Overview

Dataset statistics

Number of variables3
Number of observations215
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.2 KiB
Average record size in memory24.6 B

Variable types

Text3

Dataset

Description보건의료인국가시험 중 의사, 치과의사, 한의사 전환성적을 발급한 병원에 대한 정보(병원명, 주소, 우편번호)를 제공합니다.
URLhttps://www.data.go.kr/data/3068132/fileData.do

Reproduction

Analysis started2023-12-12 07:56:37.167622
Analysis finished2023-12-12 07:56:37.593909
Duration0.43 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

병원명
Text

Distinct201
Distinct (%)93.5%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
2023-12-12T16:56:37.819130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length16
Mean length8.4511628
Min length3

Characters and Unicode

Total characters1817
Distinct characters174
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique187 ?
Unique (%)87.0%

Sample

1st row(재)일산자생한방병원
2nd row(재)자생의료재단 광주자생한방병원
3rd row(재)자생의료재단 광화문자생한방병원
4th row(재)자생의료재단 대구자생한방병원
5th row(재)자생의료재단 대전자생한방병원
ValueCountFrequency (%)
재)자생의료재단 12
 
4.2%
한방병원 9
 
3.1%
병원 8
 
2.8%
치과대학 4
 
1.4%
치과병원 3
 
1.0%
의료원 3
 
1.0%
부속 3
 
1.0%
원광대 3
 
1.0%
대전대부속 3
 
1.0%
국립중앙의료원 2
 
0.7%
Other values (221) 239
82.7%
2023-12-12T16:56:38.340848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
원 234
 
12.9%
병 205
 
11.3%
대 131
 
7.2%
한 79
 
4.3%
75
 
4.1%
방 62
 
3.4%
학 55
 
3.0%
교 49
 
2.7%
의 35
 
1.9%
자 31
 
1.7%
Other values (164) 861
47.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1714
94.3%
Space Separator 75
 
4.1%
Close Punctuation 14
 
0.8%
Open Punctuation 14
 
0.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
원 234
 
13.7%
병 205
 
12.0%
대 131
 
7.6%
한 79
 
4.6%
방 62
 
3.6%
학 55
 
3.2%
교 49
 
2.9%
의 35
 
2.0%
자 31
 
1.8%
생 31
 
1.8%
Other values (161) 802
46.8%
Space Separator
ValueCountFrequency (%)
75
100.0%
Close Punctuation
ValueCountFrequency (%)
) 14
100.0%
Open Punctuation
ValueCountFrequency (%)
( 14
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1714
94.3%
Common 103
 
5.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
원 234
 
13.7%
병 205
 
12.0%
대 131
 
7.6%
한 79
 
4.6%
방 62
 
3.6%
학 55
 
3.2%
교 49
 
2.9%
의 35
 
2.0%
자 31
 
1.8%
생 31
 
1.8%
Other values (161) 802
46.8%
Common
ValueCountFrequency (%)
75
72.8%
) 14
 
13.6%
( 14
 
13.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1714
94.3%
ASCII 103
 
5.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
원 234
 
13.7%
병 205
 
12.0%
대 131
 
7.6%
한 79
 
4.6%
방 62
 
3.6%
학 55
 
3.2%
교 49
 
2.9%
의 35
 
2.0%
자 31
 
1.8%
생 31
 
1.8%
Other values (161) 802
46.8%
ASCII
ValueCountFrequency (%)
75
72.8%
) 14
 
13.6%
( 14
 
13.6%

주소
Text

Distinct203
Distinct (%)94.4%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
2023-12-12T16:56:38.709076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length35
Median length29
Mean length17.790698
Min length11

Characters and Unicode

Total characters3825
Distinct characters230
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique194 ?
Unique (%)90.2%

Sample

1st row경기 고양시 일산동구 중앙로 1130
2nd row광주 서구 운천로 207
3rd row서울 중구 순화동 에이스타워빌딩 1층
4th row대구 중구 달구벌대로 2033
5th row대전 서구 문정로48번길 58
ValueCountFrequency (%)
서울 57
 
6.0%
경기 32
 
3.4%
중구 19
 
2.0%
부산 14
 
1.5%
서구 13
 
1.4%
남구 10
 
1.1%
서울특별시 10
 
1.1%
대구 9
 
0.9%
광주 9
 
0.9%
대전 9
 
0.9%
Other values (511) 767
80.8%
2023-12-12T16:56:39.188225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
734
 
19.2%
구 206
 
5.4%
동 170
 
4.4%
1 160
 
4.2%
2 108
 
2.8%
로 107
 
2.8%
시 106
 
2.8%
서 100
 
2.6%
3 77
 
2.0%
산 75
 
2.0%
Other values (220) 1982
51.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2251
58.8%
Decimal Number 737
 
19.3%
Space Separator 734
 
19.2%
Dash Punctuation 67
 
1.8%
Close Punctuation 15
 
0.4%
Open Punctuation 15
 
0.4%
Other Punctuation 2
 
0.1%
Math Symbol 2
 
0.1%
Uppercase Letter 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 206
 
9.2%
동 170
 
7.6%
로 107
 
4.8%
시 106
 
4.7%
서 100
 
4.4%
산 75
 
3.3%
울 74
 
3.3%
대 71
 
3.2%
경 54
 
2.4%
남 53
 
2.4%
Other values (202) 1235
54.9%
Decimal Number
ValueCountFrequency (%)
1 160
21.7%
2 108
14.7%
3 77
10.4%
5 72
9.8%
0 65
8.8%
7 55
 
