Overview

Dataset statistics

Number of variables18
Number of observations1653
Missing cells1663
Missing cells (%)5.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory235.8 KiB
Average record size in memory146.1 B

Variable types

Text11
Categorical5
Numeric2

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

노르웨이 is highly overall correlated with 아이슬란드 and 2 other fieldsHigh correlation
아이슬란드 is highly overall correlated with 노르웨이 and 4 other fieldsHigh correlation
싱가포르 is highly overall correlated with 노르웨이 and 4 other fieldsHigh correlation
스위스 is highly overall correlated with 노르웨이 and 4 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 (73.4%)Imbalance
싱가포르 is highly imbalanced (52.9%)Imbalance
스위스 is highly imbalanced (63.0%)Imbalance
개방구분 is highly imbalanced (62.0%)Imbalance
노르웨이 has 930 (56.3%) missing valuesMissing
아이슬란드 has 733 (44.3%) missing valuesMissing
노르웨이 has 270 (16.3%) zerosZeros
아이슬란드 has 307 (18.6%) zerosZeros

Reproduction

Analysis started2023-12-11 03:07:52.306038
Analysis finished2023-12-11 03:07:55.157018
Duration2.85 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

H S K
Text

Distinct1622
Distinct (%)98.1%
Missing0
Missing (%)0.0%
Memory size13.0 KiB
2023-12-11T12:07:55.327497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters19836
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

Unique1594 ?
Unique (%)96.4%

Sample

1st row0101.21.1000
2nd row0101.21.9000
3rd row0101.29.1000
4th row0101.29.9000
5th row0101.30.1000
ValueCountFrequency (%)
2009.89.1090 3
 
0.2%
1212.94.0000 3
 
0.2%
1005.90.9000 3
 
0.2%
0403.90.9000 2
 
0.1%
0105.94.9000 2
 
0.1%
1302.19.9099 2
 
0.1%
0208.90.9090 2
 
0.1%
0808.10.0000 2
 
0.1%
2208.30.9000 2
 
0.1%
0701.90.0000 2
 
0.1%
Other values (1612) 1630
98.6%
2023-12-11T12:07:55.693288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 8202
41.3%
. 3306
16.7%
1 2560
 
12.9%
2 1652
 
8.3%
9 1567
 
7.9%
3 645
 
3.3%
4 490
 
2.5%
5 473
 
2.4%
6 342
 
1.7%
7 335
 
1.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 16530
83.3%
Other Punctuation 3306
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 8202
49.6%
1 2560
 
15.5%
2 1652
 
10.0%
9 1567
 
9.5%
3 645
 
3.9%
4 490
 
3.0%
5 473
 
2.9%
6 342
 
2.1%
7 335
 
2.0%
8 264
 
1.6%
Other Punctuation
ValueCountFrequency (%)
. 3306
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 19836
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 8202
41.3%
. 3306
16.7%
1 2560
 
12.9%
2 1652
 
8.3%
9 1567
 
7.9%
3 645
 
3.3%
4 490
 
2.5%
5 473
 
2.4%
6 342
 
1.7%
7 335
 
1.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 19836
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 8202
41.3%
. 3306
16.7%
1 2560
 
12.9%
2 1652
 
8.3%
9 1567
 
7.9%
3 645
 
3.3%
4 490
 
2.5%
5 473
 
2.4%
6 342
 
1.7%
7 335
 
1.7%

한 글 품 명
Text

Distinct1623
Distinct (%)98.2%
Missing0
Missing (%)0.0%
Memory size13.0 KiB
2023-12-11T12:07:56.043028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length62
Median length49
Mean length13.462795
Min length1

Characters and Unicode

Total characters22254
Distinct characters609
Distinct categories11 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1607 ?
Unique (%)97.2%

Sample

1st row말(번식용/농가사육용)
2nd row말(번식용/기타)
3rd row말(기타/경주말)
4th row말(기타/기타)
5th row당나귀(번식용)
ValueCountFrequency (%)
것 243
 
5.9%
기타 133
 
3.2%
or 122
 
3.0%
및 75
 
1.8%
그 35
 
0.9%
종자 29
 
0.7%
이하 26
 
0.6%
안한 26
 
0.6%
분획물 24
 
0.6%
한함 21
 
0.5%
Other values (2192) 3368
82.1%
2023-12-11T12:07:56.594054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2471
 
11.1%
( 1207
 
5.4%
) 1205
 
5.4%
기 749
 
3.4%
타 663
 
3.0%
/ 499
 
2.2%
의 348
 
1.6%
리 324
 
1.5%
조 318
 
1.4%
스 317
 
1.4%
Other values (599) 14153
63.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 15768
70.9%
Space Separator 2471
 
11.1%
Open Punctuation 1207
 
5.4%
Close Punctuation 1205
 
5.4%
Other Punctuation 740
 
3.3%
Decimal Number 382
 
1.7%
Lowercase Letter 313
 
1.4%
Dash Punctuation 163
 
0.7%
Control 2
 
< 0.1%
Math Symbol 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 749
 
4.8%
타 663
 
4.2%
의 348
 
2.2%
리 324
 
2.1%
조 318
 
2.0%
스 317
 
2.0%
유 299
 
1.9%
것 297
 
1.9%
이 296
 
1.9%
제 261
 
1.7%
Other values (562) 11896
75.4%
Lowercase Letter
ValueCountFrequency (%)
r 124
39.6%
o 124
39.6%
g 27
 
8.6%
m 16
 
5.1%
k 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%
9 17
 
4.5%
3 17
 
4.5%
7 5
 
1.3%
Other Punctuation
ValueCountFrequency (%)
/ 499
67.4%
, 152
 
20.5%
% 31
 
4.2%
· 27
 
3.6%
. 26
 
3.5%
" 2
 
0.3%
? 2
 
0.3%
: 1
 
0.1%
Math Symbol
ValueCountFrequency (%)
> 1
50.0%
< 1
50.0%
Space Separator
ValueCountFrequency (%)
2471
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1207
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1205
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 163
100.0%
Control
ValueCountFrequency (%)
2
100.0%
Uppercase Letter
ValueCountFrequency (%)
A 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 15748
70.8%
Common 6172
 
27.7%
Latin 314
 
1.4%
Han 20
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 749
 
4.8%
타 663
 
4.2%
의 348
 
2.2%
리 324
 
2.1%
조 318
 
2.0%
스 317
 
2.0%
유 299
 
1.9%
것 297
 
1.9%
이 296
 
1.9%
제 261
 
1.7%
Other values (552) 11876
75.4%
Common
ValueCountFrequency (%)
2471
40.0%
( 1207
19.6%
) 1205
19.5%
/ 499
 
