Overview

Dataset statistics

Number of variables17
Number of observations2117
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory302.0 KiB
Average record size in memory146.1 B

Variable types

Numeric7
Categorical10

Dataset

Description중소벤처기업진흥공단의 정책자금(일시적경영애로) 자금의 2022년 12월 31일 기준, 지원 현황 데이터를 개방합니다.
URLhttps://www.data.go.kr/data/15119780/fileData.do

Alerts

사업1 has constant value ""Constant
사업2 has constant value ""Constant
신청금액(시설_백만원) has constant value ""Constant
추천금액(시설_백만원) has constant value ""Constant
대여금액(시설_백만원) has constant value ""Constant
신청금액(운전_백만원) is highly overall correlated with 신청금액(합계_백만원) and 4 other fieldsHigh correlation
신청금액(합계_백만원) is highly overall correlated with 신청금액(운전_백만원) and 4 other fieldsHigh correlation
추천금액(운전_백만원) is highly overall correlated with 신청금액(운전_백만원) and 4 other fieldsHigh correlation
추천금액(합계_백만원) is highly overall correlated with 신청금액(운전_백만원) and 4 other fieldsHigh correlation
대여금액(운전_백만원) is highly overall correlated with 신청금액(운전_백만원) and 4 other fieldsHigh correlation
대여금액(합계_백만원) is highly overall correlated with 신청금액(운전_백만원) and 4 other fieldsHigh correlation
일련번호 has unique valuesUnique

Reproduction

Analysis started2023-12-12 13:19:33.988730
Analysis finished2023-12-12 13:19:41.007543
Duration7.02 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

일련번호
Real number (ℝ)

UNIQUE 

Distinct2117
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1059
Minimum1
Maximum2117
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size18.7 KiB
2023-12-12T22:19:41.096057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile106.8
Q1530
median1059
Q31588
95-th percentile2011.2
Maximum2117
Range2116
Interquartile range (IQR)1058

Descriptive statistics

Standard deviation611.26958
Coefficient of variation (CV)0.57721396
Kurtosis-1.2
Mean1059
Median Absolute Deviation (MAD)529
Skewness0
Sum2241903
Variance373650.5
MonotonicityStrictly increasing
2023-12-12T22:19:41.255578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
< 0.1%
1408 1
 
< 0.1%
1422 1
 
< 0.1%
1421 1
 
< 0.1%
1420 1
 
< 0.1%
1419 1
 
< 0.1%
1418 1
 
< 0.1%
1417 1
 
< 0.1%
1416 1
 
< 0.1%
1415 1
 
< 0.1%
Other values (2107) 2107
99.5%
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 (%)
2117 1
< 0.1%
2116 1
< 0.1%
2115 1
< 0.1%
2114 1
< 0.1%
2113 1
< 0.1%
2112 1
< 0.1%
2111 1
< 0.1%
2110 1
< 0.1%
2109 1
< 0.1%
2108 1
< 0.1%

사업1
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size16.7 KiB
일시적경영애로
2117 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
일시적경영애로 2117
100.0%

Length

2023-12-12T22:19:41.396576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:19:41.525318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일시적경영애로 2117
100.0%

사업2
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size16.7 KiB
긴급경영안정
2117 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
긴급경영안정 2117
100.0%

Length

2023-12-12T22:19:41.653883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:19:41.764054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
긴급경영안정 2117
100.0%

자산규모
Categorical

Distinct7
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size16.7 KiB
30억미만
650 
10억미만
648 
70억미만
478 
100억미만
142 
200억미만
115 
Other values (2)
84 

Length

Max length6
Median length5
Mean length5.1213982
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row70억미만
2nd row70억미만
3rd row200억미만
4th row30억미만
5th row30억미만

Common Values

ValueCountFrequency (%)
30억미만 650
30.7%
10억미만 648
30.6%
70억미만 478
22.6%
100억미만 142
 
6.7%
200억미만 115
 
5.4%
<NA> 42
 
2.0%
200억이상 42
 
2.0%

Length

2023-12-12T22:19:41.880319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:19:42.038997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
30억미만 650
30.7%
10억미만 648
30.6%
70억미만 478
22.6%
100억미만 142
 
