Overview

Dataset statistics

Number of variables3
Number of observations200
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.2 KiB
Average record size in memory26.7 B

Variable types

Categorical1
Text1
Numeric1

Dataset

Description한국자산관리공사 공사채권의 금융기관별 법원사건 관리 현황데이터로 "사건년도","금융기관","차주건수" 항목을 제공하고 있습니다.
Author한국자산관리공사
URLhttps://www.data.go.kr/data/15095222/fileData.do

Alerts

사건년도 has constant value ""Constant
금융기관 has unique valuesUnique

Reproduction

Analysis started2023-12-12 08:49:50.003814
Analysis finished2023-12-12 08:49:50.460865
Duration0.46 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

사건년도
Categorical

CONSTANT 

Distinct1
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
2020
200 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2020
2nd row2020
3rd row2020
4th row2020
5th row2020

Common Values

ValueCountFrequency (%)
2020 200
100.0%

Length

2023-12-12T17:49:50.535393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:49:50.659127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2020 200
100.0%

금융기관
Text

UNIQUE 

Distinct200
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
2023-12-12T17:49:50.925812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length6.085
Min length4

Characters and Unicode

Total characters1217
Distinct characters207
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique200 ?
Unique (%)100.0%

Sample

1st row(주)아주저축은행
2nd row(주)에스비아이저축은행
3rd row(주)케이비손해보험
4th rowBYC생명
5th rowIBK캐피탈
ValueCountFrequency (%)
주)아주저축은행 1
 
0.5%
인천수협 1
 
0.5%
제주신용보증재단 1
 
0.5%
우리은행(한일 1
 
0.5%
우리카드 1
 
0.5%
울산신용보증재단 1
 
0.5%
원주시산림조합 1
 
0.5%
웰컴저축은행(주 1
 
0.5%
유니애대부 1
 
0.5%
유니온상호 1
 
0.5%
Other values (190) 190
95.0%
2023-12-12T17:49:51.357920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
은 50
 
4.1%
행 48
 
3.9%
상 40
 
3.3%
협 35
 
2.9%
호 34
 
2.8%
보 34
 
2.8%
신 31
 
2.5%
수 28
 
2.3%
산 27
 
2.2%
축 25
 
2.1%
Other values (197) 865
71.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1163
95.6%
Open Punctuation 21
 
1.7%
Close Punctuation 21
 
1.7%
Uppercase Letter 11
 
0.9%
Decimal Number 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
은 50
 
4.3%
행 48
 
4.1%
상 40
 
3.4%
협 35
 
3.0%
호 34
 
2.9%
보 34
 
2.9%
신 31
 
2.7%
수 28
 
2.4%
산 27
 
2.3%
축 25
 
2.1%
Other values (187) 811
69.7%
Uppercase Letter
ValueCountFrequency (%)
B 3
27.3%
C 2
18.2%
K 2
18.2%
S 1
 
9.1%
E 1
 
9.1%
I 1
 
9.1%
Y 1
 
9.1%
Open Punctuation
ValueCountFrequency (%)
( 21
100.0%
Close Punctuation
ValueCountFrequency (%)
) 21
100.0%
Decimal Number
ValueCountFrequency (%)
8 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1163
95.6%
Common 43
 
3.5%
Latin 11
 
0.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
은 50
 
4.3%
행 48
 
4.1%
상 40
 
3.4%
협 35
 
3.0%
호 34
 
2.9%
보 34
 
2.9%
신 31
 
2.7%
수 28
 
2.4%
산 27
 
2.3%
축 25
 
2.1%
Other values (187) 811
69.7%
Latin
ValueCountFrequency (%)
B 3
27.3%
C 2
18.2%
K 2
18.2%
S 1
 
9.1%
E 1
 
9.1%
I 1
 
9.1%
Y 1
 
9.1%
Common
ValueCountFrequency (%)
( 21
48.8%
) 21
48.8%
8 1
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1163
95.6%
ASCII 54
 
4.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
은 50
 
4.3%
행 48
 
4.1%
상 40
 
3.4%
협 35
 
3.0%
호 34
 
2.9%
보 34
 
2.9%
신 31
 
2.7%
수 28
 
2.4%
산 27
 
2.3%
축 25
 
2.1%
Other values (187) 811
69.7%
ASCII
ValueCountFrequency (%)
( 21
38.9%
) 21
38.9%
B 3
 
5.6%
C 2
 
3.7%
K 2
 
3.7%
8 1
 
1.9%
S 1
 
1.9%
E 1
 
1.9%
I 1
 
1.9%
Y 1
 
1.9%

차주건수
Real number (ℝ)

Distinct90
Distinct (%)45.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean239.385
Minimum1
Maximum10167
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2023-12-12T17:49:51.509161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median10
Q366.5
95-th percentile1046.1
Maximum10167
Range10166
Interquartile range (IQR)64.5

Descriptive statistics

Standard deviation1081.5117
Coefficient of variation (CV)4.517876
Kurtosis61.389507
Mean239.385
Median Absolute Deviation (MAD)9
Skewness7.4726647
Sum47877
Variance1169667.7
MonotonicityNot monotonic
2023-12-12T17:49:51.658316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 41
20.5%
2 20
 
10.0%
3 12
 
6.0%
5 9
 
4.5%
4 5
 
2.5%
6 4
 
2.0%
9 4
 
2.0%
12 4
 
2.0%
15 3
 
1.5%
19 3
 
1.5%
Other values (80) 95
47.5%
ValueCountFrequency (%)
1 41
20.5%
2 20
10.0%
3 12
 
6.0%
4 5
 
2.5%
5 9
 
4.5%
6 4
 
2.0%
7 3
 
1.5%
8 1
 
0.5%
9 4
 
2.0%
10 2
 
1.0%
ValueCountFrequency (%)
10167 1
0.5%
9345 1
0.5%
4061 1
0.5%
3577 1
0.5%
3225 1
0.5%
2059 1
0.5%
1581 1
0.5%
1181 1
0.5%
1144 1
0.5%
1067 1
0.5%

Interactions

2023-12-12T17:49:50.160918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Missing values

2023-12-12T17:49:50.310631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T17:49:50.416762image/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

사건년도금융기관차주건수
02020(주)아주저축은행1
12020(주)에스비아이저축은행476
22020(주)케이비손해보험68
32020BYC생명1
42020IBK캐피탈1
52020KEB하나은행69
62020SC은행298
72020가평군산림조합1
82020강릉시산림조합1
92020강원신용보증재단47
사건년도금융기관차주건수
1902020한중상호19
1912020한진상호1
1922020한화손해보험(주)88
1932020함안군산림조합2
1942020항도종금3
1952020현대스위스상호271
1962020현대캐피탈4061
1972020현대해상화재보험(주)113
1982020횡성군산림조합1
1992020희망모아10167