Overview

Dataset statistics

Number of variables7
Number of observations44
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.6 KiB
Average record size in memory61.0 B

Variable types

Numeric2
Text2
Categorical3

Dataset

Description부산광역시 해외마케팅(수출지원)사업에 대한 정보 제공
Author부산광역시
URLhttps://www.data.go.kr/data/15023984/fileData.do

Alerts

연번 is highly overall correlated with 업체수 and 1 other fieldsHigh correlation
업체수 is highly overall correlated with 연번High correlation
업종 is highly overall correlated with 수행기관High correlation
수행기관 is highly overall correlated with 연번 and 1 other fieldsHigh correlation
연번 has unique valuesUnique
사업구분 has unique valuesUnique
업체수 has 1 (2.3%) zerosZeros

Reproduction

Analysis started2023-12-12 04:26:58.856723
Analysis finished2023-12-12 04:27:00.069766
Duration1.21 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct44
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean22.5
Minimum1
Maximum44
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size528.0 B
2023-12-12T13:27:00.148750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3.15
Q111.75
median22.5
Q333.25
95-th percentile41.85
Maximum44
Range43
Interquartile range (IQR)21.5

Descriptive statistics

Standard deviation12.845233
Coefficient of variation (CV)0.57089923
Kurtosis-1.2
Mean22.5
Median Absolute Deviation (MAD)11
Skewness0
Sum990
Variance165
MonotonicityStrictly increasing
2023-12-12T13:27:00.290364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=44)
ValueCountFrequency (%)
1 1
 
2.3%
24 1
 
2.3%
26 1
 
2.3%
27 1
 
2.3%
28 1
 
2.3%
29 1
 
2.3%
30 1
 
2.3%
31 1
 
2.3%
32 1
 
2.3%
33 1
 
2.3%
Other values (34) 34
77.3%
ValueCountFrequency (%)
1 1
2.3%
2 1
2.3%
3 1
2.3%
4 1
2.3%
5 1
2.3%
6 1
2.3%
7 1
2.3%
8 1
2.3%
9 1
2.3%
10 1
2.3%
ValueCountFrequency (%)
44 1
2.3%
43 1
2.3%
42 1
2.3%
41 1
2.3%
40 1
2.3%
39 1
2.3%
38 1
2.3%
37 1
2.3%
36 1
2.3%
35 1
2.3%

사업구분
Text

UNIQUE 

Distinct44
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size484.0 B
2023-12-12T13:27:00.668611image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length19
Mean length15.659091
Min length9

Characters and Unicode

Total characters689
Distinct characters179
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique44 ?
Unique (%)100.0%

Sample

1st row홍콩 선물용품 박람회
2nd row태국 방콕 식품 전시회
3rd row인도네시아 산업기계 전시회
4th row오사카 한국우수 상품전시회
5th row말레이시아 국제 소매프랜차이즈 박람회
ValueCountFrequency (%)
지원사업 15
 
9.4%
박람회 5
 
3.1%
입점 5
 
3.1%
무역사절단 5
 
3.1%
중국 4
 
2.5%
전시회 3
 
1.9%
마케팅 3
 
1.9%
글로벌 2
 
1.2%
수출상담회 2
 
1.2%
소비재 2
 
1.2%
Other values (102) 114
71.2%
2023-12-12T13:27:01.257550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
117
 
17.0%
업 23
 
3.3%
사 23
 
3.3%
회 21
 
3.0%
지 18
 
2.6%
원 17
 
2.5%
아 14
 
2.0%
상 12
 
1.7%
국 11
 
1.6%
전 11
 
1.6%
Other values (169) 422
61.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 555
80.6%
Space Separator 117
 
17.0%
Uppercase Letter 7
 
1.0%
Decimal Number 4
 
0.6%
Lowercase Letter 4
 
0.6%
Dash Punctuation 2
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
업 23
 