6.7%
200억미만 115
 
5.4%
na 42
 
2.0%
200억이상 42
 
2.0%

매출규모
Categorical

Distinct7
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size16.7 KiB
50억미만
1033 
10억미만
334 
100억미만
283 
5억미만
240 
300억미만
158 
Other values (2)
 
69

Length

Max length6
Median length5
Mean length5.0878602
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
50억미만 1033
48.8%
10억미만 334
 
15.8%
100억미만 283
 
13.4%
5억미만 240
 
11.3%
300억미만 158
 
7.5%
<NA> 42
 
2.0%
300억이상 27
 
1.3%

Length

2023-12-12T22:19:42.182708image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:19:42.310699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
50억미만 1033
48.8%
10억미만 334
 
15.8%
100억미만 283
 
13.4%
5억미만 240
 
11.3%
300억미만 158
 
7.5%
na 42
 
2.0%
300억이상 27
 
1.3%
Distinct8
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size16.7 KiB
10년미만
493 
15년미만
473 
20년이상
375 
20년미만
271 
7년미만
215 
Other values (3)
290 

Length

Max length5
Median length5
Mean length4.7614549
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3년미만
2nd row15년미만
3rd row15년미만
4th row15년미만
5th row10년미만

Common Values

ValueCountFrequency (%)
10년미만 493
23.3%
15년미만 473
22.3%
20년이상 375
17.7%
20년미만 271
12.8%
7년미만 215
10.2%
5년미만 164
 
7.7%
3년미만 107
 
5.1%
1년미만 19
 
0.9%

Length

2023-12-12T22:19:42.440475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:19:42.622985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
10년미만 493
23.3%
15년미만 473
22.3%
20년이상 375
17.7%
20년미만 271
12.8%
7년미만 215
10.2%
5년미만 164
 
7.7%
3년미만 107
 
5.1%
1년미만 19
 
0.9%
Distinct17
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size16.7 KiB
경기
471 
경남
215 
서울
202 
경북
157 
부산
133 
Other values (12)
939 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row경남
2nd row전북
3rd row광주
4th row강원
5th row울산

Common Values

ValueCountFrequency (%)
경기 471
22.2%
경남 215
10.2%
서울 202
9.5%
경북 157
 
7.4%
부산 133
 
6.3%
충북 130
 
6.1%
대구 121
 
5.7%
인천 110
 
5.2%
강원 109
 
5.1%
충남 102
 
4.8%
Other values (7) 367
17.3%

Length

2023-12-12T22:19:42.748960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
경기 471
22.2%
경남 215
10.2%
서울 202
9.5%
경북 157
 
7.4%
부산 133
 
6.3%
충북 130
 
6.1%
대구 121
 
5.7%
인천 110
 
5.2%
강원 109
 
5.1%
충남 102
 
4.8%
Other values (7) 367
17.3%

신청금액(시설_백만원)
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size16.7 KiB
0
2117 

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 2117
100.0%

Length

2023-12-12T22:19:42.900042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:19:42.997296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 2117
100.0%

신청금액(운전_백만원)
Real number (ℝ)

HIGH CORRELATION 

Distinct34
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean181.73925
Minimum30
Maximum1000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size18.7 KiB
2023-12-12T22:19:43.101274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum30
5-th percentile50
Q1100
median150
Q3200
95-th percentile500
Maximum1000
Range970
Interquartile range (IQR)100

Descriptive statistics

Standard deviation135.00302
Coefficient of variation (CV)0.74283909
Kurtosis11.410306
Mean181.73925
Median Absolute Deviation (MAD)50
Skewness2.733154
Sum384742
Variance18225.816
MonotonicityNot monotonic
2023-12-12T22:19:43.225117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
100 756
35.7%
200 547
25.8%
300 241
 
11.4%
50 170
 
8.0%
150 145
 
6.8%
500 111
 
5.2%
1000 19
 
0.9%
70 17
 
0.8%
80 16
 
0.8%
250 15
 
0.7%
Other values (24) 80
 
3.8%
ValueCountFrequency (%)
30 6
 
0.3%
40 8
 
0.4%
50 170
 
8.0%
60 3
 
0.1%
70 17
 
0.8%
80 16
 
0.8%
90 11
 
0.5%
100 756
35.7%
120 7
 
0.3%
130 3
 
0.1%
ValueCountFrequency (%)
1000 19
 
0.9%
700 2
 
0.1%
600 4
 
0.2%
500 111
5.2%
450 1
 
< 0.1%
400 13
 
0.6%
300 241
11.4%
290 1
 
< 0.1%
280 2
 
0.1%
260 1
 
< 0.1%

신청금액(합계_백만원)
Real number (ℝ)

