Overview

Dataset statistics

Number of variables4
Number of observations31
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.2 KiB
Average record size in memory39.3 B

Variable types

Categorical1
Text1
Numeric2

Dataset

Description지역본지부 제증명(원리금상환내역서,금융거래확인서) 온라인 발급 통계 자료
Author중소벤처기업진흥공단
URLhttps://www.data.go.kr/data/15040520/fileData.do

Alerts

년도 has constant value ""Constant
금융거래확인서 is highly overall correlated with 원리금회수내역확인서High correlation
원리금회수내역확인서 is highly overall correlated with 금융거래확인서High correlation
지역본(지)부 has unique valuesUnique
금융거래확인서 has unique valuesUnique
원리금회수내역확인서 has unique valuesUnique

Reproduction

Analysis started2023-12-12 12:27:07.315222
Analysis finished2023-12-12 12:27:08.227108
Duration0.91 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

년도
Categorical

CONSTANT 

Distinct1
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size380.0 B
2019
31 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2019
2nd row2019
3rd row2019
4th row2019
5th row2019

Common Values

ValueCountFrequency (%)
2019 31
100.0%

Length

2023-12-12T21:27:08.346641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:27:08.487390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2019 31
100.0%

지역본(지)부
Text

UNIQUE 

Distinct31
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size380.0 B
2023-12-12T21:27:08.737724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length6
Mean length6.0967742
Min length6

Characters and Unicode

Total characters189
Distinct characters26
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

Unique31 ?
Unique (%)100.0%

Sample

1st row서울지역본부
2nd row서울동남부지부
3rd row서울북부지부
4th row인천지역본부
5th row인천서부지부
ValueCountFrequency (%)
서울지역본부 1
 
3.2%
경북지역본부 1
 
3.2%
경남서부지부 1
 
3.2%
경남동부지부 1
 
3.2%
경남지역본부 1
 
3.2%
울산지역본부 1
 
3.2%
부산동부지부 1
 
3.2%
부산지역본부 1
 
3.2%
전남동부지부 1
 
3.2%
전남지역본부 1
 
3.2%
Other values (21) 21
67.7%
2023-12-12T21:27:09.224860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
부 47
24.9%
지 31
16.4%
역 16
 
8.5%
본 16
 
8.5%
북 10
 
5.3%
경 10
 
5.3%
남 8
 
4.2%
서 7
 
3.7%
동 7
 
3.7%
전 5
 
2.6%
Other values (16) 32
16.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 189
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
부 47
24.9%
지 31
16.4%
역 16
 
8.5%
본 16
 
8.5%
북 10
 
5.3%
경 10
 
5.3%
남 8
 
4.2%
서 7
 
3.7%
동 7
 
3.7%
전 5
 
2.6%
Other values (16) 32
16.9%

Most occurring scripts

ValueCountFrequency (%)
Hangul 189
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
부 47
24.9%
지 31
16.4%
역 16
 
8.5%
본 16
 
8.5%
북 10
 
5.3%
경 10
 
5.3%
남 8
 
4.2%
서 7
 
3.7%
동 7
 
3.7%
전 5
 
2.6%
Other values (16) 32
16.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 189
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
부 47
24.9%
지 31
16.4%
역 16
 
8.5%
본 16
 
8.5%
북 10
 
5.3%
경 10
 
5.3%
남 8
 
4.2%
서 7
 
3.7%
동 7
 
3.7%
전 5
 
2.6%
Other values (16) 32
16.9%

금융거래확인서
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct31
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1176.6129
Minimum212
Maximum3123
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size411.0 B
2023-12-12T21:27:09.394912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum212
5-th percentile399.5
Q1679
median1174
Q31561.5
95-th percentile1974
Maximum3123
Range2911
Interquartile range (IQR)882.5

