Overview

Dataset statistics

Number of variables13
Number of observations108
Missing cells178
Missing cells (%)12.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory11.3 KiB
Average record size in memory107.2 B

Variable types

Numeric2
Text4
Categorical7

Dataset

Description1. 데이터 개요본 데이터는 해외 예금보험기구 현황에 대한 자료임2. 데이터 주석책무 [Pay-box: 단순 보험금 지급형, Pay-box Plus: 강화된 보험금 지급형, Loss Minimiser: 손실 최소화형, Risk Mininiser: 위험 최소화형]자금조달방식 [Ex-ante: 사전적 기금조성, Ex-post: 사후적 기금조성]3. 예금보호한도 금액 단위는 통화단위를 기준으로 한다4. 보호대상 금융상품 정보의 경우 금융안정위원회(FSB) 회원기구 중심으로 작성* 위 내용은 이해를 돕기 위해 임의로 번역한 사항으로, 정확한 내용 및 설명은 국제예금보험기구협회(International Associaion of Deposit Insurers; IADI) 홈페이지 (www.iadi.org)에서 확인하시기 바랍니다.
Author예금보험공사
URLhttps://www.data.go.kr/data/15112647/fileData.do

Alerts

예금보호한도 is highly overall correlated with 부보기관 종류(DIS member banks institutions)High correlation
기구 성격(Deposit Insurance System) is highly overall correlated with 예금보험 필수가입여부(Mandatory membership in the DIS for banks institutions) and 1 other fieldsHigh correlation
책무(Mandate of DIA) is highly overall correlated with 예금보험 필수가입여부(Mandatory membership in the DIS for banks institutions)High correlation
부보기관 종류(DIS member banks institutions) is highly overall correlated with 예금보호한도 and 1 other fieldsHigh correlation
예금보험 필수가입여부(Mandatory membership in the DIS for banks institutions) is highly overall correlated with 기구 성격(Deposit Insurance System) and 3 other fieldsHigh correlation
자금조달방식(Types of funding used by DIS) is highly overall correlated with 보험료율제(Method for assessing or levying premiums on member banks institutions)High correlation
보험료율제(Method for assessing or levying premiums on member banks institutions) is highly overall correlated with 기구 성격(Deposit Insurance System) and 2 other fieldsHigh correlation
예금보험 필수가입여부(Mandatory membership in the DIS for banks institutions) is highly imbalanced (77.0%)Imbalance
자금조달방식(Types of funding used by DIS) is highly imbalanced (58.2%)Imbalance
보호대상 금융상품 is highly imbalanced (63.7%)Imbalance
예금보호한도 has 89 (82.4%) missing valuesMissing
통화단위 has 89 (82.4%) missing valuesMissing
연번(Number) has unique valuesUnique
기구명(Name of Deposit Insurer) has unique valuesUnique

Reproduction

Analysis started2024-05-04 07:00:42.592955
Analysis finished2024-05-04 07:00:46.808875
Duration4.22 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번(Number)
Real number (ℝ)

UNIQUE 

Distinct108
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean54.5
Minimum1
Maximum108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2024-05-04T07:00:47.054880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile6.35
Q127.75
median54.5
Q381.25
95-th percentile102.65
Maximum108
Range107
Interquartile range (IQR)53.5

Descriptive statistics

Standard deviation31.32092
Coefficient of variation (CV)0.57469577
Kurtosis-1.2
Mean54.5
Median Absolute Deviation (MAD)27
Skewness0
Sum5886
Variance981
MonotonicityStrictly increasing
2024-05-04T07:00:47.497043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.9%
70 1
 
0.9%
81 1
 
0.9%
80 1
 
0.9%
79 1
 
0.9%
78 1
 
0.9%
77 1
 
0.9%
76 1
 
0.9%
75 1
 
0.9%
74 1
 
0.9%
Other values (98) 98
90.7%
ValueCountFrequency (%)
1 1
0.9%
2 1
0.9%
3 1
0.9%
4 1
0.9%
5 1
0.9%
6 1
0.9%
7 1
0.9%
8 1
0.9%
9 1
0.9%
10 1
0.9%
ValueCountFrequency (%)
108 1
0.9%
107 1
0.9%
106 1
0.9%
105 1
0.9%
104 1
0.9%
103 1
0.9%
102 1
0.9%
101 1
0.9%
100 1
0.9%
99 1
0.9%

국가(Jurisdiction)
Text

Distinct97
Distinct (%)89.8%
Missing0
Missing (%)0.0%
Memory size996.0 B
2024-05-04T07:00:48.298866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length139
Median length25
Mean length10.462963
Min length4

Characters and Unicode

Total characters1130
Distinct characters53
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique89 ?
Unique (%)82.4%

