Overview

Dataset statistics

Number of variables6
Number of observations22
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.3 KiB
Average record size in memory59.8 B

Variable types

Numeric5
Categorical1

Dataset

Description무역구제조치 반덤핑, 세이프가드, 불공정 무역행위와 FTA무역 피해지원에 대한 통계 자료로 불공정한 무역행위별로 조치 현황 자료를 포함
Author산업통상자원부
URLhttps://www.data.go.kr/data/15054385/fileData.do

Alerts

반덤핑_국가 is highly overall correlated with 반덤핑_품목High correlation
반덤핑_품목 is highly overall correlated with 반덤핑_국가High correlation
세이프가드 is highly imbalanced (56.1%)Imbalance
연도 has unique valuesUnique
FTA무역피해지원 has 14 (63.6%) zerosZeros

Reproduction

Analysis started2024-03-14 11:58:21.751968
Analysis finished2024-03-14 11:58:27.255972
Duration5.5 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연도
Real number (ℝ)

UNIQUE 

Distinct22
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2012.5
Minimum2002
Maximum2023
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size326.0 B
2024-03-14T20:58:27.386076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2002
5-th percentile2003.05
Q12007.25
median2012.5
Q32017.75
95-th percentile2021.95
Maximum2023
Range21
Interquartile range (IQR)10.5

Descriptive statistics

Standard deviation6.4935866
Coefficient of variation (CV)0.0032266269
Kurtosis-1.2
Mean2012.5
Median Absolute Deviation (MAD)5.5
Skewness0
Sum44275
Variance42.166667
MonotonicityStrictly increasing
2024-03-14T20:58:27.797031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
2002 1
 
4.5%
2014 1
 
4.5%
2023 1
 
4.5%
2022 1
 
4.5%
2021 1
 
4.5%
2020 1
 
4.5%
2019 1
 
4.5%
2018 1
 
4.5%
2017 1
 
4.5%
2016 1
 
4.5%
Other values (12) 12
54.5%
ValueCountFrequency (%)
2002 1
4.5%
2003 1
4.5%
2004 1
4.5%
2005 1
4.5%
2006 1
4.5%
2007 1
4.5%
2008 1
4.5%
2009 1
4.5%
2010 1
4.5%
2011 1
4.5%
ValueCountFrequency (%)
2023 1
4.5%
2022 1
4.5%
2021 1
4.5%
2020 1
4.5%
2019 1
4.5%
2018 1
4.5%
2017 1
4.5%
2016 1
4.5%
2015 1
4.5%
2014 1
4.5%

반덤핑_국가
Real number (ℝ)

HIGH CORRELATION 

Distinct11
Distinct (%)50.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11.454545
Minimum4
Maximum18
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size326.0 B
2024-03-14T20:58:27.972877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4
5-th percentile5
Q18.25
median13
Q314.75
95-th percentile17.9
Maximum18
Range14
Interquartile range (IQR)6.5

Descriptive statistics

Standard deviation4.284271
Coefficient of variation (CV)0.37402366
Kurtosis-1.1564616
Mean11.454545
Median Absolute Deviation (MAD)3.5
Skewness-0.23692413
Sum252
Variance18.354978
MonotonicityNot monotonic
2024-03-14T20:58:28.185660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
14 4
18.2%
15 3
13.6%
9 3
13.6%
18 2
9.1%
5 2
9.1%
7 2
9.1%
13 2
9.1%
4 1
 
4.5%
8 1
 
4.5%
16 1
 
4.5%
ValueCountFrequency (%)
4 1
 
4.5%
5 2
9.1%
7 2
9.1%
8 1
 
4.5%
9 3
13.6%
10 1
 
4.5%
13 2
9.1%
14 4
18.2%
15 3
13.6%
16 1
 
4.5%
ValueCountFrequency (%)
18 2
9.1%
16 1
 
4.5%
15 3
13.6%
14 4
18.2%
13 2
9.1%
10 1
 
4.5%
9 3
13.6%
8 1
 
4.5%
7 2
9.1%
5 2
9.1%

반덤핑_품목
Real number (ℝ)

HIGH CORRELATION 

Distinct8
Distinct (%)36.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.2272727
Minimum3
Maximum11
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size326.0 B
2024-03-14T20:58:28.431641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile4
Q15
median6
Q37
95-th percentile9.9
Maximum11
Range8
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.900672
Coefficient of variation (CV)0.3052174
Kurtosis0.99263687
Mean6.2272727
Median Absolute Deviation (MAD)1
Skewness0.87742925
Sum137
Variance3.6125541
MonotonicityNot monotonic
2024-03-14T20:58:28.676095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
6 7
31.8%
5 5
22.7%
8 3
13.6%
7 2
 
9.1%
4 2
 
9.1%
11 1
 
4.5%
3 1
 
4.5%
10 1
 
4.5%
ValueCountFrequency (%)
3 1
 
4.5%
4 2
 
9.1%
5 5
22.7%
6 7
31.8%
7 2
 
9.1%
8 3
13.6%
10 1
 
4.5%
11 1
 
4.5%
ValueCountFrequency (%)
11 1
 
4.5%
10 1
 
4.5%
8 3
13.6%
7 2
 
9.1%
6 7
31.8%
5 5
22.7%
4 2
 
9.1%
3 1
 
4.5%

세이프가드
Categorical

IMBALANCE 

Distinct2
Distinct (%)9.1%
Missing0
Missing (%)0.0%
Memory size304.0 B
0
20 
1
 
2

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 20
90.9%
1 2
 
9.1%

Length

2024-03-14T20:58:28.894982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T20:58:29.067980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 20
90.9%
1 2
 
