Overview

Dataset statistics

Number of variables4
Number of observations2090
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory65.4 KiB
Average record size in memory32.1 B

Variable types

Categorical1
Text3

Dataset

Description(부보금융회사 종합정보)보험사고가 발생한 부보금융회사의 예금자가 예금보험금 지급을 청구한 경우 공사의 보험금 지급 업무를 대행해 주는 금융회사 지점 목록과 해당 지점의 연락처 등의 정보
Author예금보험공사
URLhttps://www.data.go.kr/data/15083216/fileData.do

Reproduction

Analysis started2024-04-13 12:48:28.405899
Analysis finished2024-04-13 12:48:30.350564
Duration1.94 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

은행명
Categorical

Distinct6
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size16.5 KiB
기업은행
623 
우리
620 
하나은행
597 
농협은행
137 
KB국민은행
 
57

Length

Max length6
Median length4
Mean length3.461244
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
기업은행 623
29.8%
우리 620
29.7%
하나은행 597
28.6%
농협은행 137
 
6.6%
KB국민은행 57
 
2.7%
신한은행 56
 
2.7%

Length

2024-04-13T21:48:30.496778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-13T21:48:30.730476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
기업은행 623
29.8%
우리 620
29.7%
하나은행 597
28.6%
농협은행 137
 
6.6%
kb국민은행 57
 
2.7%
신한은행 56
 
2.7%

지점명
Text

Distinct1848
Distinct (%)88.4%
Missing0
Missing (%)0.0%
Memory size16.5 KiB
2024-04-13T21:48:31.699529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length14
Mean length4.9200957
Min length2

Characters and Unicode

Total characters10283
Distinct characters401
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1626 ?
Unique (%)77.8%

Sample

1st row가능역지점
2nd row가락동지점
3rd row가락시장지점
4th row가양중앙지점
5th row간석지점
ValueCountFrequency (%)
pb센터 9
 
0.4%
신촌 4
 
0.2%
장산역 4
 
0.2%
이수역 4
 
0.2%
구로디지털금융센터 3
 
0.1%
서귀포 3
 
0.1%
평택 3
 
0.1%
동대문 3
 
0.1%
여의도 3
 
0.1%
신사동 3
 
0.1%
Other values (1842) 2071
98.2%
2024-04-13T21:48:33.005482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
지 605
 
5.9%
동 533
 
5.2%
점 521
 
5.1%
센 390
 
3.8%
터 384
 
3.7%
금 356
 
3.5%
융 337
 
3.3%
역 298
 
2.9%
산 230
 
2.2%
대 165
 
1.6%
Other values (391) 6464
62.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 9820
95.5%
Uppercase Letter 188
 
1.8%
Open Punctuation 102
 
1.0%
Close Punctuation 102
 
1.0%
Decimal Number 40
 
0.4%
Space Separator 20
 
0.2%
Lowercase Letter 11
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 605
 
6.2%
동 533
 
5.4%
점 521
 
5.3%
센 390
 
4.0%
터 384
 
3.9%
금 356
 
3.6%
융 337
 
3.4%
역 298
 
3.0%
산 230
 
2.3%
대 165
 
1.7%
Other values (351) 6001
61.1%
Uppercase Letter
ValueCountFrequency (%)
M 26
13.8%
W 22
11.7%
C 21
11.2%
B 15
8.0%
T 14
 
7.4%
S 14
 
7.4%
P 14
 
7.4%
I 9
 
4.8%
O 8
 
4.3%
L 8
 
4.3%
Other values (13) 37
19.7%
Decimal Number
ValueCountFrequency (%)
2 10
25.0%
3 9
22.5%
1 6
15.0%
5 4
 
10.0%
4 4
 
10.0%
6 4
 
10.0%
7 2
 
5.0%
8 1
 
2.5%
Lowercase Letter
ValueCountFrequency (%)
b 3
27.3%
l 2
18.2%
u 2
18.2%
c 2
18.2%
j 1
 
9.1%
t 1
 
9.1%
Open Punctuation
ValueCountFrequency (%)
( 102
100.0%
Close Punctuation
ValueCountFrequency (%)
) 102
100.0%
Space Separator
ValueCountFrequency (%)
20
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 9820
95.5%
Common 264
 
