Overview

Dataset statistics

Number of variables10
Number of observations927
Missing cells461
Missing cells (%)5.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory76.2 KiB
Average record size in memory84.1 B

Variable types

Numeric4
Text2
DateTime4

Dataset

Description대구광역시 수출지원사업현황 데이터로, 수출지원사업명, 사업시작일, 사업종료일, 사업개요, 담당연락처, 지원금액한도 등의 항목을 포함합니다.
URLhttps://www.data.go.kr/data/15087834/fileData.do

Alerts

신청시작일자 has 194 (20.9%) missing valuesMissing
신청종료일자 has 187 (20.2%) missing valuesMissing
연락처 has 74 (8.0%) missing valuesMissing
사업번호 has unique valuesUnique
지원업체수 has 80 (8.6%) zerosZeros
사업지원금액한도(천원) has 196 (21.1%) zerosZeros
사업지원금_1회당(천원) has 877 (94.6%) zerosZeros

Reproduction

Analysis started2023-12-12 13:08:32.253773
Analysis finished2023-12-12 13:08:35.262580
Duration3.01 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

사업번호
Real number (ℝ)

UNIQUE 

Distinct927
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean464.29989
Minimum1
Maximum935
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size8.3 KiB
2023-12-12T22:08:35.346508image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile47.3
Q1232.5
median464
Q3695.5
95-th percentile881.7
Maximum935
Range934
Interquartile range (IQR)463

Descriptive statistics

Standard deviation268.23959
Coefficient of variation (CV)0.57772916
Kurtosis-1.1931457
Mean464.29989
Median Absolute Deviation (MAD)232
Skewness0.0057486203
Sum430406
Variance71952.476
MonotonicityNot monotonic
2023-12-12T22:08:35.554175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
935 1
 
0.1%
110 1
 
0.1%
122 1
 
0.1%
121 1
 
0.1%
120 1
 
0.1%
119 1
 
0.1%
118 1
 
0.1%
117 1
 
0.1%
116 1
 
0.1%
115 1
 
0.1%
Other values (917) 917
98.9%
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 (%)
935 1
0.1%
934 1
0.1%
933 1
0.1%
932 1
0.1%
931 1
0.1%
930 1
0.1%
929 1
0.1%
928 1
0.1%
927 1
0.1%
926 1
0.1%

사업명
Text

Distinct881
Distinct (%)95.0%
Missing0
Missing (%)0.0%
Memory size7.4 KiB
2023-12-12T22:08:35.875893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length50
Median length39
Mean length23.755124
Min length2

Characters and Unicode

Total characters22021
Distinct characters404
Distinct categories13 ?
Distinct scripts4 ?
Distinct blocks7 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique853 ?
Unique (%)92.0%

Sample

1st row2023 대구 북미차 중심의 종합 무역사절단 모집 안내
2nd row2023년 대구 중국 리오프닝 시장개척단 파견 지원 사업
3rd row[공동관] 2023 호치민 국제섬유의류산업 전시회 참가기업 모집
4th row2023년 수출물류비 지원사업
5th row2023 KOTRA 해외시장조사 지원사업
ValueCountFrequency (%)
모집 191
 
4.7%
대구 123
 
3.0%
참가기업 104
 
2.5%
지원 89
 
2.2%
무역사절단 84
 
2.1%
종합무역사절단 81
 
2.0%
전시회 77
 
1.9%
공동관 70
 
1.7%
지원사업 65
 
1.6%
참가업체 42
 
1.0%
Other values (938) 3157
77.3%
2023-12-12T22:08:36.364532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3163
 
14.4%
2 916
 
4.2%
0 647
 
2.9%
1 507
 
2.3%
업 502
 
2.3%
사 481
 
2.2%
동 415
 
1.9%
기 403
 
1.8%
시 342
 
1.6%
회 340
 
1.5%
Other values (394) 14305
65.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 14608
66.3%
Space Separator 3163
 
14.4%
Decimal Number 2552
 
11.6%
Open Punctuation 533
 
2.4%
Close Punctuation 530
 
2.4%
Uppercase Letter 406
 
1.8%
Lowercase Letter 148
 
0.7%
Other Punctuation 35
 
0.2%
Dash Punctuation 29
 
0.1%
Final Punctuation 6
 
< 0.1%
Other values (3) 11
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
업 502
 