HIGH CORRELATION 

Distinct34
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean181.73925
Minimum30
Maximum1000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size18.7 KiB
2023-12-12T22:19:43.355508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum30
5-th percentile50
Q1100
median150
Q3200
95-th percentile500
Maximum1000
Range970
Interquartile range (IQR)100

Descriptive statistics

Standard deviation135.00302
Coefficient of variation (CV)0.74283909
Kurtosis11.410306
Mean181.73925
Median Absolute Deviation (MAD)50
Skewness2.733154
Sum384742
Variance18225.816
MonotonicityNot monotonic
2023-12-12T22:19:43.475806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
100 756
35.7%
200 547
25.8%
300 241
 
11.4%
50 170
 
8.0%
150 145
 
6.8%
500 111
 
5.2%
1000 19
 
0.9%
70 17
 
0.8%
80 16
 
0.8%
250 15
 
0.7%
Other values (24) 80
 
3.8%
ValueCountFrequency (%)
30 6
 
0.3%
40 8
 
0.4%
50 170
 
8.0%
60 3
 
0.1%
70 17
 
0.8%
80 16
 
0.8%
90 11
 
0.5%
100 756
35.7%
120 7
 
0.3%
130 3
 
0.1%
ValueCountFrequency (%)
1000 19
 
0.9%
700 2
 
0.1%
600 4
 
0.2%
500 111
5.2%
450 1
 
< 0.1%
400 13
 
0.6%
300 241
11.4%
290 1
 
< 0.1%
280 2
 
0.1%
260 1
 
< 0.1%

추천금액(시설_백만원)
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size16.7 KiB
0
2117 

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 2117
100.0%

Length

2023-12-12T22:19:43.588566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:19:43.684352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 2117
100.0%

추천금액(운전_백만원)
Real number (ℝ)

HIGH CORRELATION 

Distinct38
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean139.54795
Minimum30
Maximum1000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size18.7 KiB
2023-12-12T22:19:43.791149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum30
5-th percentile50
Q1100
median100
Q3200
95-th percentile300
Maximum1000
Range970
Interquartile range (IQR)100

Descriptive statistics

Standard deviation85.713155
Coefficient of variation (CV)0.61422012
Kurtosis8.9833637
Mean139.54795
Median Absolute Deviation (MAD)50
Skewness2.1651385
Sum295423
Variance7346.745
MonotonicityNot monotonic
2023-12-12T22:19:43.918914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=38)
ValueCountFrequency (%)
100 893
42.2%
200 427
20.2%
50 275
 
13.0%
150 173
 
8.2%
300 139
 
6.6%
70 38
 
1.8%
80 37
 
1.7%
500 33
 
1.6%
250 23
 
1.1%
30 16
 
0.8%
Other values (28) 63
 
3.0%
ValueCountFrequency (%)
30 16
 
0.8%
40 8
 
0.4%
50 275
 
13.0%
60 4
 
0.2%
70 38
 
1.8%
80 37
 
1.7%
90 12
 
0.6%
100 893
42.2%
110 1
 
< 0.1%
120 5
 
0.2%
ValueCountFrequency (%)
1000 1
 
< 0.1%
700 1
 
< 0.1%
500 33
 
1.6%
450 2
 
0.1%
430 1
 
< 0.1%
400 1
 
< 0.1%
385 1
 
< 0.1%
300 139
6.6%
290 1
 
< 0.1%
280 1
 
< 0.1%

추천금액(합계_백만원)
Real number (ℝ)

HIGH CORRELATION 

Distinct38
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean139.54795
Minimum30
Maximum1000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size18.7 KiB
2023-12-12T22:19:44.057555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum30
5-th percentile50
Q1100
median100
Q3200
95-th percentile300
Maximum1000
Range970
Interquartile range (IQR)100

