Overview

Dataset statistics

Number of variables5
Number of observations617
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory26.0 KiB
Average record size in memory43.2 B

Variable types

Numeric3
Categorical2

Dataset

Description중소벤처기업부 정책자금 운용계획 공고 기준에 따른 제조현장스마트화 자금 지원현황으로 정책자금의 업종별 지역별 지원현황 리스트
Author중소벤처기업진흥공단
URLhttps://www.data.go.kr/data/15040453/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
번호 has unique valuesUnique
지원금액(시설_백만원) has 130 (21.1%) zerosZeros
지원금액(운전_백만원) has 487 (78.9%) zerosZeros

Reproduction

Analysis started2024-03-14 09:24:09.500983
Analysis finished2024-03-14 09:24:11.992112
Duration2.49 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct617
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean309
Minimum1
Maximum617
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.5 KiB
2024-03-14T18:24:12.120546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile31.8
Q1155
median309
Q3463
95-th percentile586.2
Maximum617
Range616
Interquartile range (IQR)308

Descriptive statistics

Standard deviation178.25684
Coefficient of variation (CV)0.57688297
Kurtosis-1.2
Mean309
Median Absolute Deviation (MAD)154
Skewness0
Sum190653
Variance31775.5
MonotonicityStrictly increasing
2024-03-14T18:24:12.470780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.2%
415 1
 
0.2%
408 1
 
0.2%
409 1
 
0.2%
410 1
 
0.2%
411 1
 
0.2%
412 1
 
0.2%
413 1
 
0.2%
414 1
 
0.2%
416 1
 
0.2%
Other values (607) 607
98.4%
ValueCountFrequency (%)
1 1
0.2%
2 1
0.2%
3 1
0.2%
4 1
0.2%
5 1
0.2%
6 1
0.2%
7 1
0.2%
8 1
0.2%
9 1
0.2%
10 1
0.2%
ValueCountFrequency (%)
617 1
0.2%
616 1
0.2%
615 1
0.2%
614 1
0.2%
613 1
0.2%
612 1
0.2%
611 1
0.2%
610 1
0.2%
609 1
0.2%
608 1
0.2%

업종
Categorical

Distinct10
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
기계
180 
금속
104 
식료
87 
화공
79 
잡화
71 
Other values (5)
96 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
기계 180
29.2%
금속 104
16.9%
식료 87
14.1%
화공 79
12.8%
잡화 71
 
11.5%
전자 27
 
4.4%
전기 23
 
3.7%
기타 21
 
3.4%
섬유 13
 
2.1%
유통 12
 
1.9%

Length

2024-03-14T18:24:12.745646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T18:24:12.970862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
기계 180
29.2%
금속 104
16.9%
식료 87
14.1%
화공 79
12.8%
잡화 71
 
11.5%
전자 27
 
4.4%
전기 23
 
3.7%
기타 21
 
3.4%
섬유 13
 
2.1%
유통 12
 
1.9%

지역
Categorical

Distinct17
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Memory size4.9 KiB
경기
133 
경남
78 
서울
54 
경북
49 
충북
39 
Other values (12)
264 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row경기
2nd row강원
3rd row충남
4th row경기
5th row경기

Common Values

ValueCountFrequency (%)
경기 133
21.6%
경남 78
12.6%
서울 54
8.8%
경북 49
 
7.9%
충북 39
 
6.3%
대구 37
 
6.0%
충남 36
 
5.8%
부산 31
 
5.0%
울산 28
 
4.5%
전북 27
 
4.4%
Other values (7) 105
17.0%

Length

2024-03-14T18:24:13.210100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
경기 133
21.6%
경남 78
12.6%
서울 54
8.8%
경북 49
 
7.9%
충북 39
 
6.3%
대구 37
 
6.0%
충남 36
 
5.8%
부산 31
 
5.0%
울산 28
 
4.5%
전북 27
 
4.4%
Other values (7) 105
17.0%

지원금액(시설_백만원)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct229
Distinct (%)37.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean652.35656
Minimum0
Maximum9200
Zeros130
Zeros (%)21.1%
Negative0
Negative (%)0.0%
Memory size5.5 KiB
2024-03-14T18:24:13.428962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q198
median350
Q3940
95-th percentile2048
Maximum9200
Range9200
Interquartile range (IQR)842

Descriptive statistics

Standard deviation934.81526
Coefficient of variation (CV)1.4329821
Kurtosis22.88303
Mean652.35656
Median Absolute Deviation (MAD)350
Skewness3.8206992
Sum402504
Variance873879.57
MonotonicityNot monotonic
2024-03-14T18:24:13.757639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 130
 