3.4%
사 481
 
3.3%
동 415
 
2.8%
기 403
 
2.8%
시 342
 
2.3%
회 340
 
2.3%
전 334
 
2.3%
역 325
 
2.2%
대 318
 
2.2%
가 300
 
2.1%
Other values (317) 10848
74.3%
Uppercase Letter
ValueCountFrequency (%)
S 55
13.5%
A 38
 
9.4%
C 34
 
8.4%
T 33
 
8.1%
I 32
 
7.9%
E 29
 
7.1%
B 25
 
6.2%
M 24
 
5.9%
K 23
 
5.7%
O 18
 
4.4%
Other values (14) 95
23.4%
Lowercase Letter
ValueCountFrequency (%)
e 26
17.6%
a 19
12.8%
o 16
10.8%
u 15
10.1%
b 15
10.1%
t 11
7.4%
l 8
 
5.4%
r 8
 
5.4%
n 5
 
3.4%
i 5
 
3.4%
Other values (9) 20
13.5%
Decimal Number
ValueCountFrequency (%)
2 916
35.9%
0 647
25.4%
1 507
19.9%
8 79
 
3.1%
7 78
 
3.1%
3 71
 
2.8%
5 68
 
2.7%
9 65
 
2.5%
6 62
 
2.4%
4 59
 
2.3%
Other Punctuation
ValueCountFrequency (%)
· 11
31.4%
, 10
28.6%
. 5
14.3%
' 3
 
8.6%
/ 2
 
5.7%
& 2
 
5.7%
? 2
 
5.7%
Open Punctuation
ValueCountFrequency (%)
[ 325
61.0%
( 195
36.6%
「 10
 
1.9%
『 2
 
0.4%
〔 1
 
0.2%
Close Punctuation
ValueCountFrequency (%)
] 325
61.3%
) 191
36.0%
」 11
 
2.1%
』 2
 
0.4%
〕 1
 
0.2%
Math Symbol
ValueCountFrequency (%)
+ 3
75.0%
~ 1
 
25.0%
Space Separator
ValueCountFrequency (%)
3163
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 29
100.0%
Final Punctuation
ValueCountFrequency (%)
’ 6
100.0%
Initial Punctuation
ValueCountFrequency (%)
‘ 6
100.0%
Other Symbol
ValueCountFrequency (%)
★ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 14600
66.3%
Common 6859
31.1%
Latin 554
 
2.5%
Han 8
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
업 502
 
3.4%
사 481
 
3.3%
동 415
 
2.8%
기 403
 
2.8%
시 342
 
2.3%
회 340
 
2.3%
전 334
 
2.3%
역 325
 
2.2%
대 318
 
2.2%
가 300
 
2.1%
Other values (316) 10840
74.2%
Latin
ValueCountFrequency (%)
S 55
 
9.9%
A 38
 
6.9%
C 34
 
6.1%
T 33
 
6.0%
I 32
 
5.8%
E 29
 
5.2%
e 26
 
4.7%
B 25
 
4.5%
M 24
 
4.3%
K 23
 
4.2%
Other values (33) 235
42.4%
Common
ValueCountFrequency (%)
3163
46.1%
2 916
 
13.4%
0 647
 
9.4%
1 507
 
7.4%
[ 325
 
4.7%
] 325
 
4.7%
( 195
 
2.8%
) 191
 
2.8%
8 79
 
1.2%
7 78
 
1.1%
Other values (24) 433
 
6.3%
Han
ValueCountFrequency (%)
社 8
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 14596
66.3%
ASCII 7362
33.4%
None 38
 
0.2%
Punctuation 12
 
0.1%
CJK 8
 
< 0.1%
Compat Jamo 4
 
< 0.1%
Misc Symbols 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3163
43.0%
2 916
 
12.4%
0 647
 
8.8%
1 507
 
6.9%
[ 325
 
4.4%
] 325
 
4.4%
( 195
 
2.6%
) 191
 
2.6%
8 79
 
1.1%
7 78
 
1.1%
Other values (57) 936
 
12.7%
Hangul
ValueCountFrequency (%)
업 502
 
3.4%
사 481
 
3.3%
동 415
 
2.8%
기 403
 
2.8%
시 342
 
2.3%
회 340
 
2.3%
전 334
 
2.3%
역 325
 
2.2%
대 318
 
2.2%
가 300
 
2.1%
Other values (315) 10836
74.2%
None
ValueCountFrequency (%)
」 11
28.9%
· 11
28.9%
「 10
26.3%
』 2
 