7.5%
4 54
 
7.3%
6 52
 
7.1%
9 48
 
6.5%
8 46
 
6.2%
Uppercase Letter
ValueCountFrequency (%)
S 1
50.0%
H 1
50.0%
Space Separator
ValueCountFrequency (%)
734
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 67
100.0%
Close Punctuation
ValueCountFrequency (%)
) 15
100.0%
Open Punctuation
ValueCountFrequency (%)
( 15
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2251
58.8%
Common 1572
41.1%
Latin 2
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 206
 
9.2%
동 170
 
7.6%
로 107
 
4.8%
시 106
 
4.7%
서 100
 
4.4%
산 75
 
3.3%
울 74
 
3.3%
대 71
 
3.2%
경 54
 
2.4%
남 53
 
2.4%
Other values (202) 1235
54.9%
Common
ValueCountFrequency (%)
734
46.7%
1 160
 
10.2%
2 108
 
6.9%
3 77
 
4.9%
5 72
 
4.6%
- 67
 
4.3%
0 65
 
4.1%
7 55
 
3.5%
4 54
 
3.4%
6 52
 
3.3%
Other values (6) 128
 
8.1%
Latin
ValueCountFrequency (%)
S 1
50.0%
H 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2251
58.8%
ASCII 1574
41.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
734
46.6%
1 160
 
10.2%
2 108
 
6.9%
3 77
 
4.9%
5 72
 
4.6%
- 67
 
4.3%
0 65
 
4.1%
7 55
 
3.5%
4 54
 
3.4%
6 52
 
3.3%
Other values (8) 130
 
8.3%
Hangul
ValueCountFrequency (%)
구 206
 
9.2%
동 170
 
7.6%
로 107
 
4.8%
시 106
 
4.7%
서 100
 
4.4%
산 75
 
3.3%
울 74
 
3.3%
대 71
 
3.2%
경 54
 
2.4%
남 53
 
2.4%
Other values (202) 1235
54.9%

우편번호
Text

Distinct188
Distinct (%)87.4%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
2023-12-12T16:56:39.503947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length7
Mean length7
Min length7

Characters and Unicode

Total characters1505
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique167 ?
Unique (%)77.7%

Sample

1st row410-350
2nd row502-827
3rd row100-712
4th row700-814
5th row302-857
ValueCountFrequency (%)
150-037 7
 
3.3%
626-815 3
 
1.4%
405-220 2
 
0.9%
435-040 2
 
0.9%
614-710 2
 
0.9%
132-030 2
 
0.9%
410-820 2
 
0.9%
612-030 2
 
0.9%
501-840 2
 
0.9%
135-090 2
 
0.9%
Other values (178) 189
87.9%
2023-12-12T16:56:39.935998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 348
23.1%
- 215
14.3%
1 174
11.6%
3 148
9.8%
4 114
 
7.6%
2 107
 
7.1%
5 100
 
6.6%
7 89
 
5.9%
8 86
 
5.7%
6 80
 
5.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1290
85.7%
Dash Punctuation 215
 
14.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 348
27.0%
1 174
13.5%
3 148
11.5%
4 114
 
8.8%
2 107
 
8.3%
5 100
 
7.8%
7 89
 
6.9%
8 86
 
6.7%
6 80
 
6.2%
9 44
 
3.4%
Dash Punctuation
ValueCountFrequency (%)
- 215
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1505
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 348
23.1%
- 215
14.3%
1 174
11.6%
3 148
9.8%
4 114
 
7.6%
2 107
 
7.1%
5 100
 
6.6%
7 89
 
5.9%
8 86
 
5.7%
6 80
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1505
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 348
23.1%
- 215
14.3%
1 174
11.6%
3 148
9.8%
4 114
 
7.6%
2 107
 
7.1%
5 100
 
6.6%
7 89
 
5.9%
8 86
 
5.7%
6 80
 
5.3%

Missing values

2023-12-12T16:56:37.464383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T16:56:37.556522image/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

병원명주소우편번호
0(재)일산자생한방병원경기 고양시 일산동구 중앙로 1130410-350
1(재)자생의료재단 광주자생한방병원광주 서구 운천로 207502-827
2(재)자생의료재단 광화문자생한방병원서울 중구 순화동 에이스타워빌딩 1층100-712
3(재)자생의료재단 대구자생한방병원대구 중구 달구벌대로 2033700-814
4(재)자생의료재단 대전자생한방병원대전 서구 문정로48번길 58302-857
5(재)자생의료재단 부천자생한방병원경기 부천시 원미구 상동 414420-030
6(재)자생의료재단 안산자생한방병원경기 안산시 단원구 광덕대로 241425-020
7(재)자생의료재단 울산자생한방병원울산 남구 신정동 662-9680-010
8(재)자생의료재단 인천자생한방병원인천 남동구 구월동 1464 인천자생한방병원405-220
9(재)자생의료재단 잠실자생한방병원서울 송파구 오금로 81(방이동, 송파빌딩 4층)138-050
병원명주소우편번호
205한림대동탄성심병원서울 영등포구 버드나루로 55150-037
206한림대성심병원서울 영등포구 버드나루로 55150-037
207한림대성심병원서울 영등포구 영등포동7가 94-17150-037
208한림대춘천성심병원서울 영등포구 버드나루로 55150-037
209한림병원인천 계양구 장제로 722407-060
210한양대학교병원서울 성동구 사근동 110133-817
211한양대학교병원서울특별시 성동구 왕십리로 222-1004-763
212한전병원서울 도봉구 쌍문동 388-1132-030
213홍익병원서울 양천구 목동로 225158-738
214효산의료재단 지샘병원경기도 군포시 군포로 591015-839