Overview

Dataset statistics

Number of variables8
Number of observations89
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.0 KiB
Average record size in memory68.5 B

Variable types

Categorical6
Numeric2

Dataset

Description동 데이터는 중소벤처기업진흥공단 정책자금 방식 중 하나인 성장공유형대출이며, 2022년 지원기업의 지원현황(업종, 지역, 종업원규모, 매출규모 등)을 제공합니다.
Author중소벤처기업진흥공단
URLhttps://www.data.go.kr/data/15124912/fileData.do

Alerts

지원연도 has constant value ""Constant
업체번호 is highly overall correlated with 지원금액_백만원High correlation
지원금액_백만원 is highly overall correlated with 업체번호High correlation
업체번호 has unique valuesUnique

Reproduction

Analysis started2023-12-12 04:12:42.794066
Analysis finished2023-12-12 04:12:44.088419
Duration1.29 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

지원연도
Categorical

CONSTANT 

Distinct1
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size844.0 B
2022
89 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2022
2nd row2022
3rd row2022
4th row2022
5th row2022

Common Values

ValueCountFrequency (%)
2022 89
100.0%

Length

2023-12-12T13:12:44.171618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:12:44.281595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022 89
100.0%

업체번호
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct89
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean45
Minimum1
Maximum89
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size933.0 B
2023-12-12T13:12:44.400034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile5.4
Q123
median45
Q367
95-th percentile84.6
Maximum89
Range88
Interquartile range (IQR)44

Descriptive statistics

Standard deviation25.836021
Coefficient of variation (CV)0.57413381
Kurtosis-1.2
Mean45
Median Absolute Deviation (MAD)22
Skewness0
Sum4005
Variance667.5
MonotonicityStrictly increasing
2023-12-12T13:12:44.588149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.1%
68 1
 
1.1%
66 1
 
1.1%
65 1
 
1.1%
64 1
 
1.1%
63 1
 
1.1%
62 1
 
1.1%
61 1
 
1.1%
60 1
 
1.1%
59 1
 
1.1%
Other values (79) 79
88.8%
ValueCountFrequency (%)
1 1
1.1%
2 1
1.1%
3 1
1.1%
4 1
1.1%
5 1
1.1%
6 1
1.1%
7 1
1.1%
8 1
1.1%
9 1
1.1%
10 1
1.1%
ValueCountFrequency (%)
89 1
1.1%
88 1
1.1%
87 1
1.1%
86 1
1.1%
85 1
1.1%
84 1
1.1%
83 1
1.1%
82 1
1.1%
81 1
1.1%
80 1
1.1%

업종
Categorical

Distinct11
Distinct (%)12.4%
Missing0
Missing (%)0.0%
Memory size844.0 B
정보
26 
전자
15 
기계
13 
화공
10 
식료
6 
Other values (6)
19 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique2 ?
Unique (%)2.2%

Sample

1st row기계
2nd row화공
3rd row전자
4th row정보
5th row정보

Common Values

ValueCountFrequency (%)
정보 26
29.2%
전자 15
16.9%
기계 13
14.6%
화공 10
 
11.2%
식료 6
 
6.7%
기타 6
 
6.7%
전기 4
 
4.5%
유통 4
 
4.5%
금속 3
 
3.4%
섬유 1
 
1.1%

Length

2023-12-12T13:12:44.764603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
정보 26
29.2%
전자 15
16.9%
기계 13
14.6%
화공 10
 
11.2%
식료 6
 
6.7%
기타 6
 
6.7%
전기 4
 
4.5%
유통 4
 
4.5%
금속 3
 
3.4%
섬유 1
 
1.1%

지역
Categorical

Distinct16
Distinct (%)18.0%
Missing0
Missing (%)0.0%
Memory size844.0 B
서울
21 
경기
16 
대전
7 
충남
5 
경남
5 
Other values (11)
35 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique2 ?
Unique (%)2.2%

