Overview

Dataset statistics

Number of variables4
Number of observations3169
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory102.3 KiB
Average record size in memory33.0 B

Variable types

DateTime1
Categorical2
Numeric1

Dataset

Description업종별 벤처기업 방송광고 지원에 대한 업종별 현황 데이터 정보를 제공합니다. 지원연월별, 시도별 및 업종별 벤처기업 방송광고 지원금액을 확인할 수 있습니다.
Author한국방송광고진흥공사
URLhttps://www.data.go.kr/data/15111067/fileData.do

Reproduction

Analysis started2024-03-15 01:01:44.590879
Analysis finished2024-03-15 01:01:45.570787
Duration0.98 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

지원연월
Date

Distinct144
Distinct (%)4.5%
Missing0
Missing (%)0.0%
Memory size24.9 KiB
Minimum2012-01-01 00:00:00
Maximum2023-12-01 00:00:00
2024-03-15T10:01:45.776583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:01:46.221891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

시도명
Categorical

Distinct17
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size24.9 KiB
서울특별시
910 
경기도
690 
대구광역시
283 
경상북도
179 
인천광역시
168 
Other values (12)
939 

Length

Max length7
Median length5
Mean length4.3442726
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row강원도
2nd row경기도
3rd row경기도
4th row경기도
5th row경기도

Common Values

ValueCountFrequency (%)
서울특별시 910
28.7%
경기도 690
21.8%
대구광역시 283
 
8.9%
경상북도 179
 
5.6%
인천광역시 168
 
5.3%
부산광역시 165
 
5.2%
전라북도 138
 
4.4%
충청북도 128
 
4.0%
대전광역시 108
 
3.4%
경상남도 105
 
3.3%
Other values (7) 295
 
9.3%

Length

2024-03-15T10:01:46.832677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
서울특별시 910
28.7%
경기도 690
21.8%
대구광역시 283
 
8.9%
경상북도 179
 
5.6%
인천광역시 168
 
5.3%
부산광역시 165
 
5.2%
전라북도 138
 
4.4%
충청북도 128
 
4.0%
대전광역시 108
 
3.4%
경상남도 105
 
3.3%
Other values (7) 295
 
9.3%

업종
Categorical

Distinct20
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size24.9 KiB
서비스
450 
식품
341 
가정용품
295 
산업기기
258 
유통
219 
Other values (15)
1606 

Length

Max length9
Median length7
Mean length4.465131
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row제약및의료
2nd row가정용전기전자
3rd row가정용품
4th row산업기기
5th row서비스

Common Values

ValueCountFrequency (%)
서비스 450
14.2%
식품 341
10.8%
가정용품 295
9.3%
산업기기 258
 
8.1%
유통 219
 
6.9%
건설,건재및부동산 210
 
6.6%
제약및의료 194
 
6.1%
화장품및보건용품 194
 
6.1%
패션 184
 
5.8%
컴퓨터및정보통신 154
 
4.9%
Other values (10) 670
21.1%

Length

2024-03-15T10:01:47.078178image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
서비스 450
14.2%
식품 341
10.8%
가정용품 295
9.3%
산업기기 258
 
8.1%
유통 219
 
6.9%
건설,건재및부동산 210
 
6.6%
제약및의료 194
 
6.1%
화장품및보건용품 194
 
6.1%
패션 184
 
5.8%
컴퓨터및정보통신 154
 
4.9%
Other values (10) 670
21.1%

지원금액
Real number (ℝ)

Distinct2654
Distinct (%)83.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.8450459 × 109
Minimum0
Maximum2.6987 × 1011
Zeros9
Zeros (%)0.3%
Negative0
Negative (%)0.0%
Memory size28.0 KiB
2024-03-15T10:01:47.475718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile58162272
Q12.041312 × 108
median6.5402064 × 108
Q32.5410812 × 109
95-th percentile1.5759002 × 1010
Maximum2.6987 × 1011
Range2.6987 × 1011
Interquartile range (IQR)2.33695 × 109

Descriptive statistics

Standard deviation1.2881788 × 1010
Coefficient of variation (CV)3.35023
Kurtosis176.29701
Mean3.8450459 × 109
Median Absolute Deviation (MAD)5.4733216 × 108
Skewness11.235675
Sum1.218495 × 1013
Variance1.6594047 × 1020
MonotonicityNot monotonic
2024-03-15T10:01:47.847345image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
23813580 21
 
0.7%
130638340 18
 
0.6%
154938000 18
 
0.6%
23045400 12
 
0.4%
149940000 12
 
0.4%
126424200 11
 
0.3%
0 9
 
0.3%
73261370 8
 
0.3%
97064100 8
 
0.3%
353858400 8
 
0.3%
Other values (2644) 3044
96.1%
ValueCountFrequency (%)
0 9
0.3%
346920 1
 
< 0.1%
438480 1
 
< 0.1%
2116800 2
 
0.1%
4051320 1
 
< 0.1%
4876200 1
 
< 0.1%
5328000 1
 
< 0.1%
7590240 1
 
< 0.1%
10478160 1
 
< 0.1%
14225400 1
 
< 0.1%
ValueCountFrequency (%)
269870004000 1
< 0.1%
241447815360 1
< 0.1%
228573573000 1
< 0.1%
225516372480 1
< 0.1%
176726459160 1
< 0.1%
156631876000 1
< 0.1%
133930521500 1
< 0.1%
105467617000 1
< 0.1%
104692326900 1
< 0.1%
97947876000 1
< 0.1%

Interactions

2024-03-15T10:01:44.863810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-15T10:01:48.012370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시도명업종지원금액
시도명1.0000.6920.083
업종0.6921.0000.068
지원금액0.0830.0681.000
2024-03-15T10:01:48.171479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시도명업종
시도명1.0000.285
업종0.2851.000
2024-03-15T10:01:48.430189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지원금액시도명업종
지원금액1.0000.0330.027
시도명0.0331.0000.285
업종0.0270.2851.000

Missing values

2024-03-15T10:01:45.158725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-15T10:01:45.446010image/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

지원연월시도명업종지원금액
02012-01강원도제약및의료127086050
12012-01경기도가정용전기전자1016089480
22012-01경기도가정용품3899246400
32012-01경기도산업기기160000000
42012-01경기도서비스11076132480
52012-01경기도식품1426124000
62012-01경기도음료및기호식품1500984660
72012-01경기도정밀기기및사무기기781256420
82012-01경기도패션140928480
92012-01경기도화장품및보건용품786534840
지원연월시도명업종지원금액
31592023-12서울특별시출판648493750
31602023-12서울특별시컴퓨터및정보통신1418684000
31612023-12서울특별시패션330122100
31622023-12서울특별시화장품및보건용품80272859940
31632023-12울산광역시그룹및기업광고15467760
31642023-12인천광역시그룹및기업광고77052360
31652023-12인천광역시산업기기181412000
31662023-12전라남도기초재368165000
31672023-12전라북도기초재80257100
31682023-12충청남도제약및의료345695000