8.1%
- 163
 
2.6%
, 152
 
2.5%
0 120
 
1.9%
1 71
 
1.2%
2 45
 
0.7%
5 40
 
0.6%
Other values (15) 199
 
3.2%
Latin
ValueCountFrequency (%)
r 124
39.5%
o 124
39.5%
g 27
 
8.6%
m 16
 
5.1%
k 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 (%)
黃 2
10.0%
芎 2
10.0%
川 2
10.0%
藥 2
10.0%
芍 2
10.0%
歸 2
10.0%
當 2
10.0%
子 2
10.0%
味 2
10.0%
五 2
10.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 15748
70.8%
ASCII 6459
29.0%
None 27
 
0.1%
CJK 20
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2471
38.3%
( 1207
18.7%
) 1205
18.7%
/ 499
 
7.7%
- 163
 
2.5%
, 152
 
2.4%
r 124
 
1.9%
o 124
 
1.9%
0 120
 
1.9%
1 71
 
1.1%
Other values (26) 323
 
5.0%
Hangul
ValueCountFrequency (%)
기 749
 
4.8%
타 663
 
4.2%
의 348
 
2.2%
리 324
 
2.1%
조 318
 
2.0%
스 317
 
2.0%
유 299
 
1.9%
것 297
 
1.9%
이 296
 
1.9%
제 261
 
1.7%
Other values (552) 11876
75.4%
None
ValueCountFrequency (%)
· 27
100.0%
CJK
ValueCountFrequency (%)
黃 2
10.0%
芎 2
10.0%
川 2
10.0%
藥 2
10.0%
芍 2
10.0%
歸 2
10.0%
當 2
10.0%
子 2
10.0%
味 2
10.0%
五 2
10.0%

영 문 품 명
Text

Distinct1584
Distinct (%)95.8%
Missing0
Missing (%)0.0%
Memory size13.0 KiB
2023-12-11T12:07:56.916142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length150
Median length85
Mean length31.756806
Min length3

Characters and Unicode

Total characters52494
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

Unique1544 ?
Unique (%)93.4%

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 371
 
5.4%
of 347
 
5.0%
other 329
 
4.8%
and 248
 
3.6%
meat 121
 
1.8%
chilled 82
 
1.2%
preserved 76
 
1.1%
the 63
 
0.9%
offal 59
 
0.9%
prepared 58
 
0.8%
Other values (1877) 5118
74.5%
2023-12-11T12:07:57.469512image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
e 5783
 
11.0%
5223
 
9.9%
r 3978
 
7.6%
o 3234
 
6.2%
a 3205
 
6.1%
s 3012
 
5.7%
t 2983
 
5.7%
i 2642
 
5.0%
n 2427
 
4.6%
d 1872
 
3.6%
Other values (66) 18135
34.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 41430
78.9%
Space Separator 5223
 
9.9%
Uppercase Letter 2586
 
4.9%
Close Punctuation 1087
 
2.1%
Open Punctuation 1087
 
2.1%
Other Punctuation 734
 
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 5783
14.0%
r 3978
 
9.6%
o 3234
 
7.8%
a 3205
 
7.7%
s 3012
 
7.3%
t 2983
 
7.2%
i 2642
 
6.4%
n 2427
 
5.9%
d 1872
 
4.5%
l 1801
 
4.3%
Other values (17) 10493
25.3%
Uppercase Letter
ValueCountFrequency (%)
O 728
28.2%
C 243
 
9.4%
S 218
 
8.4%
P 175
 
6.8%
M 174
 
6.7%
F 130
 
5.0%
B 121
 
4.7%
R 108
 
4.2%
G 108
 
4.2%
L 86
 
3.3%
Other values (16) 495
19.1%
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 (%)
/ 328
44.7%
, 228
31.1%
. 77
 
10.5%
: 41
 
5.6%
% 37
 
5.0%
' 16
 
2.2%
; 7
 
1.0%
Other Symbol
ValueCountFrequency (%)
° 4
80.0%
ⓚ 1
 
20.0%
Space Separator
ValueCountFrequency (%)
5223
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1087
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1087
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 101
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 44012
83.8%
Common 8482
 
16.2%

Most frequent character per script

Latin
ValueCountFrequency (%)
e 5783
13.1%
r 3978
 
9.0%
o 3234
 
7.3%
a 3205
 
7.3%
s 3012
 
6.8%
t 2983
 
6.8%
i 2642
 
6.0%
n 2427
 
5.5%
d 1872
 
4.3%
l 1801
 
4.1%
Other values (42) 13075
29.7%
Common
ValueCountFrequency (%)
5223
61.6%
) 1087
 
12.8%
( 1087
 
12.8%
/ 328
 
3.9%
, 228
 
2.7%
- 101
 
1.2%
. 77
 
0.9%
0 72
 
0.8%
: 41
 
0.5%
5 40
 
0.5%
Other values (14) 198
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 52485
> 99.9%
None 4
 
< 0.1%
Letterlike Symbols 4
 
< 0.1%
Enclosed Alphanum 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
e 5783
 
11.0%
5223
 
10.0%
r 3978
 
7.6%
o 3234
 
6.2%
a 3205
 
6.1%
s 3012
 
5.7%
t 2983
 
5.7%
i 2642
 
5.0%
n 2427
 
4.6%
d 1872
 
3.6%
Other values (63) 18126
34.5%
None
ValueCountFrequency (%)
° 4
100.0%
Letterlike Symbols
ValueCountFrequency (%)
ℓ 4
100.0%
Enclosed Alphanum
ValueCountFrequency (%)
ⓚ 1
100.0%

2014 실행세율
Text

Distinct143
Distinct (%)8.7%
Missing0
Missing (%)0.0%
Memory size13.0 KiB
2023-12-11T12:07:57.685361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length22
Mean length4.5952813
Min length3

Characters and Unicode

Total characters7596
Distinct characters36
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique55 ?
Unique (%)3.3%

Sample

1st row기본0
2nd row기본8
3rd row기본8
4th row기본8
5th row기본8
ValueCountFrequency (%)
기본8 424
25.5%
기본30 141
 
8.5%
기본27 97
 
5.8%
기본5 96
 
5.8%
기본3 95
 
5.7%
기본0 87
 
5.2%
기본45 60
 
3.6%
기본20 59
 
3.5%
기본18 55
 
3.3%
기본22.5 39
 
2.3%
Other values (136) 511
30.7%
2023-12-11T12:07:58.160844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
기 1332
17.5%
본 1332
17.5%
0 630
8.3%
8 607
 
8.0%
2 514
 
6.8%
5 452
 
6.0%
3 405
 
5.3%
/ 283
 
3.7%
허 261
 
3.4%
양 261
 
3.4%
Other values (26) 1519
20.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3499
46.1%
Decimal Number 3372
44.4%
Other Punctuation 528
 