21.1%
1000 29
 
4.7%
1500 16
 
2.6%
500 16
 
2.6%
300 14
 
2.3%
100 13
 
2.1%
400 11
 
1.8%
2000 10
 
1.6%
600 9
 
1.5%
1300 9
 
1.5%
Other values (219) 360
58.3%
ValueCountFrequency (%)
0 130
21.1%
16 1
 
0.2%
22 2
 
0.3%
29 1
 
0.2%
30 2
 
0.3%
37 1
 
0.2%
50 4
 
0.6%
70 1
 
0.2%
75 1
 
0.2%
76 1
 
0.2%
ValueCountFrequency (%)
9200 1
0.2%
8000 1
0.2%
6330 1
0.2%
6000 1
0.2%
5082 1
0.2%
5000 2
0.3%
4000 1
0.2%
3700 1
0.2%
3600 1
0.2%
3566 1
0.2%

지원금액(운전_백만원)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct37
Distinct (%)6.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean52.667747
Minimum0
Maximum1000
Zeros487
Zeros (%)78.9%
Negative0
Negative (%)0.0%
Memory size5.5 KiB
2024-03-14T18:24:13.988009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile300
Maximum1000
Range1000
Interquartile range (IQR)0

Descriptive statistics

Standard deviation130.63607
Coefficient of variation (CV)2.4803809
Kurtosis15.22949
Mean52.667747
Median Absolute Deviation (MAD)0
Skewness3.4426854
Sum32496
Variance17065.784
MonotonicityNot monotonic
2024-03-14T18:24:14.234561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=37)
ValueCountFrequency (%)
0 487
78.9%
300 25
 
4.1%
200 20
 
3.2%
100 19
 
3.1%
500 13
 
2.1%
150 7
 
1.1%
50 4
 
0.6%
90 3
 
0.5%
400 3
 
0.5%
250 3
 
0.5%
Other values (27) 33
 
5.3%
ValueCountFrequency (%)
0 487
78.9%
27 1
 
0.2%
38 1
 
0.2%
48 1
 
0.2%
50 4
 
0.6%
60 1
 
0.2%
70 2
 
0.3%
90 3
 
0.5%
99 1
 
0.2%
100 19
 
3.1%
ValueCountFrequency (%)
1000 2
 
0.3%
950 1
 
0.2%
662 1
 
0.2%
650 1
 
0.2%
500 13
2.1%
400 3
 
0.5%
376 1
 
0.2%
360 1
 
0.2%
343 1
 
0.2%
300 25
4.1%

Interactions

2024-03-14T18:24:11.247964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T18:24:09.764214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T18:24:10.535802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T18:24:11.406407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T18:24:10.028756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T18:24:10.791446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T18:24:11.552859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T18:24:10.279588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T18:24:11.036314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-14T18:24:14.386604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호업종지역지원금액(시설_백만원)지원금액(운전_백만원)
번호1.0000.4730.5190.0930.102
업종0.4731.0000.5880.1050.000
지역0.5190.5881.0000.1240.228
지원금액(시설_백만원)0.0930.1050.1241.0000.018
지원금액(운전_백만원)0.1020.0000.2280.0181.000
2024-03-14T18:24:14.554026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지역업종
지역1.0000.273
업종0.2731.000
2024-03-14T18:24:14.748689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호지원금액(시설_백만원)지원금액(운전_백만원)업종지역
번호1.000-0.045-0.0060.1620.230
지원금액(시설_백만원)-0.0451.000-0.7030.0470.049
지원금액(운전_백만원)-0.006-0.7031.0000.0000.106
업종0.1620.0470.0001.0000.273
지역0.2300.0490.1060.2731.000

Missing values

2024-03-14T18:24:11.750019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T18:24:11.920391image/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

번호업종지역지원금액(시설_백만원)지원금액(운전_백만원)
01금속경기6000
12유통강원6200
23기계충남10400
34기계경기1830
45기계경기090
56금속광주8000
67금속경북15000
78화공경북11000
89기계충남11760
910전자충남6000
번호업종지역지원금액(시설_백만원)지원금액(운전_백만원)
607608기계경남048
608609기계경기13000
609610기계충남0100
610611기계충남0150
611612화공충남0500
612613기계충남0500
613614기계대구8750
614615금속서울0360
615616식료충북027
616617기타서울0343