2.6%
Latin 199
 
1.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 605
 
6.2%
동 533
 
5.4%
점 521
 
5.3%
센 390
 
4.0%
터 384
 
3.9%
금 356
 
3.6%
융 337
 
3.4%
역 298
 
3.0%
산 230
 
2.3%
대 165
 
1.7%
Other values (351) 6001
61.1%
Latin
ValueCountFrequency (%)
M 26
13.1%
W 22
11.1%
C 21
10.6%
B 15
 
7.5%
T 14
 
7.0%
S 14
 
7.0%
P 14
 
7.0%
I 9
 
4.5%
O 8
 
4.0%
L 8
 
4.0%
Other values (19) 48
24.1%
Common
ValueCountFrequency (%)
( 102
38.6%
) 102
38.6%
20
 
7.6%
2 10
 
3.8%
3 9
 
3.4%
1 6
 
2.3%
5 4
 
1.5%
4 4
 
1.5%
6 4
 
1.5%
7 2
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 9820
95.5%
ASCII 463
 
4.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
지 605
 
6.2%
동 533
 
5.4%
점 521
 
5.3%
센 390
 
4.0%
터 384
 
3.9%
금 356
 
3.6%
융 337
 
3.4%
역 298
 
3.0%
산 230
 
2.3%
대 165
 
1.7%
Other values (351) 6001
61.1%
ASCII
ValueCountFrequency (%)
( 102
22.0%
) 102
22.0%
M 26
 
5.6%
W 22
 
4.8%
C 21
 
4.5%
20
 
4.3%
B 15
 
3.2%
T 14
 
3.0%
S 14
 
3.0%
P 14
 
3.0%
Other values (30) 113
24.4%

도로명 주소
Text

Distinct2060
Distinct (%)98.6%
Missing0
Missing (%)0.0%
Memory size16.5 KiB
2024-04-13T21:48:34.005307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length60
Median length47
Mean length21.732536
Min length11

Characters and Unicode

Total characters45421
Distinct characters486
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2032 ?
Unique (%)97.2%

Sample

1st row경기도 의정부시 평화로 630 (의정부동 228-26)
2nd row서울특별시 송파구 중대로9길 60 (가락동 71)
3rd row서울특별시 송파구 양재대로 932 (가락동 600)
4th row서울특별시 강서구 양천로57길 9-7 (가양2동 1479-10)
5th row인천광역시 남동구 남동대로 898 (간석동 207-2)
ValueCountFrequency (%)
서울 286
 
3.2%
서울특별시 285
 
3.2%
경기도 245
 
2.7%
경기 148
 
1.7%
강남구 92
 
1.0%
1f 90
 
1.0%
중구 78
 
0.9%
부산광역시 62
 
0.7%
성남시 53
 
0.6%
2f 52
 
0.6%
Other values (3333) 7565
84.5%
2024-04-13T21:48:35.323687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
8451
 
18.6%
로 2167
 
4.8%
구 1840
 
4.1%
시 1746
 
3.8%
1 1463
 
3.2%
서 1226
 
2.7%
동 1132
 
2.5%
2 1077
 
2.4%
울 859
 
1.9%
3 788
 
1.7%
Other values (476) 24672
54.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 27808
61.2%
Space Separator 8452
 
18.6%
Decimal Number 7033
 
15.5%
Open Punctuation 769
 
1.7%
Close Punctuation 767
 
1.7%
Uppercase Letter 315
 
0.7%
Dash Punctuation 176
 
0.4%
Other Punctuation 96
 
0.2%
Lowercase Letter 4
 
< 0.1%
Letter Number 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 2167
 
7.8%
구 1840
 
6.6%
시 1746
 
6.3%
서 1226
 
4.4%
동 1132
 
4.1%
울 859
 
3.1%
대 777
 
2.8%
도 693
 
2.5%
경 674
 
2.4%
산 602
 
2.2%
Other values (433) 16092
57.9%
Uppercase Letter
ValueCountFrequency (%)
F 174
55.2%
T 25
 
