Overview

Dataset statistics

Number of variables5
Number of observations286
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory11.3 KiB
Average record size in memory40.4 B

Variable types

Categorical1
Text4

Dataset

Description예금보험공사에서 관리하는 부보금융회사 종합정보 중 예금보험제도에 가입되어 예금보험적용을 받는 금융회사 목록과 해당 금융회사의 주소 및 연락처 등의 기본 정보를 제공합니다.
Author예금보험공사
URLhttps://www.data.go.kr/data/15083240/fileData.do

Alerts

금융회사명 has unique valuesUnique
주소 has unique valuesUnique
사이트(URL) has unique valuesUnique

Reproduction

Analysis started2024-03-14 19:12:59.864382
Analysis finished2024-03-14 19:13:00.972011
Duration1.11 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

금융권
Categorical

Distinct7
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
금융투자
107 
저축은행
80 
은행
53 
생명보험
22 
손해보험
22 
Other values (2)
 
2

Length

Max length5
Median length4
Mean length3.6258741
Min length2

Unique

Unique2 ?
Unique (%)0.7%

Sample

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

Common Values

ValueCountFrequency (%)
금융투자 107
37.4%
저축은행 80
28.0%
은행 53
18.5%
생명보험 22
 
7.7%
손해보험 22
 
7.7%
금융투자 1
 
0.3%
종금 1
 
0.3%

Length

2024-03-15T04:13:01.173495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T04:13:01.467276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
금융투자 108
37.8%
저축은행 80
28.0%
은행 53
18.5%
생명보험 22
 
7.7%
손해보험 22
 
7.7%
종금 1
 
0.3%

금융회사명
Text

UNIQUE 

Distinct286
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
2024-03-15T04:13:02.312891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length23
Mean length8.1538462
Min length4

Characters and Unicode

Total characters2332
Distinct characters258
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique286 ?
Unique (%)100.0%

Sample

1st rowBNP파리바은행
2nd rowDBS은행
3rd rowOCBC
4th row경남은행
5th row광주은행
ValueCountFrequency (%)
주식회사 10
 
3.1%
서울지점 8
 
2.5%
한국지점 5
 
1.6%
농협손해보험 1
 
0.3%
서울보증보험㈜ 1
 
0.3%
삼성화재해상보험주식회사 1
 
0.3%
신한ez손해보험주식회사 1
 
0.3%
미쓰이스미토모해상화재보험㈜ 1
 
0.3%
㈜케이비손해보험 1
 
0.3%
롯데손해보험주식회사 1
 
0.3%
Other values (292) 292
90.7%
2024-03-15T04:13:03.722429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
은 129
 
5.5%
행 128
 
5.5%
축 80
 
3.4%
저 80
 
3.4%
㈜ 66
 
2.8%
자 65
 
2.8%
이 61
 
2.6%
증 59
 
2.5%
권 59
 
2.5%
스 53
 
2.3%
Other values (248) 1552
66.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2140
91.8%
Uppercase Letter 69
 
3.0%
Other Symbol 67
 
2.9%
Space Separator 50
 
2.1%
Close Punctuation 3
 
0.1%
Open Punctuation 3
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
은 129
 
6.0%
행 128
 
6.0%
축 80
 
3.7%
저 80
 
3.7%
자 65
 
3.0%
이 61
 
2.9%
증 59
 
2.8%
권 59
 
2.8%
스 53
 
2.5%
산 47
 
2.2%
Other values (226) 1379
64.4%
Uppercase Letter
ValueCountFrequency (%)
B 16
23.2%
D 8
11.6%
K 6
 
8.7%
N 6
 
8.7%
I 5
 
7.2%
H 5
 
7.2%
A 4
 
5.8%
S 4
 
5.8%
G 3
 
4.3%
C 3
 
4.3%
Other values (7) 9
13.0%
Other Symbol
ValueCountFrequency (%)
㈜ 66
98.5%
㈖ 1
 
