Overview

Dataset statistics

Number of variables12
Number of observations43
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.7 KiB
Average record size in memory111.1 B

Variable types

Numeric12

Dataset

Description섬유산업의 수출입 현황에 대한 데이터로 연도별 전체산업과 섬유산업의 수출, 수출증감, 수입, 수입증감, 무역수지 등 관련 정보를 제공합니다.
Author산업통상자원부
URLhttps://www.data.go.kr/data/15051124/fileData.do

Alerts

연도 is highly overall correlated with 전체산업수출금액(백만불) and 5 other fieldsHigh correlation
전체산업수출금액(백만불) is highly overall correlated with 연도 and 5 other fieldsHigh correlation
전체산업수출증감(전년대비_퍼센트) is highly overall correlated with 전체산업수입증감(전년대비_퍼센트) and 2 other fieldsHigh correlation
전체산업수입금액(백만불) is highly overall correlated with 연도 and 5 other fieldsHigh correlation
전체산업수입증감(전년대비_퍼센트) is highly overall correlated with 전체산업수출증감(전년대비_퍼센트) and 2 other fieldsHigh correlation
전체산업무역수지(백만불) is highly overall correlated with 연도 and 5 other fieldsHigh correlation
섬유산업수출금액(백만불) is highly overall correlated with 섬유산업무역수지(백만불)High correlation
섬유산업수출증감(전년대비_퍼센트) is highly overall correlated with 전체산업수출증감(전년대비_퍼센트) and 2 other fieldsHigh correlation
섬유산업수출비중(전년대비_퍼센트) is highly overall correlated with 연도 and 5 other fieldsHigh correlation
섬유산업수입금액(백만불) is highly overall correlated with 연도 and 5 other fieldsHigh correlation
섬유산업수입증감(전년대비_퍼센트) is highly overall correlated with 전체산업수출증감(전년대비_퍼센트) and 2 other fieldsHigh correlation
섬유산업무역수지(백만불) is highly overall correlated with 연도 and 6 other fieldsHigh correlation
연도 has unique valuesUnique
전체산업수출금액(백만불) has unique valuesUnique
전체산업수입금액(백만불) has unique valuesUnique
전체산업무역수지(백만불) has unique valuesUnique
섬유산업수출금액(백만불) has unique valuesUnique
섬유산업수입금액(백만불) has unique valuesUnique
섬유산업무역수지(백만불) has unique valuesUnique
전체산업수입증감(전년대비_퍼센트) has 1 (2.3%) zerosZeros
섬유산업수출증감(전년대비_퍼센트) has 2 (4.7%) zerosZeros
섬유산업수입증감(전년대비_퍼센트) has 2 (4.7%) zerosZeros

Reproduction

Analysis started2023-12-30 04:56:38.475116
Analysis finished2023-12-30 04:57:24.408345
Duration45.93 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연도
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct43
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2001
Minimum1980
Maximum2022
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size519.0 B
2023-12-30T04:57:24.686506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1980
5-th percentile1982.1
Q11990.5
median2001
Q32011.5
95-th percentile2019.9
Maximum2022
Range42
Interquartile range (IQR)21

Descriptive statistics

Standard deviation12.556539
Coefficient of variation (CV)0.0062751318
Kurtosis-1.2
Mean2001
Median Absolute Deviation (MAD)11
Skewness0
Sum86043
Variance157.66667
MonotonicityStrictly increasing
2023-12-30T04:57:25.168150image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
1980 1
 
2.3%
1981 1
 
2.3%
2004 1
 
2.3%
2005 1
 
2.3%
2006 1
 
2.3%
2007 1
 
2.3%
2008 1
 
2.3%
2009 1
 
2.3%
2010 1
 
2.3%
2011 1
 
2.3%
Other values (33) 33
76.7%
ValueCountFrequency (%)
1980 1
2.3%
1981 1
2.3%
1982 1
2.3%
1983 1
2.3%
1984 1
2.3%
1985 1
2.3%
1986 1
2.3%
1987 1
2.3%
1988 1
2.3%
1989 1
2.3%
ValueCountFrequency (%)
2022 1
2.3%
2021 1
2.3%
2020 1
2.3%
2019 1
2.3%
2018 1
2.3%
2017 1
2.3%
2016 1
2.3%
2015 1
2.3%
2014 1
2.3%
2013 1
2.3%

