Overview

Dataset statistics

Number of variables5
Number of observations153
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.1 KiB
Average record size in memory40.9 B

Variable types

Categorical2
Text3

Dataset

Description대한적십자사 전국 헌혈의 집 정보 입니다. 관할 혈액원, 헌혈의 집 명, 주소, 전화번호 등의 항목을 제공합니다. 대한적십자사
URLhttps://www.data.go.kr/data/15050729/fileData.do

Alerts

헌혈의 집 has unique valuesUnique
주소지 has unique valuesUnique
전화번호 has unique valuesUnique

Reproduction

Analysis started2023-12-12 02:47:32.630888
Analysis finished2023-12-12 02:47:33.388473
Duration0.76 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

혈액원
Categorical

Distinct15
Distinct (%)9.8%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
서울중앙
16 
서울동부
15 
부산
14 
서울남부
13 
경기
13 
Other values (10)
82 

Length

Max length6
Median length4
Mean length3.1503268
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
서울중앙 16
10.5%
서울동부 15
9.8%
부산 14
9.2%
서울남부 13
8.5%
경기 13
8.5%
대구경북 13
8.5%
인천 11
 
7.2%
대전세종충남 11
 
7.2%
광주전남 9
 
5.9%
전북 8
 
5.2%
Other values (5) 30
19.6%

Length

2023-12-12T11:47:33.530781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
서울중앙 16
10.5%
서울동부 15
9.8%
부산 14
9.2%
서울남부 13
8.5%
경기 13
8.5%
대구경북 13
8.5%
인천 11
 
7.2%
대전세종충남 11
 
7.2%
광주전남 9
 
5.9%
전북 8
 
5.2%
Other values (5) 30
19.6%

헌혈의 집
Text

UNIQUE 

Distinct153
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2023-12-12T11:47:33.829346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length5.3071895
Min length4

Characters and Unicode

Total characters812
Distinct characters154
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique153 ?
Unique (%)100.0%

Sample

1st row중앙센터(원내)
2nd row서울역센터
3rd row대화역센터
4th row신촌센터
5th row연신내센터
ValueCountFrequency (%)
중앙센터(원내 1
 
0.7%
아산센터 1
 
0.7%
빛고을센터(원내 1
 
0.7%
으능정이센터 1
 
0.7%
둔산센터 1
 
0.7%
대전복합터미널센터 1
 
0.7%
세종센터 1
 
0.7%
노은역센터 1
 
0.7%
천안시청센터 1
 
0.7%
전북대센터 1
 
0.7%
Other values (143) 143
93.5%
2023-12-12T11:47:34.306085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
터 157
19.3%
센 153
18.8%
대 34
 
4.2%
원 23
 
2.8%
역 19
 
2.3%
내 17
 
2.1%
( 15
 
1.8%
) 15
 
1.8%
산 15
 
1.8%
동 15
 
1.8%
Other values (144) 349
43.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 776
95.6%
Open Punctuation 15
 
1.8%
Close Punctuation 15
 
1.8%
Decimal Number 5
 
0.6%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
터 157
20.2%
센 153
19.7%
대 34
 
4.4%
원 23
 
3.0%
역 19
 
2.4%
내 17
 
2.2%
산 15
 
1.9%
동 15
 
1.9%
로 11
 
1.4%
주 9
 
1.2%
Other values (139) 323
41.6%
Decimal Number
ValueCountFrequency (%)
2 4
80.0%
8 1
 
20.0%
Open Punctuation
ValueCountFrequency (%)
( 15
100.0%
Close Punctuation
ValueCountFrequency (%)
) 15
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 776
95.6%
Common 36
 
4.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
터 157
20.2%
센 153
19.7%
대 34
 
4.4%
원 23
 
3.0%
역 19
 
2.4%
내 17
 
2.2%
산 15
 
1.9%
동 15
 
1.9%
로 11
 
1.4%
주 9
 
1.2%
Other values (139) 323
41.6%
Common
ValueCountFrequency (%)
( 15
41.7%
) 15
41.7%
2 4
 
11.1%
8 1
 
2.8%
. 1
 
2.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 776
95.6%
ASCII 36
 
4.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
터 157
20.2%
센 153
19.7%
대 34
 
4.4%
원 23
 
3.0%
역 19
 
2.4%
내 17
 
2.2%
산 15
 
1.9%
동 15
 
1.9%
로 11
 
1.4%
주 9
 
1.2%
Other values (139) 323
41.6%
ASCII
ValueCountFrequency (%)
( 15
41.7%
) 15
41.7%
2 4
 
11.1%
8 1
 
2.8%
. 1
 
2.8%

구분
Categorical

Distinct5
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
국고
93 
자체
30 
원내
15 
자체대학
 
