Overview

Dataset statistics

Number of variables19
Number of observations1935
Missing cells5327
Missing cells (%)14.5%
Duplicate rows55
Duplicate rows (%)2.8%
Total size in memory293.0 KiB
Average record size in memory155.1 B

Variable types

Numeric3
Text11
Categorical5

Dataset

Description우리나라와 FTA를 체결한 국가와의 협정세율 자료 제공 목록: HSK, 한글 품명, 영문 품명, 국가별 협정세율 대상 국가: 칠레, 싱가포르, EFTA, 아세안, 인도, EU, 페루, 미국, 터키, 콜롬비아, 캐나다, 호주, 베트남, 중국, 뉴질랜드, 중미, 영국, 인도네시아, 이스라엘, RCEP 등
Author농림축산식품부
URLhttps://data.mafra.go.kr/opendata/data/indexOpenDataDetail.do?data_id=20141031000000000350

Alerts

Dataset has 55 (2.8%) duplicate rowsDuplicates
노르웨이 is highly overall correlated with 아이슬란드 and 2 other fieldsHigh correlation
아이슬란드 is highly overall correlated with 노르웨이 and 4 other fieldsHigh correlation
칠레 is highly overall correlated with 스위스High correlation
싱가포르 is highly overall correlated with 노르웨이 and 4 other fieldsHigh correlation
스위스 is highly overall correlated with 노르웨이 and 5 other fieldsHigh correlation
인도 is highly overall correlated with 아이슬란드 and 2 other fieldsHigh correlation
개방구분 is highly overall correlated with 아이슬란드 and 2 other fieldsHigh correlation
칠레 is highly imbalanced (70.7%)Imbalance
싱가포르 is highly imbalanced (56.9%)Imbalance
스위스 is highly imbalanced (67.6%)Imbalance
개방구분 is highly imbalanced (66.5%)Imbalance
일련 번호 has 313 (16.2%) missing valuesMissing
H S K has 313 (16.2%) missing valuesMissing
한 글 품 명 has 208 (10.7%) missing valuesMissing
영 문 품 명 has 307 (15.9%) missing valuesMissing
2014실행세율 has 241 (12.5%) missing valuesMissing
노르웨이 has 1217 (62.9%) missing valuesMissing
아이슬란드 has 1021 (52.8%) missing valuesMissing
아세안 has 284 (14.7%) missing valuesMissing
EU(2013.7~2014.6) has 208 (10.7%) missing valuesMissing
EU(2014.7~2015.6) has 204 (10.5%) missing valuesMissing
페루 has 251 (13.0%) missing valuesMissing
미국 has 174 (9.0%) missing valuesMissing
터키 has 293 (15.1%) missing valuesMissing
콜롬비아 has 293 (15.1%) missing valuesMissing
노르웨이 has 270 (14.0%) zerosZeros
아이슬란드 has 307 (15.9%) zerosZeros

Reproduction

Analysis started2023-12-11 03:08:08.183606
Analysis finished2023-12-11 03:08:12.238547
Duration4.05 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

일련 번호
Real number (ℝ)

MISSING 

Distinct1622
Distinct (%)100.0%
Missing313
Missing (%)16.2%
Infinite0
Infinite (%)0.0%
Mean811.5
Minimum1
Maximum1622
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size17.1 KiB
2023-12-11T12:08:12.322222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile82.05
Q1406.25
median811.5
Q31216.75
95-th percentile1540.95
Maximum1622
Range1621
Interquartile range (IQR)810.5

Descriptive statistics

Standard deviation468.37538
Coefficient of variation (CV)0.57717238
Kurtosis-1.2
Mean811.5
Median Absolute Deviation (MAD)405.5
Skewness0
Sum1316253
Variance219375.5
MonotonicityStrictly increasing
2023-12-11T12:08:12.518182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1080 1
 
0.1%
1090 1
 
0.1%
1089 1
 
0.1%
1088 1
 
0.1%
1087 1
 
0.1%
1086 1
 
0.1%
1085 1
 
0.1%
1084 1
 
0.1%
1083 1
 
0.1%
1082 1
 
0.1%
Other values (1612) 1612
83.3%
(Missing) 313
 
16.2%
ValueCountFrequency (%)
1 1
0.1%
2 1
0.1%
3 1
0.1%
4 1
0.1%
5 1
0.1%
6 1
0.1%
7 1
0.1%
8 1
0.1%
9 1
0.1%
10 1
0.1%
ValueCountFrequency (%)
1622 1
0.1%
1621 1
0.1%
1620 1
0.1%
1619 1
0.1%
1618 1
0.1%
1617 1
0.1%
1616 1
0.1%
1615 1
0.1%
1614 1
0.1%
1613 1
0.1%

H S K
Text

MISSING 

Distinct1622
Distinct (%)100.0%
Missing313
Missing (%)16.2%
Memory size15.2 KiB
2023-12-11T12:08:12.824652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters19464
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1622 ?
Unique (%)100.0%

Sample

1st row0101.21.1000
2nd row0101.21.9000
3rd row0101.29.1000
4th row0101.29.9000
5th row0101.30.1000
ValueCountFrequency (%)
0102.29.9000 1
 
0.1%
1803.20.0000 1
 
0.1%
1703.10.9000 1
 
0.1%
1801.00.1000 1
 
0.1%
1704.90.9000 1
 
0.1%
1704.90.2090 1
 
0.1%
1704.90.2020 1
 
0.1%
1704.90.2010 1
 
0.1%
1704.90.1000 1
 
0.1%
1704.10.0000 1
 
0.1%
Other values (1612) 1612
99.4%
2023-12-11T12:08:13.306234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 8069
41.5%
. 3244
16.7%
1 2518
 
12.9%
2 1623
 
8.3%
9 1508
 
7.7%
3 624
 
3.2%
4 485
 
2.5%
5 466
 
2.4%
6 342
 
1.8%
7 330
 
1.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 16220
83.3%
Other Punctuation 3244
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 8069
49.7%
1 2518
 
15.5%
2 1623
 
10.0%
9 1508
 
9.3%
3 624
 
3.8%
4 485
 
3.0%
5 466
 
2.9%
6 342
 
2.1%
7 330
 
2.0%
8 255
 
1.6%
Other Punctuation
ValueCountFrequency (%)
. 3244
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 19464
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 8069
41.5%
. 3244
16.7%
1 2518
 
12.9%
2 1623
 
8.3%
9 1508
 
7.7%
3 624
 
3.2%
4 485
 
2.5%
5 466
 
2.4%
6 342
 
1.8%
7 330
 
1.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 19464
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 8069
41.5%
. 3244
16.7%
1 2518
 
12.9%
2 1623
 
8.3%
9 1508
 
7.7%
3 624
 
3.2%
4 485
 
2.5%
5 466
 
2.4%
6 342
 
1.8%
7 330
 
1.7%

한 글 품 명
Text

MISSING 

Distinct1640
Distinct (%)95.0%
Missing208
Missing (%)10.7%
Memory size15.2 KiB
2023-12-11T12:08:13.672417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length56
Median length48
Mean length12.702374
Min length1

Characters and Unicode

Total characters21937
Distinct characters608
Distinct categories10 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1606 ?
Unique (%)93.0%

Sample

1st row말(번식용/농가사육용)
2nd row말(번식용/기타)
3rd row말(기타/경주말)
4th row말(기타/기타)
5th row당나귀(번식용)
ValueCountFrequency (%)
것 242
 
5.9%
기타 140
 
3.4%
or 121
 
2.9%
및 75
 
1.8%
그 35
 
0.8%
종자 29
 
0.7%
안한 26
 
0.6%
이하 26
 
0.6%
분획물 25
 
0.6%
25
 
0.6%
Other values (2184) 3384
82.0%
2023-12-11T12:08:14.206187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2432
 
