Overview

Dataset statistics

Number of variables7
Number of observations1217
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory66.7 KiB
Average record size in memory56.1 B

Variable types

Text7

Dataset

Description한국무역보험공사의 최근 5개년치(2017년 ~ 2021년)의 77개국별, 업종별 평균 연체율을 나타낸 데이터입니다.
Author한국무역보험공사
URLhttps://www.data.go.kr/data/15104444/fileData.do

Reproduction

Analysis started2024-04-21 02:53:00.550517
Analysis finished2024-04-21 02:53:01.674436
Duration1.12 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

국가
Text

Distinct77
Distinct (%)6.3%
Missing0
Missing (%)0.0%
Memory size9.6 KiB
2024-04-21T11:53:02.296265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length8
Mean length2.989318
Min length2

Characters and Unicode

Total characters3638
Distinct characters117
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique18 ?
Unique (%)1.5%

Sample

1st row중국
2nd row중국
3rd row중국
4th row중국
5th row중국
ValueCountFrequency (%)
미국 127
 
10.3%
중국 96
 
7.8%
인도 70
 
5.7%
일본 69
 
5.6%
독일 53
 
4.3%
베트남 52
 
4.2%
말레이시아 45
 
3.6%
대만 42
 
3.4%
인도네시아 40
 
3.2%
태국 36
 
2.9%
Other values (68) 605
49.0%
2024-04-21T11:53:03.440853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
국 309
 
8.5%
아 235
 
6.5%
미 149
 
4.1%
시 145
 
4.0%
인 128
 
3.5%
일 125
 
3.4%
도 118
 
3.2%
이 114
 
3.1%
리 98
 
2.7%
중 96
 
2.6%
Other values (107) 2121
58.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3620
99.5%
Space Separator 18
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
국 309
 
8.5%
아 235
 
6.5%
미 149
 
4.1%
시 145
 
4.0%
인 128
 
3.5%
일 125
 
3.5%
도 118
 
3.3%
이 114
 
3.1%
리 98
 
2.7%
중 96
 
2.7%
Other values (106) 2103
58.1%
Space Separator
ValueCountFrequency (%)
18
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3620
99.5%
Common 18
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
국 309
 
8.5%
아 235
 
6.5%
미 149
 
4.1%
시 145
 
4.0%
인 128
 
3.5%
일 125
 
3.5%
도 118
 
3.3%
이 114
 
3.1%
리 98
 
2.7%
중 96
 
2.7%
Other values (106) 2103
58.1%
Common
ValueCountFrequency (%)
18
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3620
99.5%
ASCII 18
 
0.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
국 309
 
8.5%
아 235
 
6.5%
미 149
 
4.1%
시 145
 
4.0%
인 128
 
3.5%
일 125
 
3.5%
도 118
 
3.3%
이 114
 
3.1%
리 98
 
2.7%
중 96
 
2.7%
Other values (106) 2103
58.1%
ASCII
ValueCountFrequency (%)
18
100.0%

업종명
Text

Distinct285
Distinct (%)23.4%
Missing0
Missing (%)0.0%
Memory size9.6 KiB
2024-04-21T11:53:04.551883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length24
Mean length15.715694
Min length4

Characters and Unicode

Total characters19126
Distinct characters279
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique111 ?
Unique (%)9.1%

Sample

1st row전구 램프 및 조명장치 도매업
2nd row전기용 기계 장비 및 관련 기자재 도매업
3rd row액정 표시장치 제조업
4th row이동 전화기 제조업
5th row그 외 기타 전자 부품 제조업
ValueCountFrequency (%)
제조업 689
 
11.6%
및 607
 
10.2%
기타 524
 
8.8%
도매업 380
 
6.4%
외 216
 
3.6%
그 216
 
3.6%
물질 114
 
1.9%
기계 113
 
1.9%
신품 112
 
1.9%
플라스틱 104
 
1.7%
Other values (472) 2887
48.4%
2024-04-21T11:53:06.124722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4864
25.4%
업 1267
 