9
국고대학
 
6

Length

Max length4
Median length2
Mean length2.1960784
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row원내
2nd row자체
3rd row국고
4th row국고
5th row국고

Common Values

ValueCountFrequency (%)
국고 93
60.8%
자체 30
 
19.6%
원내 15
 
9.8%
자체대학 9
 
5.9%
국고대학 6
 
3.9%

Length

2023-12-12T11:47:34.492014image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T11:47:34.641041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
국고 93
60.8%
자체 30
 
19.6%
원내 15
 
9.8%
자체대학 9
 
5.9%
국고대학 6
 
3.9%

주소지
Text

UNIQUE 

Distinct153
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2023-12-12T11:47:34.977369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length46
Median length33
Mean length23.542484
Min length11

Characters and Unicode

Total characters3602
Distinct characters279
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique153 ?
Unique (%)100.0%

Sample

1st row서울 강서구 공항대로 591 대한적십자사 서울중앙혈액원 3층
2nd row서울 중구 한강대로 405 서울역사 지하1층 B05호
3rd row경기 고양시 일산서구 중앙로1573, 킨텍스프라자 402호
4th row서울 서대문구 신촌로 99 엘리트 빌딩 2층
5th row서울 은평구 통일로 855-8, 연신내진원와이타운 4층 401호
ValueCountFrequency (%)
서울 36
 
4.1%
2층 31
 
3.5%
경기 26
 
2.9%
3층 15
 
1.7%
4층 15
 
1.7%
부산 14
 
1.6%
중구 10
 
1.1%
대구 9
 
1.0%
전북 8
 
0.9%
경남 7
 
0.8%
Other values (534) 713
80.7%
2023-12-12T11:47:35.635803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
735
 
20.4%
로 144
 
4.0%
구 134
 
3.7%
2 131
 
3.6%
1 107
 
3.0%
, 93
 
2.6%
층 89
 
2.5%
3 83
 
2.3%
0 79
 
2.2%
대 76
 
2.1%
Other values (269) 1931
53.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2063
57.3%
Space Separator 735
 
20.4%
Decimal Number 671
 
18.6%
Other Punctuation 94
 
2.6%
Dash Punctuation 21
 
0.6%
Uppercase Letter 10
 
0.3%
Open Punctuation 4
 
0.1%
Close Punctuation 4
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 144
 
7.0%
구 134
 
6.5%
층 89
 
4.3%
대 76
 
3.7%
시 74
 
3.6%
서 63
 
3.1%
산 54
 
2.6%
경 47
 
2.3%
울 46
 
2.2%
호 40
 
1.9%
Other values (246) 1296
62.8%
Decimal Number
ValueCountFrequency (%)
2 131
19.5%
1 107
15.9%
3 83
12.4%
0 79
11.8%
5 69
10.3%
4 53
7.9%
6 42
 
6.3%
8 37
 
5.5%
7 36
 
5.4%
9 34
 
5.1%
Uppercase Letter
ValueCountFrequency (%)
B 3
30.0%
C 2
20.0%
A 1
 
10.0%
L 1
 
10.0%
R 1
 
10.0%
D 1
 
10.0%
S 1
 
10.0%
Other Punctuation
ValueCountFrequency (%)
, 93
98.9%
. 1
 
1.1%
Space Separator
ValueCountFrequency (%)
735
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 21
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2063
57.3%
Common 1529
42.4%
Latin 10
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 144
 
7.0%
구 134
 
6.5%
층 89
 
4.3%
대 76
 
3.7%
시 74
 
3.6%
서 63
 
3.1%
산 54
 
2.6%
경 47
 
2.3%
울 46
 
2.2%
호 40
 
1.9%
Other values (246) 1296
62.8%
Common
ValueCountFrequency (%)
735
48.1%
2 131
 
8.6%
1 107
 
7.0%
, 93
 
6.1%
3 83
 
5.4%
0 79
 
5.2%
5 69
 
4.5%
4 53
 
3.5%
6 42
 
2.7%
8 37
 
2.4%
Other values (6) 100
 
6.5%
Latin
ValueCountFrequency (%)
B 3
30.0%
C 2
20.0%
A 1
 
10.0%
L 1
 
10.0%
R 1
 
10.0%
D 1
 
10.0%
S 1
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2063
57.3%
ASCII 1539
42.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
735
47.8%
2 131
 
8.5%
1 107
 
7.0%
, 93
 
6.0%
3 83
 
5.4%
0 79
 
5.1%
5 69
 
4.5%
4 53
 
3.4%
6 42
 
2.7%
8 37
 
2.4%
Other values (13) 110
 
7.1%
Hangul
ValueCountFrequency (%)
로 144
 
7.0%
구 134
 
6.5%
층 89
 
4.3%
대 76
 
3.7%
시 74
 
3.6%
서 63
 
3.1%
산 54
 
2.6%
경 47
 
2.3%
울 46
 
2.2%
호 40
 
1.9%
Other values (246) 1296
62.8%

전화번호
Text

UNIQUE 

Distinct153
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2023-12-12T11:47:35.934813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length11.816993
Min length11

