Overview

Dataset statistics

Number of variables4
Number of observations108
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.5 KiB
Average record size in memory33.2 B

Variable types

Categorical1
Text3

Dataset

Description대구광역시 동구 관내 은행, 신협 등 금융기관 현황에 대한 데이터로 은행명, 지점명, 위치, 연락처 항목을 제공합니다.
Author대구광역시 동구
URLhttps://www.data.go.kr/data/3072350/fileData.do

Reproduction

Analysis started2024-03-14 13:18:51.408726
Analysis finished2024-03-14 13:18:52.023262
Duration0.61 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

은행명
Categorical

Distinct10
Distinct (%)9.3%
Missing0
Missing (%)0.0%
Memory size992.0 B
새마을금고
34 
농협은행
32 
신협
17 
대구은행
12 
국민은행
 
3
Other values (5)
10 

Length

Max length7
Median length6
Mean length4.0833333
Min length2

Unique

Unique1 ?
Unique (%)0.9%

Sample

1st rowKEB하나은행
2nd rowKEB하나은행
3rd row국민은행
4th row국민은행
5th row국민은행

Common Values

ValueCountFrequency (%)
새마을금고 34
31.5%
농협은행 32
29.6%
신협 17
15.7%
대구은행 12
 
11.1%
국민은행 3
 
2.8%
우리은행 3
 
2.8%
KEB하나은행 2
 
1.9%
기업은행 2
 
1.9%
신한은행 2
 
1.9%
한국수출입은행 1
 
0.9%

Length

2024-03-14T22:18:52.179560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T22:18:52.488160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
새마을금고 34
31.5%
농협은행 32
29.6%
신협 17
15.7%
대구은행 12
 
11.1%
국민은행 3
 
2.8%
우리은행 3
 
2.8%
keb하나은행 2
 
1.9%
기업은행 2
 
1.9%
신한은행 2
 
1.9%
한국수출입은행 1
 
0.9%

지점명
Text

Distinct102
Distinct (%)94.4%
Missing0
Missing (%)0.0%
Memory size992.0 B
2024-03-14T22:18:53.506259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length13
Mean length7.8055556
Min length2

Characters and Unicode

Total characters843
Distinct characters113
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

Unique98 ?
Unique (%)90.7%

Sample

1st row가스공사
2nd row대구혁신도시
3rd row신암동
4th row대구혁신도시
5th row대구이시아폴리스
ValueCountFrequency (%)
반야월농협 7
 
5.1%
동촌농협 6
 
4.4%
대구축산농협 5
 
3.6%
대구혁신도시 4
 
2.9%
팔공신용협동조합 4
 
2.9%
방촌신용협동조합 3
 
2.2%
율하지점 3
 
2.2%
동대구농협 3
 
2.2%
동부지점 2
 
1.5%
효천신용협동조합 2
 
1.5%
Other values (88) 98
71.5%
2024-03-14T22:18:54.757670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 57
 
6.8%
점 51
 
6.0%
신 45
 
5.3%
협 43
 
5.1%
) 35
 
4.2%
( 35
 
4.2%
지 35
 
4.2%
30
 
3.6%
구 28
 
3.3%
농 27
 
3.2%
Other values (103) 457
54.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 737
87.4%
Close Punctuation 35
 
4.2%
Open Punctuation 35
 
4.2%
Space Separator 30
 
3.6%
Decimal Number 6
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 57
 
7.7%
점 51
 
6.9%
신 45
 
6.1%
협 43
 
5.8%
지 35
 
4.7%
구 28
 
3.8%
농 27
 
3.7%
대 26
 
3.5%
촌 23
 
3.1%
용 20
 
2.7%
Other values (97) 382
51.8%
Decimal Number
ValueCountFrequency (%)
4 3
50.0%
1 2
33.3%
2 1
 
16.7%
Close Punctuation
ValueCountFrequency (%)
) 35
100.0%
Open Punctuation
ValueCountFrequency (%)
( 35
100.0%
Space Separator
ValueCountFrequency (%)
30
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 737
87.4%
Common 106
 
