Overview

Dataset statistics

Number of variables8
Number of observations386
Missing cells614
Missing cells (%)19.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory24.6 KiB
Average record size in memory65.3 B

Variable types

Categorical2
Text6

Dataset

Description화장품 관련업종 바이어 연락처(주소, 전화번호, 이메일 등) 정보입니다.
Author한국무역보험공사
URLhttps://www.data.go.kr/data/15063396/fileData.do

Alerts

업종한글명 is highly overall correlated with 업종코드High correlation
업종코드 is highly overall correlated with 업종한글명High correlation
전화번호 has 44 (11.4%) missing valuesMissing
팩스번호 has 249 (64.5%) missing valuesMissing
이메일 has 172 (44.6%) missing valuesMissing
홈페이지 has 149 (38.6%) missing valuesMissing

Reproduction

Analysis started2023-12-12 08:40:32.235859
Analysis finished2023-12-12 08:40:32.836973
Duration0.6 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업종코드
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
46443
230 
20423
119 
47813
37 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row20423
2nd row20423
3rd row47813
4th row46443
5th row46443

Common Values

ValueCountFrequency (%)
46443 230
59.6%
20423 119
30.8%
47813 37
 
9.6%

Length

2023-12-12T17:40:32.902452image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:40:33.007744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
46443 230
59.6%
20423 119
30.8%
47813 37
 
9.6%

업종한글명
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
화장품및화장용품도매업
230 
화장품제조업
119 
화장품,비누및방향제소매업
37 

Length

Max length13
Median length11
Mean length9.6502591
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row화장품제조업
2nd row화장품제조업
3rd row화장품,비누및방향제소매업
4th row화장품및화장용품도매업
5th row화장품및화장용품도매업

Common Values

ValueCountFrequency (%)
화장품및화장용품도매업 230
59.6%
화장품제조업 119
30.8%
화장품,비누및방향제소매업 37
 
9.6%

Length

2023-12-12T17:40:33.128230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:40:33.248594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
화장품및화장용품도매업 230
59.6%
화장품제조업 119
30.8%
화장품,비누및방향제소매업 37
 
9.6%

상호명
Text

Distinct385
Distinct (%)99.7%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
2023-12-12T17:40:33.445929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length127
Median length52
Mean length24.634715
Min length3

Characters and Unicode

Total characters9509
Distinct characters35
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

Unique384 ?
Unique (%)99.5%

Sample

1st rowUNILEVERNIGERIAPLC
2nd rowINTERNATIONALFLAVORSANDFRAGRANCESIFFSOUTHAFRICAPTYLTD
3rd rowPERMARKSUPPLYNETWORKPTYLTD
4th rowPROACTIVESAPTYLTD
5th rowNORCOSMETICSAS
ValueCountFrequency (%)
beiersdorfsa 2
 
0.5%
unilevernigeriaplc 1
 
0.3%
aandhinternationalcosmeticscoltd 1
 
0.3%
guangzhoubairuncosmeticcoltd 1
 
0.3%
beijingcranetradingcoltd 1
 
0.3%
zhejiangdonghecosmeticscoltd 1
 
0.3%
gracetieshanghaiinternationaltradingcoltd 1
 
0.3%
ancorsshanghaicosmeticscoltd 1
 
0.3%
zhoushankonaelectroniccommercecoltd 1
 
0.3%
hkdinformationtechnologyhangzhoucoltd 1
 
0.3%
Other values (375) 375
97.2%
2023-12-12T17:40:34.226200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
A 888
 
9.3%
I 879
 
9.2%
E 782
 
8.2%
T 721
 
7.6%
O 701
 
7.4%
N 685
 
7.2%
L 602
 
6.3%
C 585
 
6.2%
S 523
 
5.5%
R 503
 
5.3%
Other values (25) 2640
27.8%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 9440
99.3%
Close Punctuation 29
 
0.3%
Open Punctuation 29
 
0.3%
Decimal Number 8
 
0.1%
Other Punctuation 3
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
A 888
 
9.4%
I 879
 
9.3%
E 782
 
8.3%
T 721
 
7.6%
O 701
 
7.4%
N 685
 
7.3%
L 602
 
6.4%
C 585
 
6.2%
S 523
 
5.5%
R 503
 
5.3%
Other values (17) 2571
27.2%
Decimal Number
ValueCountFrequency (%)
9 3
37.5%
1 2
25.0%
5 1
 
12.5%
6 1
 
12.5%
2 1
 
12.5%
Close Punctuation
ValueCountFrequency (%)
) 29
100.0%
Open Punctuation
ValueCountFrequency (%)
( 29
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 9439
99.3%
Common 69
 
