Overview

Dataset statistics

Number of variables7
Number of observations155
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory9.2 KiB
Average record size in memory60.9 B

Variable types

Numeric4
Categorical2
DateTime1

Dataset

Description중소벤처기업진흥공단이 원전 협력 중소기업을 대상으로 지원한 정책자금의 지역별, 업종별 데이터를 통계자료로 활용할 수 있도록 개방
Author중소벤처기업진흥공단
URLhttps://www.data.go.kr/data/15108043/fileData.do

Alerts

지원금액(시설_백만원) is highly overall correlated with 지원금액(운전_백만원) and 1 other fieldsHigh correlation
지원금액(운전_백만원) is highly overall correlated with 지원금액(시설_백만원)High correlation
지원금액(합계_백만원) is highly overall correlated with 지원금액(시설_백만원)High correlation
순번 has unique valuesUnique
지원금액(시설_백만원) has 120 (77.4%) zerosZeros
지원금액(운전_백만원) has 35 (22.6%) zerosZeros

Reproduction

Analysis started2023-12-12 04:33:13.596682
Analysis finished2023-12-12 04:33:15.853150
Duration2.26 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

UNIQUE 

Distinct155
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean78
Minimum1
Maximum155
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2023-12-12T13:33:15.936160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile8.7
Q139.5
median78
Q3116.5
95-th percentile147.3
Maximum155
Range154
Interquartile range (IQR)77

Descriptive statistics

Standard deviation44.888751
Coefficient of variation (CV)0.57549681
Kurtosis-1.2
Mean78
Median Absolute Deviation (MAD)39
Skewness0
Sum12090
Variance2015
MonotonicityStrictly increasing
2023-12-12T13:33:16.116013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.6%
108 1
 
0.6%
101 1
 
0.6%
102 1
 
0.6%
103 1
 
0.6%
104 1
 
0.6%
105 1
 
0.6%
106 1
 
0.6%
107 1
 
0.6%
109 1
 
0.6%
Other values (145) 145
93.5%
ValueCountFrequency (%)
1 1
0.6%
2 1
0.6%
3 1
0.6%
4 1
0.6%
5 1
0.6%
6 1
0.6%
7 1
0.6%
8 1
0.6%
9 1
0.6%
10 1
0.6%
ValueCountFrequency (%)
155 1
0.6%
154 1
0.6%
153 1
0.6%
152 1
0.6%
151 1
0.6%
150 1
0.6%
149 1
0.6%
148 1
0.6%
147 1
0.6%
146 1
0.6%

업력
Categorical

Distinct8
Distinct (%)5.2%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
20년이상
56 
20년미만
20 
5년미만
19 
15년미만
18 
3년미만
12 
Other values (3)
30 

Length

Max length5
Median length5
Mean length4.6774194
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row20년미만
2nd row20년미만
3rd row15년미만
4th row20년미만
5th row20년미만

Common Values

ValueCountFrequency (%)
20년이상 56
36.1%
20년미만 20
 
12.9%
5년미만 19
 
12.3%
15년미만 18
 
11.6%
3년미만 12
 
7.7%
10년미만 11
 
7.1%
7년미만 11
 
7.1%
1년미만 8
 
5.2%

Length

2023-12-12T13:33:16.300944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:33:16.448021image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20년이상 56
36.1%
20년미만 20
 
12.9%
5년미만 19
 
12.3%
15년미만 18
 
11.6%
3년미만 12
 
7.7%
10년미만 11
 
7.1%
7년미만 11
 
7.1%
1년미만 8
 
5.2%

업종
Categorical

Distinct11
Distinct (%)7.1%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
금속
43 
기계
30 
기타
25 
정보
17 
전기
16 
Other values (6)
24 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique2 ?
Unique (%)1.3%

Sample

1st row금속
2nd row금속
3rd row전기
4th row기타
5th row기타

Common Values

ValueCountFrequency (%)
금속 43
27.7%
기계 30
19.4%
기타 25
16.1%
정보 17
 
11.0%
전기 16
 
10.3%
전자 10
 
6.5%
화공 7
 
4.5%
섬유 3
 
1.9%
유통 2
 
1.3%
식료 1
 
0.6%

Length

2023-12-12T13:33:16.622108image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
금속 43
27.7%
기계 30
19.4%
기타 25
16.1%
정보 17
 