7.0%
Dash Punctuation 61
 
0.8%
Close Punctuation 54
 
0.7%
Open Punctuation 54
 
0.7%
Lowercase Letter 14
 
0.2%
Space Separator 12
 
0.2%
Control 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 1332
38.1%
본 1332
38.1%
허 261
 
7.5%
양 261
 
7.5%
말 54
 
1.5%
할 54
 
1.5%
월 54
 
1.5%
당 54
 
1.5%
제 35
 
1.0%
국 35
 
1.0%
Other values (3) 27
 
0.8%
Decimal Number
ValueCountFrequency (%)
0 630
18.7%
8 607
18.0%
2 514
15.2%
5 452
13.4%
3 405
12.0%
4 224
 
6.6%
1 201
 
6.0%
7 182
 
5.4%
6 98
 
2.9%
9 59
 
1.7%
Other Punctuation
ValueCountFrequency (%)
/ 283
53.6%
. 182
34.5%
, 60
 
11.4%
% 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 (%)
) 54
100.0%
Open Punctuation
ValueCountFrequency (%)
( 54
100.0%
Space Separator
ValueCountFrequency (%)
12
100.0%
Control
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4083
53.8%
Hangul 3499
46.1%
Latin 14
 
0.2%

Most frequent character per script

Common
ValueCountFrequency (%)
0 630
15.4%
8 607
14.9%
2 514
12.6%
5 452
11.1%
3 405
9.9%
/ 283
6.9%
4 224
 
5.5%
1 201
 
4.9%
. 182
 
4.5%
7 182
 
4.5%
Other values (9) 403
9.9%
Hangul
ValueCountFrequency (%)
기 1332
38.1%
본 1332
38.1%
허 261
 
7.5%
양 261
 
7.5%
말 54
 
1.5%
할 54
 
1.5%
월 54
 
1.5%
당 54
 
1.5%
제 35
 
1.0%
국 35
 
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 4097
53.9%
Hangul 3499
46.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
기 1332
38.1%
본 1332
38.1%
허 261
 
7.5%
양 261
 
7.5%
말 54
 
1.5%
할 54
 
1.5%
월 54
 
1.5%
당 54
 
1.5%
제 35
 
1.0%
국 35
 
1.0%
Other values (3) 27
 
0.8%
ASCII
ValueCountFrequency (%)
0 630
15.4%
8 607
14.8%
2 514
12.5%
5 452
11.0%
3 405
9.9%
/ 283
6.9%
4 224
 
5.5%
1 201
 
4.9%
. 182
 
4.4%
7 182
 
4.4%
Other values (13) 417
10.2%

칠레
Categorical

IMBALANCE 

Distinct19
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size13.0 KiB
0
1119 
<NA>
493 
0/20(1,000톤)
 
6
30
 
4
0/30(100톤)
 
4
Other values (14)
 
27

Length

Max length14
Median length1
Mean length2.0816697
Min length1

Unique

Unique5 ?
Unique (%)0.3%

Sample

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

Common Values

ValueCountFrequency (%)
0 1119
67.7%
<NA> 493
29.8%
0/20(1,000톤) 6
 
0.4%
30 4
 
0.2%
0/30(100톤) 4
 
0.2%
0/20(2,000톤) 4
 
0.2%
0/30(2,000톤) 3
 
0.2%
21.8 3
 
0.2%
0/30(200톤) 2
 
0.1%
4.8 2
 
0.1%
Other values (9) 13
 
0.8%

Length

2023-12-11T12:07:58.319829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0 1119
67.6%
na 493
29.8%
0/20(1,000톤 6
 
0.4%
30 4
 
0.2%
0/30(100톤 4
 
0.2%
0/20(2,000톤 4
 
0.2%
0/30(2,000톤 3
 
0.2%
21.8 3
 
0.2%
200톤 2
 
0.1%
0/36(1,000톤 2
 
0.1%
Other values (10) 15
 
0.9%

싱가포르
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct44
Distinct (%)2.7%
Missing0
Missing (%)0.0%
Memory size13.0 KiB
0
646 
<NA>
587 
5.5
 
64
4.9
 
60
1.5
 
56
Other values (39)
240 

Length

Max length16
Median length15
Mean length2.6473079
Min length1

Unique

Unique19 ?
Unique (%)1.1%

Sample

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

Common Values

ValueCountFrequency (%)
0 646
39.1%
<NA> 587
35.5%
5.5 64
 
3.9%
4.9 60
 
3.6%
1.5 56
 
3.4%
3.6 51
 
3.1%
8.2 33
 
2.0%
3.3 27
 
1.6%
4.1 20
 
1.2%
2.7 14
 
0.8%
Other values (34) 95
 
5.7%

Length

2023-12-11T12:07:58.455601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
0 646
38.7%
na 587
35.1%
5.5 70
 
4.2%
4.9 60
 
3.6%
1.5 56
 
3.4%
3.6 51
 
3.1%
8.2 33
 
2.0%
3.3 27
 
1.6%
4.1 20
 
1.2%
2.7 14
 
0.8%
Other values (36) 107
 
6.4%

스위스
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct39
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size13.0 KiB
<NA>
1131 
0
196 
6.4
 
101
4.8
 
44
4
 
31
Other values (34)
150 

Length

Max length19
Median length4
Mean length3.4646098
Min length1

Unique

Unique10 ?
Unique (%)0.6%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1131
68.4%
0 196
 
11.9%
6.4 101
 
6.1%
4.8 44
 
2.7%
4 31
 
1.9%
27 16
 
1.0%
18 15
 
0.9%
2.7 14
 
0.8%
24 13
 
0.8%
1.4 9
 
0.5%
Other values (29) 83
 
5.0%

Length

2023-12-11T12:07:58.611546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 1131
67.8%
0 196
 
11.8%
6.4 101
 
6.1%
4.8 44
 
2.6%
4 31
 
1.9%
27 16
 
1.0%
18 15
 
0.9%
2.7 14
 
0.8%
24 13
 
0.8%
1.4 9
 
0.5%
Other values (33) 98
 
5.9%

노르웨이
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct32
Distinct (%)4.4%
Missing930
Missing (%)56.3%
Infinite0
Infinite (%)0.0%
Mean4.9918396
Minimum0
Maximum36
Zeros270
Zeros (%)16.3%
Negative0
Negative (%)0.0%
Memory size14.7 KiB
2023-12-11T12:07:58.757272image/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 deviation6.1345218
Coefficient of variation (CV)1.22891
Kurtosis6.7354177
Mean4.9918396
Median Absolute Deviation (MAD)2.4
Skewness2.3034409
Sum3609.1
Variance37.632357
MonotonicityNot monotonic
2023-12-11T12:07:58.911909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
0.0 270
 