Descriptive statistics

Standard deviation85.713155
Coefficient of variation (CV)0.61422012
Kurtosis8.9833637
Mean139.54795
Median Absolute Deviation (MAD)50
Skewness2.1651385
Sum295423
Variance7346.745
MonotonicityNot monotonic
2023-12-12T22:19:44.206783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=38)
ValueCountFrequency (%)
100 893
42.2%
200 427
20.2%
50 275
 
13.0%
150 173
 
8.2%
300 139
 
6.6%
70 38
 
1.8%
80 37
 
1.7%
500 33
 
1.6%
250 23
 
1.1%
30 16
 
0.8%
Other values (28) 63
 
3.0%
ValueCountFrequency (%)
30 16
 
0.8%
40 8
 
0.4%
50 275
 
13.0%
60 4
 
0.2%
70 38
 
1.8%
80 37
 
1.7%
90 12
 
0.6%
100 893
42.2%
110 1
 
< 0.1%
120 5
 
0.2%
ValueCountFrequency (%)
1000 1
 
< 0.1%
700 1
 
< 0.1%
500 33
 
1.6%
450 2
 
0.1%
430 1
 
< 0.1%
400 1
 
< 0.1%
385 1
 
< 0.1%
300 139
6.6%
290 1
 
< 0.1%
280 1
 
< 0.1%

대여금액(시설_백만원)
Categorical

CONSTANT 

Distinct1
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size16.7 KiB
0
2117 

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 2117
100.0%

Length

2023-12-12T22:19:44.635434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T22:19:44.732422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 2117
100.0%

대여금액(운전_백만원)
Real number (ℝ)

HIGH CORRELATION 

Distinct39
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean139.42041
Minimum30
Maximum1000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size18.7 KiB
2023-12-12T22:19:44.898322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum30
5-th percentile50
Q1100
median100
Q3200
95-th percentile300
Maximum1000
Range970
Interquartile range (IQR)100

Descriptive statistics

Standard deviation85.559246
Coefficient of variation (CV)0.61367807
Kurtosis9.0178446
Mean139.42041
Median Absolute Deviation (MAD)50
Skewness2.1652691
Sum295153
Variance7320.3846
MonotonicityNot monotonic
2023-12-12T22:19:45.045796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
ValueCountFrequency (%)
100 893
42.2%
200 425
20.1%
50 275
 
13.0%
150 174
 
8.2%
300 139
 
6.6%
70 38
 
1.8%
80 38
 
1.8%
500 33
 
1.6%
250 23
 
1.1%
30 16
 
0.8%
Other values (29) 63
 
3.0%
ValueCountFrequency (%)
30 16
 
0.8%
40 8
 
0.4%
50 275
 
13.0%
60 4
 
0.2%
70 38
 
1.8%
80 38
 
1.8%
90 12
 
0.6%
100 893
42.2%
110 1
 
< 0.1%
120 5
 
0.2%
ValueCountFrequency (%)
1000 1
 
< 0.1%
700 1
 
< 0.1%
500 33
 
1.6%
450 1
 
< 0.1%
430 1
 
< 0.1%
400 1
 
< 0.1%
385 1
 
< 0.1%
350 1
 
< 0.1%
300 139
6.6%
290 1
 
< 0.1%

대여금액(합계_백만원)
Real number (ℝ)

HIGH CORRELATION 

Distinct39
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean139.42041
Minimum30
Maximum1000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size18.7 KiB
2023-12-12T22:19:45.213342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum30
5-th percentile50
Q1100
median100
Q3200
95-th percentile300
Maximum1000
Range970
Interquartile range (IQR)100

Descriptive statistics

Standard deviation85.559246
Coefficient of variation (CV)0.61367807
Kurtosis9.0178446
Mean139.42041
Median Absolute Deviation (MAD)50
Skewness2.1652691
Sum295153
Variance7320.3846
MonotonicityNot monotonic
2023-12-12T22:19:45.350260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
ValueCountFrequency (%)
100 893
42.2%
200 425
20.1%
50 275
 