Sample

1st rowAlbania
2nd rowAngola
3rd rowArgentina
4th rowArmenia
5th rowAustralia
ValueCountFrequency (%)
germany 4
 
2.5%
canada 4
 
2.5%
republic 4
 
2.5%
mexico 3
 
1.8%
african 3
 
1.8%
and 3
 
1.8%
sar 2
 
1.2%
monetary 2
 
1.2%
of 2
 
1.2%
central 2
 
1.2%
Other values (127) 134
82.2%
2024-05-04T07:00:49.407372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 161
 
14.2%
n 96
 
8.5%
i 84
 
7.4%
e 81
 
7.2%
67
 
5.9%
o 60
 
5.3%
r 59
 
5.2%
l 39
 
3.5%
t 36
 
3.2%
d 34
 
3.0%
Other values (43) 413
36.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 891
78.8%
Uppercase Letter 162
 
14.3%
Space Separator 67
 
5.9%
Close Punctuation 5
 
0.4%
Open Punctuation 5
 
0.4%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
a 161
18.1%
n 96
10.8%
i 84
9.4%
e 81
 
9.1%
o 60
 
6.7%
r 59
 
6.6%
l 39
 
4.4%
t 36
 
4.0%
d 34
 
3.8%
u 33
 
3.7%
Other values (16) 208
23.3%
Uppercase Letter
ValueCountFrequency (%)
C 17
 
10.5%
S 16
 
9.9%
M 15
 
9.3%
B 14
 
8.6%
G 12
 
7.4%
A 11
 
6.8%
T 9
 
5.6%
R 9
 
5.6%
P 8
 
4.9%
U 7
 
4.3%
Other values (14) 44
27.2%
Space Separator
ValueCountFrequency (%)
67
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 1053
93.2%
Common 77
 
6.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
a 161
15.3%
n 96
 
9.1%
i 84
 
8.0%
e 81
 
7.7%
o 60
 
5.7%
r 59
 
5.6%
l 39
 
3.7%
t 36
 
3.4%
d 34
 
3.2%
u 33
 
3.1%
Other values (40) 370
35.1%
Common
ValueCountFrequency (%)
67
87.0%
) 5
 
6.5%
( 5
 
6.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1130
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 161
 
14.2%
n 96
 
8.5%
i 84
 
7.4%
e 81
 
7.2%
67
 
5.9%
o 60
 
5.3%
r 59
 
5.2%
l 39
 
3.5%
t 36
 
3.2%
d 34
 
3.0%
Other values (43) 413
36.5%

기구명(Name of Deposit Insurer)
Text

UNIQUE 

Distinct108
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size996.0 B
2024-05-04T07:00:50.212283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length257
Median length72.5
Mean length50.564815
Min length18

Characters and Unicode

Total characters5461
Distinct characters55
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique108 ?
Unique (%)100.0%

Sample

1st rowAlbanian Deposit Insurance Agency (ASD)
2nd rowFundo de Garantia de Depositos - FGD (AFGD)
3rd rowSeguro de Depositos Sociedad Anonima (SEDESA)
4th rowArmenian Deposit Guarantee Fund (ADGF)
5th rowAustralian Prudential Regulation Authority (APRA)
ValueCountFrequency (%)
deposit 64
 
8.9%
insurance 41
 
5.7%
fund 35
 
4.9%
de 34
 
4.7%
of 29
 
4.0%
corporation 25
 
3.5%
guarantee 22
 
3.1%
protection 14
 
1.9%
and 12
 
1.7%
bank 10
 
1.4%
Other values (298) 432
60.2%
2024-05-04T07:00:51.511394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
631
 
11.6%
o 408
 
7.5%
e 404
 
7.4%
n 397
 
7.3%
a 345
 
6.3%
i 314
 
5.7%
t 301
 
5.5%
r 279
 
5.1%
s 252
 
4.6%
D 168
 
3.1%
Other values (45) 1962
35.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 3578
65.5%
Uppercase Letter 991
 
18.1%
Space Separator 631
 
11.6%
Open Punctuation 110
 
2.0%
Close Punctuation 110
 
2.0%
Dash Punctuation 36
 
0.7%
Other Punctuation 4
 
0.1%
Final Punctuation 1
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 408
11.4%
e 404
11.3%
n 397
11.1%
a 345
9.6%
i 314
8.8%
t 301
8.4%
r 279
7.8%
s 252
7.0%
d 158
 
4.4%
u 155
 
4.3%
Other values (15) 565
15.8%
Uppercase Letter
ValueCountFrequency (%)
D 168
17.0%
F 108
10.9%
C 108
10.9%
I 99
10.0%
G 77
7.8%
S 75
7.6%
B 69
7.0%
A 58
 