16.3%
6.4 238
 
14.4%
4.8 44
 
2.7%
4.0 31
 
1.9%
7.2 22
 
1.3%
18.0 12
 
0.7%
1.4 9
 
0.5%
11.3 8
 
0.5%
3.6 7
 
0.4%
27.0 7
 
0.4%
Other values (22) 75
 
4.5%
(Missing) 930
56.3%
ValueCountFrequency (%)
0.0 270
16.3%
1.4 9
 
0.5%
2.4 6
 
0.4%
2.7 4
 
0.2%
3.6 7
 
0.4%
3.8 1
 
0.1%
4.0 31
 
1.9%
4.3 5
 
0.3%
4.5 1
 
0.1%
4.8 44
 
2.7%
ValueCountFrequency (%)
36.0 4
 
0.2%
32.0 1
 
0.1%
28.8 6
0.4%
27.0 7
0.4%
24.0 7
0.4%
21.6 5
0.3%
20.3 2
 
0.1%
18.0 12
0.7%
16.2 2
 
0.1%
15.8 6
0.4%

아이슬란드
Real number (ℝ)

HIGH CORRELATION  MISSING  ZEROS 

Distinct35
Distinct (%)3.8%
Missing733
Missing (%)44.3%
Infinite0
Infinite (%)0.0%
Mean6.7822826
Minimum0
Maximum36
Zeros307
Zeros (%)18.6%
Negative0
Negative (%)0.0%
Memory size14.7 KiB
2023-12-11T12:07:59.105403image/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 deviation7.7218062
Coefficient of variation (CV)1.1385262
Kurtosis1.0900749
Mean6.7822826
Median Absolute Deviation (MAD)6.4
Skewness1.3786079
Sum6239.7
Variance59.626291
MonotonicityNot monotonic
2023-12-11T12:07:59.271626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
0.0 307
18.6%
6.4 281
 
17.0%
24.3 53
 
3.2%
4.8 44
 
2.7%
4.0 35
 
2.1%
18.0 34
 
2.1%
16.2 25
 
1.5%
7.2 23
 
1.4%
22.5 9
 
0.5%
1.4 9
 
0.5%
Other values (25) 100
 
6.0%
(Missing) 733
44.3%
ValueCountFrequency (%)
0.0 307
18.6%
1.4 9
 
0.5%
2.4 6
 
0.4%
2.7 4
 
0.2%
3.6 7
 
0.4%
3.8 1
 
0.1%
4.0 35
 
2.1%
4.3 5
 
0.3%
4.5 1
 
0.1%
4.8 44
 
2.7%
ValueCountFrequency (%)
36.0 3
 
0.2%
32.0 1
 
0.1%
28.8 6
 
0.4%
27.0 7
 
0.4%
24.3 53
3.2%
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

Distinct81
Distinct (%)4.9%
Missing0
Missing (%)0.0%
Memory size13.0 KiB
2023-12-11T12:07:59.517372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length1
Mean length1.9788264
Min length1

Characters and Unicode

Total characters3271
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

Unique26 ?
Unique (%)1.6%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
0 1080
62.9%
20 125
 
7.3%
미양허 64
 
3.7%
8 38
 
2.2%
30 32
 
1.9%
45 28
 
1.6%
18 27
 
1.6%
or 25
 
1.5%
36 22
 
1.3%
754.3 16
 
0.9%
Other values (80) 261
 
15.2%
2023-12-11T12:07:59.887065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1386
42.4%
2 226
 
6.9%
3 147
 
4.5%
5 139
 
4.2%
8 138
 
4.2%
4 103
 
3.1%
. 95
 
2.9%
7 78
 
2.4%
6 75
 
2.3%
74
 
2.3%
Other values (32) 810
24.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2399
73.3%
Other Letter 285
 
8.7%
Other Punctuation 211
 
6.5%
Uppercase Letter 128
 
3.9%
Lowercase Letter 100
 
3.1%
Space Separator 74
 
2.3%
Open Punctuation 37
 
1.1%
Close Punctuation 37
 
1.1%

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 1386
57.8%
2 226
 
9.4%
3 147
 
6.1%
5 139
 
5.8%
8 138
 
5.8%
4 103
 
4.3%
7 78
 
3.3%
6 75
 
3.1%
1 70
 
2.9%
9 37
 
1.5%
Other Letter
ValueCountFrequency (%)
허 64
22.5%
양 64
22.5%
미 64
22.5%
외 28
9.8%
제 28
9.8%
원 25
 
8.8%
톤 9
 
3.2%
년 1
 
0.4%
월 1
 
0.4%
일 1
 
0.4%
Other Punctuation
ValueCountFrequency (%)
. 95
45.0%
, 54
25.6%
/ 34
 
16.1%
% 28
 
13.3%
Lowercase Letter
ValueCountFrequency (%)
k 25
25.0%
g 25
25.0%
o 25
25.0%
r 25
25.0%
Space Separator
ValueCountFrequency (%)
74
100.0%
Open Punctuation
ValueCountFrequency (%)
( 37
100.0%
Close Punctuation
ValueCountFrequency (%)
) 37
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2758
84.3%
Hangul 285
 
8.7%
Latin 228
 
7.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1386
50.3%
2 226
 
8.2%
3 147
 
5.3%
5 139
 
5.0%
8 138
 
5.0%
4 103
 
3.7%
. 95
 
3.4%
7 78
 
2.8%
6 75
 
2.7%
74
 
2.7%
Other values (7) 297
 
10.8%
Latin
ValueCountFrequency (%)
H 29
12.7%
k 25
11.0%
g 25
11.0%
o 25
11.0%
r 25
11.0%
P 17
7.5%
V 13
5.7%
N 13
5.7%
M 13
5.7%
T 12
 
5.3%
Other values (5) 31
13.6%
Hangul
ValueCountFrequency (%)
허 64
22.5%
양 64
22.5%
미 64
22.5%
외 28
9.8%
제 28
9.8%
원 25
 
8.8%
톤 9
 
3.2%
년 1
 
0.4%
월 1
 
0.4%
일 1
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2986
91.3%
Hangul 285
 
8.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1386
46.4%
2 226
 
7.6%
3 147
 
4.9%
5 139
 
4.7%
8 138
 
4.6%
4 103
 
3.4%
. 95
 
3.2%
7 78
 
2.6%
6 75
 
2.5%
74
 
2.5%
Other values (22) 525
 
17.6%
Hangul
ValueCountFrequency (%)
허 64
22.5%
양 64
22.5%
미 64
22.5%
외 28
9.8%
제 28
9.8%
원 25
 
8.8%
톤 9
 
3.2%
년 1
 
0.4%
월 1
 
0.4%
일 1
 
0.4%

인도
Categorical

HIGH CORRELATION 

Distinct42
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size13.0 KiB
미양허
798 
5.5
203 
3
183 
0
156 
1.9
 
