Overview

Dataset statistics

Number of variables7
Number of observations744
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory43.7 KiB
Average record size in memory60.2 B

Variable types

Numeric4
Categorical2
DateTime1

Dataset

Description중소벤처기업진흥공단의 정책자금 중 비대면창업자금의 업종, 업력, 지원금액 등의 지원 실적을 공공에 개방하여, 통계자료로 활용하고자 함
Author중소벤처기업진흥공단
URLhttps://www.data.go.kr/data/15108238/fileData.do

Alerts

지원금액(시설_백만원) is highly overall correlated with 지원금액(운전_백만원)High correlation
지원금액(운전_백만원) is highly overall correlated with 지원금액(시설_백만원)High correlation
순번 has unique valuesUnique
지원금액(시설_백만원) has 665 (89.4%) zerosZeros
지원금액(운전_백만원) has 79 (10.6%) zerosZeros

Reproduction

Analysis started2023-12-12 23:58:01.497589
Analysis finished2023-12-12 23:58:03.268064
Duration1.77 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

UNIQUE 

Distinct744
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean372.5
Minimum1
Maximum744
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.7 KiB
2023-12-13T08:58:03.327469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile38.15
Q1186.75
median372.5
Q3558.25
95-th percentile706.85
Maximum744
Range743
Interquartile range (IQR)371.5

Descriptive statistics

Standard deviation214.91859
Coefficient of variation (CV)0.57696266
Kurtosis-1.2
Mean372.5
Median Absolute Deviation (MAD)186
Skewness0
Sum277140
Variance46190
MonotonicityStrictly increasing
2023-12-13T08:58:03.458414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.1%
501 1
 
0.1%
492 1
 
0.1%
493 1
 
0.1%
494 1
 
0.1%
495 1
 
0.1%
496 1
 
0.1%
497 1
 
0.1%
498 1
 
0.1%
499 1
 
0.1%
Other values (734) 734
98.7%
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 (%)
744 1
0.1%
743 1
0.1%
742 1
0.1%
741 1
0.1%
740 1
0.1%
739 1
0.1%
738 1
0.1%
737 1
0.1%
736 1
0.1%
735 1
0.1%

업력
Categorical

Distinct8
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size5.9 KiB
3년미만
268 
5년미만
200 
7년미만
143 
1년미만
91 
10년미만
 
22
Other values (3)
 
20

Length

Max length5
Median length4
Mean length4.0564516
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row5년미만
2nd row7년미만
3rd row10년미만
4th row1년미만
5th row5년미만

Common Values

ValueCountFrequency (%)
3년미만 268
36.0%
5년미만 200
26.9%
7년미만 143
19.2%
1년미만 91
 
12.2%
10년미만 22
 
3.0%
15년미만 11
 
1.5%
20년이상 5
 
0.7%
20년미만 4
 
0.5%

Length

2023-12-13T08:58:03.605664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:58:03.722340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3년미만 268
36.0%
5년미만 200
26.9%
7년미만 143
19.2%
1년미만 91
 
12.2%
10년미만 22
 
3.0%
15년미만 11
 
1.5%
20년이상 5
 
0.7%
20년미만 4
 
0.5%

업종
Categorical

Distinct11
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size5.9 KiB
정보
294 
기타
105 
유통
96 
식료
84 
기계
52 
Other values (6)
113 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row유통
2nd row기타
3rd row식료
4th row식료
5th row유통

Common Values

ValueCountFrequency (%)
정보 294
39.5%
기타 105
 
14.1%
유통 96
 
12.9%
식료 84
 
11.3%
기계 52
 
7.0%
전자 39
 
5.2%
잡화 18
 
2.4%
섬유 16
 
2.2%
화공 14
 
1.9%
전기 13
 
1.7%

Length

2023-12-13T08:58:03.830670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
정보 294
39.5%
기타 105
 
