Overview

Dataset statistics

Number of variables6
Number of observations7694
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory383.3 KiB
Average record size in memory51.0 B

Variable types

Numeric3
Categorical3

Dataset

Description중소벤처기업부 정책자금 운용계획 공고 기준에 따른 소재부품장비산업 영위기업 지원현황으로 업력별 연도별 월별 업종별로 정책자금을 지원한 리스트 현황
Author중소벤처기업진흥공단
URLhttps://www.data.go.kr/data/15063414/fileData.do

Alerts

일련번호 has unique valuesUnique

Reproduction

Analysis started2023-12-12 05:45:43.955412
Analysis finished2023-12-12 05:45:45.902548
Duration1.95 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

일련번호
Real number (ℝ)

UNIQUE 

Distinct7694
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3847.5
Minimum1
Maximum7694
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size67.8 KiB
2023-12-12T14:45:46.008436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile385.65
Q11924.25
median3847.5
Q35770.75
95-th percentile7309.35
Maximum7694
Range7693
Interquartile range (IQR)3846.5

Descriptive statistics

Standard deviation2221.2108
Coefficient of variation (CV)0.57731275
Kurtosis-1.2
Mean3847.5
Median Absolute Deviation (MAD)1923.5
Skewness0
Sum29602665
Variance4933777.5
MonotonicityStrictly increasing
2023-12-12T14:45:46.216483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
< 0.1%
5291 1
 
< 0.1%
5139 1
 
< 0.1%
5138 1
 
< 0.1%
5137 1
 
< 0.1%
5136 1
 
< 0.1%
5135 1
 
< 0.1%
5134 1
 
< 0.1%
5133 1
 
< 0.1%
5132 1
 
< 0.1%
Other values (7684) 7684
99.9%
ValueCountFrequency (%)
1 1
< 0.1%
2 1
< 0.1%
3 1
< 0.1%
4 1
< 0.1%
5 1
< 0.1%
6 1
< 0.1%
7 1
< 0.1%
8 1
< 0.1%
9 1
< 0.1%
10 1
< 0.1%
ValueCountFrequency (%)
7694 1
< 0.1%
7693 1
< 0.1%
7692 1
< 0.1%
7691 1
< 0.1%
7690 1
< 0.1%
7689 1
< 0.1%
7688 1
< 0.1%
7687 1
< 0.1%
7686 1
< 0.1%
7685 1
< 0.1%

지역
Categorical

Distinct17
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size60.2 KiB
경기
2030 
경남
1094 
경북
756 
서울
653 
인천
404 
Other values (12)
2757 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row경기
2nd row대전
3rd row강원
4th row경북
5th row경북

Common Values

ValueCountFrequency (%)
경기 2030
26.4%
경남 1094
14.2%
경북 756
 
9.8%
서울 653
 
8.5%
인천 404
 
5.3%
부산 384
 
5.0%
충남 384
 
5.0%
대구 381
 
5.0%
충북 331
 
4.3%
울산 271
 
3.5%
Other values (7) 1006
13.1%

Length

2023-12-12T14:45:46.675107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
경기 2030
26.4%
경남 1094
14.2%
경북 756
 
9.8%
서울 653
 
8.5%
인천 404
 
5.3%
부산 384
 
5.0%
충남 384
 
5.0%
대구 381
 
5.0%
충북 331
 
4.3%
울산 271
 
3.5%
Other values (7) 1006
13.1%

업력
Categorical

Distinct8
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size60.2 KiB
3년미만
1595 
5년미만
1249 
7년미만
1040 
1년미만
919 
20년이상
914 
Other values (3)
1977 

Length

Max length5
Median length4
Mean length4.3757473
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row20년이상
2nd row7년미만
3rd row20년이상
4th row20년미만
5th row20년미만

Common Values

ValueCountFrequency (%)
3년미만 1595
20.7%
5년미만 1249
16.2%
7년미만 1040
13.5%
1년미만 919
11.9%
20년이상 914
11.9%
15년미만 784
10.2%
10년미만 644
8.4%
20년미만 549
 
7.1%

Length

2023-12-12T14:45:46.825666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T14:45:46.996842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3년미만 1595
20.7%
5년미만 1249
16.2%
7년미만 1040
13.5%
1년미만 919
11.9%
20년이상 914
11.9%
15년미만 784
10.2%
10년미만 644
8.4%
20년미만 549
 
7.1%

대출일자
Real number (ℝ)

Distinct184
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20230480
Minimum20230103
Maximum20230927
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size67.8 KiB
2023-12-12T14:45:47.184149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20230103
5-th percentile20230203
Q120230307
median20230414
Q320230628
95-th percentile20230920
Maximum20230927
Range824
Interquartile range (IQR)321

Descriptive statistics

Standard deviation241.72899
Coefficient of variation (CV)1.1948752 × 10-5
Kurtosis-0.97355442
Mean20230480
Median Absolute Deviation (MAD)193
Skewness0.50093123
Sum1.5565331 × 1011
Variance58432.903
MonotonicityNot monotonic
2023-12-12T14:45:47.328671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20230227 109
 
1.4%
20230329 107
 
1.4%
20230228 103
 
1.3%
20230927 101
 
1.3%
20230310 98
 
1.3%
20230313 96
 
1.2%
20230217 95
 
1.2%
20230628 93
 
1.2%
20230309 93
 
1.2%
20230210 90
 
1.2%
Other values (174) 6709
87.2%
ValueCountFrequency (%)
20230103 1
 
< 0.1%
20230104 1
 
< 0.1%
20230105 1
 
< 0.1%
20230106 10
0.1%
20230109 7
 
0.1%
20230110 6
 
0.1%
20230111 3
 
< 0.1%
20230112 4
 
0.1%
20230113 18
0.2%
20230116 7
 
0.1%
ValueCountFrequency (%)
20230927 101
1.3%
20230926 78
1.0%
20230925 64
0.8%
20230922 87
1.1%
20230921 43
0.6%
20230920 41
0.5%
20230919 39
 