54
Other values (37)
259 

Length

Max length18
Median length3
Mean length2.7168784
Min length1

Unique

Unique12 ?
Unique (%)0.7%

Sample

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

Common Values

ValueCountFrequency (%)
미양허 798
48.3%
5.5 203
 
12.3%
3 183
 
11.1%
0 156
 
9.4%
1.9 54
 
3.3%
1.1 45
 
2.7%
13.7 38
 
2.3%
6.1 20
 
1.2%
10.3 17
 
1.0%
12.4 13
 
0.8%
Other values (32) 126
 
7.6%

Length

2023-12-11T12:08:00.051406image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
미양허 798
47.9%
5.5 203
 
12.2%
3 183
 
11.0%
0 156
 
9.4%
1.9 54
 
3.2%
1.1 45
 
2.7%
13.7 38
 
2.3%
6.1 20
 
1.2%
10.3 17
 
1.0%
6.8 13
 
0.8%
Other values (37) 140
 
8.4%

EU(2013.7~2014.6)
Text

Distinct175
Distinct (%)10.6%
Missing0
Missing (%)0.0%
Memory size13.0 KiB
2023-12-11T12:08:00.277474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length1
Mean length3.0278282
Min length1

Characters and Unicode

Total characters5005
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 (%)4.6%

Sample

1st row0
2nd row4
3rd row4
4th row4
5th row4
ValueCountFrequency (%)
0 682
38.6%
4 122
 
6.9%
or 55
 
3.1%
5.8 49
 
2.8%
15 43
 
2.4%
21.8 40
 
2.3%
19.6 33
 
1.9%
16.3 32
 
1.8%
10 29
 
1.6%
13.5 29
 
1.6%
Other values (178) 651
36.9%
2023-12-11T12:08:00.633217image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 885
17.7%
. 623
12.4%
1 546
10.9%
2 416
8.3%
5 354
 
7.1%
4 280
 
5.6%
3 276
 
5.5%
6 265
 
5.3%
8 228
 
4.6%
7 152
 
3.0%
Other values (16) 980
19.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3551
70.9%
Other Punctuation 845
 
16.9%
Lowercase Letter 224
 
4.5%
Other Letter 150
 
3.0%
Space Separator 143
 
2.9%
Close Punctuation 46
 
0.9%
Open Punctuation 46
 
0.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 885
24.9%
1 546
15.4%
2 416
11.7%
5 354
 
10.0%
4 280
 
7.9%
3 276
 
7.8%
6 265
 
7.5%
8 228
 
6.4%
7 152
 
4.3%
9 149
 
4.2%
Other Letter
ValueCountFrequency (%)
원 56
37.3%
톤 46
30.7%
양 16
 
10.7%
미 16
 
10.7%
허 16
 
10.7%
Other Punctuation
ValueCountFrequency (%)
. 623
73.7%
/ 104
 
12.3%
, 62
 
7.3%
% 56
 
6.6%
Lowercase Letter
ValueCountFrequency (%)
k 56
25.0%
r 56
25.0%
o 56
25.0%
g 56
25.0%
Space Separator
ValueCountFrequency (%)
143
100.0%
Close Punctuation
ValueCountFrequency (%)
) 46
100.0%
Open Punctuation
ValueCountFrequency (%)
( 46
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4631
92.5%
Latin 224
 
4.5%
Hangul 150
 
3.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 885
19.1%
. 623
13.5%
1 546
11.8%
2 416
9.0%
5 354
 
7.6%
4 280
 
6.0%
3 276
 
6.0%
6 265
 
5.7%
8 228
 
4.9%
7 152
 
3.3%
Other values (7) 606
13.1%
Hangul
ValueCountFrequency (%)
원 56
37.3%
톤 46
30.7%
양 16
 
10.7%
미 16
 
10.7%
허 16
 
10.7%
Latin
ValueCountFrequency (%)
k 56
25.0%
r 56
25.0%
o 56
25.0%
g 56
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4855
97.0%
Hangul 150
 
3.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 885
18.2%
. 623
12.8%
1 546
11.2%
2 416
8.6%
5 354
 
7.3%
4 280
 
5.8%
3 276
 
5.7%
6 265
 
5.5%
8 228
 
4.7%
7 152
 
3.1%
Other values (11) 830
17.1%
Hangul
ValueCountFrequency (%)
원 56
37.3%
톤 46
30.7%
양 16
 
10.7%
미 16
 
10.7%
허 16
 
10.7%

EU(2014.7~2015.6)
Text

Distinct165
Distinct (%)10.0%
Missing0
Missing (%)0.0%
Memory size13.0 KiB
2023-12-11T12:08:00.831716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length20
Mean length2.9455535
Min length1

Characters and Unicode

Total characters4869
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

Unique69 ?
Unique (%)4.2%

Sample

1st row0
2nd row2.6
3rd row2.6
4th row2.6
5th row2.6
ValueCountFrequency (%)
0 699
39.6%
2.6 122
 
6.9%
or 56
 
3.2%
5 52
 
2.9%
10 46
 
2.6%
15 44
 
2.5%
19 40
 
2.3%
17.1 33
 
1.9%
14.3 32
 
1.8%
9 31
 
1.8%
Other values (166) 611
34.6%
2023-12-11T12:08:01.252255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 944
19.4%
. 595
12.2%
1 521
10.7%
2 439
9.0%
6 334
 
6.9%
5 301
 
6.2%
3 225
 
4.6%
4 203
 
4.2%
7 180
 
3.7%
9 166
 
3.4%
Other values (17) 961
19.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3443
70.7%
Other Punctuation 816
 
16.8%
Lowercase Letter 222
 
4.6%
Other Letter 150
 
3.1%
Space Separator 145
 
3.0%
Close Punctuation 46
 
0.9%
Open Punctuation 46
 
0.9%
Other Symbol 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 944
27.4%
1 521
15.1%
2 439
12.8%
6 334
 
9.7%
5 301
 
8.7%
3 225
 
6.5%
4 203
 
5.9%
7 180
 
5.2%
9 166
 
4.8%
8 130
 
3.8%
Other Letter
ValueCountFrequency (%)
원 56
37.3%
톤 46
30.7%
허 16
 
10.7%
양 16
 
10.7%
미 16
 
10.7%
Other Punctuation
ValueCountFrequency (%)
. 595
72.9%
/ 104
 
12.7%
, 61
 
7.5%
% 56
 
6.9%
Lowercase Letter
ValueCountFrequency (%)
o 56
25.2%
r 56
25.2%
k 55
24.8%
g 55
24.8%
Space Separator
ValueCountFrequency (%)
145
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 4497
92.4%
Latin 222
 