11.0%
전기 16
 
10.3%
전자 10
 
6.5%
화공 7
 
4.5%
섬유 3
 
1.9%
유통 2
 
1.3%
식료 1
 
0.6%

지원일자
Date

Distinct94
Distinct (%)60.6%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
Minimum2023-01-13 00:00:00
Maximum2023-10-31 00:00:00
2023-12-12T13:33:16.765567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:33:16.908345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

지원금액(시설_백만원)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct29
Distinct (%)18.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean256.35484
Minimum0
Maximum9200
Zeros120
Zeros (%)77.4%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2023-12-12T13:33:17.038853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1600
Maximum9200
Range9200
Interquartile range (IQR)0

Descriptive statistics

Standard deviation879.60709
Coefficient of variation (CV)3.4312092
Kurtosis70.264601
Mean256.35484
Median Absolute Deviation (MAD)0
Skewness7.4210454
Sum39735
Variance773708.64
MonotonicityNot monotonic
2023-12-12T13:33:17.183569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
0.0 120
77.4%
800.0 3
 
1.9%
700.0 2
 
1.3%
500.0 2
 
1.3%
2200.0 2
 
1.3%
1600.0 2
 
1.3%
2000.0 2
 
1.3%
747.0 1
 
0.6%
450.0 1
 
0.6%
520.0 1
 
0.6%
Other values (19) 19
 
12.3%
ValueCountFrequency (%)
0.0 120
77.4%
110.0 1
 
0.6%
153.0 1
 
0.6%
176.0 1
 
0.6%
195.0 1
 
0.6%
200.0 1
 
0.6%
252.388 1
 
0.6%
300.0 1
 
0.6%
323.0 1
 
0.6%
400.0 1
 
0.6%
ValueCountFrequency (%)
9200.0 1
 
0.6%
2500.0 1
 
0.6%
2400.0 1
 
0.6%
2200.0 2
1.3%
2000.0 2
1.3%
1600.0 2
1.3%
1300.0 1
 
0.6%
1230.0 1
 
0.6%
800.0 3
1.9%
747.0 1
 
0.6%

지원금액(운전_백만원)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct17
Distinct (%)11.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean207.28387
Minimum0
Maximum1300
Zeros35
Zeros (%)22.6%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2023-12-12T13:33:17.339056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q154.5
median200
Q3300
95-th percentile500
Maximum1300
Range1300
Interquartile range (IQR)245.5

Descriptive statistics

Standard deviation202.28496
Coefficient of variation (CV)0.97588374
Kurtosis6.7052578
Mean207.28387
Median Absolute Deviation (MAD)100
Skewness1.9207207
Sum32129
Variance40919.205
MonotonicityNot monotonic
2023-12-12T13:33:17.503609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
0 35
22.6%
300 30
19.4%
200 26
16.8%
100 22
14.2%
500 15
9.7%
400 6
 
3.9%
150 6
 
3.9%
50 4
 
2.6%
70 2
 
1.3%
1000 2
 
1.3%
Other values (7) 7
 
4.5%
ValueCountFrequency (%)
0 35
22.6%
50 4
 
2.6%
59 1
 
0.6%
60 1
 
0.6%
70 2
 
1.3%
100 22
14.2%
130 1
 
0.6%
150 6
 
3.9%
200 26
16.8%
240 1
 
0.6%
ValueCountFrequency (%)
1300 1
 
0.6%
1000 2
 
1.3%
550 1
 
0.6%
500 15
9.7%
400 6
 
3.9%
300 30
19.4%
250 1
 
0.6%
240 1
 
0.6%
200 26
16.8%
150 6
 
3.9%

지원금액(합계_백만원)
Real number (ℝ)

HIGH CORRELATION 

Distinct39
Distinct (%)25.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean463.63871
Minimum50
Maximum9200
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2023-12-12T13:33:17.672351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum50
5-th percentile91
Q1164.5
median300
Q3500
95-th percentile1600
Maximum9200
Range9150
Interquartile range (IQR)335.5