5.9%
P 50
 
5.0%
O 26
 
2.6%
Other values (13) 153
15.4%
Other Punctuation
ValueCountFrequency (%)
" 2
50.0%
. 2
50.0%
Space Separator
ValueCountFrequency (%)
631
100.0%
Open Punctuation
ValueCountFrequency (%)
( 110
100.0%
Close Punctuation
ValueCountFrequency (%)
) 110
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 36
100.0%
Final Punctuation
ValueCountFrequency (%)
’ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 4569
83.7%
Common 892
 
16.3%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 408
 
8.9%
e 404
 
8.8%
n 397
 
8.7%
a 345
 
7.6%
i 314
 
6.9%
t 301
 
6.6%
r 279
 
6.1%
s 252
 
5.5%
D 168
 
3.7%
d 158
 
3.5%
Other values (38) 1543
33.8%
Common
ValueCountFrequency (%)
631
70.7%
( 110
 
12.3%
) 110
 
12.3%
- 36
 
4.0%
" 2
 
0.2%
. 2
 
0.2%
’ 1
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5460
> 99.9%
Punctuation 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
631
 
11.6%
o 408
 
7.5%
e 404
 
7.4%
n 397
 
7.3%
a 345
 
6.3%
i 314
 
5.8%
t 301
 
5.5%
r 279
 
5.1%
s 252
 
4.6%
D 168
 
3.1%
Other values (44) 1961
35.9%
Punctuation
ValueCountFrequency (%)
’ 1
100.0%

제도 도입연도(Year DIS Introduced)
Text

Distinct51
Distinct (%)47.2%
Missing0
Missing (%)0.0%
Memory size996.0 B
2024-05-04T07:00:51.956074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length4
Mean length4.1851852
Min length4

Characters and Unicode

Total characters452
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

Unique27 ?
Unique (%)25.0%

Sample

1st row2002
2nd row2015
3rd row1995
4th row2005
5th row2008
ValueCountFrequency (%)
1999 9
 
8.0%
2004 6
 
5.4%
1996 5
 
4.5%
1995 5
 
4.5%
2002 5
 
4.5%
2011 5
 
4.5%
1998 5
 
4.5%
2005 4
 
3.6%
2008 4
 
3.6%
2016 4
 
3.6%
Other values (40) 60
53.6%
2024-05-04T07:00:52.699615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
9 105
23.2%
1 94
20.8%
0 90
19.9%
2 62
13.7%
8 22
 
4.9%
6 18
 
4.0%
5 17
 
3.8%
4 14
 
3.1%
7 14
 
3.1%
3 12
 
2.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 448
99.1%
Space Separator 4
 
0.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
9 105
23.4%
1 94
21.0%
0 90
20.1%
2 62
13.8%
8 22
 
4.9%
6 18
 
4.0%
5 17
 
3.8%
4 14
 
3.1%
7 14
 
3.1%
3 12
 
2.7%
Space Separator
ValueCountFrequency (%)
4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 452
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
9 105
23.2%
1 94
20.8%
0 90
19.9%
2 62
13.7%
8 22
 
4.9%
6 18
 
4.0%
5 17
 
3.8%
4 14
 
3.1%
7 14
 
3.1%
3 12
 
2.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 452
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
9 105
23.2%
1 94
20.8%
0 90
19.9%
2 62
13.7%
8 22
 
4.9%
6 18
 
4.0%
5 17
 
3.8%
4 14
 
3.1%
7 14
 
3.1%
3 12
 
2.7%

기구 성격(Deposit Insurance System)
Categorical

HIGH CORRELATION 

Distinct7
Distinct (%)6.5%
Missing0
Missing (%)0.0%
Memory size996.0 B
Government legislated and administered
53 
Government legislated and privately administered
24 
Government legislated and administered by Central Bank
19 
Privately established and administered
9 
Association of deposit insurers
 
1
Other values (2)
 
2

Length

Max length54
Median length38
Mean length42.342593
Min length3

Unique

Unique3 ?
Unique (%)2.8%

Sample

1st rowGovernment legislated and administered
2nd rowGovernment legislated and administered
3rd rowPrivately established and administered
4th rowGovernment legislated and privately administered
5th rowGovernment legislated and administered

Common Values

ValueCountFrequency (%)
Government legislated and administered 53
49.1%
Government legislated and privately administered 24
22.2%
Government legislated and administered by Central Bank 19
 
17.6%
Privately established and administered 9
 
8.3%
Association of deposit insurers 1
 
0.9%
N A 1
 
0.9%
Other 1
 
0.9%

Length

2024-05-04T07:00:53.124178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T07:00:53.462531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
and 105
20.7%
administered 105
20.7%
government 96
18.9%
legislated 96
18.9%
privately 33
 
