Overview

Dataset statistics

Number of variables8
Number of observations27
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.0 KiB
Average record size in memory75.7 B

Variable types

Text1
Numeric7

Dataset

Description중소벤처기업진흥공단 정책자금의 2023년 각 사업별 신청금액, 추천금액, 대출금액 데이터를 개방하여 활용할 수 있도록 함.
Author중소벤처기업진흥공단
URLhttps://www.data.go.kr/data/15069472/fileData.do

Alerts

예산(백만원) is highly overall correlated with 신청금액(시설_백만원) and 5 other fieldsHigh correlation
신청금액(시설_백만원) is highly overall correlated with 예산(백만원) and 5 other fieldsHigh correlation
신청금액(운전_백만원) is highly overall correlated with 예산(백만원) and 5 other fieldsHigh correlation
추천금액(시설_백만원) is highly overall correlated with 예산(백만원) and 5 other fieldsHigh correlation
추천금액(운전_백만원) is highly overall correlated with 예산(백만원) and 5 other fieldsHigh correlation
대출금액(시설_백만원) is highly overall correlated with 예산(백만원) and 5 other fieldsHigh correlation
대출금액(운전_백만원) is highly overall correlated with 예산(백만원) and 5 other fieldsHigh correlation
신청금액(운전_백만원) has unique valuesUnique
추천금액(운전_백만원) has unique valuesUnique
대출금액(운전_백만원) has unique valuesUnique
예산(백만원) has 1 (3.7%) zerosZeros
신청금액(시설_백만원) has 8 (29.6%) zerosZeros
추천금액(시설_백만원) has 8 (29.6%) zerosZeros
대출금액(시설_백만원) has 8 (29.6%) zerosZeros

Reproduction

Analysis started2024-03-14 18:57:49.825673
Analysis finished2024-03-14 18:58:05.176386
Duration15.35 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구분
Text

Distinct25
Distinct (%)92.6%
Missing0
Missing (%)0.0%
Memory size344.0 B
2024-03-15T03:58:05.709203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length10
Mean length6.5925926
Min length2

Characters and Unicode

Total characters178
Distinct characters76
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique24 ?
Unique (%)88.9%

Sample

1st row혁신창업사업화
2nd row창업기반지원
3rd row일반
4th row 대환대출
5th row청년전용창업(일반)
ValueCountFrequency (%)
일반 3
 
10.0%
스케일업금융 1
 
3.3%
신시장진출지원자금 1
 
3.3%
재창업 1
 
3.3%
무역조정 1
 
3.3%
사업전환 1
 
3.3%
재도약지원자금 1
 
3.3%
포항피해기업지원 1
 
3.3%
재해중소기업 1
 
3.3%
일시적경영애로 1
 
3.3%
Other values (18) 18
60.0%
2024-03-15T03:58:06.584699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
업 15
 
8.4%
기 9
 
5.1%
일 6
 
3.4%
반 6
 
3.4%
6
 
3.4%
화 6
 
3.4%
창 6
 
3.4%
원 5
 
2.8%
금 5
 
2.8%
지 5
 
2.8%
Other values (66) 109
61.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 160
89.9%
Space Separator 6
 
3.4%
Lowercase Letter 5
 
2.8%
Close Punctuation 2
 
1.1%
Open Punctuation 2
 
1.1%
Uppercase Letter 2
 
1.1%
Dash Punctuation 1
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
업 15
 
9.4%
기 9
 
5.6%
일 6
 
3.8%
반 6
 
3.8%
화 6
 
3.8%
창 6
 
3.8%
원 5
 
3.1%
금 5
 
3.1%
지 5
 
3.1%
전 4
 
2.5%
Other values (56) 93
58.1%
Lowercase Letter
ValueCountFrequency (%)
e 2
40.0%
t 1
20.0%
r 1
20.0%
o 1
20.0%
Uppercase Letter
ValueCountFrequency (%)
N 1
50.0%
Z 1
50.0%
Space Separator
ValueCountFrequency (%)
6
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 160
89.9%
Common 11
 
6.2%
Latin 7
 
3.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
업 15
 
9.4%
기 9
 
5.6%
일 6
 
3.8%
반 6
 
3.8%
화 6
 
3.8%
창 6
 
3.8%
원 5
 
3.1%
금 5
 
3.1%
지 5
 
3.1%
전 4
 
2.5%
Other values (56) 93
58.1%
Latin
ValueCountFrequency (%)
e 2
28.6%
N 1
14.3%
t 1
14.3%
Z 1
14.3%
r 1
14.3%
o 1
14.3%
Common
ValueCountFrequency (%)
6
54.5%
) 2
 