4.1%
사 23
 
4.1%
회 21
 
3.8%
지 18
 
3.2%
원 17
 
3.1%
아 14
 
2.5%
상 12
 
2.2%
국 11
 
2.0%
전 11
 
2.0%
시 11
 
2.0%
Other values (154) 394
71.0%
Uppercase Letter
ValueCountFrequency (%)
K 2
28.6%
U 1
14.3%
B 1
14.3%
A 1
14.3%
T 1
14.3%
M 1
14.3%
Lowercase Letter
ValueCountFrequency (%)
d 1
25.0%
a 1
25.0%
n 1
25.0%
r 1
25.0%
Decimal Number
ValueCountFrequency (%)
2 2
50.0%
3 1
25.0%
0 1
25.0%
Space Separator
ValueCountFrequency (%)
117
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 555
80.6%
Common 123
 
17.9%
Latin 11
 
1.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
업 23
 
4.1%
사 23
 
4.1%
회 21
 
3.8%
지 18
 
3.2%
원 17
 
3.1%
아 14
 
2.5%
상 12
 
2.2%
국 11
 
2.0%
전 11
 
2.0%
시 11
 
2.0%
Other values (154) 394
71.0%
Latin
ValueCountFrequency (%)
K 2
18.2%
d 1
9.1%
U 1
9.1%
a 1
9.1%
n 1
9.1%
r 1
9.1%
B 1
9.1%
A 1
9.1%
T 1
9.1%
M 1
9.1%
Common
ValueCountFrequency (%)
117
95.1%
- 2
 
1.6%
2 2
 
1.6%
3 1
 
0.8%
0 1
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 555
80.6%
ASCII 134
 
19.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
117
87.3%
K 2
 
1.5%
- 2
 
1.5%
2 2
 
1.5%
d 1
 
0.7%
U 1
 
0.7%
a 1
 
0.7%
n 1
 
0.7%
r 1
 
0.7%
B 1
 
0.7%
Other values (5) 5
 
3.7%
Hangul
ValueCountFrequency (%)
업 23
 
4.1%
사 23
 
4.1%
회 21
 
3.8%
지 18
 
3.2%
원 17
 
3.1%
아 14
 
2.5%
상 12
 
2.2%
국 11
 
2.0%
전 11
 
2.0%
시 11
 
2.0%
Other values (154) 394
71.0%

시기
Categorical

Distinct17
Distinct (%)38.6%
Missing0
Missing (%)0.0%
Memory size484.0 B
연중
9 
03월~12월
6 
05월
4 
04월
3 
06월
3 
Other values (12)
19 

Length

Max length11
Median length3
Mean length3.7954545
Min length2

Unique

Unique6 ?
Unique (%)13.6%

Sample

1st row04월
2nd row05월
3rd row12월
4th row06월
5th row07월

Common Values

ValueCountFrequency (%)
연중 9
20.5%
03월~12월 6
13.6%
05월 4
9.1%
04월 3
 
6.8%
06월 3
 
6.8%
07월 3
 
6.8%
12월 2
 
4.5%
09월 2
 
4.5%
08월 2
 
4.5%
11월 2
 
4.5%
Other values (7) 8
18.2%

Length

2023-12-12T13:27:01.448987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
연중 9
20.5%
03월~12월 6
13.6%
05월 4
9.1%
04월 3
 
6.8%
06월 3
 
6.8%
07월 3
 
6.8%
10월 2
 
4.5%
11월 2
 
4.5%
08월 2
 
4.5%
09월 2
 
4.5%
Other values (7) 8
18.2%

국가
Text

Distinct22
Distinct (%)50.0%
Missing0
Missing (%)0.0%
Memory size484.0 B
2023-12-12T13:27:01.649705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length7
Mean length3.2954545
Min length2

Characters and Unicode

Total characters145
Distinct characters49
Distinct categories4 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique15 ?
Unique (%)34.1%