1.5%
Space Separator
ValueCountFrequency (%)
50
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2207
94.6%
Latin 69
 
3.0%
Common 56
 
2.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
은 129
 
5.8%
행 128
 
5.8%
축 80
 
3.6%
저 80
 
3.6%
㈜ 66
 
3.0%
자 65
 
2.9%
이 61
 
2.8%
증 59
 
2.7%
권 59
 
2.7%
스 53
 
2.4%
Other values (228) 1427
64.7%
Latin
ValueCountFrequency (%)
B 16
23.2%
D 8
11.6%
K 6
 
8.7%
N 6
 
8.7%
I 5
 
7.2%
H 5
 
7.2%
A 4
 
5.8%
S 4
 
5.8%
G 3
 
4.3%
C 3
 
4.3%
Other values (7) 9
13.0%
Common
ValueCountFrequency (%)
50
89.3%
) 3
 
5.4%
( 3
 
5.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2140
91.8%
ASCII 125
 
5.4%
None 67
 
2.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
은 129
 
6.0%
행 128
 
6.0%
축 80
 
3.7%
저 80
 
3.7%
자 65
 
3.0%
이 61
 
2.9%
증 59
 
2.8%
권 59
 
2.8%
스 53
 
2.5%
산 47
 
2.2%
Other values (226) 1379
64.4%
None
ValueCountFrequency (%)
㈜ 66
98.5%
㈖ 1
 
1.5%
ASCII
ValueCountFrequency (%)
50
40.0%
B 16
 
12.8%
D 8
 
6.4%
K 6
 
4.8%
N 6
 
4.8%
I 5
 
4.0%
H 5
 
4.0%
A 4
 
3.2%
S 4
 
3.2%
G 3
 
2.4%
Other values (10) 18
 
14.4%

주소
Text

UNIQUE 

Distinct286
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
2024-03-15T04:13:05.089833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length52
Median length34
Mean length25.552448
Min length13

Characters and Unicode

Total characters7308
Distinct characters276
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique286 ?
Unique (%)100.0%

Sample

1st row서울특별시 중구 퇴계로 100 스테이트타워 남산 24-25층
2nd row서울특별시 중구 세종대로 136 서울파이낸스센터 18층
3rd row서울특별시 중구 세종대로 136 서울파이낸스센터 25층
4th row경상남도 창원시 마산회원구 3·15대로 642
5th row광주시 동구 제봉로 225
ValueCountFrequency (%)
서울특별시 127
 
8.1%
영등포구 78
 
5.0%
서울시 61
 
3.9%
중구 59
 
3.7%
종로구 35
 
2.2%
서울 30
 
1.9%
강남구 28
 
1.8%
국제금융로 25
 
1.6%
세종대로 17
 
1.1%
10 15
 
1.0%
Other values (603) 1100
69.8%
2024-03-15T04:13:06.923108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1297
 
17.7%
로 333
 
4.6%
구 280
 
3.8%
서 263
 
3.6%
1 253
 
3.5%
시 239
 
3.3%
울 234
 
3.2%
2 173
 
2.4%
층 141
 
1.9%
3 134
 
1.8%
Other values (266) 3961
54.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4539
62.1%
Space Separator 1297
 
17.7%
Decimal Number 1080
 
14.8%
Uppercase Letter 120
 
1.6%
Open Punctuation 98
 
1.3%
Close Punctuation 98
 
1.3%
Lowercase Letter 36
 
0.5%
Other Punctuation 20
 
0.3%
Dash Punctuation 18
 
0.2%
Letter Number 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 333
 
7.3%
구 280
 
6.2%
서 263
 
5.8%
시 239
 
5.3%
울 234
 
5.2%
층 141
 
3.1%
별 129
 
2.8%
특 128
 
2.8%
대 106
 
2.3%
동 106
 
2.3%
Other values (224) 2580
56.8%
Uppercase Letter
ValueCountFrequency (%)
B 18
15.0%
C 16
13.3%
I 14
11.7%
F 12
10.0%
T 10
8.3%
D 10
8.3%
A 8
6.7%
S 8
6.7%
K 6
 