Descriptive statistics

Standard deviation602.65832
Coefficient of variation (CV)0.51219761
Kurtosis2.1653546
Mean1176.6129
Median Absolute Deviation (MAD)422
Skewness1.0114456
Sum36475
Variance363197.05
MonotonicityNot monotonic
2023-12-12T21:27:09.553438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
1907 1
 
3.2%
1577 1
 
3.2%
297 1
 
3.2%
788 1
 
3.2%
1029 1
 
3.2%
1216 1
 
3.2%
1215 1
 
3.2%
502 1
 
3.2%
1498 1
 
3.2%
817 1
 
3.2%
Other values (21) 21
67.7%
ValueCountFrequency (%)
212 1
3.2%
297 1
3.2%
502 1
3.2%
618 1
3.2%
621 1
3.2%
639 1
3.2%
646 1
3.2%
667 1
3.2%
691 1
3.2%
788 1
3.2%
ValueCountFrequency (%)
3123 1
3.2%
2041 1
3.2%
1907 1
3.2%
1859 1
3.2%
1635 1
3.2%
1619 1
3.2%
1596 1
3.2%
1577 1
3.2%
1546 1
3.2%
1498 1
3.2%

원리금회수내역확인서
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct31
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean741.67742
Minimum146
Maximum1763
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size411.0 B
2023-12-12T21:27:09.743996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum146
5-th percentile240.5
Q1426.5
median836
Q3984
95-th percentile1228.5
Maximum1763
Range1617
Interquartile range (IQR)557.5

Descriptive statistics

Standard deviation376.78353
Coefficient of variation (CV)0.50801537
Kurtosis0.103082
Mean741.67742
Median Absolute Deviation (MAD)309
Skewness0.49517982
Sum22992
Variance141965.83
MonotonicityNot monotonic
2023-12-12T21:27:09.926322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
1145 1
 
3.2%
900 1
 
3.2%
186 1
 
3.2%
515 1
 
3.2%
871 1
 
3.2%
968 1
 
3.2%
1000 1
 
3.2%
383 1
 
3.2%
1242 1
 
3.2%
340 1
 
3.2%
Other values (21) 21
67.7%
ValueCountFrequency (%)
146 1
3.2%
186 1
3.2%
295 1
3.2%
307 1
3.2%
340 1
3.2%
363 1
3.2%
383 1
3.2%
405 1
3.2%
448 1
3.2%
452 1
3.2%
ValueCountFrequency (%)
1763 1
3.2%
1242 1
3.2%
1215 1
3.2%
1195 1
3.2%
1145 1
3.2%
1118 1
3.2%
1011 1
3.2%
1000 1
3.2%
968 1
3.2%
903 1
3.2%

Interactions

2023-12-12T21:27:07.755552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:27:07.492143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:27:07.892909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:27:07.610729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T21:27:10.064828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지역본(지)부금융거래확인서원리금회수내역확인서
지역본(지)부1.0001.0001.000
금융거래확인서1.0001.0000.737
원리금회수내역확인서1.0000.7371.000
2023-12-12T21:27:10.188608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
금융거래확인서원리금회수내역확인서
금융거래확인서1.0000.895
원리금회수내역확인서0.8951.000

Missing values

2023-12-12T21:27:08.060822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T21:27:08.179640image/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

년도지역본(지)부금융거래확인서원리금회수내역확인서
02019서울지역본부19071145
12019서울동남부지부1577900
22019서울북부지부873588
32019인천지역본부16351195
42019인천서부지부935598
52019경기지역본부31231763
62019경기동부지부1406837
72019경기서부지부16191011
82019경기북부지부18591118
92019대전세종지역본부1596901
년도지역본(지)부금융거래확인서원리금회수내역확인서
212019광주지역본부2041903
222019전남지역본부639307
232019전남동부지부817340
242019부산지역본부14981242
252019부산동부지부502383
262019울산지역본부12151000
272019경남지역본부1216968
282019경남동부지부1029871
292019경남서부지부788515
302019제주지역본부297186