18.2%
( 2
 
18.2%
- 1
 
9.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 160
89.9%
ASCII 18
 
10.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
업 15
 
9.4%
기 9
 
5.6%
일 6
 
3.8%
반 6
 
3.8%
화 6
 
3.8%
창 6
 
3.8%
원 5
 
3.1%
금 5
 
3.1%
지 5
 
3.1%
전 4
 
2.5%
Other values (56) 93
58.1%
ASCII
ValueCountFrequency (%)
6
33.3%
e 2
 
11.1%
) 2
 
11.1%
( 2
 
11.1%
N 1
 
5.6%
t 1
 
5.6%
- 1
 
5.6%
Z 1
 
5.6%
r 1
 
5.6%
o 1
 
5.6%

예산(백만원)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct25
Distinct (%)92.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean449613.3
Minimum0
Maximum2330000
Zeros1
Zeros (%)3.7%
Negative0
Negative (%)0.0%
Memory size371.0 B
2024-03-15T03:58:06.802212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile4128.4
Q167500
median240000
Q3429000
95-th percentile1955000
Maximum2330000
Range2330000
Interquartile range (IQR)361500

Descriptive statistics

Standard deviation643592.61
Coefficient of variation (CV)1.4314359
Kurtosis3.0279035
Mean449613.3
Median Absolute Deviation (MAD)183000
Skewness1.9882328
Sum12139559
Variance4.1421145 × 1011
MonotonicityNot monotonic
2024-03-15T03:58:07.100522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
250000.0 2
 
7.4%
100000.0 2
 
7.4%
2329999.999 1
 
3.7%
98000.0 1
 
3.7%
75000.0 1
 
3.7%
10000.0 1
 
3.7%
240000.0 1
 
3.7%
423000.0 1
 
3.7%
1612.0 1
 
3.7%
0.0 1
 
3.7%
Other values (15) 15
55.6%
ValueCountFrequency (%)
0.0 1
3.7%
1612.0 1
3.7%
10000.0 1
3.7%
20759.0 1
3.7%
30100.0 1
3.7%
45000.0 1
3.7%
60000.0 1
3.7%
75000.0 1
3.7%
98000.0 1
3.7%
100000.0 2
7.4%
ValueCountFrequency (%)
2329999.999 1
3.7%
2029999.999 1
3.7%
1779999.999 1
3.7%
1285000.0 1
3.7%
745000.0 1
3.7%
645000.0 1
3.7%
435000.0 1
3.7%
423000.0 1
3.7%
300000.0 1
3.7%
258900.0 1
3.7%

신청금액(시설_백만원)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct19
Distinct (%)70.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean335708.85
Minimum0
Maximum1757700
Zeros8
Zeros (%)29.6%
Negative0
Negative (%)0.0%
Memory size371.0 B
2024-03-15T03:58:07.402271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median32607
Q3531917.5
95-th percentile1296706.2
Maximum1757700
Range1757700
Interquartile range (IQR)531917.5

Descriptive statistics

Standard deviation526171.94
Coefficient of variation (CV)1.5673461
Kurtosis0.93798645
Mean335708.85
Median Absolute Deviation (MAD)32607
Skewness1.4701702
Sum9064139
Variance2.7685692 × 1011
MonotonicityNot monotonic
2024-03-15T03:58:07.799354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
0 8
29.6%
3195 2
 
7.4%
1311525 1
 
3.7%
71986 1
 
3.7%
1240 1
 
3.7%
32607 1
 
3.7%
1500 1
 
3.7%
256455 1
 
3.7%
257955 1
 
3.7%
291802 1
 
3.7%
Other values (9) 9
33.3%
ValueCountFrequency (%)
0 8
29.6%
300 1
 
3.7%
1240 1
 
3.7%
1500 1
 
3.7%
3195 2
 
7.4%
32607 1
 
3.7%
43578 1
 
3.7%
49396 1
 
3.7%
71986 1
 
3.7%
256455 1
 
3.7%
ValueCountFrequency (%)
1757700 1
3.7%
1311525 1
3.7%
1262129 1
3.7%
1261829 1
3.7%
870103 1
3.7%
815611 1
3.7%
772033 1
3.7%
291802 1
3.7%
257955 1
3.7%
256455 1
3.7%