13.0%
150 174
 
8.2%
300 139
 
6.6%
70 38
 
1.8%
80 38
 
1.8%
500 33
 
1.6%
250 23
 
1.1%
30 16
 
0.8%
Other values (29) 63
 
3.0%
ValueCountFrequency (%)
30 16
 
0.8%
40 8
 
0.4%
50 275
 
13.0%
60 4
 
0.2%
70 38
 
1.8%
80 38
 
1.8%
90 12
 
0.6%
100 893
42.2%
110 1
 
< 0.1%
120 5
 
0.2%
ValueCountFrequency (%)
1000 1
 
< 0.1%
700 1
 
< 0.1%
500 33
 
1.6%
450 1
 
< 0.1%
430 1
 
< 0.1%
400 1
 
< 0.1%
385 1
 
< 0.1%
350 1
 
< 0.1%
300 139
6.6%
290 1
 
< 0.1%

업종
Categorical

Distinct11
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size16.7 KiB
금속
348 
기계
315 
기타
297 
유통
285 
잡화
203 
Other values (6)
669 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
금속 348
16.4%
기계 315
14.9%
기타 297
14.0%
유통 285
13.5%
잡화 203
9.6%
화공 191
9.0%
식료 171
8.1%
전기 96
 
4.5%
섬유 83
 
3.9%
전자 66
 
3.1%

Length

2023-12-12T22:19:45.471811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
금속 348
16.4%
기계 315
14.9%
기타 297
14.0%
유통 285
13.5%
잡화 203
9.6%
화공 191
9.0%
식료 171
8.1%
전기 96
 
4.5%
섬유 83
 
3.9%
전자 66
 
3.1%

Interactions

2023-12-12T22:19:39.605847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:19:34.933134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:19:35.585250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:19:36.567667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:19:37.298354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:19:38.253379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:19:38.904024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:19:39.708944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:19:35.021838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:19:35.749665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:19:36.676171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:19:37.389901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:19:38.334796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:19:38.987239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:19:39.827715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:19:35.117486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:19:35.954069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:19:36.797819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:19:37.488641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:19:38.421101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:19:39.078152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:19:39.953791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:19:35.210086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:19:36.093927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:19:36.917288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:19:37.592637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:19:38.501586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:19:39.174991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:19:40.077404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:19:35.302979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:19:36.204699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:19:37.009612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:19:37.674678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:19:38.608592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:19:39.297390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:19:40.221175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:19:35.397741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:19:36.323193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:19:37.099650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:19:38.073660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:19:38.705582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:19:39.384431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:19:40.364462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:19:35.478539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:19:36.459838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:19:37.203413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:19:38.158421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:19:38.797904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:19:39.496355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T22:19:45.569943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
일련번호자산규모매출규모업력구분(중진공)지역구분(중진공)신청금액(운전_백만원)신청금액(합계_백만원)추천금액(운전_백만원)추천금액(합계_백만원)대여금액(운전_백만원)대여금액(합계_백만원)업종
일련번호1.0000.1160.1070.0340.2640.0740.0740.0830.0830.0930.0930.090
자산규모0.1161.0000.7940.2820.1330.3610.3610.4160.4160.4140.4140.123
매출규모0.1070.7941.0000.1840.1370.4080.4080.4470.4470.4470.4470.172
업력구분(중진공)0.0340.2820.1841.0000.2150.1880.1880.1570.1570.1550.1550.125
지역구분(중진공)0.2640.1330.1370.2151.0000.2310.2310.1990.1990.1950.1950.402
신청금액(운전_백만원)0.0740.3610.4080.1880.2311.0001.0000.7730.7730.7660.7660.085
신청금액(합계_백만원)0.0740.3610.4080.1880.2311.0001.0000.7730.7730.7660.7660.085
추천금액(운전_백만원)0.0830.4160.4470.1570.1990.7730.7731.0001.0001.0001.0000.092
추천금액(합계_백만원)0.0830.4160.4470.1570.1990.7730.7731.0001.0001.0001.0000.092
대여금액(운전_백만원)0.0930.4140.4470.1550.1950.7660.7661.0001.0001.0001.0000.099
대여금액(합계_백만원)0.0930.4140.4470.1550.1950.7660.7661.0001.0001.0001.0000.099
업종0.0900.1230.1720.1250.4020.0850.0850.0920.0920.0990.0991.000
2023-12-12T22:19:45.728305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
매출규모업력구분(중진공)지역구분(중진공)자산규모업종
매출규모1.0000.1030.0650.4030.088
업력구분(중진공)0.1031.0000.0910.1610.059
지역구분(중진공)0.0650.0911.0000.0630.162
자산규모0.4030.1610.0631.0000.063
업종0.0880.0590.1620.0631.000
2023-12-12T22:19:45.858769image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
일련번호신청금액(운전_백만원)신청금액(합계_백만원)추천금액(운전_백만원)추천금액(합계_백만원)대여금액(운전_백만원)대여금액(합계_백만원)자산규모매출규모업력구분(중진공)지역구분(중진공)업종
일련번호1.000-0.049-0.0490.0440.0440.0420.0420.0610.0560.0160.1050.038
신청금액(운전_백만원)-0.0491.0001.0000.7970.7970.7970.7970.2100.2410.0640.0990.040
신청금액(합계_백만원)-0.0491.0001.0000.7970.7970.7970.7970.2100.2410.0640.0990.040
추천금액(운전_백만원)0.0440.7970.7971.0001.0000.9990.9990.2630.2850.0850.0900.045
추천금액(합계_백만원)0.0440.7970.7971.0001.0000.9990.9990.2630.2850.0850.0900.045
대여금액(운전_백만원)0.0420.7970.7970.9990.9991.0001.0000.2620.2860.0830.0880.049
대여금액(합계_백만원)0.0420.7970.7970.9990.9991.0001.0000.2620.2860.0830.0880.049
자산규모0.0610.2100.2100.2630.2630.2620.2621.0000.4030.1610.0630.063
매출규모0.0560.2410.2410.2850.2850.2860.2860.4031.0000.1030.0650.088
업력구분(중진공)0.0160.0640.0640.0850.0850.0830.0830.1610.1031.0000.0910.059
지역구분(중진공)0.1050.0990.0990.0900.0900.0880.0880.0630.0650.0911.0000.162
업종0.0380.0400.0400.0450.0450.0490.0490.0630.0880.0590.1621.000

