Overview

Dataset statistics

Number of variables7
Number of observations27
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.8 KiB
Average record size in memory66.7 B

Variable types

Text1
Numeric6

Dataset

Description중소벤처기업진흥공단에서 운영하는 정책자금 지원실적 데이터로 각 세부사업의 자금종류별 정책자금 지원현황을 등록합니다.
Author중소벤처기업진흥공단
URLhttps://www.data.go.kr/data/15070036/fileData.do

Alerts

신청건수 is highly overall correlated with 신청금액(백만원) and 4 other fieldsHigh correlation
신청금액(백만원) is highly overall correlated with 신청건수 and 4 other fieldsHigh correlation
지원결정건수 is highly overall correlated with 신청건수 and 4 other fieldsHigh correlation
지원결정금액(백만원) is highly overall correlated with 신청건수 and 4 other fieldsHigh correlation
대출건수 is highly overall correlated with 신청건수 and 4 other fieldsHigh correlation
대출금액(백만원) is highly overall correlated with 신청건수 and 4 other fieldsHigh correlation
신청건수 has unique valuesUnique
신청금액(백만원) has unique valuesUnique
지원결정건수 has unique valuesUnique
지원결정금액(백만원) has unique valuesUnique
대출건수 has unique valuesUnique

Reproduction

Analysis started2024-03-14 08:57:49.569368
Analysis finished2024-03-14 08:57:58.621459
Duration9.05 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
2024-03-14T17:57:59.138867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length9
Mean length6.5185185
Min length2

Characters and Unicode

Total characters176
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 row대환대출
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%
2024-03-14T17:58:00.272410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
업 15
 
8.5%
기 9
 
5.1%
일 6
 
3.4%
창 6
 
3.4%
반 6
 
3.4%
화 6
 
3.4%
금 5
 
2.8%
원 5
 
2.8%
지 5
 
2.8%
4
 
2.3%
Other values (66) 109
61.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 160
90.9%
Lowercase Letter 5
 
2.8%
Space Separator 4
 
2.3%
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%
창 6
 
3.8%
반 6
 
3.8%
화 6
 
3.8%
금 5
 
3.1%
원 5
 
3.1%
지 5
 
3.1%
자 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 (%)
4
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
90.9%
Common 9
 
5.1%
Latin 7
 
4.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
업 15
 
9.4%
기 9
 
5.6%
일 6
 
3.8%
창 6
 
3.8%
반 6
 
3.8%
화 6
 
3.8%
금 5
 
3.1%
원 5
 
3.1%
지 5
 
3.1%
자 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 (%)
4
44.4%
) 2
22.2%
( 2
22.2%
- 1
 
11.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 160
90.9%
ASCII 16
 
9.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
업 15
 
9.4%
기 9
 
5.6%
일 6
 
3.8%
창 6
 
3.8%
반 6
 
3.8%
화 6
 
3.8%
금 5
 
3.1%
원 5
 
3.1%
지 5
 
3.1%
자 4
 
2.5%
Other values (56) 93
58.1%
ASCII
ValueCountFrequency (%)
4
25.0%
) 2
12.5%
( 2
12.5%
e 2
12.5%
N 1
 
6.2%
t 1
 
6.2%
- 1
 
6.2%
Z 1
 
6.2%
r 1
 
6.2%
o 1
 
6.2%

신청건수
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct27
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2042.0741
Minimum1
Maximum13242
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size371.0 B
2024-03-14T17:58:00.654586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile38.9
Q1308
median699
Q31593
95-th percentile10875.7
Maximum13242
Range13241
Interquartile range (IQR)1285

Descriptive statistics

Standard deviation3460.1267
Coefficient of variation (CV)1.6944178
Kurtosis5.7779327
Mean2042.0741
Median Absolute Deviation (MAD)644
Skewness2.5604133
Sum55136
Variance11972476
MonotonicityNot monotonic
2024-03-14T17:58:01.058543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
13242 1
 
3.7%
11932 1
 
3.7%
408 1
 
3.7%
563 1
 
3.7%
32 1
 
3.7%
512 1
 
3.7%
544 1
 
3.7%
1515 1
 
3.7%
1 1
 
3.7%
136 1
 
3.7%
Other values (17) 17
63.0%
ValueCountFrequency (%)
1 1
3.7%
32 1
3.7%
55 1
3.7%
136 1
3.7%
226 1
3.7%
263 1
3.7%
290 1
3.7%
326 1
3.7%
360 1
3.7%
408 1
3.7%
ValueCountFrequency (%)
13242 1
3.7%
11932 1
3.7%
8411 1
3.7%
3161 1
3.7%
2481 1
3.7%
1874 1
3.7%
1611 1
3.7%
1575 1
3.7%
1515 1
3.7%
1438 1
3.7%

신청금액(백만원)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct27
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean675077.26
Minimum39
Maximum3210576
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size371.0 B
2024-03-14T17:58:01.436386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum39
5-th percentile14726
Q1116902.5
median312226
Q3705156
95-th percentile2749449.8
Maximum3210576
Range3210537
Interquartile range (IQR)588253.5