6.5%
by 19
 
3.7%
central 19
 
3.7%
bank 19
 
3.7%
established 9
 
1.8%
association 1
 
0.2%
Other values (6) 6
 
1.2%

책무(Mandate of DIA)
Categorical

HIGH CORRELATION 

Distinct6
Distinct (%)5.6%
Missing0
Missing (%)0.0%
Memory size996.0 B
Pay-box Plus
46 
Pay-box
25 
Loss Minimiser
18 
Risk Minimiser
12 
Other
5 

Length

Max length14
Median length12
Mean length10.907407
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowPay-box Plus
2nd rowPay-box Plus
3rd rowPay-box Plus
4th rowPay-box
5th rowRisk Minimiser

Common Values

ValueCountFrequency (%)
Pay-box Plus 46
42.6%
Pay-box 25
23.1%
Loss Minimiser 18
 
16.7%
Risk Minimiser 12
 
11.1%
Other 5
 
4.6%
N A 2
 
1.9%

Length

2024-05-04T07:00:53.940448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T07:00:54.332395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
pay-box 71
38.2%
plus 46
24.7%
minimiser 30
16.1%
loss 18
 
9.7%
risk 12
 
6.5%
other 5
 
2.7%
n 2
 
1.1%
a 2
 
1.1%

부보기관 종류(DIS member banks institutions)
Categorical

HIGH CORRELATION 

Distinct35
Distinct (%)32.4%
Missing0
Missing (%)0.0%
Memory size996.0 B
Commercial Banks Credit Unions Financial Cooperatives Insurance Companies Investment Banks Islamic Banks Micro Finance Institutions Rural Banks Community Banks Savings Banks Securities Companies Other Deposit-taking Institutions
27 
Commercial Banks
20 
Commercial Banks Other Deposit-taking Institutions
6 
Commercial Banks Islamic Banks
5 
Commercial Banks Credit Unions
 
4
Other values (30)
46 

Length

Max length238
Median length112
Mean length91.685185
Min length3

Unique

Unique19 ?
Unique (%)17.6%

Sample

1st rowCommercial Banks Credit Unions
2nd rowCommercial Banks
3rd rowCommercial Banks Other Deposit-taking Institutions
4th rowCommercial Banks Credit Unions Financial Cooperatives Insurance Companies Investment Banks Islamic Banks Micro Finance Institutions Rural Banks Community Banks Savings Banks Securities Companies Other Deposit-taking Institutions
5th rowCommercial Banks Credit Unions Insurance Companies Other Deposit-taking Institutions

Common Values

ValueCountFrequency (%)
Commercial Banks Credit Unions Financial Cooperatives Insurance Companies Investment Banks Islamic Banks Micro Finance Institutions Rural Banks Community Banks Savings Banks Securities Companies Other Deposit-taking Institutions 27
25.0%
Commercial Banks 20
18.5%
Commercial Banks Other Deposit-taking Institutions 6
 
5.6%
Commercial Banks Islamic Banks 5
 
4.6%
Commercial Banks Credit Unions 4
 
3.7%
Commercial Banks Credit Unions Other Deposit-taking Institutions 4
 
3.7%
Commercial Banks Micro Finance Institutions 3
 
2.8%
Commercial Banks Micro Finance Institutions Other Deposit-taking Institutions 3
 
2.8%
Financial Cooperatives 3
 
2.8%
N A 2
 
1.9%
Other values (25) 31
28.7%

Length

2024-05-04T07:00:54.754177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
banks 264
24.2%
commercial 94
 
8.6%
institutions 93
 
8.5%
companies 62
 
5.7%
deposit-taking 53
 
4.9%
other 53
 
4.9%
micro 40
 
3.7%
finance 40
 
3.7%
savings 39
 
3.6%
unions 39
 
3.6%
Other values (12) 312
28.7%

예금보험 필수가입여부(Mandatory membership in the DIS for banks institutions)
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct3
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size996.0 B
O
102 
X
 
3
N A
 
3

Length

Max length3
Median length1
Mean length1.0555556
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowO
2nd rowX
3rd rowO
4th rowO
5th rowN A

Common Values

ValueCountFrequency (%)
O 102
94.4%
X 3
 
2.8%
N A 3
 
2.8%

Length

2024-05-04T07:00:55.191649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T07:00:55.524690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
o 102
91.9%
x 3
 
2.7%
n 3
 
2.7%
a 3
 
2.7%

자금조달방식(Types of funding used by DIS)
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct5
Distinct (%)4.6%
Missing0
Missing (%)0.0%
Memory size996.0 B
Ex-ante
86 
Ex-ante Ex-post
16 
Ex-post
 
