Overview

Dataset statistics

Number of variables7
Number of observations146
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory8.7 KiB
Average record size in memory60.9 B

Variable types

Numeric3
Categorical3
DateTime1

Dataset

Description중소벤처기업진흥공단이 자연재해 등으로 피해를 받은 기업에게 지원한 정책자금의 지역별, 업종별 데이터를 통계 자료 등으로 활용할 수 있도록 개방
Author중소벤처기업진흥공단
URLhttps://www.data.go.kr/data/15108044/fileData.do

Alerts

지원금액(시설_백만원) has constant value ""Constant
지원금액(운전_백만원) is highly overall correlated with 지원금액(합계_백만원)High correlation
지원금액(합계_백만원) is highly overall correlated with 지원금액(운전_백만원)High correlation
순번 has unique valuesUnique

Reproduction

Analysis started2023-12-11 23:01:07.299685
Analysis finished2023-12-11 23:01:08.453012
Duration1.15 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

UNIQUE 

Distinct146
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean73.5
Minimum1
Maximum146
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2023-12-12T08:01:08.515718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile8.25
Q137.25
median73.5
Q3109.75
95-th percentile138.75
Maximum146
Range145
Interquartile range (IQR)72.5

Descriptive statistics

Standard deviation42.290661
Coefficient of variation (CV)0.57538314
Kurtosis-1.2
Mean73.5
Median Absolute Deviation (MAD)36.5
Skewness0
Sum10731
Variance1788.5
MonotonicityStrictly increasing
2023-12-12T08:01:08.652812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.7%
111 1
 
0.7%
95 1
 
0.7%
96 1
 
0.7%
97 1
 
0.7%
98 1
 
0.7%
99 1
 
0.7%
100 1
 
0.7%
101 1
 
0.7%
102 1
 
0.7%
Other values (136) 136
93.2%
ValueCountFrequency (%)
1 1
0.7%
2 1
0.7%
3 1
0.7%
4 1
0.7%
5 1
0.7%
6 1
0.7%
7 1
0.7%
8 1
0.7%
9 1
0.7%
10 1
0.7%
ValueCountFrequency (%)
146 1
0.7%
145 1
0.7%
144 1
0.7%
143 1
0.7%
142 1
0.7%
141 1
0.7%
140 1
0.7%
139 1
0.7%
138 1
0.7%
137 1
0.7%

업력
Categorical

Distinct7
Distinct (%)4.8%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
20년이상
38 
15년미만
27 
20년미만
22 
10년미만
20 
7년미만
20 
Other values (2)
19 

Length

Max length5
Median length5
Mean length4.7328767
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row15년미만
2nd row5년미만
3rd row15년미만
4th row20년미만
5th row15년미만

Common Values

ValueCountFrequency (%)
20년이상 38
26.0%
15년미만 27
18.5%
20년미만 22
15.1%
10년미만 20
13.7%
7년미만 20
13.7%
5년미만 14
 
9.6%
3년미만 5
 
3.4%

Length

2023-12-12T08:01:08.768385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:01:08.897273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
20년이상 38
26.0%
15년미만 27
18.5%
20년미만 22
15.1%
10년미만 20
13.7%
7년미만 20
13.7%
5년미만 14
 
9.6%
3년미만 5
 
3.4%

업종
Categorical

Distinct10
Distinct (%)6.8%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
기타
28 
유통
23 
식료
20 
기계
15 
금속
15 
Other values (5)
45 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique1 ?
Unique (%)0.7%

Sample

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

Common Values

ValueCountFrequency (%)
기타 28
19.2%
유통 23
15.8%
식료 20
13.7%
기계 15
10.3%
금속 15
10.3%
섬유 15
10.3%
화공 13
8.9%
잡화 12
8.2%
전기 4
 
2.7%
전자 1
 
0.7%

Length

2023-12-12T08:01:09.029823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:01:09.131413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
기타 28
19.2%
유통 23
15.8%
식료 20
13.7%
기계 15
10.3%
금속 15
10.3%
섬유 15
10.3%
화공 13
8.9%
잡화 12
8.2%
전기 4
 
2.7%
전자 1
 
0.7%

지원일자
Date

Distinct74
Distinct (%)50.7%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
Minimum2023-01-06 00:00:00
Maximum2023-10-31 00:00:00
2023-12-12T08:01:09.250344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:01:09.357924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

지원금액(시설_백만원)
Categorical

CONSTANT 

Distinct1
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
0
146 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 146
100.0%

Length

2023-12-12T08:01:09.459932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:01:09.533224image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 146
100.0%

지원금액(운전_백만원)
Real number (ℝ)

HIGH CORRELATION 

Distinct43
Distinct (%)29.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean231.22603
Minimum30
Maximum1000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2023-12-12T08:01:09.617524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum30
5-th percentile50
Q1100
median177.5
Q3270
95-th percentile700
Maximum1000
Range970
Interquartile range (IQR)170