신청금액(운전_백만원)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct27
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean350587.07
Minimum1814
Maximum1867644
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size371.0 B
2024-03-15T03:58:08.195243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1814
5-th percentile6319.8
Q158793.5
median171990
Q3335626
95-th percentile1437472.7
Maximum1867644
Range1865830
Interquartile range (IQR)276832.5

Descriptive statistics

Standard deviation471032.2
Coefficient of variation (CV)1.3435527
Kurtosis4.445223
Mean350587.07
Median Absolute Deviation (MAD)145865
Skewness2.2074193
Sum9465851
Variance2.2187133 × 1011
MonotonicityNot monotonic
2024-03-15T03:58:08.485001image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
1867644 1
 
3.7%
1531286 1
 
3.7%
145222 1
 
3.7%
77581 1
 
3.7%
9600 1
 
3.7%
149960 1
 
3.7%
159560 1
 
3.7%
382363 1
 
3.7%
1814 1
 
3.7%
40006 1
 
3.7%
Other values (17) 17
63.0%
ValueCountFrequency (%)
1814 1
3.7%
4914 1
3.7%
9600 1
3.7%
23796 1
3.7%
32860 1
3.7%
37445 1
3.7%
40006 1
3.7%
77581 1
3.7%
97100 1
3.7%
138050 1
3.7%
ValueCountFrequency (%)
1867644 1
3.7%
1531286 1
3.7%
1218575 1
3.7%
798818 1
3.7%
421565 1
3.7%
382363 1
3.7%
336358 1
3.7%
334894 1
3.7%
324465 1
3.7%
317855 1
3.7%

추천금액(시설_백만원)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct19
Distinct (%)70.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean299281.52
Minimum0
Maximum1543096
Zeros8
Zeros (%)29.6%
Negative0
Negative (%)0.0%
Memory size371.0 B
2024-03-15T03:58:08.797005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median29670
Q3469746
95-th percentile1172943.2
Maximum1543096
Range1543096
Interquartile range (IQR)469746

Descriptive statistics

Standard deviation468634.88
Coefficient of variation (CV)1.5658664
Kurtosis0.87168306
Mean299281.52
Median Absolute Deviation (MAD)29670
Skewness1.4631125
Sum8080601
Variance2.1961865 × 1011
MonotonicityNot monotonic
2024-03-15T03:58:09.021945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
0 8
29.6%
3038 2
 
7.4%
1186958 1
 
3.7%
63566 1
 
3.7%
1240 1
 
3.7%
29670 1
 
3.7%
800 1
 
3.7%
232142 1
 
3.7%
232942 1
 
3.7%
263852 1
 
3.7%
Other values (9) 9
33.3%
ValueCountFrequency (%)
0 8
29.6%
245 1
 
3.7%
800 1
 
3.7%
1240 1
 
3.7%
3038 2
 
7.4%
29670 1
 
3.7%
37889 1
 
3.7%
46716 1
 
3.7%
63566 1
 
3.7%
232142 1
 
3.7%
ValueCountFrequency (%)
1543096 1
3.7%
1186958 1
3.7%
1140242 1
3.7%
1139997 1
3.7%
766001 1
3.7%
713529 1
3.7%
675640 1
3.7%
263852 1
3.7%
232942 1
3.7%
232142 1
3.7%

추천금액(운전_백만원)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct27
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean258050.37
Minimum1612
Maximum1459241
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size371.0 B
2024-03-15T03:58:09.247012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1612
5-th percentile6047.2
Q144526
median122981
Q3260259.5
95-th percentile1116468.1
Maximum1459241
Range1457629
Interquartile range (IQR)215733.5

Descriptive statistics

Standard deviation362615.79
Coefficient of variation (CV)1.4052132
Kurtosis5.2867981
Mean258050.37
Median Absolute Deviation (MAD)101178
Skewness2.38176
Sum6967360
Variance1.3149021 × 1011
MonotonicityNot monotonic
2024-03-15T03:58:09.499138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
1459241 1
 
