Overview

Dataset statistics

Number of variables7
Number of observations31
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.9 KiB
Average record size in memory63.3 B

Variable types

Categorical6
Numeric1

Dataset

Description2015년 ~ 2019년까지의 중소기업유통센터 지원사업(중소기업전용판매장, 홈쇼핑방송판매대행) 카테고리별 매출비중 정보 제공
Author(주)중소기업유통센터
URLhttps://www.data.go.kr/data/15005965/fileData.do

Alerts

연도 has constant value ""Constant
월 has constant value ""Constant
단위 has constant value ""Constant
매장 is highly overall correlated with 판매형태High correlation
판매형태 is highly overall correlated with 매장 and 1 other fieldsHigh correlation
카테고리 is highly overall correlated with 판매형태High correlation
매출비중 has 1 (3.2%) zerosZeros

Reproduction

Analysis started2023-12-11 22:57:58.674775
Analysis finished2023-12-11 22:57:59.052893
Duration0.38 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

판매형태
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)6.5%
Missing0
Missing (%)0.0%
Memory size380.0 B
중소기업전용판매장
20 
홈쇼핑 판매대행
11 

Length

Max length9
Median length9
Mean length8.6451613
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
중소기업전용판매장 20
64.5%
홈쇼핑 판매대행 11
35.5%

Length

2023-12-12T07:57:59.123600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T07:57:59.217279image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
중소기업전용판매장 20
47.6%
홈쇼핑 11
26.2%
판매대행 11
26.2%

연도
Categorical

CONSTANT 

Distinct1
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size380.0 B
2019
31 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2019
2nd row2019
3rd row2019
4th row2019
5th row2019

Common Values

ValueCountFrequency (%)
2019 31
100.0%

Length

2023-12-12T07:57:59.297215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T07:57:59.368141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2019 31
100.0%

월
Categorical

CONSTANT 

Distinct1
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size380.0 B
12
31 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row12
2nd row12
3rd row12
4th row12
5th row12

Common Values

ValueCountFrequency (%)
12 31
100.0%

Length

2023-12-12T07:57:59.441509image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T07:57:59.519143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
12 31
100.0%

매장
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)16.1%
Missing0
Missing (%)0.0%
Memory size380.0 B
홈쇼핑
11 
아임쇼핑 부산역
5 
아임쇼핑 인천공항서편
5 
아임쇼핑 인천공항동편
5 
아임쇼핑 화성휴게소
5 

Length

Max length11
Median length10
Mean length7.516129
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row아임쇼핑 부산역
2nd row아임쇼핑 부산역
3rd row아임쇼핑 부산역
4th row아임쇼핑 부산역
5th row아임쇼핑 부산역

Common Values

ValueCountFrequency (%)
홈쇼핑 11
35.5%
아임쇼핑 부산역 5
16.1%
아임쇼핑 인천공항서편 5
16.1%
아임쇼핑 인천공항동편 5
16.1%
아임쇼핑 화성휴게소 5
16.1%

Length

2023-12-12T07:57:59.610460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T07:57:59.715075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
아임쇼핑 20
39.2%
홈쇼핑 11
21.6%
부산역 5
 
9.8%
인천공항서편 5
 
9.8%
인천공항동편 5
 
9.8%
화성휴게소 5
 
9.8%

카테고리
Categorical

HIGH CORRELATION 

Distinct15
Distinct (%)48.4%
Missing0
Missing (%)0.0%
Memory size380.0 B
패션잡화
5 
디지털/가전
4 
생활/주방/욕실
4 
뷰티
4 
식품
4 
Other values (10)
10 

Length

Max length8
Median length6
Mean length4.1290323
Min length2

Unique

Unique10 ?
Unique (%)32.3%

Sample

1st row디지털/가전
2nd row생활/주방/욕실
3rd row뷰티
4th row식품
5th row패션잡화

Common Values

ValueCountFrequency (%)
패션잡화 5
16.1%
디지털/가전 4
12.9%
생활/주방/욕실 4
12.9%
뷰티 4
12.9%
식품 4
12.9%
의류속옷 1
 
3.2%
생활용품 1
 
3.2%
가전/컴퓨터 1
 
3.2%
레저스포츠 1
 
3.2%
주방 1
 
3.2%
Other values (5) 5
16.1%

Length

2023-12-12T07:57:59.820977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
패션잡화 5
16.1%
디지털/가전 4
12.9%
생활/주방/욕실 4
12.9%
뷰티 4
12.9%
식품 4
12.9%
의류속옷 1
 
3.2%
생활용품 1
 
3.2%
가전/컴퓨터 1
 
3.2%
레저스포츠 1
 
3.2%
주방 1
 
3.2%
Other values (5) 5
16.1%

매출비중
Real number (ℝ)