Sample

1st row대전
2nd row부산
3rd row경기
4th row서울
5th row서울

Common Values

ValueCountFrequency (%)
서울 21
23.6%
경기 16
18.0%
대전 7
 
7.9%
충남 5
 
5.6%
경남 5
 
5.6%
대구 5
 
5.6%
부산 4
 
4.5%
충북 4
 
4.5%
경북 4
 
4.5%
광주 4
 
4.5%
Other values (6) 14
15.7%

Length

2023-12-12T13:12:44.922367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
서울 21
23.6%
경기 16
18.0%
대전 7
 
7.9%
충남 5
 
5.6%
경남 5
 
5.6%
대구 5
 
5.6%
부산 4
 
4.5%
충북 4
 
4.5%
경북 4
 
4.5%
광주 4
 
4.5%
Other values (6) 14
15.7%

종업원규모
Categorical

Distinct5
Distinct (%)5.6%
Missing0
Missing (%)0.0%
Memory size844.0 B
50인미만
27 
20인미만
24 
10인미만
20 
5인미만
13 
100인미만
5 

Length

Max length6
Median length5
Mean length4.9101124
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row50인미만
2nd row50인미만
3rd row50인미만
4th row50인미만
5th row50인미만

Common Values

ValueCountFrequency (%)
50인미만 27
30.3%
20인미만 24
27.0%
10인미만 20
22.5%
5인미만 13
14.6%
100인미만 5
 
5.6%

Length

2023-12-12T13:12:45.127209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:12:45.292594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
50인미만 27
30.3%
20인미만 24
27.0%
10인미만 20
22.5%
5인미만 13
14.6%
100인미만 5
 
5.6%

매출규모
Categorical

Distinct6
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Memory size844.0 B
5억미만
32 
50억미만
24 
100억미만
13 
10억미만
13 
300억이상
4 

Length

Max length6
Median length5
Mean length4.8651685
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row5억미만
2nd row5억미만
3rd row100억미만
4th row50억미만
5th row10억미만

Common Values

ValueCountFrequency (%)
5억미만 32
36.0%
50억미만 24
27.0%
100억미만 13
14.6%
10억미만 13
14.6%
300억이상 4
 
4.5%
300억미만 3
 
3.4%

Length

2023-12-12T13:12:45.489708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:12:45.667068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
5억미만 32
36.0%
50억미만 24
27.0%
100억미만 13
14.6%
10억미만 13
14.6%
300억이상 4
 
4.5%
300억미만 3
 
3.4%

업력
Categorical

Distinct7
Distinct (%)7.9%
Missing0
Missing (%)0.0%
Memory size844.0 B
3년미만
27 
7년미만
23 
5년미만
19 
10년미만
7 
20년이상
6 
Other values (2)
7 

Length

Max length5
Median length4
Mean length4.1910112
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row7년미만
2nd row7년미만
3rd row20년이상
4th row7년미만
5th row5년미만

Common Values

ValueCountFrequency (%)
3년미만 27
30.3%
7년미만 23
25.8%
5년미만 19
21.3%
10년미만 7
 
7.9%
20년이상 6
 
6.7%
15년미만 4
 
4.5%
1년미만 3
 
3.4%

Length

2023-12-12T13:12:45.848314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:12:46.061679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3년미만 27
30.3%
7년미만 23
25.8%
5년미만 19
21.3%
10년미만 7
 
7.9%
20년이상 6
 
6.7%
15년미만 4
 
4.5%
1년미만 3
 
3.4%

지원금액_백만원
Real number (ℝ)

HIGH CORRELATION 

Distinct16
Distinct (%)18.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean674.20225
Minimum100
Maximum2000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size933.0 B
2023-12-12T13:12:46.247001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum100
5-th percentile100
Q1300
median500
Q31000
95-th percentile1500
Maximum2000
Range1900
Interquartile range (IQR)700