6.6%
제 1007
 
5.3%
기 934
 
4.9%
조 732
 
3.8%
품 637
 
3.3%
및 607
 
3.2%
타 568
 
3.0%
매 469
 
2.5%
도 421
 
2.2%
Other values (269) 7620
39.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 14238
74.4%
Space Separator 4864
 
25.4%
Decimal Number 22
 
0.1%
Open Punctuation 1
 
< 0.1%
Close Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
업 1267
 
8.9%
제 1007
 
7.1%
기 934
 
6.6%
조 732
 
5.1%
품 637
 
4.5%
및 607
 
4.3%
타 568
 
4.0%
매 469
 
3.3%
도 421
 
3.0%
용 336
 
2.4%
Other values (265) 7260
51.0%
Space Separator
ValueCountFrequency (%)
4864
100.0%
Decimal Number
ValueCountFrequency (%)
1 22
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 14238
74.4%
Common 4888
 
25.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
업 1267
 
8.9%
제 1007
 
7.1%
기 934
 
6.6%
조 732
 
5.1%
품 637
 
4.5%
및 607
 
4.3%
타 568
 
4.0%
매 469
 
3.3%
도 421
 
3.0%
용 336
 
2.4%
Other values (265) 7260
51.0%
Common
ValueCountFrequency (%)
4864
99.5%
1 22
 
0.5%
( 1
 
< 0.1%
) 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 14238
74.4%
ASCII 4888
 
25.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4864
99.5%
1 22
 
0.5%
( 1
 
< 0.1%
) 1
 
< 0.1%
Hangul
ValueCountFrequency (%)
업 1267
 
8.9%
제 1007
 
7.1%
기 934
 
6.6%
조 732
 
5.1%
품 637
 
4.5%
및 607
 
4.3%
타 568
 
4.0%
매 469
 
3.3%
도 421
 
3.0%
용 336
 
2.4%
Other values (265) 7260
51.0%

2017
Text

Distinct335
Distinct (%)27.5%
Missing0
Missing (%)0.0%
Memory size9.6 KiB
2024-04-21T11:53:07.294793image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length4.9868529
Min length1

Characters and Unicode

Total characters6069
Distinct characters13
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique187 ?
Unique (%)15.4%

Sample

1st row0.00%
2nd row8.00%
3rd row6.80%
4th row1.00%
5th row10.30%
ValueCountFrequency (%)
0.00 436
39.6%
100.00 20
 
1.8%
33.30 11
 
1.0%
1.40 10
 
0.9%
20.00 9
 
0.8%
50.00 9
 
0.8%
10.00 8
 
0.7%
25.00 8
 
0.7%
12.50 7
 
0.6%
16.70 7
 
0.6%
Other values (324) 575
52.3%
2024-04-21T11:53:08.920147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2245
37.0%
. 1100
18.1%
% 1100
18.1%
1 272
 
4.5%
2 211
 
3.5%
3 209
 
3.4%
5 159
 
2.6%
4 154
 
2.5%
6 134
 
2.2%
7 132
 
2.2%
Other values (3) 353
 
5.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3752
61.8%
Other Punctuation 2200
36.2%
Space Separator 117
 
1.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2245
59.8%
1 272
 
7.2%
2 211
 
5.6%
3 209
 
5.6%
5 159
 
4.2%
4 154
 
4.1%
6 134
 
3.6%
7 132
 
3.5%
8 127
 
3.4%
9 109
 
2.9%
Other Punctuation
ValueCountFrequency (%)
. 1100
50.0%
% 1100
50.0%
Space Separator
ValueCountFrequency (%)
117
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 6069
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2245
37.0%
. 1100
18.1%
% 1100
18.1%
1 272
 
4.5%
2 211
 
3.5%
3 209
 
3.4%
5 159
 
2.6%
4 154
 
2.5%
6 134
 
2.2%
7 132
 
2.2%
Other values (3) 353
 
5.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6069
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2245
37.0%
. 1100
18.1%
% 1100
18.1%
1 272
 