전체산업수출금액(백만불)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct43
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean264961.09
Minimum17505
Maximum683585
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size519.0 B
2023-12-30T04:57:25.735309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum17505
5-th percentile22112.2
Q168443
median162471
Q3503962
95-th percentile601743.4
Maximum683585
Range666080
Interquartile range (IQR)435519

Descriptive statistics

Standard deviation221262.56
Coefficient of variation (CV)0.83507568
Kurtosis-1.3891829
Mean264961.09
Median Absolute Deviation (MAD)133226
Skewness0.48023706
Sum11393327
Variance4.8957122 × 1010
MonotonicityNot monotonic
2023-12-30T04:57:26.257997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
17505 1
 
2.3%
21254 1
 
2.3%
253845 1
 
2.3%
284419 1
 
2.3%
325465 1
 
2.3%
371489 1
 
2.3%
422007 1
 
2.3%
363534 1
 
2.3%
466384 1
 
2.3%
555214 1
 
2.3%
Other values (33) 33
76.7%
ValueCountFrequency (%)
17505 1
2.3%
21254 1
2.3%
21853 1
2.3%
24445 1
2.3%
29245 1
2.3%
30283 1
2.3%
34714 1
2.3%
47281 1
2.3%
60696 1
2.3%
62377 1
2.3%
ValueCountFrequency (%)
683585 1
2.3%
644400 1
2.3%
604860 1
2.3%
573694 1
2.3%
572665 1
2.3%
559632 1
2.3%
555214 1
2.3%
547870 1
2.3%
542233 1
2.3%
526757 1
2.3%

전체산업수출증감(전년대비_퍼센트)
Real number (ℝ)

HIGH CORRELATION 

Distinct29
Distinct (%)67.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9.9302326
Minimum-14
Maximum36
Zeros0
Zeros (%)0.0%
Negative8
Negative (%)18.6%
Memory size519.0 B
2023-12-30T04:57:26.662148image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-14
5-th percentile-9.8
Q13
median9
Q318
95-th percentile29.8
Maximum36
Range50
Interquartile range (IQR)15

Descriptive statistics

Standard deviation12.111379
Coefficient of variation (CV)1.219647
Kurtosis-0.40381521
Mean9.9302326
Median Absolute Deviation (MAD)7
Skewness0.049286301
Sum427
Variance146.68549
MonotonicityNot monotonic
2023-12-30T04:57:27.136873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
14 3
 
7.0%
4 3
 
7.0%
16 2
 
4.7%
28 2
 
4.7%
2 2
 
4.7%
5 2
 
4.7%
-6 2
 
4.7%
7 2
 
4.7%
19 2
 
4.7%
20 2
 
4.7%
Other values (19) 21
48.8%
ValueCountFrequency (%)
-14 1
 
2.3%
-13 1
 
2.3%
-10 1
 
2.3%
-8 1
 
2.3%
-6 2
4.7%
-3 1
 
2.3%
-1 1
 
2.3%
2 2
4.7%
3 2
4.7%
4 3
7.0%
ValueCountFrequency (%)
36 1
2.3%
31 1
2.3%
30 1
2.3%
28 2
4.7%
26 1
2.3%
21 1
2.3%
20 2
4.7%
19 2
4.7%
17 1
2.3%
16 2
4.7%

전체산업수입금액(백만불)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct43
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean247345.49
Minimum22292
Maximum731370
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size519.0 B
2023-12-30T04:57:27.506421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum22292
5-th percentile26137.1
Q175684.5
median152126
Q3435887
95-th percentile534233.3
Maximum731370
Range709078
Interquartile range (IQR)360202.5

Descriptive statistics

Standard deviation204914.32
Coefficient of variation (CV)0.82845385
Kurtosis-1.0077318
Mean247345.49
Median Absolute Deviation (MAD)121495
Skewness0.58806579
Sum10635856
Variance4.198988 × 1010
MonotonicityNot monotonic
2023-12-30T04:57:27.814272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
22292 1
 