7.9%
A 23
 
7.3%
P 20
 
6.3%
B 11
 
3.5%
C 9
 
2.9%
K 7
 
2.2%
L 7
 
2.2%
M 6
 
1.9%
I 6
 
1.9%
Other values (11) 27
 
8.6%
Decimal Number
ValueCountFrequency (%)
1 1463
20.8%
2 1077
15.3%
3 788
11.2%
5 629
8.9%
4 590
8.4%
6 566
 
8.0%
0 551
 
7.8%
7 492
 
7.0%
8 463
 
6.6%
9 414
 
5.9%
Lowercase Letter
ValueCountFrequency (%)
o 1
25.0%
e 1
25.0%
r 1
25.0%
w 1
25.0%
Space Separator
ValueCountFrequency (%)
8451
> 99.9%
　 1
 
< 0.1%
Other Punctuation
ValueCountFrequency (%)
, 94
97.9%
. 2
 
2.1%
Open Punctuation
ValueCountFrequency (%)
( 769
100.0%
Close Punctuation
ValueCountFrequency (%)
) 767
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 176
100.0%
Letter Number
ValueCountFrequency (%)
Ⅲ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 27808
61.2%
Common 17293
38.1%
Latin 320
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 2167
 
7.8%
구 1840
 
6.6%
시 1746
 
6.3%
서 1226
 
4.4%
동 1132
 
4.1%
울 859
 
3.1%
대 777
 
2.8%
도 693
 
2.5%
경 674
 
2.4%
산 602
 
2.2%
Other values (433) 16092
57.9%
Latin
ValueCountFrequency (%)
F 174
54.4%
T 25
 
7.8%
A 23
 
7.2%
P 20
 
6.2%
B 11
 
3.4%
C 9
 
2.8%
K 7
 
2.2%
L 7
 
2.2%
M 6
 
1.9%
I 6
 
1.9%
Other values (16) 32
 
10.0%
Common
ValueCountFrequency (%)
8451
48.9%
1 1463
 
8.5%
2 1077
 
6.2%
3 788
 
4.6%
( 769
 
4.4%
) 767
 
4.4%
5 629
 
3.6%
4 590
 
3.4%
6 566
 
3.3%
0 551
 
3.2%
Other values (7) 1642
 
9.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 27808
61.2%
ASCII 17611
38.8%
None 1
 
< 0.1%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
8451
48.0%
1 1463
 
8.3%
2 1077
 
6.1%
3 788
 
4.5%
( 769
 
4.4%
) 767
 
4.4%
5 629
 
3.6%
4 590
 
3.4%
6 566
 
3.2%
0 551
 
3.1%
Other values (31) 1960
 
11.1%
Hangul
ValueCountFrequency (%)
로 2167
 
7.8%
구 1840
 
6.6%
시 1746
 
6.3%
서 1226
 
4.4%
동 1132
 
4.1%
울 859
 
3.1%
대 777
 
2.8%
도 693
 
2.5%
경 674
 
2.4%
산 602
 
2.2%
Other values (433) 16092
57.9%
None
ValueCountFrequency (%)
　 1
100.0%
Number Forms
ValueCountFrequency (%)
Ⅲ 1
100.0%

전화번호
Text

Distinct2086
Distinct (%)99.8%
Missing0
Missing (%)0.0%
Memory size16.5 KiB
2024-04-13T21:48:36.099835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length12
Mean length12.183732
Min length11

Characters and Unicode

Total characters25464
Distinct characters17
Distinct categories6 ?
Distinct scripts1 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2083 ?
Unique (%)99.7%

Sample

1st row031-842-1290
2nd row02-3401-9541
3rd row02-408-6612
4th row02-2658-3290
5th row032-423-6431
ValueCountFrequency (%)
031-239-6571 3
 
0.1%
055-282-2111 2
 
0.1%
02)2002-3000 2
 
0.1%
032-469-8477 1
 
< 0.1%
061)244-2111 1
 
< 0.1%
032)743-1050 1
 
< 0.1%
061)792-2550 1
 
< 0.1%
061)332-1899 1
 
< 0.1%
061)726-6400 1
 
< 0.1%
032)831-7150 1
 
< 0.1%
Other values (2077) 2077
99.3%
2024-04-13T21:48:37.093435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 4021
15.8%
- 3562
14.0%
0 3495
13.7%
2 2709
10.6%
3 2316
9.1%
5 1831
7.2%
4 1659
6.5%
6 1452
 
