Overview

Dataset statistics

Number of variables5
Number of observations197
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory8.0 KiB
Average record size in memory41.7 B

Variable types

Numeric1
Categorical4

Dataset

Description진로제시컨설팅 결과, "구조개선" 처방을 받고 2022년 구조개선자금을 지원받은 기업의 지역, 업종 업력 등에 관한 현황. 구조개선 수요 및 수혜 지역 개방으로 중소기업 대상 구조개선 지원 활성화를 기대함.
Author중소벤처기업진흥공단
URLhttps://www.data.go.kr/data/15107160/fileData.do

Alerts

업종1 is highly overall correlated with 업종2High correlation
업종2 is highly overall correlated with 업종1High correlation
연번 has unique valuesUnique

Reproduction

Analysis started2024-04-17 11:52:37.161307
Analysis finished2024-04-17 11:52:37.558546
Duration0.4 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct197
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean99
Minimum1
Maximum197
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.9 KiB
2024-04-17T20:52:37.621290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile10.8
Q150
median99
Q3148
95-th percentile187.2
Maximum197
Range196
Interquartile range (IQR)98

Descriptive statistics

Standard deviation57.013156
Coefficient of variation (CV)0.57589047
Kurtosis-1.2
Mean99
Median Absolute Deviation (MAD)49
Skewness0
Sum19503
Variance3250.5
MonotonicityStrictly increasing
2024-04-17T20:52:37.731551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.5%
125 1
 
0.5%
127 1
 
0.5%
128 1
 
0.5%
129 1
 
0.5%
130 1
 
0.5%
131 1
 
0.5%
132 1
 
0.5%
133 1
 
0.5%
134 1
 
0.5%
Other values (187) 187
94.9%
ValueCountFrequency (%)
1 1
0.5%
2 1
0.5%
3 1
0.5%
4 1
0.5%
5 1
0.5%
6 1
0.5%
7 1
0.5%
8 1
0.5%
9 1
0.5%
10 1
0.5%
ValueCountFrequency (%)
197 1
0.5%
196 1
0.5%
195 1
0.5%
194 1
0.5%
193 1
0.5%
192 1
0.5%
191 1
0.5%
190 1
0.5%
189 1
0.5%
188 1
0.5%

지역
Categorical

Distinct16
Distinct (%)8.1%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
경기
50 
서울
27 
경남
22 
인천
16 
부산
14 
Other values (11)
68 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique1 ?
Unique (%)0.5%

Sample

1st row서울
2nd row경남
3rd row서울
4th row경기
5th row서울

Common Values

ValueCountFrequency (%)
경기 50
25.4%
서울 27
13.7%
경남 22
11.2%
인천 16
 
8.1%
부산 14
 
7.1%
대구 13
 
6.6%
경북 11
 
5.6%
충북 11
 
5.6%
전남 9
 
4.6%
충남 7
 
3.6%
Other values (6) 17
 
8.6%

Length

2024-04-17T20:52:37.847761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
경기 50
25.4%
서울 27
13.7%
경남 22
11.2%
인천 16
 
8.1%
부산 14
 
7.1%
대구 13
 
6.6%
경북 11
 
5.6%
충북 11
 
5.6%
전남 9
 
4.6%
충남 7
 
3.6%
Other values (6) 17
 
8.6%

업종1
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
제조업
147 
도소매업
25 
서비스업
 
12
정보통신업
 
10
운수 및 창고업
 
3

Length

Max length8
Median length3
Mean length3.3654822
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row도소매업
2nd row제조업
3rd row제조업
4th row제조업
5th row서비스업

Common Values

ValueCountFrequency (%)
제조업 147
74.6%
도소매업 25
 
12.7%
서비스업 12
 
6.1%
정보통신업 10
 
5.1%
운수 및 창고업 3
 
1.5%

Length

2024-04-17T20:52:37.944634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T20:52:38.054305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
제조업 147
72.4%
도소매업 25
 
12.3%
서비스업 12
 
5.9%
정보통신업 10
 
4.9%
운수 3
 
1.5%
및 3
 
1.5%
창고업 3
 
1.5%

업종2
Categorical

HIGH CORRELATION 

Distinct11
Distinct (%)5.6%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
기계
38 
금속
26 
유통
25 
식료
23 
화공
19 
Other values (6)
66 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
기계 38
19.3%
금속 26
13.2%
유통 25
12.7%
식료 23
11.7%
화공 19
9.6%
기타 16
8.1%
잡화 14
 
7.1%
정보 10
 
5.1%
전기 10
 
5.1%
섬유 9
 
4.6%

Length

2024-04-17T20:52:38.155699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
기계 38
19.3%
금속 26
13.2%
유통 25
12.7%
식료 23
11.7%
화공 19
9.6%
기타 16
8.1%
잡화 14
 
7.1%
정보 10
 
5.1%
전기 10
 
5.1%
섬유 9
 
4.6%

업력
Categorical

Distinct8
Distinct (%)4.1%
Missing0
Missing (%)0.0%
Memory size1.7 KiB
10년미만
39 
15년미만
37 
20년이상
33 
7년미만
30 
5년미만
30 
Other values (3)
28 

Length

Max length5
Median length5
Mean length4.6497462
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row10년미만
2nd row20년이상
3rd row20년미만
4th row7년미만
5th row7년미만

Common Values

ValueCountFrequency (%)
10년미만 39
19.8%
15년미만 37
18.8%
20년이상 33
16.8%
7년미만 30
15.2%
5년미만 30
15.2%
20년미만 19
9.6%
3년미만 7
 
3.6%
1년미만 2
 
1.0%

Length

2024-04-17T20:52:38.254369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T20:52:38.357933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
10년미만 39
19.8%
15년미만 37
18.8%
20년이상 33
16.8%
7년미만 30
15.2%
5년미만 30
15.2%
20년미만 19
9.6%
3년미만 7
 
3.6%
1년미만 2
 
1.0%

Interactions

2024-04-17T20:52:37.344466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-17T20:52:38.441379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번지역업종1업종2업력
연번1.0000.1410.2700.0990.265
지역0.1411.0000.1820.4360.000
업종10.2700.1821.0000.9360.000
업종20.0990.4360.9361.0000.199
업력0.2650.0000.0000.1991.000
2024-04-17T20:52:38.526321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지역업종2업종1업력
지역1.0000.1770.0890.000
업종20.1771.0000.8340.092
업종10.0890.8341.0000.000
업력0.0000.0920.0001.000
2024-04-17T20:52:38.606926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번지역업종1업종2업력
연번1.0000.0520.1170.0470.127
지역0.0521.0000.0890.1770.000
업종10.1170.0891.0000.8340.000
업종20.0470.1770.8341.0000.092
업력0.1270.0000.0000.0921.000

Missing values

2024-04-17T20:52:37.442931image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-17T20:52:37.528016image/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

연번지역업종1업종2업력
01서울도소매업유통10년미만
12경남제조업금속20년이상
23서울제조업섬유20년미만
34경기제조업기계7년미만
45서울서비스업기타7년미만
56대전도소매업유통15년미만
67서울도소매업유통20년미만
78서울서비스업기타15년미만
89경기제조업식료10년미만
910서울정보통신업정보20년이상
연번지역업종1업종2업력
187188경기제조업화공10년미만
188189경기제조업식료15년미만
189190인천제조업화공7년미만
190191인천제조업기계5년미만
191192서울서비스업기타5년미만
192193부산제조업잡화20년이상
193194경기제조업잡화20년이상
194195경남제조업기계15년미만
195196경기제조업기계20년이상
196197전남제조업전자5년미만