4
N A
 
1
X
 
1

Length

Max length16
Median length7
Mean length8.2407407
Min length1

Unique

Unique2 ?
Unique (%)1.9%

Sample

1st rowEx-ante
2nd rowEx-ante
3rd rowEx-ante
4th rowEx-ante
5th rowEx-post

Common Values

ValueCountFrequency (%)
Ex-ante 86
79.6%
Ex-ante Ex-post 16
 
14.8%
Ex-post 4
 
3.7%
N A 1
 
0.9%
X 1
 
0.9%

Length

2024-05-04T07:00:55.894837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T07:00:56.231670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
ex-ante 102
81.6%
ex-post 20
 
16.0%
n 1
 
0.8%
a 1
 
0.8%
x 1
 
0.8%

보험료율제(Method for assessing or levying premiums on member banks institutions)
Categorical

HIGH CORRELATION 

Distinct6
Distinct (%)5.6%
Missing0
Missing (%)0.0%
Memory size996.0 B
Differential rate
52 
Flat rate
51 
Other
 
2
Association of deposit insurers
 
1
N A
 
1

Length

Max length31
Median length17
Mean length12.851852
Min length1

Unique

Unique3 ?
Unique (%)2.8%

Sample

1st rowFlat rate
2nd rowFlat rate
3rd rowDifferential rate
4th rowDifferential rate
5th rowOther

Common Values

ValueCountFrequency (%)
Differential rate 52
48.1%
Flat rate 51
47.2%
Other 2
 
1.9%
Association of deposit insurers 1
 
0.9%
N A 1
 
0.9%
X 1
 
0.9%

Length

2024-05-04T07:00:56.613080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T07:00:57.155993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
rate 103
47.9%
differential 52
24.2%
flat 51
23.7%
other 2
 
0.9%
association 1
 
0.5%
of 1
 
0.5%
deposit 1
 
0.5%
insurers 1
 
0.5%
n 1
 
0.5%
a 1
 
0.5%

예금보호한도
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct10
Distinct (%)52.6%
Missing89
Missing (%)82.4%
Infinite0
Infinite (%)0.0%
Mean1.0873335 × 108
Minimum75000
Maximum2 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.1 KiB
2024-05-04T07:00:57.495436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum75000
5-th percentile97500
Q1100000
median250000
Q3450000
95-th percentile2.45 × 108
Maximum2 × 109
Range1.999925 × 109
Interquartile range (IQR)350000

Descriptive statistics

Standard deviation4.5813476 × 108
Coefficient of variation (CV)4.2133784
Kurtosis18.971915
Mean1.0873335 × 108
Median Absolute Deviation (MAD)150000
Skewness4.3543822
Sum2.0659337 × 109
Variance2.0988746 × 1017
MonotonicityNot monotonic
2024-05-04T07:00:57.873346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
100000 7
 
6.5%
250000 4
 
3.7%
500000 1
 
0.9%
2000000000 1
 
0.9%
10000000 1
 
0.9%
50000000 1
 
0.9%
3058720 1
 
0.9%
200000 1
 
0.9%
75000 1
 
0.9%
400000 1
 
0.9%
(Missing) 89
82.4%
ValueCountFrequency (%)
75000 1
 
0.9%
100000 7
6.5%
200000 1
 
0.9%
250000 4
3.7%
400000 1
 
0.9%
500000 1
 
0.9%
3058720 1
 
0.9%
10000000 1
 
0.9%
50000000 1
 
0.9%
2000000000 1
 
0.9%
ValueCountFrequency (%)
2000000000 1
 
0.9%
50000000 1
 
0.9%
10000000 1
 
0.9%
3058720 1
 
0.9%
500000 1
 
0.9%
400000 1
 
0.9%
250000 4
3.7%
200000 1
 
0.9%
100000 7
6.5%
75000 1
 
0.9%

통화단위
Text

MISSING 

Distinct15
Distinct (%)78.9%
Missing89
Missing (%)82.4%
Memory size996.0 B
2024-05-04T07:00:58.270950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters57
Distinct characters21
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique14 ?
Unique (%)73.7%

Sample

1st rowARS
2nd rowAUD
3rd rowBRL
4th rowCAD
5th rowEUR
ValueCountFrequency (%)
eur 5
26.3%
ars 1
 
5.3%
aud 1
 
5.3%
brl 1
 
5.3%
cad 1
 
5.3%
inr 1
 
5.3%
idr 1
 
5.3%
jpy 1
 
5.3%
krw 1
 
5.3%
mxn 1
 
5.3%
Other values (5) 5
26.3%
2024-05-04T07:00:58.958932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
R 12
21.1%
U 7
12.3%
E 5
8.8%
D 5
8.8%
A 4
 