Descriptive statistics

Standard deviation934479.1
Coefficient of variation (CV)1.384255
Kurtosis2.0936388
Mean675077.26
Median Absolute Deviation (MAD)264983
Skewness1.8135992
Sum18227086
Variance8.732512 × 1011
MonotonicityNot monotonic
2024-03-14T17:58:01.839127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
3210576 1
 
3.7%
2806187 1
 
3.7%
152126 1
 
3.7%
112857 1
 
3.7%
10400 1
 
3.7%
301826 1
 
3.7%
312226 1
 
3.7%
577209 1
 
3.7%
39 1
 
3.7%
39519 1
 
3.7%
Other values (17) 17
63.0%
ValueCountFrequency (%)
39 1
3.7%
10400 1
3.7%
24820 1
3.7%
39519 1
3.7%
40110 1
3.7%
43281 1
3.7%
112857 1
3.7%
120948 1
3.7%
143610 1
3.7%
152126 1
3.7%
ValueCountFrequency (%)
3210576 1
3.7%
2806187 1
3.7%
2617063 1
3.7%
2374482 1
3.7%
1102134 1
3.7%
954051 1
3.7%
833103 1
3.7%
577209 1
3.7%
517597 1
3.7%
404389 1
3.7%

지원결정건수
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct27
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1784.1481
Minimum1
Maximum11282
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size371.0 B
2024-03-14T17:58:02.218456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile38.5
Q1276
median663
Q31503.5
95-th percentile9352.7
Maximum11282
Range11281
Interquartile range (IQR)1227.5

Descriptive statistics

Standard deviation2962.9961
Coefficient of variation (CV)1.6607344
Kurtosis5.5044358
Mean1784.1481
Median Absolute Deviation (MAD)614
Skewness2.5235176
Sum48172
Variance8779346.1
MonotonicityNot monotonic
2024-03-14T17:58:02.602971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
11282 1
 
3.7%
10046 1
 
3.7%
398 1
 
3.7%
473 1
 
3.7%
34 1
 
3.7%
497 1
 
3.7%
531 1
 
3.7%
1402 1
 
3.7%
1 1
 
3.7%
132 1
 
3.7%
Other values (17) 17
63.0%
ValueCountFrequency (%)
1 1
3.7%
34 1
3.7%
49 1
3.7%
94 1
3.7%
132 1
3.7%
258 1
3.7%
260 1
3.7%
292 1
3.7%
324 1
3.7%
398 1
3.7%
ValueCountFrequency (%)
11282 1
3.7%
10046 1
3.7%
7735 1
3.7%
2244 1
3.7%
2019 1
3.7%
1777 1
3.7%
1519 1
3.7%
1488 1
3.7%
1402 1
3.7%
1363 1
3.7%

지원결정금액(백만원)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct27
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean450410.48
Minimum37
Maximum2352326
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size371.0 B
2024-03-14T17:58:02.990805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37
5-th percentile13311.1
Q167810
median223759
Q3439207.5
95-th percentile1975458
Maximum2352326
Range2352289
Interquartile range (IQR)371397.5

Descriptive statistics

Standard deviation648979.49
Coefficient of variation (CV)1.4408623
Kurtosis3.1114039
Mean450410.48
Median Absolute Deviation (MAD)188638
Skewness2.0112373
Sum12161083
Variance4.2117437 × 1011
MonotonicityNot monotonic
2024-03-14T17:58:03.375664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
2352326 1
 
3.7%
2050392 1
 
3.7%
97280 1
 
3.7%
75620 1
 
3.7%
10000 1
 
3.7%
235078 1
 
3.7%
245078 1
 
3.7%
417978 1
 
3.7%
37 1
 
3.7%
31904 1
 
3.7%
Other values (17) 17
63.0%
ValueCountFrequency (%)
37 1
3.7%
10000 1
3.7%
21037 1
3.7%
30040 1
3.7%
31904 1
3.7%
35121 1
3.7%
60000 1
3.7%
75620 1
3.7%
97280 1
3.7%
99980 1
3.7%
ValueCountFrequency (%)
2352326 1
3.7%
2050392 1
3.7%
1800612 1
3.7%
1282342 1
3.7%
726784 1
3.7%
624818 1
3.7%
460437 1
3.7%
417978 1
3.7%
301934 1
3.7%
255700 1
3.7%

대출건수
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct27
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1801.1481
Minimum5
Maximum11308
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size371.0 B
2024-03-14T17:58:03.740422image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5
5-th percentile44.2
Q1276.5
median660
Q31543
95-th percentile9374.2
Maximum11308
Range11303
Interquartile range (IQR)1266.5

Descriptive statistics

Standard deviation2968.443
Coefficient of variation (CV)1.6480838
Kurtosis5.4689576
Mean1801.1481
Median Absolute Deviation (MAD)592
Skewness2.5141868
Sum48631
Variance8811654.1
MonotonicityNot monotonic
2024-03-14T17:58:04.131825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
11308 1
 