Sample

1st row홍콩
2nd row태국
3rd row인도네시아
4th row일본
5th row말레이시아
ValueCountFrequency (%)
전지역 15
32.6%
중국 4
 
8.7%
일본 2
 
4.3%
미국 2
 
4.3%
인도 2
 
4.3%
베트남 2
 
4.3%
아세안 2
 
4.3%
태국 2
 
4.3%
등 2
 
4.3%
카자흐스탄,우즈베키스탄 1
 
2.2%
Other values (12) 12
26.1%
2023-12-12T13:27:02.034096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
지 16
 
11.0%
역 15
 
10.3%
전 15
 
10.3%
국 9
 
6.2%
중 7
 
4.8%
아 6
 
4.1%
, 6
 
4.1%
일 5
 
3.4%
미 4
 
2.8%
베 4
 
2.8%
Other values (39) 58
40.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 134
92.4%
Other Punctuation 6
 
4.1%
Uppercase Letter 3
 
2.1%
Space Separator 2
 
1.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 16
 
11.9%
역 15
 
11.2%
전 15
 
11.2%
국 9
 
6.7%
중 7
 
5.2%
아 6
 
4.5%
일 5
 
3.7%
미 4
 
3.0%
베 4
 
3.0%
본 3
 
2.2%
Other values (34) 50
37.3%
Uppercase Letter
ValueCountFrequency (%)
E 1
33.3%
A 1
33.3%
U 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 6
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 134
92.4%
Common 8
 
5.5%
Latin 3
 
2.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 16
 
11.9%
역 15
 
11.2%
전 15
 
11.2%
국 9
 
6.7%
중 7
 
5.2%
아 6
 
4.5%
일 5
 
3.7%
미 4
 
3.0%
베 4
 
3.0%
본 3
 
2.2%
Other values (34) 50
37.3%
Latin
ValueCountFrequency (%)
E 1
33.3%
A 1
33.3%
U 1
33.3%
Common
ValueCountFrequency (%)
, 6
75.0%
2
 
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 134
92.4%
ASCII 11
 
7.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
지 16
 
11.9%
역 15
 
11.2%
전 15
 
11.2%
국 9
 
6.7%
중 7
 
5.2%
아 6
 
4.5%
일 5
 
3.7%
미 4
 
3.0%
베 4
 
3.0%
본 3
 
2.2%
Other values (34) 50
37.3%
ASCII
ValueCountFrequency (%)
, 6
54.5%
2
 
18.2%
E 1
 
9.1%
A 1
 
9.1%
U 1
 
9.1%

업종
Categorical

HIGH CORRELATION 

Distinct11
Distinct (%)25.0%
Missing0
Missing (%)0.0%
Memory size484.0 B
종합
20 
소비재
11 
교육
3 
식음료
 
2
전지역
 
2
Other values (6)
6 

Length

Max length5
Median length2
Mean length2.5227273
Min length2

Unique

Unique6 ?
Unique (%)13.6%

Sample

1st row소비재
2nd row식음료
3rd row기계
4th row종합
5th row소비재

Common Values

ValueCountFrequency (%)
종합 20
45.5%
소비재 11
25.0%
교육 3
 
6.8%
식음료 2
 
4.5%
전지역 2
 
4.5%
기계 1
 
2.3%
제조기계 1
 
2.3%
기자재 1
 
2.3%
산업재 1
 
2.3%
화장품 1
 
2.3%

Length

2023-12-12T13:27:02.169398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
종합 20
45.5%
소비재 11
25.0%
교육 3
 
6.8%
식음료 2
 
4.5%
전지역 2
 
4.5%
기계 1
 
2.3%
제조기계 1
 
2.3%
기자재 1
 
2.3%
산업재 1
 
2.3%
화장품 1
 
2.3%

업체수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct18
Distinct (%)40.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean36.068182
Minimum0
Maximum200
Zeros1
Zeros (%)2.3%
Negative0
Negative (%)0.0%
Memory size528.0 B
2023-12-12T13:27:02.294097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile6.3
Q18
median13
Q346.25
95-th percentile120
Maximum200
Range200
Interquartile range (IQR)38.25