2.3%
26131 1
 
2.3%
224463 1
 
2.3%
261238 1
 
2.3%
309383 1
 
2.3%
356846 1
 
2.3%
435275 1
 
2.3%
323085 1
 
2.3%
425212 1
 
2.3%
524413 1
 
2.3%
Other values (33) 33
76.7%
ValueCountFrequency (%)
22292 1
2.3%
24251 1
2.3%
26131 1
2.3%
26192 1
2.3%
30631 1
2.3%
31136 1
2.3%
31584 1
2.3%
41020 1
2.3%
51811 1
2.3%
61465 1
2.3%
ValueCountFrequency (%)
731370 1
2.3%
615093 1
2.3%
535202 1
2.3%
525515 1
2.3%
524413 1
2.3%
519584 1
2.3%
515586 1
2.3%
503343 1
2.3%
478478 1
2.3%
467633 1
2.3%

전체산업수입증감(전년대비_퍼센트)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct29
Distinct (%)67.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9.9534884
Minimum-36
Maximum34
Zeros1
Zeros (%)2.3%
Negative11
Negative (%)25.6%
Memory size519.0 B
2023-12-30T04:57:28.154185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-36
5-th percentile-16.5
Q1-0.5
median14
Q320.5
95-th percentile32
Maximum34
Range70
Interquartile range (IQR)21

Descriptive statistics

Standard deviation16.077126
Coefficient of variation (CV)1.6152253
Kurtosis0.41027449
Mean9.9534884
Median Absolute Deviation (MAD)12
Skewness-0.73478914
Sum428
Variance258.47398
MonotonicityNot monotonic
2023-12-30T04:57:28.545201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
18 3
 
7.0%
32 3
 
7.0%
-7 3
 
7.0%
17 3
 
7.0%
8 2
 
4.7%
2 2
 
4.7%
26 2
 
4.7%
19 2
 
4.7%
-1 2
 
4.7%
22 2
 
4.7%
Other values (19) 19
44.2%
ValueCountFrequency (%)
-36 1
 
2.3%
-26 1
 
2.3%
-17 1
 
2.3%
-12 1
 
2.3%
-7 3
7.0%
-6 1
 
2.3%
-4 1
 
2.3%
-1 2
4.7%
0 1
 
2.3%
1 1
 
2.3%
ValueCountFrequency (%)
34 1
 
2.3%
32 3
7.0%
30 1
 
2.3%
28 1
 
2.3%
26 2
4.7%
23 1
 
2.3%
22 2
4.7%
19 2
4.7%
18 3
7.0%
17 3
7.0%

전체산업무역수지(백만불)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct43
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean17615.558
Minimum-47785
Maximum95216
Zeros0
Zeros (%)0.0%
Negative16
Negative (%)37.2%
Memory size519.0 B
2023-12-30T04:57:28.944907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-47785
5-th percentile-12946.4
Q1-3592
median10344
Q334845.5
95-th percentile87275.4
Maximum95216
Range143001
Interquartile range (IQR)38437.5

Descriptive statistics

Standard deviation30185.598
Coefficient of variation (CV)1.713576
Kurtosis0.93419952
Mean17615.558
Median Absolute Deviation (MAD)16679
Skewness0.85766656
Sum757469
Variance9.1117032 × 108
MonotonicityNot monotonic
2023-12-30T04:57:29.368700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
-4787 1
 
2.3%
-4878 1
 
2.3%
29382 1
 
2.3%
23180 1
 
2.3%
16082 1
 
2.3%
14643 1
 
2.3%
-13267 1
 
2.3%
40449 1
 
2.3%
41172 1
 
2.3%
30801 1
 
2.3%
Other values (33) 33
76.7%
ValueCountFrequency (%)
-47785 1
2.3%
-20624 1
2.3%
-13267 1
2.3%
-10061 1
2.3%
-9655 1
2.3%
-8452 1
2.3%
-6335 1
2.3%
-5144 1
2.3%
-4878 1
2.3%
-4828 1
2.3%
ValueCountFrequency (%)
95216 1
2.3%
90258 1
2.3%
89233 1
2.3%
69657 1
2.3%
47150 1
2.3%
44865 1
2.3%
44047 1
2.3%
41172 1
2.3%
40449 1
2.3%
39031 1
2.3%