12.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 57
 
7.7%
점 51
 
6.9%
신 45
 
6.1%
협 43
 
5.8%
지 35
 
4.7%
구 28
 
3.8%
농 27
 
3.7%
대 26
 
3.5%
촌 23
 
3.1%
용 20
 
2.7%
Other values (97) 382
51.8%
Common
ValueCountFrequency (%)
) 35
33.0%
( 35
33.0%
30
28.3%
4 3
 
2.8%
1 2
 
1.9%
2 1
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 737
87.4%
ASCII 106
 
12.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 57
 
7.7%
점 51
 
6.9%
신 45
 
6.1%
협 43
 
5.8%
지 35
 
4.7%
구 28
 
3.8%
농 27
 
3.7%
대 26
 
3.5%
촌 23
 
3.1%
용 20
 
2.7%
Other values (97) 382
51.8%
ASCII
ValueCountFrequency (%)
) 35
33.0%
( 35
33.0%
30
28.3%
4 3
 
2.8%
1 2
 
1.9%
2 1
 
0.9%

주소
Text

Distinct105
Distinct (%)97.2%
Missing0
Missing (%)0.0%
Memory size992.0 B
2024-03-14T22:18:55.967339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length20
Mean length15.592593
Min length11

Characters and Unicode

Total characters1684
Distinct characters81
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

Unique102 ?
Unique (%)94.4%

Sample

1st row대구광역시 동구 첨단로 120 한국가스공사
2nd row대구광역시 동구 이노밸리로 309
3rd row대구광역시 동구 아양로 34
4th row대구광역시 동구 이노밸리로322
5th row대구광역시 동구 팔공로 249
ValueCountFrequency (%)
동구 108
25.0%
대구광역시 74
17.1%
대구 34
 
7.9%
아양로 11
 
2.5%
동촌로 9
 
2.1%
동부로 6
 
1.4%
이노밸리로 5
 
1.2%
팔공로 5
 
1.2%
반야월로 5
 
1.2%
효목로 5
 
1.2%
Other values (134) 170
39.4%
2024-03-14T22:18:57.450255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
326
19.4%
구 218
12.9%
동 140
 
8.3%
대 110
 
6.5%
로 108
 
6.4%
시 74
 
4.4%
역 74
 
4.4%
광 74
 
4.4%
1 61
 
3.6%
2 53
 
3.1%
Other values (71) 446
26.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1044
62.0%
Space Separator 326
 
19.4%
Decimal Number 308
 
18.3%
Dash Punctuation 6
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 218
20.9%
동 140
13.4%
대 110
10.5%
로 108
10.3%
시 74
 
7.1%
역 74
 
7.1%
광 74
 
7.1%
길 26
 
2.5%
양 16
 
1.5%
아 16
 
1.5%
Other values (59) 188
18.0%
Decimal Number
ValueCountFrequency (%)
1 61
19.8%
2 53
17.2%
3 33
10.7%
0 29
9.4%
6 28
9.1%
7 25
8.1%
4 22
 
7.1%
5 20
 
6.5%
9 20
 
6.5%
8 17
 
5.5%
Space Separator
ValueCountFrequency (%)
326
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1044
62.0%
Common 640
38.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 218
20.9%
동 140
13.4%
대 110
10.5%
로 108
10.3%
시 74
 
7.1%
역 74
 
7.1%
광 74
 
7.1%
길 26
 
2.5%
양 16
 
1.5%
아 16
 
1.5%
Other values (59) 188
18.0%
Common
ValueCountFrequency (%)
326
50.9%
1 61
 
9.5%
2 53
 
8.3%
3 33
 
5.2%
0 29
 
4.5%
6 28
 
4.4%
7 25
 
3.9%
4 22
 
3.4%
5 20
 
3.1%
9 20
 
3.1%
Other values (2) 23
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1044
62.0%
ASCII 640
38.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
326
50.9%
1 61
 
9.5%
2 53
 
8.3%
3 33
 
5.2%
0 29
 
4.5%
6 28
 
4.4%
7 25
 
3.9%
4 22
 
3.4%
5 20
 
3.1%
9 20
 
3.1%
Other values (2) 23
 
3.6%
Hangul
ValueCountFrequency (%)
구 218
20.9%
동 140
13.4%
대 110
10.5%
로 108
10.3%
시 74
 