11.1%
( 1191
 
5.4%
) 1189
 
5.4%
기 728
 
3.3%
타 644
 
2.9%
/ 495
 
2.3%
의 345
 
1.6%
리 318
 
1.4%
조 315
 
1.4%
스 309
 
1.4%
Other values (598) 13971
63.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 15536
70.8%
Space Separator 2432
 
11.1%
Open Punctuation 1191
 
5.4%
Close Punctuation 1189
 
5.4%
Other Punctuation 806
 
3.7%
Decimal Number 382
 
1.7%
Lowercase Letter 311
 
1.4%
Dash Punctuation 87
 
0.4%
Math Symbol 2
 
< 0.1%
Uppercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 728
 
4.7%
타 644
 
4.1%
의 345
 
2.2%
리 318
 
2.0%
조 315
 
2.0%
스 309
 
2.0%
유 297
 
1.9%
것 296
 
1.9%
이 294
 
1.9%
제 259
 
1.7%
Other values (562) 11731
75.5%
Lowercase Letter
ValueCountFrequency (%)
o 123
39.5%
r 123
39.5%
g 27
 
8.7%
k 16
 
5.1%
m 16
 
5.1%
t 1
 
0.3%
i 1
 
0.3%
v 1
 
0.3%
a 1
 
0.3%
u 1
 
0.3%
Decimal Number
ValueCountFrequency (%)
0 120
31.4%
1 71
18.6%
2 45
 
11.8%
5 40
 
10.5%
4 25
 
6.5%
6 22
 
5.8%
8 20
 
5.2%
3 17
 
4.5%
9 17
 
4.5%
7 5
 
1.3%
Other Punctuation
ValueCountFrequency (%)
/ 495
61.4%
, 150
 
18.6%
? 74
 
9.2%
% 31
 
3.8%
· 27
 
3.3%
. 26
 
3.2%
" 2
 
0.2%
: 1
 
0.1%
Math Symbol
ValueCountFrequency (%)
> 1
50.0%
< 1
50.0%
Space Separator
ValueCountFrequency (%)
2432
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1191
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1189
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 87
100.0%
Uppercase Letter
ValueCountFrequency (%)
A 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 15526
70.8%
Common 6089
 
27.8%
Latin 312
 
1.4%
Han 10
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 728
 
4.7%
타 644
 
4.1%
의 345
 
2.2%
리 318
 
2.0%
조 315
 
2.0%
스 309
 
2.0%
유 297
 
1.9%
것 296
 
1.9%
이 294
 
1.9%
제 259
 
1.7%
Other values (552) 11721
75.5%
Common
ValueCountFrequency (%)
2432
39.9%
( 1191
19.6%
) 1189
19.5%
/ 495
 
8.1%
, 150
 
2.5%
0 120
 
2.0%
- 87
 
1.4%
? 74
 
1.2%
1 71
 
1.2%
2 45
 
0.7%
Other values (14) 235
 
3.9%
Latin
ValueCountFrequency (%)
o 123
39.4%
r 123
39.4%
g 27
 
8.7%
k 16
 
5.1%
m 16
 
5.1%
t 1
 
0.3%
i 1
 
0.3%
v 1
 
0.3%
a 1
 
0.3%
u 1
 
0.3%
Other values (2) 2
 
0.6%
Han
ValueCountFrequency (%)
川 1
10.0%
芎 1
10.0%
黃 1
10.0%
歸 1
10.0%
芍 1
10.0%
藥 1
10.0%
五 1
10.0%
味 1
10.0%
子 1
10.0%
當 1
10.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 15526
70.8%
ASCII 6374
29.1%
None 27
 
0.1%
CJK 10
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2432
38.2%
( 1191
18.7%
) 1189
18.7%
/ 495
 
7.8%
, 150
 
2.4%
o 123
 
1.9%
r 123
 
1.9%
0 120
 
1.9%
- 87
 
1.4%
? 74
 
1.2%
Other values (25) 390
 
6.1%
Hangul
ValueCountFrequency (%)
기 728
 
4.7%
타 644
 
4.1%
의 345
 
2.2%
리 318
 
2.0%
조 315
 
2.0%
스 309
 
2.0%
유 297
 
1.9%
것 296
 
1.9%
이 294
 
1.9%
제 259
 
1.7%
Other values (552) 11721
75.5%
None
ValueCountFrequency (%)
· 27
100.0%
CJK
ValueCountFrequency (%)
川 1
10.0%
芎 1
10.0%
黃 1
10.0%
歸 1
10.0%
芍 1
10.0%
藥 1
10.0%
五 1
10.0%
味 1
10.0%
子 1
10.0%
當 1
10.0%

영 문 품 명
Text

MISSING 

Distinct1586
Distinct (%)97.4%
Missing307
Missing (%)15.9%
Memory size15.2 KiB
2023-12-11T12:08:14.659702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length150
Median length85
Mean length31.651106
Min length3

Characters and Unicode

Total characters51528
Distinct characters76
Distinct categories9 ?
Distinct scripts2 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1570 ?
Unique (%)96.4%

Sample

1st rowHorses: Pure-bred breeding anmials(For farm breeding)
2nd rowHorses: Pure-bred breeding anmials(Other)
3rd rowHorses: Other(Horses for racing)
4th rowHorses: Other(Other)
5th rowAsses: Pure-bred breeding animals
ValueCountFrequency (%)
or 364
 
5.4%
of 342
 
5.1%
other 320
 
4.7%
and 243
 
3.6%
meat 118
 
1.7%
chilled 81
 
1.2%
preserved 76
 
1.1%
the 62
 
0.9%
prepared 58
 
0.9%
offal 57
 
0.8%
Other values (1875) 5032
74.5%
2023-12-11T12:08:15.305577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 5696
 
11.1%
5129
 
10.0%
r 3914
 
7.6%
o 3185
 
6.2%
a 3120
 
6.1%
s 2955
 
5.7%
t 2918
 
5.7%
i 2576
 
5.0%
n 2386
 
4.6%
d 1850
 
3.6%
Other values (66) 17799
34.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 40659
78.9%
Space Separator 5129
 
10.0%
Uppercase Letter 2522
 
4.9%
Open Punctuation 1073
 
2.1%
Close Punctuation 1073
 
2.1%
Other Punctuation 725
 
1.4%
Decimal Number 241
 
0.5%
Dash Punctuation 101
 
0.2%
Other Symbol 5
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
e 5696
14.0%
r 3914
 
9.6%
o 3185
 
7.8%
a 3120
 
7.7%
s 2955
 
7.3%
t 2918
 
7.2%
i 2576
 
6.3%
n 2386
 
5.9%
d 1850
 
4.6%
l 1766
 
4.3%
Other values (17) 10293
25.3%
Uppercase Letter
ValueCountFrequency (%)
O 709
28.1%
C 239
 
9.5%
S 211
 
8.4%
M 170
 
6.7%
P 169
 
6.7%
F 128
 
5.1%
B 121
 
4.8%
G 106
 
4.2%
R 104
 
4.1%
L 85
 
3.4%
Other values (16) 480
19.0%
Decimal Number
ValueCountFrequency (%)
0 72
29.9%
5 40
16.6%
1 39
16.2%
2 26
 
10.8%
4 18
 
7.5%
9 14
 
5.8%
8 13
 
5.4%
3 10
 
4.1%
6 6
 
2.5%
7 3
 
1.2%
Other Punctuation
ValueCountFrequency (%)
/ 326
45.0%
, 222
30.6%
. 77
 
10.6%
: 40
 
5.5%
% 37
 
5.1%
' 16
 
2.2%
; 7
 
1.0%
Other Symbol
ValueCountFrequency (%)
° 4
80.0%
ⓚ 1
 
20.0%
Space Separator
ValueCountFrequency (%)
5129
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1073
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1073
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 101
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 43177
83.8%
Common 8351
 