섬유산업수출금액(백만불)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct43
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13615.302
Minimum5099
Maximum18783
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size519.0 B
2023-12-30T04:57:29.846773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5099
5-th percentile6152.4
Q112554
median14171
Q315932
95-th percentile18601.6
Maximum18783
Range13684
Interquartile range (IQR)3378

Descriptive statistics

Standard deviation3631.0869
Coefficient of variation (CV)0.26669161
Kurtosis0.24676235
Mean13615.302
Median Absolute Deviation (MAD)1859
Skewness-0.94271876
Sum585458
Variance13184792
MonotonicityNot monotonic
2023-12-30T04:57:30.170198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
5099 1
 
2.3%
6282 1
 
2.3%
14891 1
 
2.3%
13650 1
 
2.3%
13016 1
 
2.3%
13580 1
 
2.3%
13433 1
 
2.3%
11685 1
 
2.3%
13980 1
 
2.3%
16052 1
 
2.3%
Other values (33) 33
76.7%
ValueCountFrequency (%)
5099 1
2.3%
6002 1
2.3%
6138 1
2.3%
6282 1
2.3%
7084 1
2.3%
7195 1
2.3%
8815 1
2.3%
11238 1
2.3%
11685 1
2.3%
11834 1
2.3%
ValueCountFrequency (%)
18783 1
2.3%
18738 1
2.3%
18656 1
2.3%
18112 1
2.3%
17462 1
2.3%
17424 1
2.3%
16864 1
2.3%
16096 1
2.3%
16072 1
2.3%
16052 1
2.3%

섬유산업수출증감(전년대비_퍼센트)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct26
Distinct (%)60.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.8604651
Minimum-17
Maximum34
Zeros2
Zeros (%)4.7%
Negative19
Negative (%)44.2%
Memory size519.0 B
2023-12-30T04:57:30.557666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-17
5-th percentile-12.7
Q1-3.5
median1
Q38
95-th percentile22.7
Maximum34
Range51
Interquartile range (IQR)11.5

Descriptive statistics

Standard deviation10.888136
Coefficient of variation (CV)3.8064214
Kurtosis0.57502997
Mean2.8604651
Median Absolute Deviation (MAD)6
Skewness0.76577117
Sum123
Variance118.5515
MonotonicityNot monotonic
2023-12-30T04:57:30.847225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
-2 4
 
9.3%
-5 3
 
7.0%
2 3
 
7.0%
8 2
 
4.7%
-13 2
 
4.7%
-10 2
 
4.7%
4 2
 
4.7%
0 2
 
4.7%
-8 2
 
4.7%
-1 2
 
4.7%
Other values (16) 19
44.2%
ValueCountFrequency (%)
-17 1
 
2.3%
-13 2
4.7%
-10 2
4.7%
-8 2
4.7%
-5 3
7.0%
-4 1
 
2.3%
-3 2
4.7%
-2 4
9.3%
-1 2
4.7%
0 2
4.7%
ValueCountFrequency (%)
34 1
2.3%
24 1
2.3%
23 1
2.3%
20 2
4.7%
17 1
2.3%
15 1
2.3%
14 1
2.3%
11 1
2.3%
9 1
2.3%
8 2
4.7%

섬유산업수출비중(전년대비_퍼센트)
Real number (ℝ)

HIGH CORRELATION 

Distinct23
Distinct (%)53.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12.209302
Minimum2
Maximum30
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size519.0 B
2023-12-30T04:57:31.178179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile2
Q13
median10
Q322.5
95-th percentile27.7
Maximum30
Range28
Interquartile range (IQR)19.5

Descriptive statistics

Standard deviation9.6622933
Coefficient of variation (CV)0.79138783
Kurtosis-1.4223695
Mean12.209302
Median Absolute Deviation (MAD)7
Skewness0.41922761
Sum525
Variance93.359911
MonotonicityNot monotonic
2023-12-30T04:57:31.587061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
3 9
20.9%
2 6
14.0%
25 4
 