4.6%
Hangul 150
 
3.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 944
21.0%
. 595
13.2%
1 521
11.6%
2 439
9.8%
6 334
 
7.4%
5 301
 
6.7%
3 225
 
5.0%
4 203
 
4.5%
7 180
 
4.0%
9 166
 
3.7%
Other values (8) 589
13.1%
Hangul
ValueCountFrequency (%)
원 56
37.3%
톤 46
30.7%
허 16
 
10.7%
양 16
 
10.7%
미 16
 
10.7%
Latin
ValueCountFrequency (%)
o 56
25.2%
r 56
25.2%
k 55
24.8%
g 55
24.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4718
96.9%
Hangul 150
 
3.1%
CJK Compat 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 944
20.0%
. 595
12.6%
1 521
11.0%
2 439
9.3%
6 334
 
7.1%
5 301
 
6.4%
3 225
 
4.8%
4 203
 
4.3%
7 180
 
3.8%
9 166
 
3.5%
Other values (11) 810
17.2%
Hangul
ValueCountFrequency (%)
원 56
37.3%
톤 46
30.7%
허 16
 
10.7%
양 16
 
10.7%
미 16
 
10.7%
CJK Compat
ValueCountFrequency (%)
㎏ 1
100.0%

페루
Text

Distinct146
Distinct (%)8.8%
Missing0
Missing (%)0.0%
Memory size13.0 KiB
2023-12-11T12:08:01.597713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length19
Mean length2.9001815
Min length1

Characters and Unicode

Total characters4794
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 (%)3.4%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0
ValueCountFrequency (%)
0 475
26.9%
1.6 230
 
13.0%
18 79
 
4.5%
16.2 71
 
4.0%
27 60
 
3.4%
or 57
 
3.2%
4.8 54
 
3.1%
13.5 43
 
2.4%
6 36
 
2.0%
10.8 31
 
1.8%
Other values (146) 631
35.7%
2023-12-11T12:08:02.254351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 738
15.4%
1 676
14.1%
0 639
13.3%
6 472
9.8%
2 432
9.0%
8 278
 
5.8%
5 230
 
4.8%
3 225
 
4.7%
4 217
 
4.5%
7 182
 
3.8%
Other values (17) 705
14.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3434
71.6%
Other Punctuation 874
 
18.2%
Lowercase Letter 230
 
4.8%
Space Separator 149
 
3.1%
Other Letter 105
 
2.2%
Uppercase Letter 1
 
< 0.1%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 676
19.7%
0 639
18.6%
6 472
13.7%
2 432
12.6%
8 278
8.1%
5 230
 
6.7%
3 225
 
6.6%
4 217
 
6.3%
7 182
 
5.3%
9 83
 
2.4%
Lowercase Letter
ValueCountFrequency (%)
o 57
24.8%
r 57
24.8%
k 57
24.8%
g 57
24.8%
e 1
 
0.4%
p 1
 
0.4%
Other Punctuation
ValueCountFrequency (%)
. 738
84.4%
/ 58
 
6.6%
% 57
 
6.5%
, 21
 
2.4%
Other Letter
ValueCountFrequency (%)
원 57
54.3%
허 16
 
15.2%
양 16
 
15.2%
미 16
 
15.2%
Space Separator
ValueCountFrequency (%)
149
100.0%
Uppercase Letter
ValueCountFrequency (%)
S 1
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4458
93.0%
Latin 231
 
4.8%
Hangul 105
 
2.2%

Most frequent character per script

Common
ValueCountFrequency (%)
. 738
16.6%
1 676
15.2%
0 639
14.3%
6 472
10.6%
2 432
9.7%
8 278
 
6.2%
5 230
 
5.2%
3 225
 
5.0%
4 217
 
4.9%
7 182
 
4.1%
Other values (6) 369
8.3%
Latin
ValueCountFrequency (%)
o 57
24.7%
r 57
24.7%
k 57
24.7%
g 57
24.7%
S 1
 
0.4%
e 1
 
0.4%
p 1
 
0.4%
Hangul
ValueCountFrequency (%)
원 57
54.3%
허 16
 
15.2%
양 16
 
15.2%
미 16
 
15.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4689
97.8%
Hangul 105
 
2.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 738
15.7%
1 676
14.4%
0 639
13.6%
6 472
10.1%
2 432
9.2%
8 278
 
5.9%
5 230
 
4.9%
3 225
 
4.8%
4 217
 
4.6%
7 182
 
3.9%
Other values (13) 600
12.8%
Hangul
ValueCountFrequency (%)
원 57
54.3%
허 16
 
15.2%
양 16
 
15.2%
미 16
 
15.2%

미국
Text

Distinct163
Distinct (%)9.9%
Missing0
Missing (%)0.0%
Memory size13.0 KiB
2023-12-11T12:08:02.539870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length33
Median length28
Mean length3.4476709
Min length1

Characters and Unicode

Total characters5699
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

Unique63 ?
Unique (%)3.8%

Sample

1st row3.2
2nd row3.2
3rd row3.2
4th row3.2
5th row3.2
ValueCountFrequency (%)
0 628
35.4%
3.2 160
 
9.0%
5.6 57
 
3.2%
or 54
 
3.0%
21 48
 
2.7%
12 39
 
2.2%
18.9 36
 
2.0%
15.7 35
 
2.0%
8 34
 
1.9%
14 26
 
1.5%
Other values (169) 656
37.0%
2023-12-11T12:08:03.010024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 908
15.9%
. 690
12.1%
2 640
11.2%
1 584
10.2%
3 379
 
6.7%
5 365
 
6.4%
8 295
 
5.2%
6 242
 
4.2%
4 232
 
4.1%
/ 196
 
3.4%
Other values (16) 1168
20.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3909
68.6%
Other Punctuation 1026
 
18.0%
Lowercase Letter 216
 
3.8%
Other Letter 199
 
3.5%
Space Separator 154
 
2.7%
Close Punctuation 98
 
1.7%
Open Punctuation 97
 
1.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 908
23.2%
2 640
16.4%
1 584
14.9%
3 379
9.7%
5 365
9.3%
8 295
 
7.5%
6 242
 
6.2%
4 232
 
5.9%
7 152
 
3.9%
9 112
 
2.9%
Other Letter
ValueCountFrequency (%)
톤 97
48.7%
원 54
27.1%
양 16
 
8.0%
미 16
 
8.0%
허 16
 
8.0%
Other Punctuation
ValueCountFrequency (%)
. 690
67.3%
/ 196
 
19.1%
, 86
 
8.4%
% 54
 
5.3%
Lowercase Letter
ValueCountFrequency (%)
o 54
25.0%
k 54
25.0%
r 54
25.0%
g 54
25.0%
Space Separator
ValueCountFrequency (%)
154
100.0%
Close Punctuation
ValueCountFrequency (%)
) 98
100.0%
Open Punctuation
ValueCountFrequency (%)
( 97
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5284
92.7%
Latin 216
 