16.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 5696
13.2%
r 3914
 
9.1%
o 3185
 
7.4%
a 3120
 
7.2%
s 2955
 
6.8%
t 2918
 
6.8%
i 2576
 
6.0%
n 2386
 
5.5%
d 1850
 
4.3%
l 1766
 
4.1%
Other values (42) 12811
29.7%
Common
ValueCountFrequency (%)
5129
61.4%
( 1073
 
12.8%
) 1073
 
12.8%
/ 326
 
3.9%
, 222
 
2.7%
- 101
 
1.2%
. 77
 
0.9%
0 72
 
0.9%
: 40
 
0.5%
5 40
 
0.5%
Other values (14) 198
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 51519
> 99.9%
None 4
 
< 0.1%
Letterlike Symbols 4
 
< 0.1%
Enclosed Alphanum 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 5696
 
11.1%
5129
 
10.0%
r 3914
 
7.6%
o 3185
 
6.2%
a 3120
 
6.1%
s 2955
 
5.7%
t 2918
 
5.7%
i 2576
 
5.0%
n 2386
 
4.6%
d 1850
 
3.6%
Other values (63) 17790
34.5%
None
ValueCountFrequency (%)
° 4
100.0%
Letterlike Symbols
ValueCountFrequency (%)
ℓ 4
100.0%
Enclosed Alphanum
ValueCountFrequency (%)
ⓚ 1
100.0%

2014실행세율
Text

MISSING 

Distinct150
Distinct (%)8.9%
Missing241
Missing (%)12.5%
Memory size15.2 KiB
2023-12-11T12:08:15.559778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length14
Mean length4.3996458
Min length2

Characters and Unicode

Total characters7453
Distinct characters35
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique58 ?
Unique (%)3.4%

Sample

1st row기본0
2nd row기본8
3rd row기본8
4th row기본8
5th row기본8
ValueCountFrequency (%)
기본8 413
24.3%
기본30 142
 
8.4%
기본3 100
 
5.9%
기본5 99
 
5.8%
기본27 97
 
5.7%
기본0 87
 
5.1%
기본20 59
 
3.5%
기본45 58
 
3.4%
기본18 54
 
3.2%
할당0,12월말 39
 
2.3%
Other values (130) 552
32.5%
2023-12-11T12:08:15.932979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
기 1309
17.6%
본 1309
17.6%
0 624
8.4%
8 589
 
7.9%
2 508
 
6.8%
5 445
 
6.0%
3 397
 
5.3%
/ 278
 
3.7%
허 256
 
3.4%
양 256
 
3.4%
Other values (25) 1482
19.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3433
46.1%
Decimal Number 3312
44.4%
Other Punctuation 520
 
7.0%
Dash Punctuation 61
 
0.8%
Close Punctuation 52
 
0.7%
Open Punctuation 52
 
0.7%
Lowercase Letter 14
 
0.2%
Space Separator 9
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 1309
38.1%
본 1309
38.1%
허 256
 
7.5%
양 256
 
7.5%
말 52
 
1.5%
월 52
 
1.5%
당 52
 
1.5%
할 52
 
1.5%
국 34
 
1.0%
제 34
 
1.0%
Other values (3) 27
 
0.8%
Decimal Number
ValueCountFrequency (%)
0 624
18.8%
8 589
17.8%
2 508
15.3%
5 445
13.4%
3 397
12.0%
4 219
 
6.6%
1 198
 
6.0%
7 179
 
5.4%
6 95
 
2.9%
9 58
 
1.8%
Other Punctuation
ValueCountFrequency (%)
/ 278
53.5%
. 181
34.8%
, 58
 
11.2%
% 3
 
0.6%
Lowercase Letter
ValueCountFrequency (%)
k 5
35.7%
g 5
35.7%
o 2
 
14.3%
r 2
 
14.3%
Dash Punctuation
ValueCountFrequency (%)
- 61
100.0%
Close Punctuation
ValueCountFrequency (%)
) 52
100.0%
Open Punctuation
ValueCountFrequency (%)
( 52
100.0%
Space Separator
ValueCountFrequency (%)
9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4006
53.8%
Hangul 3433
46.1%
Latin 14
 
0.2%

Most frequent character per script

Common
ValueCountFrequency (%)
0 624
15.6%
8 589
14.7%
2 508
12.7%
5 445
11.1%
3 397
9.9%
/ 278
6.9%
4 219
 
5.5%
1 198
 
4.9%
. 181
 
4.5%
7 179
 
4.5%
Other values (8) 388
9.7%
Hangul
ValueCountFrequency (%)
기 1309
38.1%
본 1309
38.1%
허 256
 
7.5%
양 256
 
7.5%
말 52
 
1.5%
월 52
 
1.5%
당 52
 
1.5%
할 52
 
1.5%
국 34
 
1.0%
제 34
 
1.0%
Other values (3) 27
 
0.8%
Latin
ValueCountFrequency (%)
k 5
35.7%
g 5
35.7%
o 2
 
14.3%
r 2
 
14.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4020
53.9%
Hangul 3433
46.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
기 1309
38.1%
본 1309
38.1%
허 256
 
7.5%
양 256
 
7.5%
말 52
 
1.5%
월 52
 
1.5%
당 52
 
1.5%
할 52
 
1.5%
국 34
 
1.0%
제 34
 
1.0%
Other values (3) 27
 
0.8%
ASCII
ValueCountFrequency (%)
0 624
15.5%
8 589
14.7%
2 508
12.6%
5 445
11.1%
3 397
9.9%
/ 278
6.9%
4 219
 
5.4%
1 198
 
4.9%
. 181
 
4.5%
7 179
 
4.5%
Other values (12) 402
10.0%

칠레
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct21
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size15.2 KiB
0
1099 
<NA>
770 
0/20
 
10
0/30
 
9
(2,000톤)
 
9
Other values (16)
 
38

Length

Max length11
Median length1
Mean length2.3405685
Min length1

Unique

Unique6 ?
Unique (%)0.3%

Sample

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

Common Values

ValueCountFrequency (%)
0 1099
56.8%
<NA> 770
39.8%
0/20 10
 
0.5%
0/30 9
 
0.5%
(2,000톤) 9
 
0.5%
(1,000톤) 8
 
0.4%
(100톤) 5
 
0.3%
30 4
 
0.2%
21.8 3
 
0.2%
0/30 (200톤) 2
 
0.1%
Other values (11) 16
 
0.8%

Length

2023-12-11T12:08:16.071836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0 1099
56.7%
na 770
39.8%
0/30 11
 
0.6%
0/20 10
 
0.5%
2,000톤 9
 
0.5%
1,000톤 8
 
0.4%
100톤 5
 
0.3%
30 4
 
0.2%
200톤 4
 
0.2%
21.8 3
 
0.2%
Other values (10) 14
 
0.7%

싱가포르
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct47
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size15.2 KiB
<NA>
885 
0
632 
5.5
 
63
4.9
 
60
1.5
 
55
Other values (42)
240 

Length

Max length16
Median length15
Mean length2.8578811
Min length1

Unique

Unique21 ?
Unique (%)1.1%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 885
45.7%
0 632
32.7%
5.5 63
 
3.3%
4.9 60
 
3.1%
1.5 55
 
2.8%
3.6 50
 
2.6%
8.2 33
 
1.7%
3.3 26
 
1.3%
4.1 19
 
1.0%
2.7 14
 
0.7%
Other values (37) 98
 
5.1%

Length

2023-12-11T12:08:16.558735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 885
45.4%
0 632
32.4%
5.5 69
 