14.1%
유통 96
 
12.9%
식료 84
 
11.3%
기계 52
 
7.0%
전자 39
 
5.2%
잡화 18
 
2.4%
섬유 16
 
2.2%
화공 14
 
1.9%
전기 13
 
1.7%

지원일자
Date

Distinct170
Distinct (%)22.8%
Missing0
Missing (%)0.0%
Memory size5.9 KiB
Minimum2023-01-05 00:00:00
Maximum2023-10-30 00:00:00
2023-12-13T08:58:03.933947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:58:04.314718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

지원금액(시설_백만원)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct57
Distinct (%)7.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean80.375
Minimum0
Maximum3000
Zeros665
Zeros (%)89.4%
Negative0
Negative (%)0.0%
Memory size6.7 KiB
2023-12-13T08:58:04.424024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile500
Maximum3000
Range3000
Interquartile range (IQR)0

Descriptive statistics

Standard deviation317.27772
Coefficient of variation (CV)3.9474677
Kurtosis28.852806
Mean80.375
Median Absolute Deviation (MAD)0
Skewness5.0769641
Sum59799
Variance100665.15
MonotonicityNot monotonic
2023-12-13T08:58:04.552779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 665
89.4%
300.0 6
 
0.8%
86.4 4
 
0.5%
225.0 3
 
0.4%
2000.0 3
 
0.4%
800.0 3
 
0.4%
500.0 2
 
0.3%
1000.0 2
 
0.3%
470.0 2
 
0.3%
900.0 2
 
0.3%
Other values (47) 52
 
7.0%
ValueCountFrequency (%)
0.0 665
89.4%
80.0 1
 
0.1%
86.4 4
 
0.5%
98.0 1
 
0.1%
100.0 2
 
0.3%
115.0 1
 
0.1%
140.0 1
 
0.1%
150.0 1
 
0.1%
160.0 1
 
0.1%
172.0 1
 
0.1%
ValueCountFrequency (%)
3000.0 1
 
0.1%
2460.0 1
 
0.1%
2250.0 1
 
0.1%
2000.0 3
0.4%
1930.0 1
 
0.1%
1760.0 2
0.3%
1700.0 1
 
0.1%
1530.0 1
 
0.1%
1520.0 1
 
0.1%
1500.0 1
 
0.1%

지원금액(운전_백만원)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct26
Distinct (%)3.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean137.98656
Minimum0
Maximum2000
Zeros79
Zeros (%)10.6%
Negative0
Negative (%)0.0%
Memory size6.7 KiB
2023-12-13T08:58:04.659858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q180
median100
Q3160
95-th percentile300
Maximum2000
Range2000
Interquartile range (IQR)80

Descriptive statistics

Standard deviation169.23962
Coefficient of variation (CV)1.2264935
Kurtosis51.062808
Mean137.98656
Median Absolute Deviation (MAD)50
Skewness6.0162392
Sum102662
Variance28642.048
MonotonicityNot monotonic
2023-12-13T08:58:04.784344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
100 302
40.6%
200 111
 
14.9%
50 81
 
10.9%
0 79
 
10.6%
150 60
 
8.1%
300 41
 
5.5%
250 10
 
1.3%
70 10
 
1.3%
1000 9
 
1.2%
500 9
 
1.2%
Other values (16) 32
 
4.3%
ValueCountFrequency (%)
0 79
10.6%
18 1
 
0.1%
26 1
 
0.1%
30 7
 
0.9%
40 1
 
0.1%
47 1
 
0.1%
50 81
10.9%
60 2
 
0.3%
63 1
 
0.1%
70 10
 
1.3%
ValueCountFrequency (%)
2000 2
 
0.3%
1500 1
 
0.1%
1000 9
 
1.2%
500 9
 
1.2%
496 1
 
0.1%
400 1
 
0.1%
300 41
 
5.5%
250 10
 
1.3%
200 111
14.9%
190 1
 
0.1%

지원금액(합계_백만원)
Real number (ℝ)

Distinct71
Distinct (%)9.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean218.36156
Minimum18
Maximum3000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size6.7 KiB
2023-12-13T08:58:04.914952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum18
5-th percentile50
Q1100
median100
Q3200
95-th percentile900
Maximum3000
Range2982
Interquartile range (IQR)100