Characters and Unicode

Total characters1808
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

Unique153 ?
Unique (%)100.0%

Sample

1st row02-6711-0184
2nd row02-752-9020
3rd row031-919-4930
4th row02-312-1247
5th row02-353-7750
ValueCountFrequency (%)
02-6711-0184 1
 
0.7%
041-534-2166 1
 
0.7%
062-600-0600 1
 
0.7%
042-252-2166 1
 
0.7%
042-486-2166 1
 
0.7%
042-631-2166 1
 
0.7%
044-865-2166 1
 
0.7%
042-826-2166 1
 
0.7%
041-523-2166 1
 
0.7%
063-275-9907 1
 
0.7%
Other values (143) 143
93.5%
2023-12-12T11:47:36.412266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 306
16.9%
0 258
14.3%
2 213
11.8%
5 199
11.0%
3 163
9.0%
1 155
8.6%
6 144
8.0%
4 114
 
6.3%
7 92
 
5.1%
8 85
 
4.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1502
83.1%
Dash Punctuation 306
 
16.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 258
17.2%
2 213
14.2%
5 199
13.2%
3 163
10.9%
1 155
10.3%
6 144
9.6%
4 114
7.6%
7 92
 
6.1%
8 85
 
5.7%
9 79
 
5.3%
Dash Punctuation
ValueCountFrequency (%)
- 306
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1808
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 306
16.9%
0 258
14.3%
2 213
11.8%
5 199
11.0%
3 163
9.0%
1 155
8.6%
6 144
8.0%
4 114
 
6.3%
7 92
 
5.1%
8 85
 
4.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1808
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 306
16.9%
0 258
14.3%
2 213
11.8%
5 199
11.0%
3 163
9.0%
1 155
8.6%
6 144
8.0%
4 114
 
6.3%
7 92
 
5.1%
8 85
 
4.7%

Correlations

2023-12-12T11:47:36.523020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
혈액원구분
혈액원1.0000.000
구분0.0001.000
2023-12-12T11:47:36.607514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분혈액원
구분1.0000.000
혈액원0.0001.000
2023-12-12T11:47:36.702832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
혈액원구분
혈액원1.0000.000
구분0.0001.000

Missing values

2023-12-12T11:47:32.918488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T11:47:33.344782image/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

혈액원헌혈의 집구분주소지전화번호
0서울중앙중앙센터(원내)원내서울 강서구 공항대로 591 대한적십자사 서울중앙혈액원 3층02-6711-0184
1서울중앙서울역센터자체서울 중구 한강대로 405 서울역사 지하1층 B05호02-752-9020
2서울중앙대화역센터국고경기 고양시 일산서구 중앙로1573, 킨텍스프라자 402호031-919-4930
3서울중앙신촌센터국고서울 서대문구 신촌로 99 엘리트 빌딩 2층02-312-1247
4서울중앙연신내센터국고서울 은평구 통일로 855-8, 연신내진원와이타운 4층 401호02-353-7750
5서울중앙홍대센터국고서울 마포구 양화로 152, 대화빌딩 6층02-323-5420
6서울중앙구로디지털단지역센터국고서울 관악구 시흥대로 576, 2층02-869-9415
7서울중앙서울대역센터국고서울 관악구 관악로 152, 2층02-873-4364
8서울중앙대방역센터자체서울 영등포구 여의대방로 30002-825-6560
9서울중앙신도림테크노마트센터자체서울 구로구 새말로 97, 신도림테크노마트 지하광장02-861-0801
혈액원헌혈의 집구분주소지전화번호
143제주한라센터국고제주 제주시 중앙로 222, 3층064-757-8101
144제주서귀포센터자체제주 서귀포시 중앙로 101번길 11, 2층064-763-8101
145울산함월센터(원내)원내울산 중구 함월10길 25052-210-8553
146울산성남동센터국고울산 중구 젊음의거리 30-5, 다남빌딩 2층052-243-8799
147울산울산대센터자체대학울산 남구 대학로 93, 종합서비스센터 105호052-224-3969
148울산울산과학대센터자체대학울산 동구 봉수로 101, 제3대학관 2층052-236-3459
149울산양산센터국고경남 양산시 양산역2길 7, 대상골드타워 3층055-366-5201
150울산경주센터자체경북 경주시 원효로 122, 1층054-777-7521
151울산공업탑센터국고울산 남구 삼산로 17, 4층052-260-7918
152울산울산삼산동센터국고울산 남구 삼산로 275, 킴스메디컬빌딩 2층052-266-5225