4.5%
2 211
 
3.5%
3 209
 
3.4%
5 159
 
2.6%
4 154
 
2.5%
6 134
 
2.2%
7 132
 
2.2%
Other values (3) 353
 
5.8%

2018
Text

Distinct343
Distinct (%)28.2%
Missing0
Missing (%)0.0%
Memory size9.6 KiB
2024-04-21T11:53:10.106752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length5.0443714
Min length1

Characters and Unicode

Total characters6139
Distinct characters13
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique193 ?
Unique (%)15.9%

Sample

1st row0.00%
2nd row7.10%
3rd row8.20%
4th row3.10%
5th row7.90%
ValueCountFrequency (%)
0.00 413
37.0%
100.00 22
 
2.0%
20.00 11
 
1.0%
12.50 10
 
0.9%
25.00 9
 
0.8%
6.70 9
 
0.8%
14.30 9
 
0.8%
7.70 8
 
0.7%
66.70 8
 
0.7%
11.10 7
 
0.6%
Other values (332) 609
54.6%
2024-04-21T11:53:11.741846image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2180
35.5%
. 1115
18.2%
% 1115
18.2%
1 301
 
4.9%
2 241
 
3.9%
3 200
 
3.3%
5 190
 
3.1%
6 171
 
2.8%
4 166
 
2.7%
7 134
 
2.2%
Other values (3) 326
 
5.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3807
62.0%
Other Punctuation 2230
36.3%
Space Separator 102
 
1.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2180
57.3%
1 301
 
7.9%
2 241
 
6.3%
3 200
 
5.3%
5 190
 
5.0%
6 171
 
4.5%
4 166
 
4.4%
7 134
 
3.5%
8 120
 
3.2%
9 104
 
2.7%
Other Punctuation
ValueCountFrequency (%)
. 1115
50.0%
% 1115
50.0%
Space Separator
ValueCountFrequency (%)
102
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 6139
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2180
35.5%
. 1115
18.2%
% 1115
18.2%
1 301
 
4.9%
2 241
 
3.9%
3 200
 
3.3%
5 190
 
3.1%
6 171
 
2.8%
4 166
 
2.7%
7 134
 
2.2%
Other values (3) 326
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6139
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2180
35.5%
. 1115
18.2%
% 1115
18.2%
1 301
 
4.9%
2 241
 
3.9%
3 200
 
3.3%
5 190
 
3.1%
6 171
 
2.8%
4 166
 
2.7%
7 134
 
2.2%
Other values (3) 326
 
5.3%

2019
Text

Distinct379
Distinct (%)31.1%
Missing0
Missing (%)0.0%
Memory size9.6 KiB
2024-04-21T11:53:13.019404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length5.2037798
Min length1

Characters and Unicode

Total characters6333
Distinct characters13
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique213 ?
Unique (%)17.5%

Sample

1st row9.90%
2nd row7.70%
3rd row14.50%
4th row0.00%
5th row14.20%
ValueCountFrequency (%)
0.00 401
34.9%
100.00 16
 
1.4%
50.00 16
 
1.4%
25.00 11
 
1.0%
14.30 10
 
0.9%
33.30 10
 
0.9%
7.70 10
 
0.9%
12.50 7
 
0.6%
1.00 7
 
0.6%
22.20 7
 
0.6%
Other values (368) 653
56.9%
2024-04-21T11:53:14.722526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2210
34.9%
. 1148
18.1%
% 1148
18.1%
1 333
 
5.3%
2 258
 
4.1%
3 231
 
3.6%
5 201
 
3.2%
4 164
 
2.6%
7 164
 
2.6%
6 157
 
2.5%
Other values (3) 319
 
5.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3968
62.7%
Other Punctuation 2296
36.3%
Space Separator 69
 