5.0%
H 4
 
3.3%
Other values (8) 14
11.7%
Decimal Number
ValueCountFrequency (%)
1 253
23.4%
2 173
16.0%
3 134
12.4%
6 101
 
9.4%
0 88
 
8.1%
4 88
 
8.1%
5 80
 
7.4%
7 70
 
6.5%
8 63
 
5.8%
9 30
 
2.8%
Lowercase Letter
ValueCountFrequency (%)
e 16
44.4%
r 7
19.4%
h 7
19.4%
o 2
 
5.6%
w 2
 
5.6%
n 2
 
5.6%
Other Punctuation
ValueCountFrequency (%)
, 19
95.0%
· 1
 
5.0%
Space Separator
ValueCountFrequency (%)
1297
100.0%
Open Punctuation
ValueCountFrequency (%)
( 98
100.0%
Close Punctuation
ValueCountFrequency (%)
) 98
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 18
100.0%
Letter Number
ValueCountFrequency (%)
Ⅰ 1
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4539
62.1%
Common 2612
35.7%
Latin 157
 
2.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 333
 
7.3%
구 280
 
6.2%
서 263
 
5.8%
시 239
 
5.3%
울 234
 
5.2%
층 141
 
3.1%
별 129
 
2.8%
특 128
 
2.8%
대 106
 
2.3%
동 106
 
2.3%
Other values (224) 2580
56.8%
Latin
ValueCountFrequency (%)
B 18
11.5%
e 16
10.2%
C 16
10.2%
I 14
 
8.9%
F 12
 
7.6%
T 10
 
6.4%
D 10
 
6.4%
A 8
 
5.1%
S 8
 
5.1%
r 7
 
4.5%
Other values (15) 38
24.2%
Common
ValueCountFrequency (%)
1297
49.7%
1 253
 
9.7%
2 173
 
6.6%
3 134
 
5.1%
6 101
 
3.9%
( 98
 
3.8%
) 98
 
3.8%
0 88
 
3.4%
4 88
 
3.4%
5 80
 
3.1%
Other values (7) 202
 
7.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4539
62.1%
ASCII 2767
37.9%
Number Forms 1
 
< 0.1%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1297
46.9%
1 253
 
9.1%
2 173
 
6.3%
3 134
 
4.8%
6 101
 
3.7%
( 98
 
3.5%
) 98
 
3.5%
0 88
 
3.2%
4 88
 
3.2%
5 80
 
2.9%
Other values (30) 357
 
12.9%
Hangul
ValueCountFrequency (%)
로 333
 
7.3%
구 280
 
6.2%
서 263
 
5.8%
시 239
 
5.3%
울 234
 
5.2%
층 141
 
3.1%
별 129
 
2.8%
특 128
 
2.8%
대 106
 
2.3%
동 106
 
2.3%
Other values (224) 2580
56.8%
Number Forms
ValueCountFrequency (%)
Ⅰ 1
100.0%
None
ValueCountFrequency (%)
· 1
100.0%

연락처
Text

Distinct283
Distinct (%)99.0%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
2024-03-15T04:13:08.014040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length11.052448
Min length9

Characters and Unicode

Total characters3161
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique280 ?
Unique (%)97.9%

Sample

1st row02-317-1700
2nd row02-6322-2660
3rd row02-2021-3900
4th row055-290-8000
5th row062-239-5000
ValueCountFrequency (%)
02-399-4848 2
 
0.7%
02-317-1800 2
 
0.7%
02-2195-7777 2
 
0.7%
032-657-5000 1
 
0.3%
02-3702-5800 1
 
0.3%
1588-5959 1
 
0.3%
1566-5800 1
 
0.3%
02-6940-4702 1
 
0.3%
1566-1566 1
 
0.3%
1588-5656 1
 
0.3%
Other values (273) 273
95.5%
2024-03-15T04:13:09.402146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 749
23.7%
- 494
15.6%
2 332
10.5%
1 286
 