7.0%
S 4
 
7.0%
I 2
 
3.5%
Y 2
 
3.5%
P 2
 
3.5%
N 2
 
3.5%
Other values (11) 12
21.1%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 57
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
R 12
21.1%
U 7
12.3%
E 5
8.8%
D 5
8.8%
A 4
 
7.0%
S 4
 
7.0%
I 2
 
3.5%
Y 2
 
3.5%
P 2
 
3.5%
N 2
 
3.5%
Other values (11) 12
21.1%

Most occurring scripts

ValueCountFrequency (%)
Latin 57
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
R 12
21.1%
U 7
12.3%
E 5
8.8%
D 5
8.8%
A 4
 
7.0%
S 4
 
7.0%
I 2
 
3.5%
Y 2
 
3.5%
P 2
 
3.5%
N 2
 
3.5%
Other values (11) 12
21.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 57
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
R 12
21.1%
U 7
12.3%
E 5
8.8%
D 5
8.8%
A 4
 
7.0%
S 4
 
7.0%
I 2
 
3.5%
Y 2
 
3.5%
P 2
 
3.5%
N 2
 
3.5%
Other values (11) 12
21.1%

보호대상 금융상품
Categorical

IMBALANCE 

Distinct7
Distinct (%)6.5%
Missing0
Missing (%)0.0%
Memory size996.0 B
<NA>
89 
저축성예금 당좌예금 양도성 예금증서 외화예금 등
10 
저축성예금 당좌예금 양도성예금증서 외화예금 등
 
4
저축성예금 당좌예금 양도성 예금증서 등
 
2
저축성예금 양도성예금증서 등
 
1
Other values (2)
 
2

Length

Max length29
Median length4
Mean length7.8796296
Min length4

Unique

Unique3 ?
Unique (%)2.8%

Sample

1st row<NA>
2nd row<NA>
3rd row저축성예금 당좌예금 양도성 예금증서 등
4th row<NA>
5th row저축성예금 당좌예금 양도성예금증서 외화예금 등

Common Values

ValueCountFrequency (%)
<NA> 89
82.4%
저축성예금 당좌예금 양도성 예금증서 외화예금 등 10
 
9.3%
저축성예금 당좌예금 양도성예금증서 외화예금 등 4
 
3.7%
저축성예금 당좌예금 양도성 예금증서 등 2
 
1.9%
저축성예금 양도성예금증서 등 1
 
0.9%
저축성예금 당좌예금 등 1
 
0.9%
당좌예금 저축예금 외화예금 등 1
 
0.9%

Length

2024-05-04T07:00:59.395035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-04T07:00:59.744898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 89
47.1%
등 19
 