9.1%

불공정무역행위
Real number (ℝ)

Distinct9
Distinct (%)40.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.8636364
Minimum3
Maximum13
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size326.0 B
2024-03-14T20:58:29.231000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile4.05
Q15.25
median8
Q39
95-th percentile12
Maximum13
Range10
Interquartile range (IQR)3.75

Descriptive statistics

Standard deviation2.7132032
Coefficient of variation (CV)0.34503163
Kurtosis-0.66518104
Mean7.8636364
Median Absolute Deviation (MAD)2
Skewness0.063721849
Sum173
Variance7.3614719
MonotonicityNot monotonic
2024-03-14T20:58:29.410461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
9 5
22.7%
5 4
18.2%
8 4
18.2%
6 2
 
9.1%
12 2
 
9.1%
10 2
 
9.1%
4 1
 
4.5%
13 1
 
4.5%
3 1
 
4.5%
ValueCountFrequency (%)
3 1
 
4.5%
4 1
 
4.5%
5 4
18.2%
6 2
 
9.1%
8 4
18.2%
9 5
22.7%
10 2
 
9.1%
12 2
 
9.1%
13 1
 
4.5%
ValueCountFrequency (%)
13 1
 
4.5%
12 2
 
9.1%
10 2
 
9.1%
9 5
22.7%
8 4
18.2%
6 2
 
9.1%
5 4
18.2%
4 1
 
4.5%
3 1
 
4.5%

FTA무역피해지원
Real number (ℝ)

ZEROS 

Distinct8
Distinct (%)36.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.8636364
Minimum0
Maximum31
Zeros14
Zeros (%)63.6%
Negative0
Negative (%)0.0%
Memory size326.0 B
2024-03-14T20:58:29.636558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q33
95-th percentile27.7
Maximum31
Range31
Interquartile range (IQR)3

Descriptive statistics

Standard deviation9.5732537
Coefficient of variation (CV)1.9683325
Kurtosis2.9483224
Mean4.8636364
Median Absolute Deviation (MAD)0
Skewness2.0395902
Sum107
Variance91.647186
MonotonicityNot monotonic
2024-03-14T20:58:29.864463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
0 14
63.6%
3 2
 
9.1%
2 1
 
4.5%
13 1
 
4.5%
31 1
 
4.5%
28 1
 
4.5%
22 1
 
4.5%
5 1
 
4.5%
ValueCountFrequency (%)
0 14
63.6%
2 1
 
4.5%
3 2
 
9.1%
5 1
 
4.5%
13 1
 
4.5%
22 1
 
4.5%
28 1
 
4.5%
31 1
 
4.5%
ValueCountFrequency (%)
31 1
 
4.5%
28 1
 
4.5%
22 1
 
4.5%
13 1
 
4.5%
5 1
 
4.5%
3 2
 
9.1%
2 1
 
4.5%
0 14
63.6%

Interactions

2024-03-14T20:58:26.155363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:58:21.954071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:58:23.138959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:58:24.383476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:58:25.369966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:58:26.294801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:58:22.170174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:58:23.373098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:58:24.619558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:58:25.491745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:58:26.449934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:58:22.415336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:58:23.630071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:58:24.883786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:58:25.640440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:58:26.612225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:58:22.673325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:58:23.894263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:58:25.071376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:58:25.793381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:58:26.748097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:58:22.898568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:58:24.132482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:58:25.213301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T20:58:25.923630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-14T20:58:30.016870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연도반덤핑_국가반덤핑_품목세이프가드불공정무역행위FTA무역피해지원
연도1.0000.0000.2630.3710.5410.891
반덤핑_국가0.0001.0000.8250.3230.4480.185
반덤핑_품목0.2630.8251.0000.7720.0000.340
세이프가드0.3710.3230.7721.0000.0000.144
불공정무역행위0.5410.4480.0000.0001.0000.000
FTA무역피해지원0.8910.1850.3400.1440.0001.000
2024-03-14T20:58:30.200927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연도반덤핑_국가반덤핑_품목불공정무역행위FTA무역피해지원세이프가드
연도1.000-0.1800.0560.245-0.0010.000
반덤핑_국가-0.1801.0000.7650.034-0.2630.162
반덤핑_품목0.0560.7651.0000.196-0.3640.488
불공정무역행위0.2450.0340.1961.0000.4270.000
FTA무역피해지원-0.001-0.263-0.3640.4271.0000.133
세이프가드0.0000.1620.4880.0000.1331.000

Missing values

2024-03-14T20:58:26.943594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T20:58:27.127438image/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

연도반덤핑_국가반덤핑_품목세이프가드불공정무역행위FTA무역피해지원
020021811190
12003157050
2200455050
3200574060
42006156050
52007188040
6200843063
72009146093
82010760122
92011156080
연도반덤핑_국가반덤핑_품목세이프가드불공정무역행위FTA무역피해지원
122014161001028
132015540922
142016950125
152017147090
1620181460100
1720191380130
18202095030
19202196050
202022136080
212023108080