Overview

Dataset statistics

Number of variables3
Number of observations24
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory756.0 B
Average record size in memory31.5 B

Variable types

Text1
Numeric2

Dataset

Description중소벤처기업진흥공단 융자 종류인 매출채권팩토링 지원기업의 데이터를 제공합니다. 동 데이터는 2022년 팩토링 지원기업의 업종별 현황을 나타냅니다.
Author중소벤처기업진흥공단
URLhttps://www.data.go.kr/data/15124913/fileData.do

Alerts

업종 has unique valuesUnique
판매업체_개수 has 4 (16.7%) zerosZeros
구매업체_개수 has 6 (25.0%) zerosZeros

Reproduction

Analysis started2023-12-12 10:31:39.935091
Analysis finished2023-12-12 10:31:40.780853
Duration0.85 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업종
Text

UNIQUE 

Distinct24
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size324.0 B
2023-12-12T19:31:40.921389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length7.1666667
Min length2

Characters and Unicode

Total characters172
Distinct characters65
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique24 ?
Unique (%)100.0%

Sample

1st row1차금속제조업
2nd row기타과학기술서비스업
3rd row고무및플라스틱제품제조업
4th row금속가공제품 제조업
5th row기타기계제조업
ValueCountFrequency (%)
1차금속제조업 1
 
4.0%
식료품제조업 1
 
4.0%
종이제품제조업 1
 
4.0%
출판업 1
 
4.0%
통신장비제조업 1
 
4.0%
전기장비제조업 1
 
4.0%
전문직별공사업 1
 
4.0%
자동차제조업 1
 
4.0%
자동차및부품판매업 1
 
4.0%
의복제조업 1
 
4.0%
Other values (15) 15
60.0%
2023-12-12T19:31:41.295987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
업 25
 
14.5%
제 21
 
12.2%
조 15
 
8.7%
품 9
 
5.2%
기 8
 
4.7%
비 6
 
3.5%
학 3
 
1.7%
매 3
 
1.7%
스 3
 
1.7%
장 3
 
1.7%
Other values (55) 76
44.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 170
98.8%
Decimal Number 1
 
0.6%
Space Separator 1
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
업 25
 
14.7%
제 21
 
12.4%
조 15
 
8.8%
품 9
 
5.3%
기 8
 
4.7%
비 6
 
3.5%
학 3
 
1.8%
매 3
 
1.8%
스 3
 
1.8%
장 3
 
1.8%
Other values (53) 74
43.5%
Decimal Number
ValueCountFrequency (%)
1 1
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 170
98.8%
Common 2
 
1.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
업 25
 
14.7%
제 21
 
12.4%
조 15
 
8.8%
품 9
 
5.3%
기 8
 
4.7%
비 6
 
3.5%
학 3
 
1.8%
매 3
 
1.8%
스 3
 
1.8%
장 3
 
1.8%
Other values (53) 74
43.5%
Common
ValueCountFrequency (%)
1 1
50.0%
1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 170
98.8%
ASCII 2
 
1.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
업 25
 
14.7%
제 21
 
12.4%
조 15
 
8.8%
품 9
 
5.3%
기 8
 
4.7%
비 6
 
3.5%
학 3
 
1.8%
매 3
 
1.8%
스 3
 
1.8%
장 3
 
1.8%
Other values (53) 74
43.5%
ASCII
ValueCountFrequency (%)
1 1
50.0%
1
50.0%

판매업체_개수
Real number (ℝ)

ZEROS 

Distinct11
Distinct (%)45.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.5416667
Minimum0
Maximum35
Zeros4
Zeros (%)16.7%
Negative0
Negative (%)0.0%
Memory size348.0 B
2023-12-12T19:31:41.444370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median1.5
Q36.25
95-th percentile11
Maximum35
Range35
Interquartile range (IQR)5.25

Descriptive statistics

Standard deviation7.3778704
Coefficient of variation (CV)1.6244852
Kurtosis13.101945
Mean4.5416667
Median Absolute Deviation (MAD)1.5
Skewness3.3273383
Sum109
Variance54.432971
MonotonicityNot monotonic
2023-12-12T19:31:41.554914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
1 8
33.3%
0 4
16.7%
11 2
 
8.3%
3 2
 
8.3%
2 2
 
8.3%
4 1
 
4.2%
7 1
 
4.2%
8 1
 
4.2%
35 1
 
4.2%
6 1
 
4.2%
ValueCountFrequency (%)
0 4
16.7%
1 8
33.3%
2 2
 
8.3%
3 2
 
8.3%
4 1
 
4.2%
6 1
 
4.2%
7 1
 
4.2%
8 1
 
4.2%
9 1
 
4.2%
11 2
 
8.3%
ValueCountFrequency (%)
35 1
 
4.2%
11 2
 
8.3%
9 1
 
4.2%
8 1
 
4.2%
7 1
 
4.2%
6 1
 
4.2%
4 1
 
4.2%
3 2
 
8.3%
2 2
 
8.3%
1 8
33.3%

구매업체_개수
Real number (ℝ)

ZEROS 

Distinct8
Distinct (%)33.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.4166667
Minimum0
Maximum10
Zeros6
Zeros (%)25.0%
Negative0
Negative (%)0.0%
Memory size348.0 B
2023-12-12T19:31:41.682048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10.75
median1
Q33
95-th percentile8.85
Maximum10
Range10
Interquartile range (IQR)2.25

Descriptive statistics

Standard deviation2.9179604
Coefficient of variation (CV)1.2074319
Kurtosis1.6116078
Mean2.4166667
Median Absolute Deviation (MAD)1
Skewness1.5758868
Sum58
Variance8.5144928
MonotonicityNot monotonic
2023-12-12T19:31:41.804266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
1 7
29.2%
0 6
25.0%
2 4
16.7%
3 2
 
8.3%
5 2
 
8.3%
9 1
 
4.2%
8 1
 
4.2%
10 1
 
4.2%
ValueCountFrequency (%)
0 6
25.0%
1 7
29.2%
2 4
16.7%
3 2
 
8.3%
5 2
 
8.3%
8 1
 
4.2%
9 1
 
4.2%
10 1
 
4.2%
ValueCountFrequency (%)
10 1
 
4.2%
9 1
 
4.2%
8 1
 
4.2%
5 2
 
8.3%
3 2
 
8.3%
2 4
16.7%
1 7
29.2%
0 6
25.0%

Interactions

2023-12-12T19:31:40.190403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:31:40.031132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:31:40.278610image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:31:40.113655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T19:31:41.899628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업종판매업체_개수구매업체_개수
업종1.0001.0001.000
판매업체_개수1.0001.0000.530
구매업체_개수1.0000.5301.000
2023-12-12T19:31:42.015714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
판매업체_개수구매업체_개수
판매업체_개수1.0000.383
구매업체_개수0.3831.000

Missing values

2023-12-12T19:31:40.659412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T19:31:40.737393image/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

업종판매업체_개수구매업체_개수
01차금속제조업119
1기타과학기술서비스업10
2고무및플라스틱제품제조업43
3금속가공제품 제조업72
4기타기계제조업82
5기타운송장비제조업01
6농업10
7도매및상품중개업358
8비금속광물제품제조업01
9사업지원서비스업10
업종판매업체_개수구매업체_개수
14의료정밀광학기기제조업01
15의복제조업20
16자동차및부품판매업11
17자동차제조업33
18전문직별공사업05
19전기장비제조업60
20통신장비제조업95
21출판업11
22종이제품제조업11
23화학제품제조업111