3.5%
4.9 60
 
3.1%
1.5 55
 
2.8%
3.6 50
 
2.6%
8.2 33
 
1.7%
3.3 26
 
1.3%
4.1 19
 
1.0%
2.7 14
 
0.7%
Other values (36) 105
 
5.4%

스위스
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct41
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Memory size15.2 KiB
<NA>
1416 
0
196 
6.4
 
101
4.8
 
44
4
 
31
Other values (36)
147 

Length

Max length19
Median length4
Mean length3.5436693
Min length1

Unique

Unique12 ?
Unique (%)0.6%

Sample

1st row6.4
2nd row6.4
3rd row0
4th row4
5th row6.4

Common Values

ValueCountFrequency (%)
<NA> 1416
73.2%
0 196
 
10.1%
6.4 101
 
5.2%
4.8 44
 
2.3%
4 31
 
1.6%
27 16
 
0.8%
2.7 14
 
0.7%
18 14
 
0.7%
24 13
 
0.7%
1.4 9
 
0.5%
Other values (31) 81
 
4.2%

Length

2023-12-11T12:08:16.709894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 1416
72.6%
0 196
 
10.1%
6.4 101
 
5.2%
4.8 44
 
2.3%
4 31
 
1.6%
27 16
 
0.8%
2.7 14
 
0.7%
18 14
 
0.7%
24 13
 
0.7%
1.4 9
 
0.5%
Other values (35) 96
 
4.9%

노르웨이
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct32
Distinct (%)4.5%
Missing1217
Missing (%)62.9%
Infinite0
Infinite (%)0.0%
Mean4.9516713
Minimum0
Maximum36
Zeros270
Zeros (%)14.0%
Negative0
Negative (%)0.0%
Memory size17.1 KiB
2023-12-11T12:08:16.874245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median4.8
Q36.4
95-th percentile18
Maximum36
Range36
Interquartile range (IQR)6.4

Descriptive statistics

Standard deviation6.1222475
Coefficient of variation (CV)1.2364002
Kurtosis6.9017639
Mean4.9516713
Median Absolute Deviation (MAD)2.4
Skewness2.3320559
Sum3555.3
Variance37.481915
MonotonicityNot monotonic
2023-12-11T12:08:17.031192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
0.0 270
 
14.0%
6.4 236
 
12.2%
4.8 44
 
2.3%
4.0 31
 
1.6%
7.2 21
 
1.1%
18.0 11
 
0.6%
1.4 9
 
0.5%
11.3 8
 
0.4%
3.6 7
 
0.4%
27.0 7
 
0.4%
Other values (22) 74
 
3.8%
(Missing) 1217
62.9%
ValueCountFrequency (%)
0.0 270
14.0%
1.4 9
 
0.5%
2.4 6
 
0.3%
2.7 4
 
0.2%
3.6 7
 
0.4%
3.8 1
 
0.1%
4.0 31
 
1.6%
4.3 5
 
0.3%
4.5 1
 
0.1%
4.8 44
 
2.3%
ValueCountFrequency (%)
36.0 4
 
0.2%
32.0 1
 
0.1%
28.8 6
0.3%
27.0 7
0.4%
24.0 7
0.4%
21.6 5
0.3%
20.3 2
 
0.1%
18.0 11
0.6%
16.2 2
 
0.1%
15.8 5
0.3%

아이슬란드
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct35
Distinct (%)3.8%
Missing1021
Missing (%)52.8%
Infinite0
Infinite (%)0.0%
Mean6.7502188
Minimum0
Maximum36
Zeros307
Zeros (%)15.9%
Negative0
Negative (%)0.0%
Memory size17.1 KiB
2023-12-11T12:08:17.169370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median6.4
Q36.4
95-th percentile24.3
Maximum36
Range36
Interquartile range (IQR)6.4

Descriptive statistics

Standard deviation7.7260959
Coefficient of variation (CV)1.1445697
Kurtosis1.1216773
Mean6.7502188
Median Absolute Deviation (MAD)6.4
Skewness1.3907619
Sum6169.7
Variance59.692557
MonotonicityNot monotonic
2023-12-11T12:08:17.318923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
0.0 307
 
15.9%
6.4 279
 
14.4%
24.3 53
 
2.7%
4.8 44
 
2.3%
4.0 35
 
1.8%
18.0 33
 
1.7%
16.2 24
 
1.2%
7.2 22
 
1.1%
22.5 9
 
0.5%
1.4 9
 
0.5%
Other values (25) 99
 
5.1%
(Missing) 1021
52.8%
ValueCountFrequency (%)
0.0 307
15.9%
1.4 9
 
0.5%
2.4 6
 
0.3%
2.7 4
 
0.2%
3.6 7
 
0.4%
3.8 1
 
0.1%
4.0 35
 
1.8%
4.3 5
 
0.3%
4.5 1
 
0.1%
4.8 44
 
2.3%
ValueCountFrequency (%)
36.0 3
 
0.2%
32.0 1
 
0.1%
28.8 6
 
0.3%
27.0 7
 
0.4%
24.3 53
2.7%
24.0 7
 
0.4%
23.0 1
 
0.1%
22.5 9
 
0.5%
21.6 5
 
0.3%
20.3 5
 
0.3%

아세안
Text

MISSING 

Distinct100
Distinct (%)6.1%
Missing284
Missing (%)14.7%
Memory size15.2 KiB
2023-12-11T12:08:17.600884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length1
Mean length1.9370079
Min length1

Characters and Unicode

Total characters3198
Distinct characters42
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique41 ?
Unique (%)2.5%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
0 1064
62.8%
20 122
 
7.2%
미양허 64
 
3.8%
8 38
 
2.2%
30 32
 
1.9%
18 27
 
1.6%
45 24
 
1.4%
or 24
 
1.4%
36 22
 
1.3%
754.3 16
 
0.9%
Other values (87) 262
 
15.5%
2023-12-11T12:08:18.023541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1367
42.7%
2 221
 
6.9%
3 143
 
4.5%
8 134
 
4.2%
5 132
 
4.1%
4 96
 
3.0%
. 95
 
3.0%
7 76
 
2.4%
6 74
 
2.3%
1 70
 
2.2%
Other values (32) 790
24.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2349
73.5%
Other Letter 284
 
8.9%
Other Punctuation 208
 
6.5%
Uppercase Letter 128
 
4.0%
Lowercase Letter 96
 
3.0%
Space Separator 59
 
1.8%
Open Punctuation 37
 
1.2%
Close Punctuation 37
 
1.2%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
H 29
22.7%
P 17
13.3%
V 13
10.2%
N 13
10.2%
M 13
10.2%
T 12
9.4%
Y 11
 
8.6%
L 6
 
4.7%
A 6
 
4.7%
I 4
 
3.1%
Decimal Number
ValueCountFrequency (%)
0 1367
58.2%
2 221
 
9.4%
3 143
 
6.1%
8 134
 
5.7%
5 132
 
5.6%
4 96
 
4.1%
7 76
 
3.2%
6 74
 
3.2%
1 70
 
3.0%
9 36
 
1.5%
Other Letter
ValueCountFrequency (%)
허 64
22.5%
양 64
22.5%
미 64
22.5%
외 28
9.9%
제 28
9.9%
원 24
 
8.5%
톤 9
 
3.2%
년 1
 
0.4%
월 1
 
0.4%
일 1
 
0.4%
Other Punctuation
ValueCountFrequency (%)
. 95
45.7%
, 54
26.0%
/ 33
 
15.9%
% 26
 
12.5%
Lowercase Letter
ValueCountFrequency (%)
o 24
25.0%
r 24
25.0%
k 24
25.0%
g 24
25.0%
Space Separator
ValueCountFrequency (%)
59
100.0%
Open Punctuation
ValueCountFrequency (%)
( 37
100.0%
Close Punctuation
ValueCountFrequency (%)
) 37
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2690
84.1%
Hangul 284
 