3.8%
Hangul 199
 
3.5%

Most frequent character per script

Common
ValueCountFrequency (%)
0 908
17.2%
. 690
13.1%
2 640
12.1%
1 584
11.1%
3 379
7.2%
5 365
6.9%
8 295
 
5.6%
6 242
 
4.6%
4 232
 
4.4%
/ 196
 
3.7%
Other values (7) 753
14.3%
Hangul
ValueCountFrequency (%)
톤 97
48.7%
원 54
27.1%
양 16
 
8.0%
미 16
 
8.0%
허 16
 
8.0%
Latin
ValueCountFrequency (%)
o 54
25.0%
k 54
25.0%
r 54
25.0%
g 54
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5500
96.5%
Hangul 199
 
3.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 908
16.5%
. 690
12.5%
2 640
11.6%
1 584
10.6%
3 379
 
6.9%
5 365
 
6.6%
8 295
 
5.4%
6 242
 
4.4%
4 232
 
4.2%
/ 196
 
3.6%
Other values (11) 969
17.6%
Hangul
ValueCountFrequency (%)
톤 97
48.7%
원 54
27.1%
양 16
 
8.0%
미 16
 
8.0%
허 16
 
8.0%

터키
Text

Distinct139
Distinct (%)8.4%
Missing0
Missing (%)0.0%
Memory size13.0 KiB
2023-12-11T12:08:03.321991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length19
Mean length3.0102843
Min length1

Characters and Unicode

Total characters4976
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

Unique45 ?
Unique (%)2.7%

Sample

1st row0
2nd row6.5
3rd row6.5
4th row6.5
5th row6.5
ValueCountFrequency (%)
6.5 251
 
14.1%
0 154
 
8.7%
30 123
 
6.9%
5.3 100
 
5.6%
27 98
 
5.5%
2 74
 
4.2%
or 61
 
3.4%
45 58
 
3.3%
18 49
 
2.8%
8 48
 
2.7%
Other values (142) 759
42.8%
2023-12-11T12:08:03.875741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 731
14.7%
5 659
13.2%
2 510
10.2%
0 481
9.7%
3 476
9.6%
6 447
9.0%
4 284
 
5.7%
1 240
 
4.8%
7 223
 
4.5%
8 221
 
4.4%
Other values (13) 704
14.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3609
72.5%
Other Punctuation 885
 
17.8%
Lowercase Letter 244
 
4.9%
Space Separator 130
 
2.6%
Other Letter 108
 
2.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 659
18.3%
2 510
14.1%
0 481
13.3%
3 476
13.2%
6 447
12.4%
4 284
7.9%
1 240
 
6.7%
7 223
 
6.2%
8 221
 
6.1%
9 68
 
1.9%
Other Punctuation
ValueCountFrequency (%)
. 731
82.6%
/ 61
 
6.9%
% 61
 
6.9%
, 32
 
3.6%
Lowercase Letter
ValueCountFrequency (%)
g 61
25.0%
k 61
25.0%
o 61
25.0%
r 61
25.0%
Other Letter
ValueCountFrequency (%)
원 60
55.6%
허 16
 
14.8%
양 16
 
14.8%
미 16
 
14.8%
Space Separator
ValueCountFrequency (%)
130
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4624
92.9%
Latin 244
 
4.9%
Hangul 108
 
2.2%

Most frequent character per script

Common
ValueCountFrequency (%)
. 731
15.8%
5 659
14.3%
2 510
11.0%
0 481
10.4%
3 476
10.3%
6 447
9.7%
4 284
 
6.1%
1 240
 
5.2%
7 223
 
4.8%
8 221
 
4.8%
Other values (5) 352
7.6%
Latin
ValueCountFrequency (%)
g 61
25.0%
k 61
25.0%
o 61
25.0%
r 61
25.0%
Hangul
ValueCountFrequency (%)
원 60
55.6%
허 16
 
14.8%
양 16
 
14.8%
미 16
 
14.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4868
97.8%
Hangul 108
 
2.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 731
15.0%
5 659
13.5%
2 510
10.5%
0 481
9.9%
3 476
9.8%
6 447
9.2%
4 284
 
5.8%
1 240
 
4.9%
7 223
 
4.6%
8 221
 
4.5%
Other values (9) 596
12.2%
Hangul
ValueCountFrequency (%)
원 60
55.6%
허 16
 
14.8%
양 16
 
14.8%
미 16
 
14.8%

콜롬비아
Text

Distinct172
Distinct (%)10.4%
Missing0
Missing (%)0.0%
Memory size13.0 KiB
2023-12-11T12:08:04.324664image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length19
Mean length3.4107683
Min length1

Characters and Unicode

Total characters5638
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

Unique67 ?
Unique (%)4.1%

Sample

1st row0
2nd row6.4
3rd row6.4
4th row6.4
5th row6.4
ValueCountFrequency (%)
6.4 348
19.7%
0 246
 
13.9%
7.2 78
 
4.4%
or 56
 
3.2%
24.3 55
 
3.1%
27 49
 
2.8%
28.1 38
 
2.2%
3.3 35
 
2.0%
18.7 31
 
1.8%
40.5 28
 
1.6%
Other values (171) 801
45.4%
2023-12-11T12:08:05.010672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
. 1085
19.2%
4 695
12.3%
2 587
10.4%
6 549
9.7%
0 437
7.8%
3 407
 
7.2%
7 341
 
6.0%
1 341
 
6.0%
5 288
 
5.1%
8 230
 
4.1%
Other values (16) 678
12.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3945
70.0%
Other Punctuation 1230
 
21.8%
Lowercase Letter 224
 
4.0%
Space Separator 120
 
2.1%
Other Letter 109
 
1.9%
Open Punctuation 5
 
0.1%
Close Punctuation 5
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
4 695
17.6%
2 587
14.9%
6 549
13.9%
0 437
11.1%
3 407
10.3%
7 341
8.6%
1 341
8.6%
5 288
7.3%
8 230
 
5.8%
9 70
 
1.8%
Other Letter
ValueCountFrequency (%)
원 56
51.4%
허 16
 
14.7%
양 16
 
14.7%
미 16
 
14.7%
톤 5
 
4.6%
Other Punctuation
ValueCountFrequency (%)
. 1085
88.2%
/ 62
 
5.0%
% 56
 
4.6%
, 27
 
2.2%
Lowercase Letter
ValueCountFrequency (%)
o 56
25.0%
r 56
25.0%
k 56
25.0%
g 56
25.0%
Space Separator
ValueCountFrequency (%)
120
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5305
94.1%
Latin 224
 