5.3%
『 2
 
5.3%
〔 1
 
2.6%
〕 1
 
2.6%
CJK
ValueCountFrequency (%)
社 8
100.0%
Punctuation
ValueCountFrequency (%)
’ 6
50.0%
‘ 6
50.0%
Compat Jamo
ValueCountFrequency (%)
ㆍ 4
100.0%
Misc Symbols
ValueCountFrequency (%)
★ 1
100.0%

사업시작일자
Date

Distinct578
Distinct (%)62.6%
Missing3
Missing (%)0.3%
Memory size7.4 KiB
Minimum2012-01-01 00:00:00
Maximum2023-09-11 00:00:00
2023-12-12T22:08:36.532255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:08:36.713847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

사업종료일자
Date

Distinct525
Distinct (%)56.8%
Missing3
Missing (%)0.3%
Memory size7.4 KiB
Minimum2012-01-13 00:00:00
Maximum2023-12-31 00:00:00
2023-12-12T22:08:36.880519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:08:37.024652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

신청시작일자
Date

MISSING 

Distinct522
Distinct (%)71.2%
Missing194
Missing (%)20.9%
Memory size7.4 KiB
Minimum2013-02-01 00:00:00
Maximum2023-07-05 00:00:00
2023-12-12T22:08:37.200807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:08:37.365705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

신청종료일자
Date

MISSING 

Distinct527
Distinct (%)71.2%
Missing187
Missing (%)20.2%
Memory size7.4 KiB
Minimum2012-01-01 00:00:00
Maximum2023-12-31 00:00:00
2023-12-12T22:08:37.501333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:08:37.650836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

연락처
Text

MISSING 

Distinct192
Distinct (%)22.5%
Missing74
Missing (%)8.0%
Memory size7.4 KiB
2023-12-12T22:08:37.922424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length11.98476
Min length11

Characters and Unicode

Total characters10223
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique92 ?
Unique (%)10.8%

Sample

1st row053-659-2536
2nd row053-260-4027
3rd row053-252-4082
4th row053-757-3762
5th row053-659-2556
ValueCountFrequency (%)
053-753-7531 52
 
6.1%
053-601-5262 45
 
5.3%
053-260-4027 37
 
4.3%
053-260-4028 29
 
3.4%
053-659-2536 27
 
3.2%
053-260-4026 26
 
3.0%
053-659-2533 24
 
2.8%
053-659-2534 24
 
2.8%
053-659-2535 20
 
2.3%
053-358-0991 19
 
2.2%
Other values (182) 550
64.5%
2023-12-12T22:08:38.312470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 1706
16.7%
5 1669
16.3%
0 1494
14.6%
3 1461
14.3%
2 968
9.5%
6 633
 
6.2%
1 538
 
5.3%
7 529
 
5.2%
4 511
 
5.0%
9 385
 
3.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 8517
83.3%
Dash Punctuation 1706
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 1669
19.6%
0 1494
17.5%
3 1461
17.2%
2 968
11.4%
6 633
 
7.4%
1 538
 
6.3%
7 529
 
6.2%
4 511
 
6.0%
9 385
 
4.5%
8 329
 
3.9%
Dash Punctuation
ValueCountFrequency (%)
- 1706
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 10223
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 1706
16.7%
5 1669
16.3%
0 1494
14.6%
3 1461
14.3%
2 968
9.5%
6 633
 
6.2%
1 538
 
5.3%
7 529
 
5.2%
4 511
 
5.0%
9 385
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10223
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 1706
16.7%
5 1669
16.3%
0 1494
14.6%
3 1461
14.3%
2 968
9.5%
6 633
 
6.2%
1 538
 
5.3%
7 529
 
5.2%
4 511
 
5.0%
9 385
 
3.8%

지원업체수
Real number (ℝ)

ZEROS 

Distinct113
Distinct (%)12.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean21.581446
Minimum0
Maximum370
Zeros80
Zeros (%)8.6%
Negative0
Negative (%)0.0%
Memory size8.3 KiB
2023-12-12T22:08:38.464210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q15
median10
Q319
95-th percentile98.5
Maximum370
Range370
Interquartile range (IQR)14