0.5%
20230918 25
 
0.3%
20230915 24
 
0.3%
20230914 34
 
0.4%

대출금액(백만원)
Real number (ℝ)

Distinct419
Distinct (%)5.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean262.04906
Minimum1
Maximum9200
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size67.8 KiB
2023-12-12T14:45:47.492289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile50
Q1100
median101
Q3250
95-th percentile1000
Maximum9200
Range9199
Interquartile range (IQR)150

Descriptive statistics

Standard deviation435.13701
Coefficient of variation (CV)1.6605173
Kurtosis75.696713
Mean262.04906
Median Absolute Deviation (MAD)51
Skewness6.6817253
Sum2016205.5
Variance189344.22
MonotonicityNot monotonic
2023-12-12T14:45:47.656060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
100.0 2672
34.7%
200.0 1184
15.4%
50.0 793
 
10.3%
300.0 581
 
7.6%
150.0 539
 
7.0%
500.0 247
 
3.2%
70.0 140
 
1.8%
250.0 109
 
1.4%
1000.0 100
 
1.3%
80.0 95
 
1.2%
Other values (409) 1234
16.0%
ValueCountFrequency (%)
1.0 1
 
< 0.1%
10.0 4
0.1%
11.0 1
 
< 0.1%
15.0 1
 
< 0.1%
16.0 1
 
< 0.1%
17.0 1
 
< 0.1%
18.0 1
 
< 0.1%
20.0 5
0.1%
21.0 1
 
< 0.1%
24.0 1
 
< 0.1%
ValueCountFrequency (%)
9200.0 1
< 0.1%
8000.0 1
< 0.1%
7000.0 1
< 0.1%
6330.0 1
< 0.1%
6000.0 2
< 0.1%
5900.0 1
< 0.1%
5082.0 1
< 0.1%
5000.0 1
< 0.1%
4500.0 1
< 0.1%
3700.0 1
< 0.1%

업종
Categorical

Distinct9
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size60.2 KiB
기계
2409 
금속
1714 
전자
839 
정보
834 
화공
815 
Other values (4)
1083 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row기계
2nd row화공
3rd row화공
4th row금속
5th row금속

Common Values

ValueCountFrequency (%)
기계 2409
31.3%
금속 1714
22.3%
전자 839
 
10.9%
정보 834
 
10.8%
화공 815
 
10.6%
전기 696
 
9.0%
섬유 214
 
2.8%
잡화 131
 
1.7%
기타 42
 
0.5%

Length

2023-12-12T14:45:47.790684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T14:45:47.922548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
기계 2409
31.3%
금속 1714
22.3%
전자 839
 
10.9%
정보 834
 
10.8%
화공 815
 
10.6%
전기 696
 
9.0%
섬유 214
 
2.8%
잡화 131
 
1.7%
기타 42
 
0.5%

Interactions

2023-12-12T14:45:45.310437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:45:44.555733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:45:44.957731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:45:45.437104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:45:44.714469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:45:45.096220image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:45:45.559517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:45:44.827294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T14:45:45.203455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T14:45:48.054567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
일련번호지역업력대출일자대출금액(백만원)업종
일련번호1.0000.1790.5780.7460.1970.172
지역0.1791.0000.1160.1380.0390.478
업력0.5780.1161.0000.0930.0600.141
대출일자0.7460.1380.0931.0000.1410.043
대출금액(백만원)0.1970.0390.0600.1411.0000.053
업종0.1720.4780.1410.0430.0531.000
2023-12-12T14:45:48.176572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업력업종지역
업력1.0000.0690.049
업종0.0691.0000.212
지역0.0490.2121.000
2023-12-12T14:45:48.276756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
일련번호대출일자대출금액(백만원)지역업력업종
일련번호1.0000.140-0.1220.0700.3220.078
대출일자0.1401.0000.0270.0540.0440.019
대출금액(백만원)-0.1220.0271.0000.0150.0280.024
지역0.0700.0540.0151.0000.0490.212
업력0.3220.0440.0280.0491.0000.069
업종0.0780.0190.0240.2120.0691.000

Missing values

2023-12-12T14:45:45.712604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T14:45:45.841659image/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

일련번호지역업력대출일자대출금액(백만원)업종
01경기20년이상20230227720.0기계
12대전7년미만202309141800.0화공
23강원20년이상20230719274.0화공
34경북20년미만20230131100.0금속
45경북20년미만20230131300.0금속
56강원7년미만20230113386.0화공
67부산15년미만20230119150.0금속
78대전10년미만20230113300.0기계
89인천20년이상20230120260.0기계
910대전20년이상20230113300.0화공
일련번호지역업력대출일자대출금액(백만원)업종
76847685서울15년미만20230919300.0전자
76857686서울20년이상20230922400.0전자
76867687강원3년미만20230920100.0정보
76877688서울20년이상20230927500.0기계
76887689강원10년미만20230927500.0기계
76897690강원15년미만20230927200.0정보
76907691경기15년미만20230925500.0금속
76917692경기10년미만20230927300.0금속
76927693전북5년미만20230926200.0금속
76937694전북3년미만2023092670.0금속