8.9%
Latin 224
 
7.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1367
50.8%
2 221
 
8.2%
3 143
 
5.3%
8 134
 
5.0%
5 132
 
4.9%
4 96
 
3.6%
. 95
 
3.5%
7 76
 
2.8%
6 74
 
2.8%
1 70
 
2.6%
Other values (7) 282
 
10.5%
Latin
ValueCountFrequency (%)
H 29
12.9%
o 24
10.7%
r 24
10.7%
k 24
10.7%
g 24
10.7%
P 17
7.6%
V 13
5.8%
N 13
5.8%
M 13
5.8%
T 12
 
5.4%
Other values (5) 31
13.8%
Hangul
ValueCountFrequency (%)
허 64
22.5%
양 64
22.5%
미 64
22.5%
외 28
9.9%
제 28
9.9%
원 24
 
8.5%
톤 9
 
3.2%
년 1
 
0.4%
월 1
 
0.4%
일 1
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2914
91.1%
Hangul 284
 
8.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1367
46.9%
2 221
 
7.6%
3 143
 
4.9%
8 134
 
4.6%
5 132
 
4.5%
4 96
 
3.3%
. 95
 
3.3%
7 76
 
2.6%
6 74
 
2.5%
1 70
 
2.4%
Other values (22) 506
 
17.4%
Hangul
ValueCountFrequency (%)
허 64
22.5%
양 64
22.5%
미 64
22.5%
외 28
9.9%
제 28
9.9%
원 24
 
8.5%
톤 9
 
3.2%
년 1
 
0.4%
월 1
 
0.4%
일 1
 
0.4%

인도
Categorical

HIGH CORRELATION 

Distinct45
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size15.2 KiB
미양허
782 
<NA>
301 
5.5
203 
3
180 
0
156 
Other values (40)
313 

Length

Max length18
Median length3
Mean length2.9136951
Min length1

Unique

Unique14 ?
Unique (%)0.7%

Sample

1st row3
2nd row3
3rd row3
4th row3
5th row3

Common Values

ValueCountFrequency (%)
미양허 782
40.4%
<NA> 301
 
15.6%
5.5 203
 
10.5%
3 180
 
9.3%
0 156
 
8.1%
1.9 54
 
2.8%
1.1 45
 
2.3%
13.7 38
 
2.0%
6.1 20
 
1.0%
10.3 17
 
0.9%
Other values (35) 139
 
7.2%

Length

2023-12-11T12:08:18.198368image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
미양허 782
40.2%
na 301
 
15.5%
5.5 203
 
10.4%
3 180
 
9.2%
0 156
 
8.0%
1.9 54
 
2.8%
1.1 45
 
2.3%
13.7 38
 
2.0%
6.1 20
 
1.0%
10.3 17
 
0.9%
Other values (38) 151
 
7.8%

EU(2013.7~2014.6)
Text

MISSING 

Distinct209
Distinct (%)12.1%
Missing208
Missing (%)10.7%
Memory size15.2 KiB
2023-12-11T12:08:18.422022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length18
Mean length2.8338159
Min length1

Characters and Unicode

Total characters4894
Distinct characters26
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique91 ?
Unique (%)5.3%

Sample

1st row0
2nd row4
3rd row4
4th row4
5th row4
ValueCountFrequency (%)
0 673
37.8%
4 121
 
6.8%
or 53
 
3.0%
5.8 49
 
2.8%
15 42
 
2.4%
21.8 40
 
2.2%
19.6 33
 
1.9%
16.3 31
 
1.7%
13.5 29
 
1.6%
10 29
 
1.6%
Other values (191) 681
38.2%
2023-12-11T12:08:18.865862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 882
18.0%
. 613
12.5%
1 540
11.0%
2 406
8.3%
5 346
 
7.1%
4 276
 
5.6%
3 269
 
5.5%
6 259
 
5.3%
8 226
 
4.6%
9 148
 
3.0%
Other values (16) 929
19.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3497
71.5%
Other Punctuation 831
 
17.0%
Lowercase Letter 216
 
4.4%
Other Letter 148
 
3.0%
Space Separator 110
 
2.2%
Close Punctuation 46
 
0.9%
Open Punctuation 46
 
0.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 882
25.2%
1 540
15.4%
2 406
11.6%
5 346
 
9.9%
4 276
 
7.9%
3 269
 
7.7%
6 259
 
7.4%
8 226
 
6.5%
9 148
 
4.2%
7 145
 
4.1%
Other Letter
ValueCountFrequency (%)
원 54
36.5%
톤 46
31.1%
양 16
 
10.8%
미 16
 
10.8%
허 16
 
10.8%
Other Punctuation
ValueCountFrequency (%)
. 613
73.8%
/ 102
 
12.3%
, 62
 
7.5%
% 54
 
6.5%
Lowercase Letter
ValueCountFrequency (%)
o 54
25.0%
g 54
25.0%
k 54
25.0%
r 54
25.0%
Space Separator
ValueCountFrequency (%)
110
100.0%
Close Punctuation
ValueCountFrequency (%)
) 46
100.0%
Open Punctuation
ValueCountFrequency (%)
( 46
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4530
92.6%
Latin 216
 
4.4%
Hangul 148
 
3.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 882
19.5%
. 613
13.5%
1 540
11.9%
2 406
9.0%
5 346
 
7.6%
4 276
 
6.1%
3 269
 
5.9%
6 259
 
5.7%
8 226
 
5.0%
9 148
 
3.3%
Other values (7) 565
12.5%
Hangul
ValueCountFrequency (%)
원 54
36.5%
톤 46
31.1%
양 16
 
10.8%
미 16
 
10.8%
허 16
 
10.8%
Latin
ValueCountFrequency (%)
o 54
25.0%
g 54
25.0%
k 54
25.0%
r 54
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4746
97.0%
Hangul 148
 
3.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 882
18.6%
. 613
12.9%
1 540
11.4%
2 406
8.6%
5 346
 
7.3%
4 276
 
5.8%
3 269
 
5.7%
6 259
 
5.5%
8 226
 
4.8%
9 148
 
3.1%
Other values (11) 781
16.5%
Hangul
ValueCountFrequency (%)
원 54
36.5%
톤 46
31.1%
양 16
 
10.8%
미 16
 
10.8%
허 16
 
10.8%

EU(2014.7~2015.6)
Text

MISSING 

Distinct195
Distinct (%)11.3%
Missing204
Missing (%)10.5%
Memory size15.2 KiB
2023-12-11T12:08:19.152550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length17
Mean length2.7487002
Min length1

Characters and Unicode

Total characters4758
Distinct characters27
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique76 ?
Unique (%)4.4%

Sample

1st row0
2nd row2.6
3rd row2.6
4th row2.6
5th row2.6
ValueCountFrequency (%)
0 688
38.6%
2.6 121
 
6.8%
or 54
 
3.0%
5 52
 
2.9%
10 45
 
2.5%
15 43
 
2.4%
19 40
 
2.2%
17.1 33
 
1.9%
9 31
 
1.7%
14.3 31
 
1.7%
Other values (178) 645
36.2%
2023-12-11T12:08:19.650572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 938
19.7%
. 587
12.3%
1 516
10.8%
2 430
9.0%
6 331
 
7.0%
5 296
 
6.2%
3 217
 
4.6%
4 196
 
4.1%
7 176
 
3.7%
9 163
 
3.4%
Other values (17) 908
19.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3391
71.3%
Other Punctuation 804
 
16.9%
Lowercase Letter 214
 
4.5%
Other Letter 148
 
3.1%
Space Separator 108
 
2.3%
Close Punctuation 46
 
1.0%
Open Punctuation 46
 
1.0%
Other Symbol 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 938
27.7%
1 516
15.2%
2 430
12.7%
6 331
 