9.3%
23 3
 
7.0%
4 2
 
4.7%
14 2
 
4.7%
29 1
 
2.3%
11 1
 
2.3%
5 1
 
2.3%
6 1
 
2.3%
Other values (13) 13
30.2%
ValueCountFrequency (%)
2 6
14.0%
3 9
20.9%
4 2
 
4.7%
5 1
 
2.3%
6 1
 
2.3%
8 1
 
2.3%
9 1
 
2.3%
10 1
 
2.3%
11 1
 
2.3%
12 1
 
2.3%
ValueCountFrequency (%)
30 1
 
2.3%
29 1
 
2.3%
28 1
 
2.3%
25 4
9.3%
24 1
 
2.3%
23 3
7.0%
22 1
 
2.3%
21 1
 
2.3%
20 1
 
2.3%
18 1
 
2.3%

섬유산업수입금액(백만불)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct43
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7186.5814
Minimum453
Maximum19901
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size519.0 B
2023-12-30T04:57:31.988161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum453
5-th percentile546.2
Q12550
median5504
Q312021
95-th percentile17119
Maximum19901
Range19448
Interquartile range (IQR)9471

Descriptive statistics

Standard deviation5793.4918
Coefficient of variation (CV)0.80615407
Kurtosis-0.79592053
Mean7186.5814
Median Absolute Deviation (MAD)3748
Skewness0.67406467
Sum309023
Variance33564547
MonotonicityNot monotonic
2023-12-30T04:57:32.409555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
453 1
 
2.3%
541 1
 
2.3%
6369 1
 
2.3%
6723 1
 
2.3%
7963 1
 
2.3%
8913 1
 
2.3%
8770 1
 
2.3%
7254 1
 
2.3%
9739 1
 
2.3%
12330 1
 
2.3%
Other values (33) 33
76.7%
ValueCountFrequency (%)
453 1
2.3%
541 1
2.3%
543 1
2.3%
575 1
2.3%
673 1
2.3%
719 1
2.3%
1044 1
2.3%
1567 1
2.3%
1756 1
2.3%
2089 1
2.3%
ValueCountFrequency (%)
19901 1
2.3%
18299 1
2.3%
17120 1
2.3%
17110 1
2.3%
16203 1
2.3%
15175 1
2.3%
14491 1
2.3%
14376 1
2.3%
14287 1
2.3%
13261 1
2.3%

섬유산업수입증감(전년대비_퍼센트)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct32
Distinct (%)74.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean10.27907
Minimum-45
Maximum50
Zeros2
Zeros (%)4.7%
Negative8
Negative (%)18.6%
Memory size519.0 B
2023-12-30T04:57:32.743996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-45
5-th percentile-7.9
Q11.5
median8
Q318.5
95-th percentile37.7
Maximum50
Range95
Interquartile range (IQR)17

Descriptive statistics

Standard deviation16.599377
Coefficient of variation (CV)1.6148715
Kurtosis2.4482706
Mean10.27907
Median Absolute Deviation (MAD)8
Skewness-0.26117399
Sum442
Variance275.53931
MonotonicityNot monotonic
2023-12-30T04:57:33.076764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
6 3
 
7.0%
13 3
 
7.0%
5 3
 
7.0%
-5 2
 
4.7%
0 2
 
4.7%
8 2
 
4.7%
20 2
 
4.7%
12 2
 
4.7%
34 1
 
2.3%
18 1
 
2.3%
Other values (22) 22
51.2%
ValueCountFrequency (%)
-45 1
2.3%
-17 1
2.3%
-8 1
2.3%
-7 1
2.3%
-5 2
4.7%
-2 1
2.3%
-1 1
2.3%
0 2
4.7%
1 1
2.3%
2 1
2.3%
ValueCountFrequency (%)
50 1
2.3%
45 1
2.3%
38 1
2.3%
35 1
2.3%
34 1
2.3%
27 1
2.3%
25 1
2.3%
23 1
2.3%
20 2
4.7%
19 1
2.3%