9.0%
7 254
 
8.0%
5 212
 
6.7%
8 202
 
6.4%
3 189
 
6.0%
6 180
 
5.7%
4 148
 
4.7%
Other values (2) 115
 
3.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2658
84.1%
Dash Punctuation 494
 
15.6%
Space Separator 9
 
0.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 749
28.2%
2 332
12.5%
1 286
 
10.8%
7 254
 
9.6%
5 212
 
8.0%
8 202
 
7.6%
3 189
 
7.1%
6 180
 
6.8%
4 148
 
5.6%
9 106
 
4.0%
Dash Punctuation
ValueCountFrequency (%)
- 494
100.0%
Space Separator
ValueCountFrequency (%)
9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3161
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 749
23.7%
- 494
15.6%
2 332
10.5%
1 286
 
9.0%
7 254
 
8.0%
5 212
 
6.7%
8 202
 
6.4%
3 189
 
6.0%
6 180
 
5.7%
4 148
 
4.7%
Other values (2) 115
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3161
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 749
23.7%
- 494
15.6%
2 332
10.5%
1 286
 
9.0%
7 254
 
8.0%
5 212
 
6.7%
8 202
 
6.4%
3 189
 
6.0%
6 180
 
5.7%
4 148
 
4.7%
Other values (2) 115
 
3.6%

사이트(URL)
Text

UNIQUE 

Distinct286
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size2.4 KiB
2024-03-15T04:13:10.315661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length65
Median length39
Mean length21.321678
Min length10

Characters and Unicode

Total characters6098
Distinct characters38
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique286 ?
Unique (%)100.0%

Sample

1st rowhttp://www.bnpparibas.co.kr/kr/
2nd rowhttp://www.dbs.com/kr
3rd rowhttp://www.ocbc.com/group/group-home.html
4th rowhttp://www.knbank.co.kr/
5th rowhttp://www.kjbank.com
ValueCountFrequency (%)
http://www.bnpparibas.co.kr/kr 1
 
0.3%
http://www.lotteins.co.kr 1
 
0.3%
http://www.axa.co.kr 1
 
0.3%
http://www.sgic.co.kr 1
 
0.3%
http://www.samsungfire.com 1
 
0.3%
http://www.shinhanez.co.kr 1
 
0.3%
http://www.ms-ins.co.kr 1
 
0.3%
http://www.kbinsure.co.kr 1
 
0.3%
http://www.nhfire.co.kr 1
 
0.3%
http://www.chubb.com/kr 1
 
0.3%
Other values (276) 276
96.5%
2024-03-15T04:13:11.605092image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
w 824
13.5%
. 706
 
11.6%
o 400
 
6.6%
c 354
 
5.8%
t 344
 
5.6%
/ 324
 
5.3%
a 298
 
4.9%
k 293
 
4.8%
s 266
 
4.4%
n 259
 
4.2%
Other values (28) 2030
33.3%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 4908
80.5%
Other Punctuation 1150
 
18.9%
Dash Punctuation 32
 
0.5%
Uppercase Letter 5
 
0.1%
Connector Punctuation 1
 
< 0.1%
Space Separator 1
 
< 0.1%
Decimal Number 1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
w 824
16.8%
o 400
 
8.1%
c 354
 
7.2%
t 344
 
7.0%
a 298
 
6.1%
k 293
 
6.0%
s 266
 
5.4%
n 259
 
5.3%
m 242
 
4.9%
r 240
 
4.9%
Other values (16) 1388
28.3%
Uppercase Letter
ValueCountFrequency (%)
P 1
20.0%
G 1
20.0%
N 1
20.0%
S 1
20.0%
H 1
20.0%
Other Punctuation
ValueCountFrequency (%)
. 706
61.4%
/ 324
28.2%
: 120
 