Descriptive statistics

Standard deviation38.972461
Coefficient of variation (CV)1.8058318
Kurtosis20.201466
Mean21.581446
Median Absolute Deviation (MAD)5
Skewness4.0854612
Sum20006
Variance1518.8527
MonotonicityNot monotonic
2023-12-12T22:08:38.587456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 80
 
8.6%
5 79
 
8.5%
10 64
 
6.9%
6 58
 
6.3%
8 53
 
5.7%
7 51
 
5.5%
9 43
 
4.6%
12 36
 
3.9%
11 34
 
3.7%
1 30
 
3.2%
Other values (103) 399
43.0%
ValueCountFrequency (%)
0 80
8.6%
1 30
 
3.2%
2 16
 
1.7%
3 27
 
2.9%
4 21
 
2.3%
5 79
8.5%
6 58
6.3%
7 51
5.5%
8 53
5.7%
9 43
4.6%
ValueCountFrequency (%)
370 1
0.1%
266 1
0.1%
258 1
0.1%
256 1
0.1%
253 1
0.1%
252 1
0.1%
242 1
0.1%
237 1
0.1%
226 1
0.1%
218 1
0.1%

사업지원금액한도(천원)
Real number (ℝ)

ZEROS 

Distinct256
Distinct (%)27.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean65840246
Minimum0
Maximum1.995294 × 109
Zeros196
Zeros (%)21.1%
Negative0
Negative (%)0.0%
Memory size8.3 KiB
2023-12-12T22:08:38.758924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q1400000
median40000000
Q371675000
95-th percentile2.5 × 108
Maximum1.995294 × 109
Range1.995294 × 109
Interquartile range (IQR)71275000

Descriptive statistics

Standard deviation1.2006778 × 108
Coefficient of variation (CV)1.8236229
Kurtosis88.645012
Mean65840246
Median Absolute Deviation (MAD)39500000
Skewness7.2568651
Sum6.1033908 × 1010
Variance1.4416272 × 1016
MonotonicityNot monotonic
2023-12-12T22:08:38.926612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 196
21.1%
80000000 68
 
7.3%
50000000 41
 
4.4%
60000000 38
 
4.1%
100000000 29
 
3.1%
40000000 23
 
2.5%
200000000 21
 
2.3%
70000000 16
 
1.7%
30000000 16
 
1.7%
400000000 16
 
1.7%
Other values (246) 463
49.9%
ValueCountFrequency (%)
0 196
21.1%
2000 1
 
0.1%
3000 1
 
0.1%
11000 1
 
0.1%
12000 1
 
0.1%
19800 1
 
0.1%
20000 3
 
0.3%
20050 1
 
0.1%
24700 1
 
0.1%
25000 1
 
0.1%
ValueCountFrequency (%)
1995294000 1
 
0.1%
1280523264 1
 
0.1%
1000000000 1
 
0.1%
600000000 3
 
0.3%
500000000 1
 
0.1%
450000000 9
1.0%
400000000 16
1.7%
350000000 1
 
0.1%
330000000 1
 
0.1%
300000000 2
 
0.2%

사업지원금_1회당(천원)
Real number (ℝ)

ZEROS 

Distinct20
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean163156.96
Minimum0
Maximum10000000
Zeros877
Zeros (%)94.6%
Negative0
Negative (%)0.0%
Memory size8.3 KiB
2023-12-12T22:08:39.060040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile3350
Maximum10000000
Range10000000
Interquartile range (IQR)0

Descriptive statistics

Standard deviation991571.76
Coefficient of variation (CV)6.0774102
Kurtosis46.904247
Mean163156.96
Median Absolute Deviation (MAD)0
Skewness6.65912
Sum1.512465 × 108
Variance9.8321455 × 1011
MonotonicityNot monotonic
2023-12-12T22:08:39.180342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
0 877
94.6%
5000000 15
 