1.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2210
55.7%
1 333
 
8.4%
2 258
 
6.5%
3 231
 
5.8%
5 201
 
5.1%
4 164
 
4.1%
7 164
 
4.1%
6 157
 
4.0%
8 143
 
3.6%
9 107
 
2.7%
Other Punctuation
ValueCountFrequency (%)
. 1148
50.0%
% 1148
50.0%
Space Separator
ValueCountFrequency (%)
69
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 6333
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2210
34.9%
. 1148
18.1%
% 1148
18.1%
1 333
 
5.3%
2 258
 
4.1%
3 231
 
3.6%
5 201
 
3.2%
4 164
 
2.6%
7 164
 
2.6%
6 157
 
2.5%
Other values (3) 319
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6333
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2210
34.9%
. 1148
18.1%
% 1148
18.1%
1 333
 
5.3%
2 258
 
4.1%
3 231
 
3.6%
5 201
 
3.2%
4 164
 
2.6%
7 164
 
2.6%
6 157
 
2.5%
Other values (3) 319
 
5.0%

2020
Text

Distinct388
Distinct (%)31.9%
Missing0
Missing (%)0.0%
Memory size9.6 KiB
2024-04-21T11:53:16.106122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length5.2760887
Min length1

Characters and Unicode

Total characters6421
Distinct characters13
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique205 ?
Unique (%)16.8%

Sample

1st row14.50%
2nd row10.50%
3rd row14.00%
4th row0.00%
5th row15.50%
ValueCountFrequency (%)
0.00 391
33.4%
25.00 12
 
1.0%
20.00 11
 
0.9%
100.00 11
 
0.9%
2.00 9
 
0.8%
14.30 8
 
0.7%
33.30 8
 
0.7%
6.30 8
 
0.7%
1.90 7
 
0.6%
4.50 6
 
0.5%
Other values (377) 698
59.7%
2024-04-21T11:53:17.909066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2193
34.2%
. 1169
18.2%
% 1169
18.2%
1 321
 
5.0%
2 264
 
4.1%
3 229
 
3.6%
5 219
 
3.4%
4 201
 
3.1%
6 196
 
3.1%
8 154
 
2.4%
Other values (3) 306
 
4.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4035
62.8%
Other Punctuation 2338
36.4%
Space Separator 48
 
0.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2193
54.3%
1 321
 
8.0%
2 264
 
6.5%
3 229
 
5.7%
5 219
 
5.4%
4 201
 
5.0%
6 196
 
4.9%
8 154
 
3.8%
7 150
 
3.7%
9 108
 
2.7%
Other Punctuation
ValueCountFrequency (%)
. 1169
50.0%
% 1169
50.0%
Space Separator
ValueCountFrequency (%)
48
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 6421
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2193
34.2%
. 1169
18.2%
% 1169
18.2%
1 321
 
5.0%
2 264
 
4.1%
3 229
 
3.6%
5 219
 
3.4%
4 201
 
3.1%
6 196
 
3.1%
8 154
 
2.4%
Other values (3) 306
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6421
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2193
34.2%
. 1169
18.2%
% 1169
18.2%
1 321
 
5.0%
2 264
 
4.1%
3 229
 
3.6%
5 219
 
3.4%
4 201
 
3.1%
6 196
 
3.1%
8 154
 
2.4%
Other values (3) 306
 
4.8%

2021
Text

Distinct421
Distinct (%)34.6%
Missing0
Missing (%)0.0%
Memory size9.6 KiB
2024-04-21T11:53:19.306887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length5.3878389
Min length1

Characters and Unicode

Total characters6557
Distinct characters13
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique224 ?
Unique (%)18.4%

Sample

1st row78.30%
2nd row15.10%
3rd row14.50%
4th row0.00%
5th row11.50%
ValueCountFrequency (%)
0.00 347
28.9%
3.80 12
 