3.7%
1198252 1
 
3.7%
97860 1
 
3.7%
54465 1
 
3.7%
9200 1
 
3.7%
113781 1
 
3.7%
122981 1
 
3.7%
275306 1
 
3.7%
1612 1
 
3.7%
33759 1
 
3.7%
Other values (17) 17
63.0%
ValueCountFrequency (%)
1612 1
3.7%
4696 1
3.7%
9200 1
3.7%
22478 1
3.7%
30140 1
3.7%
33759 1
3.7%
34587 1
3.7%
54465 1
3.7%
60000 1
3.7%
83177 1
3.7%
ValueCountFrequency (%)
1459241 1
3.7%
1198252 1
3.7%
925639 1
3.7%
420278 1
3.7%
320995 1
3.7%
275306 1
3.7%
260989 1
3.7%
259530 1
3.7%
248211 1
3.7%
237818 1
3.7%

대출금액(시설_백만원)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct19
Distinct (%)70.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean192173.93
Minimum0
Maximum878455
Zeros8
Zeros (%)29.6%
Negative0
Negative (%)0.0%
Memory size371.0 B
2024-03-15T03:58:09.928522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median17166
Q3275758.5
95-th percentile859785.3
Maximum878455
Range878455
Interquartile range (IQR)275758.5

Descriptive statistics

Standard deviation310296.89
Coefficient of variation (CV)1.614667
Kurtosis0.84195082
Mean192173.93
Median Absolute Deviation (MAD)17166
Skewness1.5224679
Sum5188696
Variance9.628416 × 1010
MonotonicityNot monotonic
2024-03-15T03:58:10.313573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
0 8
29.6%
2089 2
 
7.4%
878455 1
 
3.7%
40995 1
 
3.7%
608 1
 
3.7%
20585 1
 
3.7%
800 1
 
3.7%
127020 1
 
3.7%
127820 1
 
3.7%
149013 1
 
3.7%
Other values (9) 9
33.3%
ValueCountFrequency (%)
0 8
29.6%
245 1
 
3.7%
608 1
 
3.7%
800 1
 
3.7%
2089 2
 
7.4%
17166 1
 
3.7%
20585 1
 
3.7%
40089 1
 
3.7%
40995 1
 
3.7%
127020 1
 
3.7%
ValueCountFrequency (%)
878455 1
3.7%
868965 1
3.7%
838366 1
3.7%
838121 1
3.7%
425466 1
3.7%
408300 1
3.7%
402504 1
3.7%
149013 1
3.7%
127820 1
3.7%
127020 1
3.7%

대출금액(운전_백만원)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct27
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean256670.52
Minimum1612
Maximum1451545
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size371.0 B
2024-03-15T03:58:10.657022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1612
5-th percentile5563.5
Q144087
median122180
Q3259405.5
95-th percentile1110479.8
Maximum1451545
Range1449933
Interquartile range (IQR)215318.5

Descriptive statistics

Standard deviation360733.01
Coefficient of variation (CV)1.4054322
Kurtosis5.2833452
Mean256670.52
Median Absolute Deviation (MAD)101421
Skewness2.3804835
Sum6930104
Variance1.3012831 × 1011
MonotonicityNot monotonic
2024-03-15T03:58:10.880585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
1451544.999 1
 
3.7%
1191633.999 1
 
3.7%
97392.0 1
 
3.7%
54415.0 1
 
3.7%
9200.0 1
 
3.7%
112980.0 1
 
3.7%
122180.0 1
 
3.7%
273987.0 1
 
3.7%
1612.0 1
 
3.7%
33759.0 1
 
3.7%
Other values (17) 17
63.0%
ValueCountFrequency (%)
1612.0 1
3.7%
4005.0 1
3.7%
9200.0 1
3.7%
20759.0 1
3.7%
30100.0 1
3.7%
32496.0 1
3.7%
33759.0 1
3.7%
54415.0 1
3.7%
60000.0 1
3.7%
82834.0 1
3.7%
ValueCountFrequency (%)
1451544.999 1
3.7%
1191633.999 1
3.7%
921119.9994 1
3.7%
416035.0 1
3.7%
319534.0 1
3.7%
273987.0 1
3.7%
259910.9997 1
3.7%
258900.0 1
3.7%
247911.0 1
3.7%
236700.0 1
3.7%