섬유산업무역수지(백만불)
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct43
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6428.6977
Minimum-7601
Maximum14040
Zeros0
Zeros (%)0.0%
Negative7
Negative (%)16.3%
Memory size519.0 B
2023-12-30T04:57:33.382994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum-7601
5-th percentile-4883.6
Q13852.5
median6365
Q312528.5
95-th percentile13631
Maximum14040
Range21641
Interquartile range (IQR)8676

Descriptive statistics

Standard deviation6060.9149
Coefficient of variation (CV)0.94279047
Kurtosis-0.50697856
Mean6428.6977
Median Absolute Deviation (MAD)4645
Skewness-0.5640624
Sum276434
Variance36734690
MonotonicityNot monotonic
2023-12-30T04:57:33.935193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
4646 1
 
2.3%
5741 1
 
2.3%
8522 1
 
2.3%
6928 1
 
2.3%
5053 1
 
2.3%
4666 1
 
2.3%
4664 1
 
2.3%
4430 1
 
2.3%
4241 1
 
2.3%
3722 1
 
2.3%
Other values (33) 33
76.7%
ValueCountFrequency (%)
-7601 1
2.3%
-5492 1
2.3%
-4965 1
2.3%
-4151 1
2.3%
-3040 1
2.3%
-1433 1
2.3%
-684 1
2.3%
203 1
2.3%
1720 1
2.3%
2811 1
2.3%
ValueCountFrequency (%)
14040 1
2.3%
13995 1
2.3%
13641 1
2.3%
13541 1
2.3%
13442 1
2.3%
13297 1
2.3%
13148 1
2.3%
12945 1
2.3%
12903 1
2.3%
12794 1
2.3%