10.1%
저축성예금 18
 
9.5%
당좌예금 18
 
9.5%
외화예금 15
 
7.9%
양도성 12
 
6.3%
예금증서 12
 
6.3%
양도성예금증서 5
 
2.6%
저축예금 1
 
0.5%

Interactions

2024-05-04T07:00:44.936314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T07:00:44.394501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T07:00:45.192526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-04T07:00:44.659096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-04T07:01:00.022989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번(Number)국가(Jurisdiction)제도 도입연도(Year DIS Introduced)기구 성격(Deposit Insurance System)책무(Mandate of DIA)부보기관 종류(DIS member banks institutions)예금보험 필수가입여부(Mandatory membership in the DIS for banks institutions)자금조달방식(Types of funding used by DIS)보험료율제(Method for assessing or levying premiums on member banks institutions)예금보호한도통화단위보호대상 금융상품
연번(Number)1.0000.9840.0000.0000.3210.0000.0000.1910.2360.0000.0000.000
국가(Jurisdiction)0.9841.0000.0000.0000.0000.4510.0000.0000.0001.0001.0001.000
제도 도입연도(Year DIS Introduced)0.0000.0001.0000.3040.4290.8140.4800.0000.0001.0000.8990.860
기구 성격(Deposit Insurance System)0.0000.0000.3041.0000.6160.8260.6890.6350.7980.0000.0000.000
책무(Mandate of DIA)0.3210.0000.4290.6161.0000.8070.8680.4850.8450.0000.8720.000
부보기관 종류(DIS member banks institutions)0.0000.4510.8140.8260.8071.0000.8460.5300.5841.0000.8930.000
예금보험 필수가입여부(Mandatory membership in the DIS for banks institutions)0.0000.0000.4800.6890.8680.8461.0000.4840.9000.0000.0000.000
자금조달방식(Types of funding used by DIS)0.1910.0000.0000.6350.4850.5300.4841.0000.8240.2800.8700.000
보험료율제(Method for assessing or levying premiums on member banks institutions)0.2360.0000.0000.7980.8450.5840.9000.8241.0000.0001.0000.583
예금보호한도0.0001.0001.0000.0000.0001.0000.0000.2800.0001.0001.0000.000
통화단위0.0001.0000.8990.0000.8720.8930.0000.8701.0001.0001.0001.000
보호대상 금융상품0.0001.0000.8600.0000.0000.0000.0000.0000.5830.0001.0001.000
2024-05-04T07:01:00.443884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
보호대상 금융상품자금조달방식(Types of funding used by DIS)기구 성격(Deposit Insurance System)예금보험 필수가입여부(Mandatory membership in the DIS for banks institutions)보험료율제(Method for assessing or levying premiums on member banks institutions)부보기관 종류(DIS member banks institutions)책무(Mandate of DIA)
보호대상 금융상품1.0000.0000.0000.0000.2330.0000.000
자금조달방식(Types of funding used by DIS)0.0001.0000.4710.4140.7190.2120.353
기구 성격(Deposit Insurance System)0.0000.4711.0000.5890.6290.4030.424
예금보험 필수가입여부(Mandatory membership in the DIS for banks institutions)0.0000.4140.5891.0000.6130.5410.562
보험료율제(Method for assessing or levying premiums on member banks institutions)0.2330.7190.6290.6131.0000.2470.463
부보기관 종류(DIS member banks institutions)0.0000.2120.4030.5410.2471.0000.430
책무(Mandate of DIA)0.0000.3530.4240.5620.4630.4301.000
2024-05-04T07:01:00.796016image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번(Number)예금보호한도기구 성격(Deposit Insurance System)책무(Mandate of DIA)부보기관 종류(DIS member banks institutions)예금보험 필수가입여부(Mandatory membership in the DIS for banks institutions)자금조달방식(Types of funding used by DIS)보험료율제(Method for assessing or levying premiums on member banks institutions)보호대상 금융상품
연번(Number)1.000-0.0950.0000.1690.0000.0000.0730.1200.000
예금보호한도-0.0951.0000.0000.0000.5420.0000.4430.0000.000
기구 성격(Deposit Insurance System)0.0000.0001.0000.4240.4030.5890.4710.6290.000
책무(Mandate of DIA)0.1690.0000.4241.0000.4300.5620.3530.4630.000
부보기관 종류(DIS member banks institutions)0.0000.5420.4030.4301.0000.5410.2120.2470.000
예금보험 필수가입여부(Mandatory membership in the DIS for banks institutions)0.0000.0000.5890.5620.5411.0000.4140.6130.000
자금조달방식(Types of funding used by DIS)0.0730.4430.4710.3530.2120.4141.0000.7190.000
보험료율제(Method for assessing or levying premiums on member banks institutions)0.1200.0000.6290.4630.2470.6130.7191.0000.233
보호대상 금융상품0.0000.0000.0000.0000.0000.0000.0000.2331.000

Missing values

2024-05-04T07:00:45.601559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-04T07:00:46.224519image/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.
2024-05-04T07:00:46.646927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