Missing values

2023-12-12T22:19:40.603793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T22:19:40.889014image/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

일련번호사업1사업2자산규모매출규모업력구분(중진공)지역구분(중진공)신청금액(시설_백만원)신청금액(운전_백만원)신청금액(합계_백만원)추천금액(시설_백만원)추천금액(운전_백만원)추천금액(합계_백만원)대여금액(시설_백만원)대여금액(운전_백만원)대여금액(합계_백만원)업종
01일시적경영애로긴급경영안정70억미만5억미만3년미만경남040040002002000200200금속
12일시적경영애로긴급경영안정70억미만100억미만15년미만전북030030003003000300300잡화
23일시적경영애로긴급경영안정200억미만100억미만15년미만광주015015001501500150150금속
34일시적경영애로긴급경영안정30억미만50억미만15년미만강원020020002002000200200잡화
45일시적경영애로긴급경영안정30억미만100억미만10년미만울산020020002002000200200유통
56일시적경영애로긴급경영안정30억미만50억미만15년미만대구015015001501500150150섬유
67일시적경영애로긴급경영안정70억미만100억미만15년미만전남025025002502500250250기타
78일시적경영애로긴급경영안정70억미만50억미만15년미만경북030030003003000300300금속
89일시적경영애로긴급경영안정10억미만50억미만5년미만경남030030001501500150150기타
910일시적경영애로긴급경영안정70억미만100억미만15년미만경기050050002002000200200유통
일련번호사업1사업2자산규모매출규모업력구분(중진공)지역구분(중진공)신청금액(시설_백만원)신청금액(운전_백만원)신청금액(합계_백만원)추천금액(시설_백만원)추천금액(운전_백만원)추천금액(합계_백만원)대여금액(시설_백만원)대여금액(운전_백만원)대여금액(합계_백만원)업종
21072108일시적경영애로긴급경영안정70억미만50억미만7년미만경남020020002002000200200전기
21082109일시적경영애로긴급경영안정10억미만50억미만5년미만전북010010001001000100100기타
21092110일시적경영애로긴급경영안정100억미만50억미만10년미만부산020020002002000200200기계
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