1.6%
300000 7
 
0.8%
7000000 5
 
0.5%
4000 3
 
0.3%
15000 2
 
0.2%
10000000 2
 
0.2%
5000 2
 
0.2%
4000000 2
 
0.2%
500000 2
 
0.2%
Other values (10) 10
 
1.1%
ValueCountFrequency (%)
0 877
94.6%
900 1
 
0.1%
1500 1
 
0.1%
3000 1
 
0.1%
3500 1
 
0.1%
4000 3
 
0.3%
5000 2
 
0.2%
7000 1
 
0.1%
8600 1
 
0.1%
15000 2
 
0.2%
ValueCountFrequency (%)
10000000 2
 
0.2%
9000000 1
 
0.1%
7000000 5
 
0.5%
5000000 15
1.6%
4000000 2
 
0.2%
1000000 1
 
0.1%
500000 2
 
0.2%
300000 7
0.8%
50000 1
 
0.1%
20000 1
 
0.1%

Interactions

2023-12-12T22:08:34.123817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:08:32.792893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:08:33.231490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:08:33.700122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:08:34.237147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:08:32.888470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:08:33.340281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:08:33.794721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:08:34.360641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:08:32.990113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:08:33.470421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:08:33.908909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:08:34.465580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:08:33.111674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:08:33.605861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T22:08:34.021230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T22:08:39.262184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
사업번호지원업체수사업지원금액한도(천원)사업지원금_1회당(천원)
사업번호1.0000.0870.1590.166
지원업체수0.0871.0000.3170.280
사업지원금액한도(천원)0.1590.3171.0000.290
사업지원금_1회당(천원)0.1660.2800.2901.000
2023-12-12T22:08:39.365947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
사업번호지원업체수사업지원금액한도(천원)사업지원금_1회당(천원)
사업번호1.0000.022-0.4490.073
지원업체수0.0221.0000.3640.120
사업지원금액한도(천원)-0.4490.3641.0000.068
사업지원금_1회당(천원)0.0730.1200.0681.000

Missing values

2023-12-12T22:08:34.612962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T22:08:34.769914image/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.
2023-12-12T22:08:35.186270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

사업번호사업명사업시작일자사업종료일자신청시작일자신청종료일자연락처지원업체수사업지원금액한도(천원)사업지원금_1회당(천원)
09352023 대구 북미차 중심의 종합 무역사절단 모집 안내2023-09-112023-09-162023-04-272023-05-18053-659-253604500000
19342023년 대구 중국 리오프닝 시장개척단 파견 지원 사업2023-04-012023-07-312023-04-122023-04-26053-260-40277400000
2933[공동관] 2023 호치민 국제섬유의류산업 전시회 참가기업 모집2023-04-012023-12-312023-04-102023-04-24053-252-40825600000
39322023년 수출물류비 지원사업2023-01-012023-12-312023-07-052023-07-07053-757-376202000000
49312023 KOTRA 해외시장조사 지원사업2023-03-272023-12-292023-03-272023-12-29053-659-25561735000900
59302023 KOTRA 해외지사화 참가 지원사업2023-03-272023-12-292023-03-272023-12-29053-659-2556442500003500
69292023년 수출초보기업 해외진출 지원사업2023-01-012023-12-312023-04-112023-04-13053-757-37628625000015000
79282023년 1社 맞춤형 해외마케팅 지원사업2023-03-132023-11-302023-03-132023-03-31053-757-37635330000020000
8927[공동관] 2023 밀라노 국제섬유기계 전시회 참가기업 모집2023-03-012023-08-312023-03-142023-03-20053-817-59546700000
9926[공동관] 2023 베트남 국제 프리미엄 소비재 전시회 참가기업 모집2023-03-012023-08-312023-03-142023-03-29053-260-402718400000
사업번호사업명사업시작일자사업종료일자신청시작일자신청종료일자연락처지원업체수사업지원금액한도(천원)사업지원금_1회당(천원)
917709대구경북아프리카종합2012-05-192012-05-26<NA><NA>053-601-5262300
918708대구경북중동종합2012-05-072012-05-15<NA><NA>053-601-5262500
919707대구경북 북중미종합2012-04-162012-04-25<NA><NA>053-601-5262500
920706대구중국종합(1차)2012-04-082012-04-14<NA><NA>053-601-5262900
921705대구경북남미종합2012-03-212012-04-01<NA><NA>053-601-5262400
922704대구동남아종합2012-03-182012-03-25<NA><NA>053-601-52621000
923703해외지사화2012-01-012012-12-31<NA><NA><NA>7300
924702수출보험료2012-01-012012-12-31<NA><NA><NA>13500
925701통번역지원2012-01-012012-12-31<NA><NA><NA>10400
926700해외시장조사2012-01-012012-12-31<NA><NA><NA>5800