1.0%
50.00 11
 
0.9%
25.00 9
 
0.8%
2.50 8
 
0.7%
0.80 7
 
0.6%
16.70 7
 
0.6%
6.10 7
 
0.6%
3.70 7
 
0.6%
9.40 7
 
0.6%
Other values (410) 778
64.8%
2024-04-21T11:53:20.819201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2140
32.6%
. 1200
18.3%
% 1200
18.3%
1 353
 
5.4%
2 268
 
4.1%
3 257
 
3.9%
4 236
 
3.6%
5 214
 
3.3%
7 181
 
2.8%
6 178
 
2.7%
Other values (3) 330
 
5.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4140
63.1%
Other Punctuation 2400
36.6%
Space Separator 17
 
0.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2140
51.7%
1 353
 
8.5%
2 268
 
6.5%
3 257
 
6.2%
4 236
 
5.7%
5 214
 
5.2%
7 181
 
4.4%
6 178
 
4.3%
8 175
 
4.2%
9 138
 
3.3%
Other Punctuation
ValueCountFrequency (%)
. 1200
50.0%
% 1200
50.0%
Space Separator
ValueCountFrequency (%)
17
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 6557
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2140
32.6%
. 1200
18.3%
% 1200
18.3%
1 353
 
5.4%
2 268
 
4.1%
3 257
 
3.9%
4 236
 
3.6%
5 214
 
3.3%
7 181
 
2.8%
6 178
 
2.7%
Other values (3) 330
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6557
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2140
32.6%
. 1200
18.3%
% 1200
18.3%
1 353
 
5.4%
2 268
 
4.1%
3 257
 
3.9%
4 236
 
3.6%
5 214
 
3.3%
7 181
 
2.8%
6 178
 
2.7%
Other values (3) 330
 
5.0%

Missing values

2024-04-21T11:53:01.141935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-21T11:53:01.527500image/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

국가업종명20172018201920202021
0중국전구 램프 및 조명장치 도매업0.00%0.00%9.90%14.50%78.30%
1중국전기용 기계 장비 및 관련 기자재 도매업8.00%7.10%7.70%10.50%15.10%
2중국액정 표시장치 제조업6.80%8.20%14.50%14.00%14.50%
3중국이동 전화기 제조업1.00%3.10%0.00%0.00%0.00%
4중국그 외 기타 전자 부품 제조업10.30%7.90%14.20%15.50%11.50%
5중국비메모리용 및 기타 전자집적회로 제조업2.60%1.30%3.00%2.40%2.50%
6중국기타 자동차 신품 부품 및 내장품 판매업28.70%24.60%11.60%11.70%1.30%
7중국접착제 및 젤라틴 제조업6.50%9.70%10.30%7.40%1.10%
8중국메모리용 전자집적회로 제조업7.10%3.30%10.80%18.50%20.10%
9중국항공 여객 운송업0.00%0.00%0.00%0.00%0.00%
국가업종명20172018201920202021
1207온두라스기타 자동차 신품 부품 및 내장품 판매업57.10%28.60%0.00%12.50%24.00%
1208튀니지기타 화학 물질 및 화학제품 도매업33.30%20.00%33.30%14.30%6.30%
1209튀니지의료 기기 도매업82.00%51.50%35.80%20.30%38.10%
1210모로코매트리스 및 침대 제조업26.40%34.70%22.40%42.30%9.30%
1211레바논기타 자동차 신품 부품 및 내장품 판매업25.00%12.50%100.00%2.60%0.00%
1212세르비아기타 자동차 신품 부품 및 내장품 판매업0.00%100.00%0.00%0.00%
1213자메이카자동차 신품 타이어 및 튜브 판매업2.70%0.00%0.00%0.00%
1214니카라과기타 자동차 신품 부품 및 내장품 판매업20.60%25.90%42.90%45.70%52.40%
1215탄자니아매트리스 및 침대 제조업0.00%3.00%0.00%0.00%0.00%
1216나이지리아전지 및 케이블 도매업0.00%10.80%56.40%