9.8%
5 296
 
8.7%
3 217
 
6.4%
4 196
 
5.8%
7 176
 
5.2%
9 163
 
4.8%
8 128
 
3.8%
Other Letter
ValueCountFrequency (%)
원 54
36.5%
톤 46
31.1%
허 16
 
10.8%
양 16
 
10.8%
미 16
 
10.8%
Other Punctuation
ValueCountFrequency (%)
. 587
73.0%
/ 102
 
12.7%
, 61
 
7.6%
% 54
 
6.7%
Lowercase Letter
ValueCountFrequency (%)
r 54
25.2%
o 54
25.2%
g 53
24.8%
k 53
24.8%
Space Separator
ValueCountFrequency (%)
108
100.0%
Close Punctuation
ValueCountFrequency (%)
) 46
100.0%
Open Punctuation
ValueCountFrequency (%)
( 46
100.0%
Other Symbol
ValueCountFrequency (%)
㎏ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4396
92.4%
Latin 214
 
4.5%
Hangul 148
 
3.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 938
21.3%
. 587
13.4%
1 516
11.7%
2 430
9.8%
6 331
 
7.5%
5 296
 
6.7%
3 217
 
4.9%
4 196
 
4.5%
7 176
 
4.0%
9 163
 
3.7%
Other values (8) 546
12.4%
Hangul
ValueCountFrequency (%)
원 54
36.5%
톤 46
31.1%
허 16
 
10.8%
양 16
 
10.8%
미 16
 
10.8%
Latin
ValueCountFrequency (%)
r 54
25.2%
o 54
25.2%
g 53
24.8%
k 53
24.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4609
96.9%
Hangul 148
 
3.1%
CJK Compat 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 938
20.4%
. 587
12.7%
1 516
11.2%
2 430
9.3%
6 331
 
7.2%
5 296
 
6.4%
3 217
 
4.7%
4 196
 
4.3%
7 176
 
3.8%
9 163
 
3.5%
Other values (11) 759
16.5%
Hangul
ValueCountFrequency (%)
원 54
36.5%
톤 46
31.1%
허 16
 
10.8%
양 16
 
10.8%
미 16
 
10.8%
CJK Compat
ValueCountFrequency (%)
㎏ 1
100.0%

페루
Text

MISSING 

Distinct167
Distinct (%)9.9%
Missing251
Missing (%)13.0%
Memory size15.2 KiB
2023-12-11T12:08:20.095348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length16
Mean length2.7850356
Min length1

Characters and Unicode

Total characters4690
Distinct characters27
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique56 ?
Unique (%)3.3%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
0 465
26.8%
1.6 227
 
13.1%
18 79
 
4.5%
16.2 70
 
4.0%
27 57
 
3.3%
or 55
 
3.2%
4.8 54
 
3.1%
13.5 43
 
2.5%
6 35
 
2.0%
10.8 30
 
1.7%
Other values (148) 622
35.8%
2023-12-11T12:08:20.683525image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 731
15.6%
1 669
14.3%
0 636
13.6%
6 465
9.9%
2 426
9.1%
8 275
 
5.9%
5 226
 
4.8%
3 224
 
4.8%
4 210
 
4.5%
7 177
 
3.8%
Other values (17) 651
13.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3388
72.2%
Other Punctuation 863
 
18.4%
Lowercase Letter 222
 
4.7%
Space Separator 112
 
2.4%
Other Letter 103
 
2.2%
Uppercase Letter 1
 
< 0.1%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 669
19.7%
0 636
18.8%
6 465
13.7%
2 426
12.6%
8 275
8.1%
5 226
 
6.7%
3 224
 
6.6%
4 210
 
6.2%
7 177
 
5.2%
9 80
 
2.4%
Lowercase Letter
ValueCountFrequency (%)
g 55
24.8%
k 55
24.8%
o 55
24.8%
r 55
24.8%
e 1
 
0.5%
p 1
 
0.5%
Other Punctuation
ValueCountFrequency (%)
. 731
84.7%
/ 56
 
6.5%
% 55
 
6.4%
, 21
 
2.4%
Other Letter
ValueCountFrequency (%)
원 55
53.4%
허 16
 
15.5%
양 16
 
15.5%
미 16
 
15.5%
Space Separator
ValueCountFrequency (%)
112
100.0%
Uppercase Letter
ValueCountFrequency (%)
S 1
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4364
93.0%
Latin 223
 
4.8%
Hangul 103
 
2.2%

Most frequent character per script

Common
ValueCountFrequency (%)
. 731
16.8%
1 669
15.3%
0 636
14.6%
6 465
10.7%
2 426
9.8%
8 275
 
6.3%
5 226
 
5.2%
3 224
 
5.1%
4 210
 
4.8%
7 177
 
4.1%
Other values (6) 325
7.4%
Latin
ValueCountFrequency (%)
g 55
24.7%
k 55
24.7%
o 55
24.7%
r 55
24.7%
S 1
 
0.4%
e 1
 
0.4%
p 1
 
0.4%
Hangul
ValueCountFrequency (%)
원 55
53.4%
허 16
 
15.5%
양 16
 
15.5%
미 16
 
15.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4587
97.8%
Hangul 103
 
2.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 731
15.9%
1 669
14.6%
0 636
13.9%
6 465
10.1%
2 426
9.3%
8 275
 
6.0%
5 226
 
4.9%
3 224
 
4.9%
4 210
 
4.6%
7 177
 
3.9%
Other values (13) 548
11.9%
Hangul
ValueCountFrequency (%)
원 55
53.4%
허 16
 
15.5%
양 16
 
15.5%
미 16
 
15.5%

미국
Text

MISSING 

Distinct203
Distinct (%)11.5%
Missing174
Missing (%)9.0%
Memory size15.2 KiB
2023-12-11T12:08:20.950999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length33
Median length28
Mean length3.1749006
Min length1

Characters and Unicode

Total characters5591
Distinct characters26
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique76 ?
Unique (%)4.3%

Sample

1st row3.2
2nd row3.2
3rd row3.2
4th row3.2
5th row3.2
ValueCountFrequency (%)
0 625
34.1%
3.2 158
 
8.6%
5.6 57
 
3.1%
or 54
 
2.9%
21 48
 
2.6%
12 38
 
2.1%
18.9 36
 
2.0%
15.7 34
 
1.9%
8 33
 
1.8%
14 26
 
1.4%
Other values (187) 725
39.5%
2023-12-11T12:08:21.361319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 904
16.2%
. 684
12.2%
2 627
11.2%
1 573
10.2%
3 375
 
6.7%
5 361
 
6.5%
8 289
 
5.2%
6 242
 
4.3%
4 230
 
4.1%
/ 190
 
3.4%
Other values (16) 1116
20.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3858
69.0%
Other Punctuation 1010
 
18.1%
Lowercase Letter 216
 
3.9%
Other Letter 197
 
3.5%
Space Separator 119
 
2.1%
Close Punctuation 96
 
1.7%
Open Punctuation 95
 
1.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 904
23.4%
2 627
16.3%
1 573
14.9%
3 375
9.7%
5 361
 
9.4%
8 289
 
7.5%
6 242
 
6.3%
4 230
 
6.0%
7 149
 
3.9%
9 108
 
2.8%
Other Letter
ValueCountFrequency (%)
톤 95
48.2%
원 54
27.4%
양 16
 
8.1%
미 16
 
8.1%
허 16
 
8.1%
Other Punctuation
ValueCountFrequency (%)
. 684
67.7%
/ 190
 
18.8%
, 82
 
8.1%
% 54
 
5.3%
Lowercase Letter
ValueCountFrequency (%)
g 54
25.0%
o 54
25.0%
r 54
25.0%
k 54
25.0%
Space Separator
ValueCountFrequency (%)
119
100.0%
Close Punctuation
ValueCountFrequency (%)
) 96
100.0%
Open Punctuation
ValueCountFrequency (%)
( 95
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5178
92.6%
Latin 216
 