ZEROS 

Distinct30
Distinct (%)96.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean16.129677
Minimum0
Maximum88.97
Zeros1
Zeros (%)3.2%
Negative0
Negative (%)0.0%
Memory size411.0 B
2023-12-12T07:57:59.921349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0.585
Q12.965
median5.77
Q323.77
95-th percentile54.58
Maximum88.97
Range88.97
Interquartile range (IQR)20.805

Descriptive statistics

Standard deviation20.622876
Coefficient of variation (CV)1.2785672
Kurtosis4.7942003
Mean16.129677
Median Absolute Deviation (MAD)4.75
Skewness2.079236
Sum500.02
Variance425.30301
MonotonicityNot monotonic
2023-12-12T07:58:00.023618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
1.47 2
 
6.5%
20.49 1
 
3.2%
5.77 1
 
3.2%
0.15 1
 
3.2%
2.77 1
 
3.2%
4.58 1
 
3.2%
7.22 1
 
3.2%
1.54 1
 
3.2%
1.35 1
 
3.2%
7.69 1
 
3.2%
Other values (20) 20
64.5%
ValueCountFrequency (%)
0.0 1
3.2%
0.15 1
3.2%
1.02 1
3.2%
1.35 1
3.2%
1.47 2
6.5%
1.54 1
3.2%
2.77 1
3.2%
3.16 1
3.2%
3.42 1
3.2%
4.24 1
3.2%
ValueCountFrequency (%)
88.97 1
3.2%
66.78 1
3.2%
42.38 1
3.2%
35.49 1
3.2%
32.11 1
3.2%
30.55 1
3.2%
29.76 1
3.2%
26.06 1
3.2%
21.48 1
3.2%
20.49 1
3.2%

단위
Categorical

CONSTANT 

Distinct1
Distinct (%)3.2%
Missing0
Missing (%)0.0%
Memory size380.0 B
%
31 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row%
2nd row%
3rd row%
4th row%
5th row%

Common Values

ValueCountFrequency (%)
% 31
100.0%

Length

2023-12-12T07:58:00.127153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T07:58:00.203681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
31
100.0%

Interactions

2023-12-12T07:57:58.825989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T07:58:00.252789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
판매형태매장카테고리매출비중
판매형태1.0001.0000.9100.441
매장1.0001.0000.0000.519
카테고리0.9100.0001.0000.000
매출비중0.4410.5190.0001.000
2023-12-12T07:58:00.332433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
매장카테고리판매형태
매장1.0000.0000.947
카테고리0.0001.0000.660
판매형태0.9470.6601.000
2023-12-12T07:58:00.411583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
매출비중판매형태매장카테고리
매출비중1.0000.4240.3430.000
판매형태0.4241.0000.9470.660
매장0.3430.9471.0000.000
카테고리0.0000.6600.0001.000

Missing values

2023-12-12T07:57:58.914425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T07:57:59.010176image/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

판매형태연도월매장카테고리매출비중단위
0중소기업전용판매장201912아임쇼핑 부산역디지털/가전20.49%
1중소기업전용판매장201912아임쇼핑 부산역생활/주방/욕실42.38%
2중소기업전용판매장201912아임쇼핑 부산역뷰티3.42%
3중소기업전용판매장201912아임쇼핑 부산역식품3.16%
4중소기업전용판매장201912아임쇼핑 부산역패션잡화30.55%
5중소기업전용판매장201912아임쇼핑 인천공항서편디지털/가전4.69%
6중소기업전용판매장201912아임쇼핑 인천공항서편생활/주방/욕실35.49%
7중소기업전용판매장201912아임쇼핑 인천공항서편뷰티13.63%
8중소기업전용판매장201912아임쇼핑 인천공항서편식품32.11%
9중소기업전용판매장201912아임쇼핑 인천공항서편패션잡화14.09%
판매형태연도월매장카테고리매출비중단위
21홈쇼핑 판매대행201912홈쇼핑생활용품4.99%
22홈쇼핑 판매대행201912홈쇼핑가전/컴퓨터7.69%
23홈쇼핑 판매대행201912홈쇼핑레저스포츠1.35%
24홈쇼핑 판매대행201912홈쇼핑주방1.47%
25홈쇼핑 판매대행201912홈쇼핑침구1.54%
26홈쇼핑 판매대행201912홈쇼핑패션잡화7.22%
27홈쇼핑 판매대행201912홈쇼핑가구4.58%
28홈쇼핑 판매대행201912홈쇼핑식품건강2.77%
29홈쇼핑 판매대행201912홈쇼핑화장품1.47%
30홈쇼핑 판매대행201912홈쇼핑교육아동0.15%