10.4%
Dash Punctuation
ValueCountFrequency (%)
- 32
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%
Decimal Number
ValueCountFrequency (%)
2 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 4913
80.6%
Common 1185
 
19.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
w 824
16.8%
o 400
 
8.1%
c 354
 
7.2%
t 344
 
7.0%
a 298
 
6.1%
k 293
 
6.0%
s 266
 
5.4%
n 259
 
5.3%
m 242
 
4.9%
r 240
 
4.9%
Other values (21) 1393
28.4%
Common
ValueCountFrequency (%)
. 706
59.6%
/ 324
27.3%
: 120
 
10.1%
- 32
 
2.7%
_ 1
 
0.1%
1
 
0.1%
2 1
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6098
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
w 824
13.5%
. 706
 
11.6%
o 400
 
6.6%
c 354
 
5.8%
t 344
 
5.6%
/ 324
 
5.3%
a 298
 
4.9%
k 293
 
4.8%
s 266
 
4.4%
n 259
 
4.2%
Other values (28) 2030
33.3%

Missing values

2024-03-15T04:13:00.519885image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-15T04:13:00.847410image/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

금융권금융회사명주소연락처사이트(URL)
0은행BNP파리바은행서울특별시 중구 퇴계로 100 스테이트타워 남산 24-25층02-317-1700http://www.bnpparibas.co.kr/kr/
1은행DBS은행서울특별시 중구 세종대로 136 서울파이낸스센터 18층02-6322-2660http://www.dbs.com/kr
2은행OCBC서울특별시 중구 세종대로 136 서울파이낸스센터 25층02-2021-3900http://www.ocbc.com/group/group-home.html
3은행경남은행경상남도 창원시 마산회원구 3·15대로 642055-290-8000http://www.knbank.co.kr/
4은행광주은행광주시 동구 제봉로 225062-239-5000http://www.kjbank.com
5은행교통은행서울특별시 중구 을지로 29 더존을지타워 6층02-2022-6888http://www.bankcomm.co.kr/
6은행국민은행서울특별시 영등포구 국제금융로 8길 2602-2073-7114https://www.kbstar.com/
7은행농협은행서울특별시 중구 통일로 12002-2080-7850http://banking.nonghyup.com
8은행뉴욕멜론은행서울특별시 영등포구 국제금융로 10 원아이에프씨 29층02-6137-0001https://www.bnymellon.com
9은행대구은행대구광역시 수성구 달구벌대로 2310053-755-8760https://www.dgb.co.kr
금융권금융회사명주소연락처사이트(URL)
276저축은행㈜키움예스저축은행서울 강남구 논현로 422 (역삼2동)02-558-2501http://www.kiwoomyesbank.com
277저축은행㈜키움저축은행경기 부천시 부천로 157 (춘의동)1670-0077www.kiwoombank.com
278저축은행(주)평택저축은행경기도 평택시 평택1로 23 (평택동)031-659-3300http://www.ptbank.co.kr
279저축은행㈜하나저축은행서울시 강남구 테헤란로 127 하나금융그룹강남사옥 161899-1122http://www.hanasavings.com
280저축은행㈜한국투자저축은행경기 성남시 분당구 서현로 1841577-6333https://sb.koreainvestment.com
281저축은행㈜한성저축은행충북 옥천군 옥천읍 중앙로 32043-730-0500www.hsbank.co.kr
282저축은행㈜한화저축은행경기 부천시 신흥로 179 6층(중동)032-657-5000http://www.hanwhasbank.com
283저축은행㈜흥국저축은행부산 연제구 중앙대로 1076 (연산동)051-925-2100www.hkbanking.co.kr
284저축은행페퍼저축은행경기 성남시 분당구 황새울로 340 6층(경기도 성남시 분당구 서현동 262-1, 페퍼존빌딩)1599-0722www.pepperbank.kr
285저축은행푸른저축은행서울 서초구 강남대로 58102-545-9000www.prsb.co.kr