10000
5th row100000

Common Values

ValueCountFrequency (%)
100000 13
41.9%
10000 10
32.3%
1000000 6
19.4%
10000000 1
 
3.2%
1000 1
 
3.2%

Length

2023-12-13T00:59:22.346340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T00:59:22.485543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
100000 13
41.9%
10000 10
32.3%
1000000 6
19.4%
10000000 1
 
3.2%
1000 1
 
3.2%

Correlations

2023-12-13T00:59:22.591901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
의료자원구분코드의료자원구분코드명인구대비기준수
의료자원구분코드1.0001.0001.000
의료자원구분코드명1.0001.0001.000
인구대비기준수1.0001.0001.000

Missing values

2023-12-13T00:59:20.796573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T00:59:20.900913image/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

의료자원구분코드의료자원구분코드명인구대비기준수
0M12산부인과인력10000
1M13요양병원인력10000
2M00의사10000
3M01치과의사10000
4M02한의사100000
5M03간호사10000
6M04약사10000
7M05조산사100000
8M06간호조무사10000
9M07물리치료사10000
의료자원구분코드의료자원구분코드명인구대비기준수
21O07한의원100000
22O08약국100000
23F00병상1000
24F01소아청소년과의원100000
25F02분만실보유산부인과100000
26F03요양병원100000
27E00CT100000
28E01MRI1000000
29E02PET1000000
30M14의사계10000