Interactions

2023-12-30T04:57:19.827716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-30T04:56:43.552158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-30T04:56:48.822351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-30T04:56:52.014239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-30T04:56:55.624244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-30T04:56:58.188363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-30T04:57:00.830293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-30T04:57:04.004535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-30T04:57:06.937164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-30T04:57:10.125031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-30T04:57:13.293411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-30T04:57:16.571463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-30T04:57:20.224709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-30T04:56:43.967271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-30T04:56:49.051828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-30T04:56:52.413204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-30T04:56:55.783352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-30T04:56:58.401268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-30T04:57:01.102657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-30T04:57:04.433768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-30T04:57:07.183510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-30T04:57:10.363861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-30T04:57:13.529088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-30T04:57:16.782722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-30T04:57:20.566047image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-30T04:56:44.467785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-30T04:56:49.365322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-30T04:56:52.857174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-30T04:56:56.180973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-30T04:56:58.709776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-30T04:57:01.366255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-30T04:57:04.686662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-30T04:57:07.428950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-30T04:57:10.604128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-30T04:57:13.793810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-30T04:57:16.948618image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-30T04:57:21.018661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-30T04:56:44.761910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-30T04:56:49.668250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-30T04:56:53.209732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-30T04:56:56.331563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-30T04:56:58.934763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-30T04:57:01.588616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-30T04:57:05.043437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-30T04:57:07.645999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-30T04:57:10.855591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-30T04:57:14.033952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-30T04:57:17.120750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-30T04:57:21.349343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-30T04:56:45.296116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-30T04:56:49.981248image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-30T04:56:53.586921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-30T04:56:56.514818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-30T04:56:59.120813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-30T04:57:01.819134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-30T04:57:05.307916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-30T04:57:07.975344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-30T04:57:11.113876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-30T04:57:14.492680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-30T04:57:17.331569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-30T04:57:21.697813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-30T04:56:45.696293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-30T04:56:50.238147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-30T04:56:53.931231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-30T04:56:56.712958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-30T04:56:59.299718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-30T04:57:02.041296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-30T04:57:05.514356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-30T04:57:08.241307image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-30T04:57:11.385588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-30T04:57:14.750591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-30T04:57:17.567787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-30T04:57:22.042165image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-30T04:56:46.026055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-30T04:56:50.505682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-30T04:56:54.311214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-30T04:56:56.956990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-30T04:56:59.504017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-30T04:57:02.299761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-30T04:57:05.677451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-30T04:57:08.496689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-30T04:57:11.665031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-30T04:57:15.021533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-30T04:57:17.834123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-30T04:57:22.424600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-30T04:56:46.517789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-30T04:56:50.760473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-30T04:56:54.647232image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-30T04:56:57.207875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-30T04:56:59.810238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-30T04:57:02.567657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-30T04:57:05.832811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-30T04:57:08.744918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-30T04:57:11.936801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-30T04:57:15.265534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-30T04:57:18.095173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-30T04:57:22.700097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-30T04:56:47.125302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-30T04:56:51.004548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-30T04:56:54.940672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-30T04:56:57.426456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-30T04:57:00.079697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-30T04:57:02.813992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-30T04:57:05.975917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-30T04:57:08.978308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-30T04:57:12.170805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-30T04:57:15.526408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-30T04:57:18.478167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-30T04:57:22.969382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-30T04:56:47.506546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-30T04:56:51.259626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-30T04:56:55.138335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-30T04:56:57.637871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-30T04:57:00.269242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-30T04:57:03.158363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-30T04:57:06.139342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-30T04:57:09.282660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-30T04:57:12.410710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-30T04:57:15.783759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-30T04:57:18.783578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-30T04:57:23.242603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-30T04:56:47.975854image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-30T04:56:51.530544image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-30T04:56:55.334653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-30T04:56:57.829564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-30T04:57:00.455941image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-30T04:57:03.438689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-30T04:57:06.418815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-30T04:57:09.553455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-30T04:57:12.680570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-30T04:57:16.078298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-30T04:57:19.124810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-30T04:57:23.587680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-30T04:56:48.369899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-30T04:56:51.771900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-30T04:56:55.488972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-30T04:56:58.012223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-30T04:57:00.600112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-30T04:57:03.647492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-30T04:57:06.703477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-30T04:57:09.788598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-30T04:57:12.946188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-30T04:57:16.322808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-30T04:57:19.523987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-30T04:57:34.361017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연도전체산업수출금액(백만불)전체산업수출증감(전년대비_퍼센트)전체산업수입금액(백만불)전체산업수입증감(전년대비_퍼센트)전체산업무역수지(백만불)섬유산업수출금액(백만불)섬유산업수출증감(전년대비_퍼센트)섬유산업수출비중(전년대비_퍼센트)섬유산업수입금액(백만불)섬유산업수입증감(전년대비_퍼센트)섬유산업무역수지(백만불)
연도1.0000.8950.0000.9040.0000.7380.7660.0000.9230.9470.3760.925
전체산업수출금액(백만불)0.8951.0000.7140.9730.4660.7170.6390.0000.8370.9570.5100.921
전체산업수출증감(전년대비_퍼센트)0.0000.7141.0000.7050.8040.0000.1900.8380.0000.7140.6180.866
전체산업수입금액(백만불)0.9040.9730.7051.0000.0000.6780.6230.0000.7950.9280.0000.845
전체산업수입증감(전년대비_퍼센트)0.0000.4660.8040.0001.0000.3080.0000.5640.0000.0000.8190.626
전체산업무역수지(백만불)0.7380.7170.0000.6780.3081.0000.4230.0000.5500.7640.0000.727
섬유산업수출금액(백만불)0.7660.6390.1900.6230.0000.4231.0000.7130.7150.6770.5300.752
섬유산업수출증감(전년대비_퍼센트)0.0000.0000.8380.0000.5640.0000.7131.0000.5990.0000.7570.605
섬유산업수출비중(전년대비_퍼센트)0.9230.8370.0000.7950.0000.5500.7150.5991.0000.8270.5420.579
섬유산업수입금액(백만불)0.9470.9570.7140.9280.0000.7640.6770.0000.8271.0000.1370.926
섬유산업수입증감(전년대비_퍼센트)0.3760.5100.6180.0000.8190.0000.5300.7570.5420.1371.0000.000
섬유산업무역수지(백만불)0.9250.9210.8660.8450.6260.7270.7520.6050.5790.9260.0001.000
2023-12-30T04:57:34.700680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연도전체산업수출금액(백만불)전체산업수출증감(전년대비_퍼센트)전체산업수입금액(백만불)전체산업수입증감(전년대비_퍼센트)전체산업무역수지(백만불)섬유산업수출금액(백만불)섬유산업수출증감(전년대비_퍼센트)섬유산업수출비중(전년대비_퍼센트)섬유산업수입금액(백만불)섬유산업수입증감(전년대비_퍼센트)섬유산업무역수지(백만불)
연도1.0000.984-0.2950.976-0.0660.6420.147-0.409-0.9910.988-0.207-0.656
전체산업수출금액(백만불)0.9841.000-0.2380.993-0.0040.6260.207-0.332-0.9800.979-0.148-0.638
전체산업수출증감(전년대비_퍼센트)-0.295-0.2381.000-0.2230.842-0.255-0.0720.7510.280-0.2500.6060.205
전체산업수입금액(백만불)0.9760.993-0.2231.0000.0130.5750.218-0.311-0.9720.981-0.137-0.636
전체산업수입증감(전년대비_퍼센트)-0.066-0.0040.8420.0131.000-0.2180.1160.6300.054-0.0280.6980.180
전체산업무역수지(백만불)0.6420.626-0.2550.575-0.2181.000-0.004-0.265-0.6350.582-0.141-0.514
섬유산업수출금액(백만불)0.1470.207-0.0720.2180.116-0.0041.0000.012-0.1280.1620.1340.534
섬유산업수출증감(전년대비_퍼센트)-0.409-0.3320.751-0.3110.630-0.2650.0121.0000.416-0.3640.6900.220
섬유산업수출비중(전년대비_퍼센트)-0.991-0.9800.280-0.9720.054-0.635-0.1280.4161.000-0.9790.2290.658
섬유산업수입금액(백만불)0.9880.979-0.2500.981-0.0280.5820.162-0.364-0.9791.000-0.169-0.661
섬유산업수입증감(전년대비_퍼센트)-0.207-0.1480.606-0.1370.698-0.1410.1340.6900.229-0.1691.0000.233
섬유산업무역수지(백만불)-0.656-0.6380.205-0.6360.180-0.5140.5340.2200.658-0.6610.2331.000