7.1%
역 74
 
7.1%
광 74
 
7.1%
길 26
 
2.5%
양 16
 
1.5%
아 16
 
1.5%
Other values (59) 188
18.0%

전화번호
Text

Distinct104
Distinct (%)96.3%
Missing0
Missing (%)0.0%
Memory size992.0 B
2024-03-14T22:18:58.410529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters1296
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

Unique103 ?
Unique (%)95.4%

Sample

1st row053-961-4080
2nd row053-621-1111
3rd row053-952-1351
4th row053-963-6515
5th row053-982-6351
ValueCountFrequency (%)
053-000-0000 5
 
4.6%
053-961-4080 1
 
0.9%
053-752-5757 1
 
0.9%
053-424-0261 1
 
0.9%
053-959-5100 1
 
0.9%
053-958-6012 1
 
0.9%
053-955-2700 1
 
0.9%
053-957-2004 1
 
0.9%
053-957-2000 1
 
0.9%
053-954-7241 1
 
0.9%
Other values (94) 94
87.0%
2024-03-14T22:18:59.446186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 236
18.2%
- 216
16.7%
5 181
14.0%
3 158
12.2%
9 109
8.4%
1 83
 
6.4%
8 76
 
5.9%
2 69
 
5.3%
6 61
 
4.7%
4 60
 
4.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1080
83.3%
Dash Punctuation 216
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 236
21.9%
5 181
16.8%
3 158
14.6%
9 109
10.1%
1 83
 
7.7%
8 76
 
7.0%
2 69
 
6.4%
6 61
 
5.6%
4 60
 
5.6%
7 47
 
4.4%
Dash Punctuation
ValueCountFrequency (%)
- 216
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1296
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 236
18.2%
- 216
16.7%
5 181
14.0%
3 158
12.2%
9 109
8.4%
1 83
 
6.4%
8 76
 
5.9%
2 69
 
5.3%
6 61
 
4.7%
4 60
 
4.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1296
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 236
18.2%
- 216
16.7%
5 181
14.0%
3 158
12.2%
9 109
8.4%
1 83
 
6.4%
8 76
 
5.9%
2 69
 
5.3%
6 61
 
4.7%
4 60
 
4.6%

Missing values

2024-03-14T22:18:51.742582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T22:18:51.964848image/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

은행명지점명주소전화번호
0KEB하나은행가스공사대구광역시 동구 첨단로 120 한국가스공사053-961-4080
1KEB하나은행대구혁신도시대구광역시 동구 이노밸리로 309053-621-1111
2국민은행신암동대구광역시 동구 아양로 34053-952-1351
3국민은행대구혁신도시대구광역시 동구 이노밸리로322053-963-6515
4국민은행대구이시아폴리스대구광역시 동구 팔공로 249053-982-6351
5기업은행대구한국부동산원대구광역시 동구 이노밸리로 291053-980-0100
6기업은행한국산업단지공단(출)대구광역시 동구 첨단로 39053-960-3901
7농협은행대구혁신도시대구광역시 동구 이노밸리로 321053-965-9131
8농협은행동촌지점대구광역시 동구 해동로 231053-982-3012
9농협은행신천역대구광역시 동구 동부로 17053-422-7812
은행명지점명주소전화번호
98새마을금고반야월(신율)대구 동구 율하동로 48053-984-0838
99새마을금고반야월(율하)대구 동구 반야월로 106053-962-2956
100새마을금고반야월(송정)대구 동구 안심로73길 22053-962-5294
101새마을금고공산(본점)대구 동구 팔공산로 1676053-983-0012
102새마을금고불로봉무(본점)대구 동구 팔공로 127053-983-6037
103새마을금고불로봉무(이시아폴리스)대구 동구 팔공로51길 3053-215-7770
104새마을금고아양(본점)대구 동구 아양로 191053-958-4482
105새마을금고아양(동서)대구 동구 아양로37길 68053-952-5100
106새마을금고팔공(본점)대구 동구 팔공로101길 63053-759-8080
107새마을금고팔공(팔공)대구 동구 동화천로 372053-743-8080