Descriptive statistics

Standard deviation451.96046
Coefficient of variation (CV)0.67036332
Kurtosis0.11448074
Mean674.20225
Median Absolute Deviation (MAD)300
Skewness0.80670116
Sum60004
Variance204268.25
MonotonicityNot monotonic
2023-12-12T13:12:46.448706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
1000 25
28.1%
500 21
23.6%
300 10
 
11.2%
200 7
 
7.9%
100 6
 
6.7%
1500 6
 
6.7%
2000 2
 
2.2%
1100 2
 
2.2%
499 2
 
2.2%
250 2
 
2.2%
Other values (6) 6
 
6.7%
ValueCountFrequency (%)
100 6
6.7%
150 1
 
1.1%
200 7
7.9%
210 1
 
1.1%
250 2
 
2.2%
290 1
 
1.1%
300 10
11.2%
356 1
 
1.1%
400 1
 
1.1%
499 2
 
2.2%
ValueCountFrequency (%)
2000 2
 
2.2%
1500 6
 
6.7%
1400 1
 
1.1%
1100 2
 
2.2%
1000 25
28.1%
500 21
23.6%
499 2
 
2.2%
400 1
 
1.1%
356 1
 
1.1%
300 10
 
11.2%

Interactions

2023-12-12T13:12:43.502438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:12:43.283496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:12:43.638316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:12:43.371215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T13:12:46.976735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업체번호업종지역종업원규모매출규모업력지원금액_백만원
업체번호1.0000.0000.0000.7130.3070.2690.597
업종0.0001.0000.6690.3240.6000.0000.000
지역0.0000.6691.0000.0730.5850.3370.293
종업원규모0.7130.3240.0731.0000.5930.4830.432
매출규모0.3070.6000.5850.5931.0000.4200.420
업력0.2690.0000.3370.4830.4201.0000.494
지원금액_백만원0.5970.0000.2930.4320.4200.4941.000
2023-12-12T13:12:47.158652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업종업력매출규모종업원규모지역
업종1.0000.0000.3480.1740.313
업력0.0001.0000.2630.3310.145
매출규모0.3480.2631.0000.4500.305
종업원규모0.1740.3310.4501.0000.000
지역0.3130.1450.3050.0001.000
2023-12-12T13:12:47.327730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업체번호지원금액_백만원업종지역종업원규모매출규모업력
업체번호1.000-0.6410.0000.0000.3580.1470.138
지원금액_백만원-0.6411.0000.0000.0900.2760.2440.289
업종0.0000.0001.0000.3130.1740.3480.000
지역0.0000.0900.3131.0000.0000.3050.145
종업원규모0.3580.2760.1740.0001.0000.4500.331
매출규모0.1470.2440.3480.3050.4501.0000.263
업력0.1380.2890.0000.1450.3310.2631.000

Missing values

2023-12-12T13:12:43.837912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T13:12:44.015972image/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

지원연도업체번호업종지역종업원규모매출규모업력지원금액_백만원
020221기계대전50인미만5억미만7년미만290
120222화공부산50인미만5억미만7년미만1000
220223전자경기50인미만100억미만20년이상1500
320224정보서울50인미만50억미만7년미만1000
420225정보서울50인미만10억미만5년미만500
520226기계경기20인미만50억미만10년미만1000
620227정보대전20인미만10억미만5년미만1000
720228전기충북50인미만100억미만10년미만1000
820229금속경북100인미만300억이상7년미만2000
9202210화공충남20인미만50억미만7년미만1000
지원연도업체번호업종지역종업원규모매출규모업력지원금액_백만원
79202280전자광주5인미만5억미만3년미만300
80202281전기경기10인미만10억미만7년미만300
81202282화공대구10인미만50억미만3년미만210
82202283전자대구10인미만5억미만5년미만200
83202284정보서울10인미만5억미만3년미만150
84202285정보부산10인미만5억미만3년미만200
85202286식료서울20인미만50억미만3년미만300
86202287정보서울10인미만5억미만5년미만200
87202288기계경기20인미만100억미만15년미만1400
88202289전자대전5인미만5억미만3년미만200