Missing values

2023-12-30T04:57:23.832434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-30T04:57:24.226236image/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

연도전체산업수출금액(백만불)전체산업수출증감(전년대비_퍼센트)전체산업수입금액(백만불)전체산업수입증감(전년대비_퍼센트)전체산업무역수지(백만불)섬유산업수출금액(백만불)섬유산업수출증감(전년대비_퍼센트)섬유산업수출비중(전년대비_퍼센트)섬유산업수입금액(백만불)섬유산업수입증감(전년대비_퍼센트)섬유산업무역수지(백만불)
0198017505162229210-478750991129453-84646
1198121254212613117-487862822330541205741
2198221853324251-7-23976002-52854305459
319832444512261928-1747613822557565563
4198429245203063117-138771951725673176523
51985302834311362-8537084-22371976365
6198634714153158413131881524251044457771
7198747281364102030626111834342515675010267
8198860696285181126888614171202317561212415
9198962377361465199121523782420891913148
연도전체산업수출금액(백만불)전체산업수출증감(전년대비_퍼센트)전체산업수입금액(백만불)전체산업수입증감(전년대비_퍼센트)전체산업무역수지(백만불)섬유산업수출금액(백만불)섬유산업수출증감(전년대비_퍼센트)섬유산업수출비중(전년대비_퍼센트)섬유산업수입금액(백만불)섬유산업수입증감(전년대비_퍼센트)섬유산업무역수지(백만불)
3320135596322515586-144047160722313261132811
342014572665252551524715016096031437681720
352015526757-8436499-179025814490-10314287-1203
362016495426-6406193-78923313807-53144911-684
37201757369416478478189521613742-12151755-1433
3820186048605535202126965714080321712013-3040
392019542233-10503343-63889012959-82171100-4151
402020512498-6467633-74486511238-13216203-5-4965
412021644400266150933229307128071421829913-5492
422022683585673137019-4778512301-42199019-7601