3.9%
Hangul 197
 
3.5%

Most frequent character per script

Common
ValueCountFrequency (%)
0 904
17.5%
. 684
13.2%
2 627
12.1%
1 573
11.1%
3 375
7.2%
5 361
 
7.0%
8 289
 
5.6%
6 242
 
4.7%
4 230
 
4.4%
/ 190
 
3.7%
Other values (7) 703
13.6%
Hangul
ValueCountFrequency (%)
톤 95
48.2%
원 54
27.4%
양 16
 
8.1%
미 16
 
8.1%
허 16
 
8.1%
Latin
ValueCountFrequency (%)
g 54
25.0%
o 54
25.0%
r 54
25.0%
k 54
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5394
96.5%
Hangul 197
 
3.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 904
16.8%
. 684
12.7%
2 627
11.6%
1 573
10.6%
3 375
7.0%
5 361
 
6.7%
8 289
 
5.4%
6 242
 
4.5%
4 230
 
4.3%
/ 190
 
3.5%
Other values (11) 919
17.0%
Hangul
ValueCountFrequency (%)
톤 95
48.2%
원 54
27.4%
양 16
 
8.1%
미 16
 
8.1%
허 16
 
8.1%

터키
Text

MISSING 

Distinct156
Distinct (%)9.5%
Missing293
Missing (%)15.1%
Memory size15.2 KiB
2023-12-11T12:08:21.730873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length17
Mean length2.953715
Min length1

Characters and Unicode

Total characters4850
Distinct characters23
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique60 ?
Unique (%)3.7%

Sample

1st row0
2nd row6.5
3rd row6.5
4th row6.5
5th row6.5
ValueCountFrequency (%)
6.5 246
 
14.1%
0 154
 
8.9%
30 123
 
7.1%
27 97
 
5.6%
5.3 93
 
5.3%
2 74
 
4.3%
or 59
 
3.4%
45 55
 
3.2%
18 48
 
2.8%
8 48
 
2.8%
Other values (142) 743
42.7%
2023-12-11T12:08:22.209542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 711
14.7%
5 638
13.2%
2 504
10.4%
0 476
9.8%
3 463
9.5%
6 438
9.0%
4 273
 
5.6%
1 238
 
4.9%
7 219
 
4.5%
8 216
 
4.5%
Other values (13) 674
13.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3529
72.8%
Other Punctuation 861
 
17.8%
Lowercase Letter 236
 
4.9%
Space Separator 118
 
2.4%
Other Letter 106
 
2.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 638
18.1%
2 504
14.3%
0 476
13.5%
3 463
13.1%
6 438
12.4%
4 273
7.7%
1 238
 
6.7%
7 219
 
6.2%
8 216
 
6.1%
9 64
 
1.8%
Other Punctuation
ValueCountFrequency (%)
. 711
82.6%
/ 59
 
6.9%
% 59
 
6.9%
, 32
 
3.7%
Lowercase Letter
ValueCountFrequency (%)
g 59
25.0%
k 59
25.0%
o 59
25.0%
r 59
25.0%
Other Letter
ValueCountFrequency (%)
원 58
54.7%
허 16
 
15.1%
양 16
 
15.1%
미 16
 
15.1%
Space Separator
ValueCountFrequency (%)
118
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4508
92.9%
Latin 236
 
4.9%
Hangul 106
 
2.2%

Most frequent character per script

Common
ValueCountFrequency (%)
. 711
15.8%
5 638
14.2%
2 504
11.2%
0 476
10.6%
3 463
10.3%
6 438
9.7%
4 273
 
6.1%
1 238
 
5.3%
7 219
 
4.9%
8 216
 
4.8%
Other values (5) 332
7.4%
Latin
ValueCountFrequency (%)
g 59
25.0%
k 59
25.0%
o 59
25.0%
r 59
25.0%
Hangul
ValueCountFrequency (%)
원 58
54.7%
허 16
 
15.1%
양 16
 
15.1%
미 16
 
15.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4744
97.8%
Hangul 106
 
2.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 711
15.0%
5 638
13.4%
2 504
10.6%
0 476
10.0%
3 463
9.8%
6 438
9.2%
4 273
 
5.8%
1 238
 
5.0%
7 219
 
4.6%
8 216
 
4.6%
Other values (9) 568
12.0%
Hangul
ValueCountFrequency (%)
원 58
54.7%
허 16
 
15.1%
양 16
 
15.1%
미 16
 
15.1%

콜롬비아
Text

MISSING 

Distinct181
Distinct (%)11.0%
Missing293
Missing (%)15.1%
Memory size15.2 KiB
2023-12-11T12:08:22.610820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length18
Mean length3.3562728
Min length1

Characters and Unicode

Total characters5511
Distinct characters26
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique71 ?
Unique (%)4.3%

Sample

1st row0
2nd row6.4
3rd row6.4
4th row6.4
5th row6.4
ValueCountFrequency (%)
6.4 336
19.4%
0 246
 
14.2%
7.2 77
 
4.4%
24.3 54
 
3.1%
or 54
 
3.1%
27 49
 
2.8%
28.1 38
 
2.2%
3.3 35
 
2.0%
18.7 31
 
1.8%
25.3 28
 
1.6%
Other values (172) 788
45.4%
2023-12-11T12:08:23.150381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 1063
19.3%
4 672
12.2%
2 577
10.5%
6 532
9.7%
0 434
7.9%
3 402
 
7.3%
1 339
 
6.2%
7 337
 
6.1%
5 280
 
5.1%
8 226
 
4.1%
Other values (16) 649
11.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3865
70.1%
Other Punctuation 1204
 
21.8%
Lowercase Letter 216
 
3.9%
Space Separator 109
 
2.0%
Other Letter 107
 
1.9%
Open Punctuation 5
 
0.1%
Close Punctuation 5
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 672
17.4%
2 577
14.9%
6 532
13.8%
0 434
11.2%
3 402
10.4%
1 339
8.8%
7 337
8.7%
5 280
7.2%
8 226
 
5.8%
9 66
 
1.7%
Other Letter
ValueCountFrequency (%)
원 54
50.5%
허 16
 
15.0%
양 16
 
15.0%
미 16
 
15.0%
톤 5
 
4.7%
Other Punctuation
ValueCountFrequency (%)
. 1063
88.3%
/ 60
 
5.0%
% 54
 
4.5%
, 27
 
2.2%
Lowercase Letter
ValueCountFrequency (%)
o 54
25.0%
r 54
25.0%
k 54
25.0%
g 54
25.0%
Space Separator
ValueCountFrequency (%)
109
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5188
94.1%
Latin 216
 
3.9%
Hangul 107
 
1.9%

Most frequent character per script

Common
ValueCountFrequency (%)
. 1063
20.5%
4 672
13.0%
2 577
11.1%
6 532
10.3%
0 434
8.4%
3 402
 
7.7%
1 339
 
6.5%
7 337
 
6.5%
5 280
 
5.4%
8 226
 
4.4%
Other values (7) 326
 
6.3%
Hangul
ValueCountFrequency (%)
원 54
50.5%
허 16
 
15.0%
양 16
 
15.0%
미 16
 
15.0%
톤 5
 
4.7%
Latin
ValueCountFrequency (%)
o 54
25.0%
r 54
25.0%
k 54
25.0%
g 54
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5404
98.1%
Hangul 107
 
1.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 1063
19.7%
4 672
12.4%
2 577
10.7%
6 532
9.8%
0 434
8.0%
3 402
 
