Overview

Dataset statistics

Number of variables4
Number of observations61
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.1 KiB
Average record size in memory35.2 B

Variable types

Categorical3
Numeric1

Dataset

Description수출화물 목재포장재 열처리 지역별, 품목별 처리수량
Author농림축산검역본부
URLhttps://data.mafra.go.kr/opendata/data/indexOpenDataDetail.do?data_id=20220214000000001866

Alerts

품목명 is highly overall correlated with 단위High correlation
단위 is highly overall correlated with 품목명High correlation

Reproduction

Analysis started2023-12-11 03:17:43.269146
Analysis finished2023-12-11 03:17:43.679157
Duration0.41 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시/도
Categorical

Distinct14
Distinct (%)23.0%
Missing0
Missing (%)0.0%
Memory size620.0 B
충청북도
8 
인천광역시
6 
경기도
6 
전라북도
6 
경상북도
6 
Other values (9)
29 

Length

Max length7
Median length4
Mean length4.3278689
Min length3

Unique

Unique2 ?
Unique (%)3.3%

Sample

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

Common Values

ValueCountFrequency (%)
충청북도 8
13.1%
인천광역시 6
9.8%
경기도 6
9.8%
전라북도 6
9.8%
경상북도 6
9.8%
경상남도 6
9.8%
부산광역시 5
8.2%
대구광역시 4
6.6%
울산광역시 4
6.6%
충청남도 4
6.6%
Other values (4) 6
9.8%

Length

2023-12-11T12:17:43.766480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
충청북도 8
13.1%
인천광역시 6
9.8%
경기도 6
9.8%
전라북도 6
9.8%
경상북도 6
9.8%
경상남도 6
9.8%
부산광역시 5
8.2%
대구광역시 4
6.6%
울산광역시 4
6.6%
충청남도 4
6.6%
Other values (4) 6
9.8%

품목명
Categorical

HIGH CORRELATION 

Distinct9
Distinct (%)14.8%
Missing0
Missing (%)0.0%
Memory size620.0 B
파렛트
13 
각재
11 
나무상자
10 
판재
9 
드럼
5 
Other values (4)
13 

Length

Max length8
Median length4
Mean length3.1967213
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row파렛트
2nd row드럼
3rd row나무상자
4th row각재
5th row판재

Common Values

ValueCountFrequency (%)
파렛트 13
21.3%
각재 11
18.0%
나무상자 10
16.4%
판재 9
14.8%
드럼 5
 
8.2%
지지목(버팀목) 4
 
6.6%
스키드 4
 
6.6%
기타 3
 
4.9%
받침목(짐깔개) 2
 
3.3%

Length

2023-12-11T12:17:44.000489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T12:17:44.201138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
파렛트 13
21.3%
각재 11
18.0%
나무상자 10
16.4%
판재 9
14.8%
드럼 5
 
8.2%
지지목(버팀목 4
 
6.6%
스키드 4
 
6.6%
기타 3
 
4.9%
받침목(짐깔개 2
 
3.3%

수량
Real number (ℝ)

Distinct59
Distinct (%)96.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean680.98379
Minimum1.44
Maximum7000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size681.0 B
2023-12-11T12:17:44.394768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.44
5-th percentile4
Q137.58
median88
Q3724
95-th percentile3471
Maximum7000
Range6998.56
Interquartile range (IQR)686.42

Descriptive statistics

Standard deviation1274.7333
Coefficient of variation (CV)1.8718995
Kurtosis10.171383
Mean680.98379
Median Absolute Deviation (MAD)86.43
Skewness2.9399843
Sum41540.011
Variance1624944.9
MonotonicityNot monotonic
2023-12-11T12:17:44.542423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
44.0 2
 
3.3%
80.0 2
 
3.3%
794.0 1
 
1.6%
1700.0 1
 
1.6%
48.0 1
 
1.6%
25.0 1
 
1.6%
24.0 1
 
1.6%
4.0 1
 
1.6%
1329.0 1
 
1.6%
2021.0 1
 
1.6%
Other values (49) 49
80.3%
ValueCountFrequency (%)
1.44 1
1.6%
1.57 1
1.6%
1.85 1
1.6%
4.0 1
1.6%
5.2 1
1.6%
9.4224 1
1.6%
10.165 1
1.6%
12.47 1
1.6%
12.66 1
1.6%
16.0 1
1.6%
ValueCountFrequency (%)
7000.0 1
1.6%
3904.0 1
1.6%
3800.0 1
1.6%
3471.0 1
1.6%
2980.0 1
1.6%
2508.0 1
1.6%
2021.0 1
1.6%
1920.0 1
1.6%
1700.0 1
1.6%
1699.0 1
1.6%

단위
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size620.0 B
개
41 
㎥
20 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row개
2nd row개
3rd row개
4th row㎥
5th row㎥

Common Values

ValueCountFrequency (%)
개 41
67.2%
㎥ 20
32.8%

Length

2023-12-11T12:17:44.724762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T12:17:44.851872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
개 41
67.2%
㎥ 20
32.8%

Interactions

2023-12-11T12:17:43.412032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T12:17:44.939864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시/도품목명수량단위
시/도1.0000.0000.0000.000
품목명0.0001.0000.4971.000
수량0.0000.4971.0000.270
단위0.0001.0000.2701.000
2023-12-11T12:17:45.072364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
품목명시/도단위
품목명1.0000.0000.939
시/도0.0001.0000.000
단위0.9390.0001.000
2023-12-11T12:17:45.170095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
수량시/도품목명단위
수량1.0000.0000.2810.273
시/도0.0001.0000.0000.000
품목명0.2810.0001.0000.939
단위0.2730.0000.9391.000

Missing values

2023-12-11T12:17:43.538598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T12:17:43.636545image/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

시/도품목명수량단위
0부산광역시파렛트794.0개
1부산광역시드럼45.0개
2부산광역시나무상자20.0개
3부산광역시각재67.085㎥
4부산광역시판재20.249㎥
5대구광역시파렛트51.0개
6대구광역시나무상자22.0개
7대구광역시각재10.165㎥
8대구광역시판재1.85㎥
9인천광역시파렛트1699.0개
시/도품목명수량단위
51경상북도나무상자215.0개
52경상북도각재50.02㎥
53경상북도지지목(버팀목)2980.0개
54경상북도스키드724.0개
55경상남도파렛트3471.0개
56경상남도드럼80.0개
57경상남도나무상자458.0개
58경상남도각재375.99435㎥
59경상남도판재78.6023㎥
60경상남도스키드88.0개