3.7%
10069 1
 
3.7%
401 1
 
3.7%
476 1
 
3.7%
34 1
 
3.7%
513 1
 
3.7%
547 1
 
3.7%
1424 1
 
3.7%
5 1
 
3.7%
146 1
 
3.7%
Other values (17) 17
63.0%
ValueCountFrequency (%)
5 1
3.7%
34 1
3.7%
68 1
3.7%
94 1
3.7%
146 1
3.7%
258 1
3.7%
260 1
3.7%
293 1
3.7%
361 1
3.7%
401 1
3.7%
ValueCountFrequency (%)
11308 1
3.7%
10069 1
3.7%
7753 1
3.7%
2364 1
3.7%
2023 1
3.7%
1841 1
3.7%
1581 1
3.7%
1505 1
3.7%
1424 1
3.7%
1357 1
3.7%

대출금액(백만원)
Real number (ℝ)

HIGH CORRELATION 

Distinct25
Distinct (%)92.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean449613.3
Minimum1612
Maximum2330000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size371.0 B
2024-03-14T17:58:04.497474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1612
5-th percentile13227.7
Q167500
median223529
Q3429000
95-th percentile1955000
Maximum2330000
Range2328388
Interquartile range (IQR)361500

Descriptive statistics

Standard deviation643141.49
Coefficient of variation (CV)1.4304325
Kurtosis3.0431496
Mean449613.3
Median Absolute Deviation (MAD)178529
Skewness1.9946887
Sum12139559
Variance4.1363098 × 1011
MonotonicityNot monotonic
2024-03-14T17:58:04.877347image/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%
33759.0 1
 
3.7%
Other values (15) 15
55.6%
ValueCountFrequency (%)
1612.0 1
3.7%
10000.0 1
3.7%
20759.0 1
3.7%
30100.0 1
3.7%
33759.0 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%
299999.9997 1
3.7%
258900.0 1
3.7%

Interactions

2024-03-14T17:57:56.648678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T17:57:49.812163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T17:57:50.714792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T17:57:52.095792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T17:57:53.564901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T17:57:55.210048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T17:57:56.893443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T17:57:49.999758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T17:57:50.867111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T17:57:52.348554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T17:57:53.809423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T17:57:55.450867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T17:57:57.139786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T17:57:50.155339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T17:57:51.116653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T17:57:52.598197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T17:57:54.054753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T17:57:55.706620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T17:57:57.375567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T17:57:50.294842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T17:57:51.363720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T17:57:52.844745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T17:57:54.291448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T17:57:55.941678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T17:57:57.609262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T17:57:50.436682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T17:57:51.604936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T17:57:53.081672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T17:57:54.733967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T17:57:56.178612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T17:57:57.797923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T17:57:50.576173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T17:57:51.852936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T17:57:53.326663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T17:57:54.973482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T17:57:56.412806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-14T17:58:05.128882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분신청건수신청금액(백만원)지원결정건수지원결정금액(백만원)대출건수대출금액(백만원)
구분1.0000.0000.0000.0000.0000.0000.000
신청건수0.0001.0000.8040.9830.8310.8780.821
신청금액(백만원)0.0000.8041.0000.9020.9310.9070.921
지원결정건수0.0000.9830.9021.0000.9381.0000.930
지원결정금액(백만원)0.0000.8310.9310.9381.0000.9691.000
대출건수0.0000.8780.9071.0000.9691.0000.962
대출금액(백만원)0.0000.8210.9210.9301.0000.9621.000
2024-03-14T17:58:05.420192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
신청건수신청금액(백만원)지원결정건수지원결정금액(백만원)대출건수대출금액(백만원)
신청건수1.0000.7880.9960.8500.9950.852
신청금액(백만원)0.7881.0000.8000.9040.8030.904
지원결정건수0.9960.8001.0000.8770.9990.879
지원결정금액(백만원)0.8500.9040.8771.0000.8821.000
대출건수0.9950.8030.9990.8821.0000.883
대출금액(백만원)0.8520.9040.8791.0000.8831.000

Missing values

2024-03-14T17:57:58.088351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T17:57:58.473078image/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

구분신청건수신청금액(백만원)지원결정건수지원결정금액(백만원)대출건수대출금액(백만원)
0혁신창업사업화132423210576112822352326113082329999.999
1창업기반지원119322806187100462050392100692029999.999
2일반841123744827735180061277531779999.999
3대환대출290248202602103725820759.0
4청년전용창업(일반)316139159520192197402023219900.0
5청년전용창업(창성패)360401102923004029330100.0
6개발기술사업화131040438912363019341239299999.9997
7신성장기반자금248126170632244128234223641285000.0
8혁신성장지원187495405117777267841841745000.0
9일반161183310315196248181581645000.0
구분신청건수신청금액(백만원)지원결정건수지원결정금액(백만원)대출건수대출금액(백만원)
17긴급경영안정자금157533090814882557001505258900.0
18일시적경영애로143829135013552237591354223529.0
19재해중소기업136395191323190414633759.0
20포항피해기업지원13913751612.0
21재도약지원자금151557720914024179781424423000.0
22사업전환544312226531245078547250000.0
23일반512301826497235078513240000.0
24무역조정321040034100003410000.0
25재창업5631128574737562047675000.0
26구조개선전용4081521263989728040198000.0