7.4%
1 339
 
6.3%
7 337
 
6.2%
5 280
 
5.2%
8 226
 
4.2%
Other values (11) 542
10.0%
Hangul
ValueCountFrequency (%)
원 54
50.5%
허 16
 
15.0%
양 16
 
15.0%
미 16
 
15.0%
톤 5
 
4.7%

개방구분
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct8
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size15.2 KiB
<NA>
1644 
TC
 
72
TM
 
51
BM
 
51
BC
 
49
Other values (3)
 
68

Length

Max length4
Median length4
Mean length3.6992248
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 1644
85.0%
TC 72
 
3.7%
TM 51
 
2.6%
BM 51
 
2.6%
BC 49
 
2.5%
BX 40
 
2.1%
ST 16
 
0.8%
TX 12
 
0.6%

Length

2023-12-11T12:08:23.334219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T12:08:23.507287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1644
85.0%
tc 72
 
3.7%
tm 51
 
2.6%
bm 51
 
2.6%
bc 49
 
2.5%
bx 40
 
2.1%
st 16
 
0.8%
tx 12
 
0.6%

Interactions

2023-12-11T12:08:10.686463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T12:08:09.830032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T12:08:10.224300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T12:08:10.840041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T12:08:09.967270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T12:08:10.391195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T12:08:10.964208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T12:08:10.090267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T12:08:10.533705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T12:08:23.654411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
일련 번호칠레싱가포르스위스노르웨이아이슬란드아세안인도개방구분
일련 번호1.0000.2590.7250.8060.7200.7110.7370.7030.674
칠레0.2591.0000.3010.8430.6600.6620.4670.0000.650
싱가포르0.7250.3011.0000.9870.8840.9160.9350.9680.878
스위스0.8060.8430.9871.0001.0001.0000.9180.9410.768
노르웨이0.7200.6600.8841.0001.0000.9990.6490.8220.800
아이슬란드0.7110.6620.9161.0000.9991.0000.6470.8650.772
아세안0.7370.4670.9350.9180.6490.6471.0000.0000.875
인도0.7030.0000.9680.9410.8220.8650.0001.0000.645
개방구분0.6740.6500.8780.7680.8000.7720.8750.6451.000
2023-12-11T12:08:23.805753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
스위스개방구분싱가포르칠레인도
스위스1.0000.5740.8200.5450.532
개방구분0.5741.0000.5540.2810.357
싱가포르0.8200.5541.0000.1630.560
칠레0.5450.2810.1631.0000.000
인도0.5320.3570.5600.0001.000
2023-12-11T12:08:23.934428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
일련 번호노르웨이아이슬란드칠레싱가포르스위스인도개방구분
일련 번호1.000-0.439-0.4080.1100.3390.4180.3240.422
노르웨이-0.4391.0000.9550.3480.6270.9810.4690.414
아이슬란드-0.4080.9551.0000.3520.7020.9810.5530.633
칠레0.1100.3480.3521.0000.1630.5450.0000.281
싱가포르0.3390.6270.7020.1631.0000.8200.5600.554
스위스0.4180.9810.9810.5450.8201.0000.5320.574
인도0.3240.4690.5530.0000.5600.5321.0000.357
개방구분0.4220.4140.6330.2810.5540.5740.3571.000

Missing values

2023-12-11T12:08:11.184003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T12:08:11.584764image/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.
2023-12-11T12:08:11.921139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

일련 번호H S K한 글 품 명영 문 품 명2014실행세율칠레싱가포르스위스노르웨이아이슬란드아세안인도EU(2013.7~2014.6)EU(2014.7~2015.6)페루미국터키콜롬비아개방구분
010101.21.1000말(번식용/농가사육용)Horses: Pure-bred breeding anmials(For farm breeding)기본0006.46.44.0030003.200<NA>
120101.21.9000말(번식용/기타)Horses: Pure-bred breeding anmials(Other)기본8006.46.46.40342.603.26.56.4<NA>
230101.29.1000말(기타/경주말)Horses: Other(Horses for racing)기본80006.40.00342.603.26.56.4<NA>
340101.29.9000말(기타/기타)Horses: Other(Other)기본80046.44.00342.603.26.56.4<NA>
450101.30.1000당나귀(번식용)Asses: Pure-bred breeding animals기본8006.46.46.40342.603.26.56.4<NA>
560101.30.9000당나귀(기타)Asses: Other기본80046.44.0035.8505.66.56.4<NA>
670101.90.0000기타(기타)Other기본80046.44.0035.8505.66.56.4<NA>
780102.21.1000축우(번식용/젖소)Cattle: Pure-bred breeding animals(For milk)양허0/89.1000<NA><NA>033.4000089.10TM
890102.21.2000축우(번식용/육우)Cattle: Pure-bred breeding animals(For meat)양허0/89.1000<NA><NA>033.4000089.10TM
9100102.21.9000축우(번식용/기타)Cattle: Pure-bred breeding animals(Other)양허0/89.1000<NA><NA>033.4000089.10TM
일련 번호H S K한 글 품 명영 문 품 명2014실행세율칠레싱가포르스위스노르웨이아이슬란드아세안인도EU(2013.7~2014.6)EU(2014.7~2015.6)페루미국터키콜롬비아개방구분
192516135203.00.0000면(카드 or 코움한 것)Cotton, carded or combed기본00000.00.000000000<NA>
192616145301.10.0000생아마 or 침지아마Flax, raw or retted기본20000.00.000000000<NA>
192716155301.21.0000아마(쇄경 or 타마한 것)Flax(broken or scutched)기본20000.00.000000000<NA>
192816165301.29.0000아마(기타)Other flax기본20000.00.000000000<NA>
192916175301.30.1000아마의 토우Flax tow기본20000.00.000000000<NA>
193016185301.30.2000아마의 웨이스트Flax waste기본20000.00.000000000<NA>
193116195302.10.0000생대마 or 침지대마True hemp, raw or retted기본20000.00.000000000<NA>
193216205302.90.1000쇄경, 탐, 핵클 or 기타의 방법으로 가공한 대마True hemp, broken, scutched, hackled or other wise processed기본20000.00.000000000<NA>
193316215302.90.2010대마의 토우Tow of true hemp기본20000.00.000000000<NA>
193416225302.90.2020대마의 웨이스트Waste of true hemp기본20000.00.000000000<NA>

Duplicate rows

Most frequently occurring

일련 번호H S K한 글 품 명영 문 품 명2014실행세율칠레싱가포르스위스노르웨이아이슬란드아세안인도EU(2013.7~2014.6)EU(2014.7~2015.6)페루미국터키콜롬비아개방구분# duplicates
28<NA><NA><NA><NA><NA>(2,000톤)<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>9
36<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>(4,696톤)(4,837톤)<NA>(7,426톤)<NA><NA><NA>9
0<NA><NA>- 기타<NA><NA><NA><NA>4.84.84.8<NA>미양허<NA><NA><NA>3.2<NA><NA><NA>6
1<NA><NA>- 제충국의 것 or 로테논을 함유하는 식물뿌리의 것<NA><NA><NA><NA>6.46.46.4<NA>3<NA><NA><NA>0<NA><NA><NA>6
9<NA><NA>?향미를 첨가하거나 착색 설탕시럽 외의 것<NA><NA><NA><NA>4.84.84.8<NA><NA><NA><NA><NA><NA><NA><NA><NA>6
15<NA><NA><NA><NA>(기본2)<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>6
21<NA><NA><NA><NA>(양허20/49.5)<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>6
34<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>(1,030톤)(1,060톤)<NA>(5,305톤)<NA><NA><NA>6
16<NA><NA><NA><NA>(기본3)<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>5
27<NA><NA><NA><NA><NA>(100톤)<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>5