4.0%
Hangul 109
 
1.9%

Most frequent character per script

Common
ValueCountFrequency (%)
. 1085
20.5%
4 695
13.1%
2 587
11.1%
6 549
10.3%
0 437
8.2%
3 407
 
7.7%
7 341
 
6.4%
1 341
 
6.4%
5 288
 
5.4%
8 230
 
4.3%
Other values (7) 345
 
6.5%
Hangul
ValueCountFrequency (%)
원 56
51.4%
허 16
 
14.7%
양 16
 
14.7%
미 16
 
14.7%
톤 5
 
4.6%
Latin
ValueCountFrequency (%)
o 56
25.0%
r 56
25.0%
k 56
25.0%
g 56
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5529
98.1%
Hangul 109
 
1.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
. 1085
19.6%
4 695
12.6%
2 587
10.6%
6 549
9.9%
0 437
7.9%
3 407
 
7.4%
7 341
 
6.2%
1 341
 
6.2%
5 288
 
5.2%
8 230
 
4.2%
Other values (11) 569
10.3%
Hangul
ValueCountFrequency (%)
원 56
51.4%
허 16
 
14.7%
양 16
 
14.7%
미 16
 
14.7%
톤 5
 
4.6%

개방구분
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct8
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size13.0 KiB
<NA>
1358 
TC
 
76
TM
 
52
BM
 
51
BC
 
49
Other values (3)
 
67

Length

Max length4
Median length4
Mean length3.6430732
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> 1358
82.2%
TC 76
 
4.6%
TM 52
 
3.1%
BM 51
 
3.1%
BC 49
 
3.0%
BX 41
 
2.5%
ST 16
 
1.0%
TX 10
 
0.6%

Length

2023-12-11T12:08:05.529442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T12:08:05.689085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1358
82.2%
tc 76
 
4.6%
tm 52
 
3.1%
bm 51
 
3.1%
bc 49
 
3.0%
bx 41
 
2.5%
st 16
 
1.0%
tx 10
 
0.6%

Interactions

2023-12-11T12:07:54.337301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T12:07:54.074385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T12:07:54.468709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T12:07:54.193961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T12:08:05.810421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
칠레싱가포르스위스노르웨이아이슬란드아세안인도개방구분
칠레1.0000.2830.4050.4730.4770.6540.0000.584
싱가포르0.2831.0000.9900.8780.9140.9380.9640.878
스위스0.4050.9901.0001.0001.0000.9410.9400.765
노르웨이0.4730.8781.0001.0000.9990.6810.8270.800
아이슬란드0.4770.9141.0000.9991.0000.6720.8630.772
아세안0.6540.9380.9410.6810.6721.0000.0000.898
인도0.0000.9640.9400.8270.8630.0001.0000.644
개방구분0.5840.8780.7650.8000.7720.8980.6441.000
2023-12-11T12:08:05.965191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
스위스개방구분싱가포르칠레인도
스위스1.0000.6180.8390.2110.533
개방구분0.6181.0000.5540.3920.357
싱가포르0.8390.5541.0000.1160.542
칠레0.2110.3920.1161.0000.000
인도0.5330.3570.5420.0001.000
2023-12-11T12:08:06.075937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
노르웨이아이슬란드칠레싱가포르스위스인도개방구분
노르웨이1.0000.9550.2210.6140.9820.4740.414
아이슬란드0.9551.0000.2260.6980.9810.5510.633
칠레0.2210.2261.0000.1160.2110.0000.392
싱가포르0.6140.6980.1161.0000.8390.5420.554
스위스0.9820.9810.2110.8391.0000.5330.618
인도0.4740.5510.0000.5420.5331.0000.357
개방구분0.4140.6330.3920.5540.6180.3571.000

Missing values

2023-12-11T12:07:54.631849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T12:07:54.873878image/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.
2023-12-11T12:07:55.039901image/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

H S K한 글 품 명영 문 품 명2014 실행세율칠레싱가포르스위스노르웨이아이슬란드아세안인도EU(2013.7~2014.6)EU(2014.7~2015.6)페루미국터키콜롬비아개방구분
00101.21.1000말(번식용/농가사육용)Horses: Pure-bred breeding anmials(For farm breeding)기본0006.46.44.0030003.200<NA>
10101.21.9000말(번식용/기타)Horses: Pure-bred breeding anmials(Other)기본8006.46.46.40342.603.26.56.4<NA>
20101.29.1000말(기타/경주말)Horses: Other(Horses for racing)기본80006.40.00342.603.26.56.4<NA>
30101.29.9000말(기타/기타)Horses: Other(Other)기본80046.44.00342.603.26.56.4<NA>
40101.30.1000당나귀(번식용)Asses: Pure-bred breeding animals기본8006.46.46.40342.603.26.56.4<NA>
50101.30.9000당나귀(기타)Asses: Other기본80046.44.0035.8505.66.56.4<NA>
60101.90.0000기타(기타)Other기본80046.44.0035.8505.66.56.4<NA>
70102.21.1000축우(번식용/젖소)Cattle: Pure-bred breeding animals(For milk)양허0/89.1000<NA><NA>033.4000089.10TM
80102.21.2000축우(번식용/육우)Cattle: Pure-bred breeding animals(For meat)양허0/89.1000<NA><NA>033.4000089.10TM
90102.21.9000축우(번식용/기타)Cattle: Pure-bred breeding animals(Other)양허0/89.1000<NA><NA>033.4000089.10TM
H S K한 글 품 명영 문 품 명2014 실행세율칠레싱가포르스위스노르웨이아이슬란드아세안인도EU(2013.7~2014.6)EU(2014.7~2015.6)페루미국터키콜롬비아개방구분
16435203.00.0000면(카드 or 코움한 것)Cotton, carded or combed기본00000.00.000000000<NA>
16445301.10.0000생아마 or 침지아마Flax, raw or retted기본20000.00.000000000<NA>
16455301.21.0000아마(쇄경 or 타마한 것)Flax(broken or scutched)기본20000.00.000000000<NA>
16465301.29.0000아마(기타)Other flax기본20000.00.000000000<NA>
16475301.30.1000아마의 토우Flax tow기본20000.00.000000000<NA>
16485301.30.2000아마의 웨이스트Flax waste기본20000.00.000000000<NA>
16495302.10.0000생대마 or 침지대마True hemp, raw or retted기본20000.00.000000000<NA>
16505302.90.1000쇄경, 탐, 핵클 or 기타의 방법으로 가공한 대마True hemp, broken, scutched, hackled or other wise processed기본20000.00.000000000<NA>
16515302.90.2010대마의 토우Tow of true hemp기본20000.00.000000000<NA>
16525302.90.2020대마의 웨이스트Waste of true hemp기본20000.00.000000000<NA>