Descriptive statistics

Standard deviation327.25526
Coefficient of variation (CV)1.4986853
Kurtosis21.285278
Mean218.36156
Median Absolute Deviation (MAD)50
Skewness4.2770607
Sum162461
Variance107096
MonotonicityNot monotonic
2023-12-13T08:58:05.038149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
100.0 304
40.9%
200.0 113
 
15.2%
50.0 81
 
10.9%
150.0 61
 
8.2%
300.0 47
 
6.3%
500.0 11
 
1.5%
1000.0 11
 
1.5%
70.0 10
 
1.3%
250.0 10
 
1.3%
80.0 9
 
1.2%
Other values (61) 87
 
11.7%
ValueCountFrequency (%)
18.0 1
 
0.1%
26.0 1
 
0.1%
30.0 7
 
0.9%
40.0 1
 
0.1%
47.0 1
 
0.1%
50.0 81
10.9%
60.0 2
 
0.3%
63.0 1
 
0.1%
70.0 10
 
1.3%
80.0 9
 
1.2%
ValueCountFrequency (%)
3000.0 1
 
0.1%
2460.0 1
 
0.1%
2250.0 1
 
0.1%
2000.0 5
0.7%
1930.0 1
 
0.1%
1760.0 2
 
0.3%
1700.0 1
 
0.1%
1530.0 1
 
0.1%
1520.0 1
 
0.1%
1500.0 2
 
0.3%

Interactions

2023-12-13T08:58:02.756852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:58:01.745005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:58:02.056499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:58:02.379255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:58:02.840393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:58:01.823070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:58:02.132614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:58:02.463988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:58:02.921480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:58:01.900620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:58:02.218844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:58:02.550509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:58:03.010686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:58:01.979888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:58:02.299340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:58:02.640613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T08:58:05.120895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번업력업종지원금액(시설_백만원)지원금액(운전_백만원)지원금액(합계_백만원)
순번1.0000.4880.2620.2380.2730.250
업력0.4881.0000.2750.0000.3270.068
업종0.2620.2751.0000.2080.0000.111
지원금액(시설_백만원)0.2380.0000.2081.0000.0000.998
지원금액(운전_백만원)0.2730.3270.0000.0001.0000.757
지원금액(합계_백만원)0.2500.0680.1110.9980.7571.000
2023-12-13T08:58:05.213714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업종업력
업종1.0000.133
업력0.1331.000
2023-12-13T08:58:05.302767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번지원금액(시설_백만원)지원금액(운전_백만원)지원금액(합계_백만원)업력업종
순번1.000-0.119-0.117-0.2590.2580.114
지원금액(시설_백만원)-0.1191.000-0.5530.4210.0000.089
지원금액(운전_백만원)-0.117-0.5531.0000.4990.1880.000
지원금액(합계_백만원)-0.2590.4210.4991.0000.0320.047
업력0.2580.0000.1880.0321.0000.133
업종0.1140.0890.0000.0470.1331.000

Missing values

2023-12-13T08:58:03.126702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T08:58:03.229417image/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)
015년미만유통2023-04-180.020002000.0
127년미만기타2023-07-240.0300300.0
2310년미만식료2023-08-180.015001500.0
341년미만식료2023-03-14470.00470.0
455년미만유통2023-01-20300.00300.0
5620년이상정보2023-03-080.0400400.0
677년미만화공2023-02-160.0300300.0
785년미만기계2023-02-090.0100100.0
897년미만기타2023-02-020.0100100.0
9107년미만전자2023-02-030.0200200.0
순번업력업종지원일자지원금액(시설_백만원)지원금액(운전_백만원)지원금액(합계_백만원)
7347353년미만정보2023-02-100.0100100.0
7357363년미만정보2023-02-100.0100100.0
7367373년미만정보2023-02-270.0100100.0
7377383년미만정보2023-02-240.0100100.0
7387393년미만정보2023-03-220.0100100.0
7397401년미만정보2023-05-220.0100100.0
7407411년미만정보2023-06-290.0100100.0
7417423년미만전자2023-08-110.0200200.0
7427433년미만유통2023-09-220.08080.0
7437441년미만정보2023-10-060.0100100.0