Descriptive statistics

Standard deviation44.977202
Coefficient of variation (CV)1.247005
Kurtosis3.6779718
Mean36.068182
Median Absolute Deviation (MAD)7
Skewness1.9769023
Sum1587
Variance2022.9487
MonotonicityNot monotonic
2023-12-12T13:27:02.701051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
8 11
25.0%
10 7
15.9%
100 3
 
6.8%
50 3
 
6.8%
30 3
 
6.8%
20 3
 
6.8%
120 2
 
4.5%
6 2
 
4.5%
12 1
 
2.3%
40 1
 
2.3%
Other values (8) 8
18.2%
ValueCountFrequency (%)
0 1
 
2.3%
6 2
 
4.5%
8 11
25.0%
10 7
15.9%
12 1
 
2.3%
14 1
 
2.3%
15 1
 
2.3%
20 3
 
6.8%
30 3
 
6.8%
31 1
 
2.3%
ValueCountFrequency (%)
200 1
 
2.3%
150 1
 
2.3%
120 2
4.5%
100 3
6.8%
70 1
 
2.3%
50 3
6.8%
45 1
 
2.3%
40 1
 
2.3%
31 1
 
2.3%
30 3
6.8%

수행기관
Categorical

HIGH CORRELATION 

Distinct7
Distinct (%)15.9%
Missing0
Missing (%)0.0%
Memory size484.0 B
경제진흥원
26 
무역협회
7 
코트라
4 
부산상의
 
2
KOTRA
 
2
Other values (2)
3 

Length

Max length13
Median length5
Mean length4.8863636
Min length3

Unique

Unique1 ?
Unique (%)2.3%

Sample

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

Common Values

ValueCountFrequency (%)
경제진흥원 26
59.1%
무역협회 7
 
15.9%
코트라 4
 
9.1%
부산상의 2
 
4.5%
KOTRA 2
 
4.5%
부산테크노파크 2
 
4.5%
조선해양기자재공업협동조합 1
 
2.3%

Length

2023-12-12T13:27:02.820165image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:27:02.930210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경제진흥원 26
59.1%
무역협회 7
 
15.9%
코트라 4
 
9.1%
부산상의 2
 
4.5%
kotra 2
 
4.5%
부산테크노파크 2
 
4.5%
조선해양기자재공업협동조합 1
 
2.3%

Interactions

2023-12-12T13:26:59.540913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:26:59.315964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:26:59.669529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T13:26:59.413701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T13:27:03.047019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번사업구분시기국가업종업체수수행기관
연번1.0001.0000.7560.6730.6710.5050.780
사업구분1.0001.0001.0001.0001.0001.0001.000
시기0.7561.0001.0000.7280.7420.7700.730
국가0.6731.0000.7281.0000.8540.0000.358
업종0.6711.0000.7420.8541.0000.0000.782
업체수0.5051.0000.7700.0000.0001.0000.000
수행기관0.7801.0000.7300.3580.7820.0001.000
2023-12-12T13:27:03.161567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시기업종수행기관
시기1.0000.3380.365
업종0.3381.0000.505
수행기관0.3650.5051.000
2023-12-12T13:27:03.289371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번업체수시기업종수행기관
연번1.0000.6590.3610.3490.521
업체수0.6591.0000.3960.0000.000
시기0.3610.3961.0000.3380.365
업종0.3490.0000.3381.0000.505
수행기관0.5210.0000.3650.5051.000

Missing values

2023-12-12T13:26:59.863466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T13:27:00.016619image/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

연번사업구분시기국가업종업체수수행기관
01홍콩 선물용품 박람회04월홍콩소비재8경제진흥원
12태국 방콕 식품 전시회05월태국식음료8경제진흥원
23인도네시아 산업기계 전시회12월인도네시아기계8경제진흥원
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