Descriptive statistics

Standard deviation841.22606
Coefficient of variation (CV)1.8144
Kurtosis76.371448
Mean463.63871
Median Absolute Deviation (MAD)150
Skewness7.7648227
Sum71864
Variance707661.29
MonotonicityNot monotonic
2023-12-12T13:33:17.840063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
ValueCountFrequency (%)
300.0 31
20.0%
200.0 27
17.4%
100.0 22
14.2%
500.0 17
11.0%
400.0 7
 
4.5%
150.0 6
 
3.9%
50.0 4
 
2.6%
800.0 3
 
1.9%
1300.0 2
 
1.3%
70.0 2
 
1.3%
Other values (29) 34
21.9%
ValueCountFrequency (%)
50.0 4
 
2.6%
59.0 1
 
0.6%
60.0 1
 
0.6%
70.0 2
 
1.3%
100.0 22
14.2%
110.0 1
 
0.6%
130.0 1
 
0.6%
150.0 6
 
3.9%
153.0 1
 
0.6%
176.0 1
 
0.6%
ValueCountFrequency (%)
9200.0 1
 
0.6%
2500.0 1
 
0.6%
2400.0 1
 
0.6%
2200.0 2
1.3%
2000.0 2
1.3%
1600.0 2
1.3%
1300.0 2
1.3%
1230.0 1
 
0.6%
1000.0 2
1.3%
800.0 3
1.9%

Interactions

2023-12-12T13:33:14.798415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:33:13.836653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:33:14.188639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:33:14.485492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:33:14.882694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:33:13.931962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:33:14.278763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:33:14.568231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:33:15.281120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:33:14.016265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:33:14.344412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:33:14.636291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:33:15.464337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:33:14.109580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:33:14.420378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:33:14.715459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T13:33:17.962018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번업력업종지원일자지원금액(시설_백만원)지원금액(운전_백만원)지원금액(합계_백만원)
순번1.0000.5570.2120.8010.0000.2640.000
업력0.5571.0000.3570.6630.0000.2460.000
업종0.2120.3571.0000.8090.0000.1450.000
지원일자0.8010.6630.8091.0000.9030.0000.902
지원금액(시설_백만원)0.0000.0000.0000.9031.0000.0000.997
지원금액(운전_백만원)0.2640.2460.1450.0000.0001.0000.500
지원금액(합계_백만원)0.0000.0000.0000.9020.9970.5001.000
2023-12-12T13:33:18.095436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업력업종
업력1.0000.174
업종0.1741.000
2023-12-12T13:33:18.204898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번지원금액(시설_백만원)지원금액(운전_백만원)지원금액(합계_백만원)업력업종
순번1.0000.111-0.1360.0040.3070.094
지원금액(시설_백만원)0.1111.000-0.7260.5470.0000.000
지원금액(운전_백만원)-0.136-0.7261.0000.1550.1320.068
지원금액(합계_백만원)0.0040.5470.1551.0000.0000.000
업력0.3070.0000.1320.0001.0000.174
업종0.0940.0000.0680.0000.1741.000

Missing values

2023-12-12T13:33:15.615578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T13:33:15.793728image/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

순번업력업종지원일자지원금액(시설_백만원)지원금액(운전_백만원)지원금액(합계_백만원)
0120년미만금속2023-08-250.0240240.0
1220년미만금속2023-08-25600.00600.0
2315년미만전기2023-02-160.0400400.0
3420년미만기타2023-02-150.0200200.0
4520년미만기타2023-02-152400.002400.0
5620년이상기계2023-02-220.0500500.0
6720년이상기계2023-02-080.0100100.0
783년미만화공2023-02-220.0100100.0
8910년미만기타2023-03-020.0150150.0
91020년이상기계2023-04-171300.001300.0
순번업력업종지원일자지원금액(시설_백만원)지원금액(운전_백만원)지원금액(합계_백만원)
14514620년이상화공2023-09-080.0200200.0
14614720년미만기계2023-09-200.0100100.0
14714820년이상기계2023-09-250.0400400.0
14814920년미만기계2023-09-210.0300300.0
14915020년이상전기2023-10-110.0500500.0
15015120년이상기타2023-10-270.0300300.0
1511527년미만기계2023-05-170.0300300.0
15215310년미만전기2023-09-130.0300300.0
15315420년미만기타2023-08-310.0550550.0
15415520년이상금속2023-09-060.0300300.0