Interactions

2024-03-15T03:58:02.397223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T03:57:50.345178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T03:57:52.069535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T03:57:53.863963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T03:57:56.077231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T03:57:58.624832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T03:58:00.629426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T03:58:02.646209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T03:57:50.579339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T03:57:52.322231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T03:57:54.112318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T03:57:56.480635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T03:57:58.880391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T03:58:00.863861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T03:58:02.932086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T03:57:50.836625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T03:57:52.592369image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T03:57:54.383773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T03:57:56.829854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T03:57:59.259281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T03:58:01.117791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T03:58:03.196550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T03:57:51.092724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T03:57:52.860087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T03:57:54.649824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T03:57:57.152667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T03:57:59.556028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T03:58:01.375902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T03:58:03.471596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T03:57:51.357353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T03:57:53.074034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T03:57:55.054325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T03:57:57.479552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T03:57:59.844559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T03:58:01.647758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T03:58:03.735716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T03:57:51.612530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T03:57:53.347010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T03:57:55.359385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T03:57:58.004398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T03:58:00.133654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T03:58:01.905884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T03:58:04.179578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T03:57:51.818107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T03:57:53.596587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T03:57:55.693193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T03:57:58.341621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T03:58:00.391961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T03:58:02.135701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-15T03:58:11.141642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분예산(백만원)신청금액(시설_백만원)신청금액(운전_백만원)추천금액(시설_백만원)추천금액(운전_백만원)대출금액(시설_백만원)대출금액(운전_백만원)
구분1.0000.0000.0000.0000.0000.0000.0000.000
예산(백만원)0.0001.0000.8890.9400.8890.9590.9590.959
신청금액(시설_백만원)0.0000.8891.0000.7941.0000.6581.0000.658
신청금액(운전_백만원)0.0000.9400.7941.0000.7940.9530.6570.953
추천금액(시설_백만원)0.0000.8891.0000.7941.0000.6581.0000.658
추천금액(운전_백만원)0.0000.9590.6580.9530.6581.0000.5941.000
대출금액(시설_백만원)0.0000.9591.0000.6571.0000.5941.0000.594
대출금액(운전_백만원)0.0000.9590.6580.9530.6581.0000.5941.000
2024-03-15T03:58:11.392843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
예산(백만원)신청금액(시설_백만원)신청금액(운전_백만원)추천금액(시설_백만원)추천금액(운전_백만원)대출금액(시설_백만원)대출금액(운전_백만원)
예산(백만원)1.0000.7770.8500.7800.9050.7790.893
신청금액(시설_백만원)0.7771.0000.5570.9990.6000.9970.589
신청금액(운전_백만원)0.8500.5571.0000.5620.9570.5770.957
추천금액(시설_백만원)0.7800.9990.5621.0000.6050.9960.594
추천금액(운전_백만원)0.9050.6000.9570.6051.0000.6170.999
대출금액(시설_백만원)0.7790.9970.5770.9960.6171.0000.607
대출금액(운전_백만원)0.8930.5890.9570.5940.9990.6071.000

Missing values

2024-03-15T03:58:04.549396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-15T03:58:04.958558image/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

구분예산(백만원)신청금액(시설_백만원)신청금액(운전_백만원)추천금액(시설_백만원)추천금액(운전_백만원)대출금액(시설_백만원)대출금액(운전_백만원)
0혁신창업사업화2329999.99913115251867644118695814592418784551451544.999
1창업기반지원2029999.99912621291531286114024211982528383661191633.999
2일반1779999.999126182912185751139997925639838121921119.9994
3대환대출20759.0023796022478020759.0
4청년전용창업(일반)219900.0300256055245219995245219655.0
5청년전용창업(창성패)30100.0032860030140030100.0
6개발기술사업화300000.0493963363584671626098940089259910.9997
7신성장기반자금1285000.017577007988181543096420278868965416035.0
8혁신성장지원745000.0815611421565713529320995425466319534.0
9일반645000.0772033324465675640237818408300236700.0
구분예산(백만원)신청금액(시설_백만원)신청금액(운전_백만원)추천금액(시설_백만원)추천금액(운전_백만원)대출금액(시설_백만원)대출금액(운전_백만원)
17긴급경영안정자금258900.0031785502595300258900.0
18일시적경영애로257288.0027603502241590223529.0
19재해중소기업0.0040006033759033759.0
20포항피해기업지원1612.0018140161201612.0
21재도약지원자금423000.0291802382363263852275306149013273987.0
22사업전환250000.0257955159560232942122981127820122180.0
23일반240000.0256455149960232142113781127020112980.0
24무역조정10000.01500960080092008009200.0
25재창업75000.0326077758129670544652058554415.0
26구조개선전용98000.0124014522212409786060897392.0