연번(Number)국가(Jurisdiction)기구명(Name of Deposit Insurer)제도 도입연도(Year DIS Introduced)기구 성격(Deposit Insurance System)책무(Mandate of DIA)부보기관 종류(DIS member banks institutions)예금보험 필수가입여부(Mandatory membership in the DIS for banks institutions)자금조달방식(Types of funding used by DIS)보험료율제(Method for assessing or levying premiums on member banks institutions)예금보호한도통화단위보호대상 금융상품
01AlbaniaAlbanian Deposit Insurance Agency (ASD)2002Government legislated and administeredPay-box PlusCommercial Banks Credit UnionsOEx-anteFlat rate<NA><NA><NA>
12AngolaFundo de Garantia de Depositos - FGD (AFGD)2015Government legislated and administeredPay-box PlusCommercial BanksXEx-anteFlat rate<NA><NA><NA>
23ArgentinaSeguro de Depositos Sociedad Anonima (SEDESA)1995Privately established and administeredPay-box PlusCommercial Banks Other Deposit-taking InstitutionsOEx-anteDifferential rate250000ARS저축성예금 당좌예금 양도성 예금증서 등
34ArmeniaArmenian Deposit Guarantee Fund (ADGF)2005Government legislated and privately administeredPay-boxCommercial Banks Credit Unions Financial Cooperatives Insurance Companies Investment Banks Islamic Banks Micro Finance Institutions Rural Banks Community Banks Savings Banks Securities Companies Other Deposit-taking InstitutionsOEx-anteDifferential rate<NA><NA><NA>
45AustraliaAustralian Prudential Regulation Authority (APRA)2008Government legislated and administeredRisk MinimiserCommercial Banks Credit Unions Insurance Companies Other Deposit-taking InstitutionsN AEx-postOther250000AUD저축성예금 당좌예금 양도성예금증서 외화예금 등
56BahamasDeposit Insurance Corporation (DIC-BS)1999Government legislated and administered by Central BankPay-box PlusCommercial Banks Credit Unions Other Deposit-taking InstitutionsOEx-anteFlat rate<NA><NA><NA>
67BangladeshBangladesh Bank (BB-BD)1984Government legislated and administered by Central BankPay-boxCommercial Banks Islamic BanksOEx-anteDifferential rate<NA><NA><NA>
78BarbadosBarbados Deposit Insurance Corporation (BDIC)2007Government legislated and administeredPay-box PlusCommercial Banks Credit Unions Financial Cooperatives Insurance Companies Investment Banks Islamic Banks Micro Finance Institutions Rural Banks Community Banks Savings Banks Securities Companies Other Deposit-taking InstitutionsOEx-anteFlat rate<NA><NA><NA>
89BelgiumGuarantee Fund for Financial Services (NBB)1974Government legislated and administeredPay-boxCommercial Banks Insurance Companies Securities CompaniesOEx-anteDifferential rate<NA><NA><NA>
910BelizeCentral Bank of Belize (BZE)2020Government legislated and administered by Central BankPay-boxCommercial Banks Credit UnionsOEx-anteFlat rate<NA><NA><NA>
연번(Number)국가(Jurisdiction)기구명(Name of Deposit Insurer)제도 도입연도(Year DIS Introduced)기구 성격(Deposit Insurance System)책무(Mandate of DIA)부보기관 종류(DIS member banks institutions)예금보험 필수가입여부(Mandatory membership in the DIS for banks institutions)자금조달방식(Types of funding used by DIS)보험료율제(Method for assessing or levying premiums on member banks institutions)예금보호한도통화단위보호대상 금융상품
9899TurkeySavings Deposit Insurance Fund (SDIF) (TMSF)1983Government legislated and administeredLoss MinimiserCommercial Banks Credit Unions Financial Cooperatives Insurance Companies Investment Banks Islamic Banks Micro Finance Institutions Rural Banks Community Banks Savings Banks Securities Companies Other Deposit-taking InstitutionsOEx-anteDifferential rate400000TRY당좌예금 저축예금 외화예금 등
99100UgandaDeposit Protection Fund (BOU)1994Government legislated and administeredPay-box PlusCommercial Banks Micro Finance Institutions Other Deposit-taking InstitutionsOEx-anteFlat rate<NA><NA><NA>
100101UkraineDeposit Guarantee Fund (FG-UA)1998Government legislated and administeredLoss MinimiserCommercial BanksOEx-anteDifferential rate<NA><NA><NA>
101102United StatesNational Credit Union Administration (NCUA)1970Government legislated and administeredOtherCredit UnionsOEx-anteFlat rate<NA><NA><NA>
102103United StatesFederal Deposit Insurance Corporation (FDIC)1933Government legislated and administeredRisk MinimiserCommercial Banks Savings Banks Other Deposit-taking InstitutionsOEx-anteDifferential rate250000USD저축성예금 당좌예금 양도성 예금증서 외화예금 등
103104UruguayCorporacion de Proteccion del Ahorro Bancario (COPAB)2005Government legislated and privately administeredLoss MinimiserCommercial Banks Credit Unions Financial Cooperatives Insurance Companies Investment Banks Islamic Banks Micro Finance Institutions Rural Banks Community Banks Savings Banks Securities Companies Other Deposit-taking InstitutionsOEx-anteDifferential rate<NA><NA><NA>
104105UzbekistanIndividuals Bank Deposit Guarantee Fund (DGF-UZ)2002Government legislated and privately administeredPay-boxCommercial BanksOEx-anteFlat rate<NA><NA><NA>
105106VietnamDeposit Insurance of Vietnam (DIV)1999Government legislated and administered by Central BankPay-box PlusCommercial Banks Financial Cooperatives Micro Finance InstitutionsOEx-anteFlat rate<NA><NA><NA>
106107West African Monetary Union (Benin Burkina Faso Cote d Ivoire Guinee Bissau Mali Niger Senegal Togo)West African Monetary Union Deposit Insurance Fund2014Government legislated and administered by Central BankPay-box PlusCommercial Banks Islamic Banks Micro Finance InstitutionsOEx-ante Ex-postFlat rate<NA><NA><NA>
107108ZimbabweDeposit Protection Corporation (DPC)2003Government legislated and privately administeredPay-box PlusCommercial Banks Investment Banks Micro Finance Institutions Savings Banks Other Deposit-taking InstitutionsOEx-anteFlat rate<NA><NA><NA>