5.7%
7 1241
 
4.9%
8 1147
 
4.5%
Other values (7) 2031
8.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 20843
81.9%
Dash Punctuation 3562
 
14.0%
Close Punctuation 620
 
2.4%
Math Symbol 396
 
1.6%
Other Punctuation 33
 
0.1%
Space Separator 10
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 4021
19.3%
0 3495
16.8%
2 2709
13.0%
3 2316
11.1%
5 1831
8.8%
4 1659
8.0%
6 1452
 
7.0%
7 1241
 
6.0%
8 1147
 
5.5%
9 972
 
4.7%
Math Symbol
ValueCountFrequency (%)
~ 395
99.7%
∼ 1
 
0.3%
Other Punctuation
ValueCountFrequency (%)
, 31
93.9%
. 2
 
6.1%
Dash Punctuation
ValueCountFrequency (%)
- 3562
100.0%
Close Punctuation
ValueCountFrequency (%)
) 620
100.0%
Space Separator
ValueCountFrequency (%)
10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 25464
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 4021
15.8%
- 3562
14.0%
0 3495
13.7%
2 2709
10.6%
3 2316
9.1%
5 1831
7.2%
4 1659
6.5%
6 1452
 
5.7%
7 1241
 
4.9%
8 1147
 
4.5%
Other values (7) 2031
8.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 25463
> 99.9%
Math Operators 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 4021
15.8%
- 3562
14.0%
0 3495
13.7%
2 2709
10.6%
3 2316
9.1%
5 1831
7.2%
4 1659
6.5%
6 1452
 
5.7%
7 1241
 
4.9%
8 1147
 
4.5%
Other values (6) 2030
8.0%
Math Operators
ValueCountFrequency (%)
∼ 1
100.0%

Missing values

2024-04-13T21:48:30.120852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-13T21:48:30.282342image/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

은행명지점명도로명 주소전화번호
0농협은행가능역지점경기도 의정부시 평화로 630 (의정부동 228-26)031-842-1290
1농협은행가락동지점서울특별시 송파구 중대로9길 60 (가락동 71)02-3401-9541
2농협은행가락시장지점서울특별시 송파구 양재대로 932 (가락동 600)02-408-6612
3농협은행가양중앙지점서울특별시 강서구 양천로57길 9-7 (가양2동 1479-10)02-2658-3290
4농협은행간석지점인천광역시 남동구 남동대로 898 (간석동 207-2)032-423-6431
5농협은행강경출장소충청남도 논산시 강경읍 계백로 112 (강경읍 대흥리 51-8)041-745-2107
6농협은행강북중앙금융센터서울특별시 강북구 도봉로 373 (수유동 174-5)02-906-0071
7농협은행경기영업부경기도 수원시 권선구 권광로139번길 11 (권선구 권선동 1015)031-230-3800
8농협은행고창군지부전라북도 고창군 고창읍 중거리당산로 169 (고창읍 읍내리 233-5)063-564-2141
9농협은행곡성군지부전라남도 곡성군 곡성읍 중앙로 112 (곡성읍 읍내리 264)061-363-2021
은행명지점명도로명 주소전화번호
2080신한은행신촌서울시 마포구 신촌로 9402-393-3929
2081신한은행길동서울특별시 강동구 양재대로 146402-482-1531
2082신한은행역삼동서울특별시 강남구 강남대로 314,(서우빌딩)02-553-5560
2083신한은행노원역서울특별시 노원구 동일로 140402-935-6691
2084신한은행광교영업부서울 중구 청계천로 5402-2010-2100
2085신한은행구로디지털금융센터서울특별시 구로구 디지털로 272,(한신아이티타워ITTOWER)02-2108-6400
2086신한은행연신내서울특별시 은평구 통일로 84502-354-5500
2087신한은행장한평역금융센터서울특별시 동대문구 천호대로 42502-2213-9106
2088신한은행삼성역지점서울특별시 강남구 테헤란로 51602-561-5559
2089신한은행세종조치원금융센터세종특별자치시 조치원읍 조치원로 28,(조치원역 전방 200M)044-864-9559