Descriptive statistics

Standard deviation210.69471
Coefficient of variation (CV)0.9112067
Kurtosis5.4621127
Mean231.22603
Median Absolute Deviation (MAD)77.5
Skewness2.3066081
Sum33759
Variance44392.259
MonotonicityNot monotonic
2023-12-12T08:01:09.744919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
200 25
17.1%
100 23
15.8%
150 15
 
10.3%
300 12
 
8.2%
50 7
 
4.8%
500 6
 
4.1%
1000 6
 
4.1%
90 4
 
2.7%
400 4
 
2.7%
95 3
 
2.1%
Other values (33) 41
28.1%
ValueCountFrequency (%)
30 1
 
0.7%
34 1
 
0.7%
35 1
 
0.7%
50 7
4.8%
60 1
 
0.7%
63 1
 
0.7%
70 2
 
1.4%
80 1
 
0.7%
84 1
 
0.7%
85 1
 
0.7%
ValueCountFrequency (%)
1000 6
4.1%
700 3
 
2.1%
600 1
 
0.7%
570 1
 
0.7%
500 6
4.1%
404 1
 
0.7%
400 4
 
2.7%
390 1
 
0.7%
300 12
8.2%
290 1
 
0.7%

지원금액(합계_백만원)
Real number (ℝ)

HIGH CORRELATION 

Distinct43
Distinct (%)29.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean231.22603
Minimum30
Maximum1000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2023-12-12T08:01:09.883563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum30
5-th percentile50
Q1100
median177.5
Q3270
95-th percentile700
Maximum1000
Range970
Interquartile range (IQR)170

Descriptive statistics

Standard deviation210.69471
Coefficient of variation (CV)0.9112067
Kurtosis5.4621127
Mean231.22603
Median Absolute Deviation (MAD)77.5
Skewness2.3066081
Sum33759
Variance44392.259
MonotonicityNot monotonic
2023-12-12T08:01:09.992225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
200 25
17.1%
100 23
15.8%
150 15
 
10.3%
300 12
 
8.2%
50 7
 
4.8%
500 6
 
4.1%
1000 6
 
4.1%
90 4
 
2.7%
400 4
 
2.7%
95 3
 
2.1%
Other values (33) 41
28.1%
ValueCountFrequency (%)
30 1
 
0.7%
34 1
 
0.7%
35 1
 
0.7%
50 7
4.8%
60 1
 
0.7%
63 1
 
0.7%
70 2
 
1.4%
80 1
 
0.7%
84 1
 
0.7%
85 1
 
0.7%
ValueCountFrequency (%)
1000 6
4.1%
700 3
 
2.1%
600 1
 
0.7%
570 1
 
0.7%
500 6
4.1%
404 1
 
0.7%
400 4
 
2.7%
390 1
 
0.7%
300 12
8.2%
290 1
 
0.7%

Interactions

2023-12-12T08:01:08.026799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:01:07.498974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:01:07.726670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:01:08.123664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:01:07.575211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:01:07.811717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:01:08.195693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:01:07.644905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:01:07.921973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T08:01:10.064546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번업력업종지원일자지원금액(운전_백만원)지원금액(합계_백만원)
순번1.0000.1660.6250.9500.3480.348
업력0.1661.0000.0000.0000.0000.000
업종0.6250.0001.0000.8190.2220.222
지원일자0.9500.0000.8191.0000.0000.000
지원금액(운전_백만원)0.3480.0000.2220.0001.0001.000
지원금액(합계_백만원)0.3480.0000.2220.0001.0001.000
2023-12-12T08:01:10.150167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업력업종
업력1.0000.000
업종0.0001.000
2023-12-12T08:01:10.233918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번지원금액(운전_백만원)지원금액(합계_백만원)업력업종
순번1.0000.0030.0030.0920.225
지원금액(운전_백만원)0.0031.0001.0000.0000.105
지원금액(합계_백만원)0.0031.0001.0000.0000.105
업력0.0920.0000.0001.0000.000
업종0.2250.1050.1050.0001.000

Missing values

2023-12-12T08:01:08.301717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T08:01:08.405751image/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)
0115년미만유통2023-01-1208888
125년미만유통2023-01-090200200
2315년미만유통2023-01-1008484
3420년미만유통2023-01-1209393
4515년미만유통2023-01-1309595
5615년미만유통2023-01-100195195
6720년이상유통2023-01-120150150
7815년미만유통2023-01-090119119
8915년미만유통2023-01-1008585
91010년미만유통2023-01-110116116
순번업력업종지원일자지원금액(시설_백만원)지원금액(운전_백만원)지원금액(합계_백만원)
13613720년이상섬유2023-09-140220220
1371383년미만식료2023-09-130300300
13813920년미만유통2023-09-130200200
13914010년미만화공2023-09-200200200
14014110년미만기타2023-09-140200200
14114220년미만화공2023-09-260100100
14214320년미만잡화2023-09-260160160
14314420년이상섬유2023-10-190150150
14414520년이상전기2023-10-260300300
14514620년이상기타2023-10-310100100