0.7%
Cyrillic 1
 
< 0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
A 888
 
9.4%
I 879
 
9.3%
E 782
 
8.3%
T 721
 
7.6%
O 701
 
7.4%
N 685
 
7.3%
L 602
 
6.4%
C 585
 
6.2%
S 523
 
5.5%
R 503
 
5.3%
Other values (16) 2570
27.2%
Common
ValueCountFrequency (%)
) 29
42.0%
( 29
42.0%
/ 3
 
4.3%
9 3
 
4.3%
1 2
 
2.9%
5 1
 
1.4%
6 1
 
1.4%
2 1
 
1.4%
Cyrillic
ValueCountFrequency (%)
С 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 9508
> 99.9%
Cyrillic 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
A 888
 
9.3%
I 879
 
9.2%
E 782
 
8.2%
T 721
 
7.6%
O 701
 
7.4%
N 685
 
7.2%
L 602
 
6.3%
C 585
 
6.2%
S 523
 
5.5%
R 503
 
5.3%
Other values (24) 2639
27.8%
Cyrillic
ValueCountFrequency (%)
С 1
100.0%

주소
Text

Distinct385
Distinct (%)99.7%
Missing0
Missing (%)0.0%
Memory size3.1 KiB
2023-12-12T17:40:34.527543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length140
Median length96
Mean length65.26943
Min length21

Characters and Unicode

Total characters25194
Distinct characters53
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique384 ?
Unique (%)99.5%

Sample

1st row1,BILLINGSWAYOREGUNIKEJALAGOSNIGERIA
2nd row34DIESELRD,ISANDO1600
3rd row50ANGUSCRES,MODDERFONTEINEDENVALE1609
4th row301STAVENUEEDENVALEEDENVALE1609ZA
5th rowASLAKVEIEN14E,0753,OSLO
ValueCountFrequency (%)
amkronbergerhang2d65824schwalbach 2
 
0.5%
1,billingswayoregunikejalagosnigeria 1
 
0.3%
factorybuilding3,4&5,no.1298,jutingrd.,fengxiandistrict,shanghai,china 1
 
0.3%
room805,self-codedbldg.b1,2707kachuangavenue,high-techindustrialdevelopmentzone,guangzhou,china 1
 
0.3%
self-numbered3,no.149taigang3rdrd.,gangwei,renhetown,baiyundistrict,guangzhou 1
 
0.3%
no.32-5019,yard5,guangshunnorthstreet,chaoyangdistrict,beijing 1
 
0.3%
room503,5thfloor,towera,yanxiangtechnologybuilding,no.333jianghongroad,changhesubdistrict,binjiangdistrict,hangzhou,zhejiang 1
 
0.3%
5f,no.310,jingaoroad,pudongnewarea,shanghaicity 1
 
0.3%
891qianqiaoroad,fengxiandistrict,shanghaicity 1
 
0.3%
room305-16002,enterpriseservicecenterofzhoushanportcomprehensivebondedzone,dinghaidistrict,zhoushancity,zhejiangprovince(pilotfreetradezone 1
 
0.3%
Other values (375) 375
97.2%
2023-12-12T17:40:35.024271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
A 2548
 
10.1%
I 1720
 
6.8%
N 1699
 
6.7%
O 1462
 
5.8%
E 1458
 
5.8%
, 1364
 
5.4%
R 1271
 
5.0%
T 1239
 
4.9%
S 1045
 
4.1%
L 820
 
3.3%
Other values (43) 10568
41.9%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 20081
79.7%
Decimal Number 3026
 
12.0%
Other Punctuation 1782
 
7.1%
Dash Punctuation 235
 
0.9%
Open Punctuation 32
 
0.1%
Close Punctuation 32
 
0.1%
Other Letter 5
 
< 0.1%
Other Symbol 1
 
< 0.1%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
A 2548
12.7%
I 1720
 
8.6%
N 1699
 
8.5%
O 1462
 
7.3%
E 1458
 
7.3%
R 1271
 
6.3%
T 1239
 
6.2%
S 1045
 
5.2%
L 820
 
4.1%
D 788
 
3.9%
Other values (17) 6031
30.0%
Decimal Number
ValueCountFrequency (%)
0 601
19.9%
1 577
19.1%
2 380
12.6%
3 307
10.1%
5 257
8.5%
4 227
 
7.5%
6 200
 
6.6%
7 193
 
6.4%
8 154
 
5.1%
9 130
 
4.3%
Other Punctuation
ValueCountFrequency (%)
, 1364
76.5%
. 299
 
16.8%
/ 76
 
4.3%
: 15
 
0.8%
# 14
 
0.8%
& 6
 
0.3%
' 4
 
0.2%
¡ 4
 
0.2%
Other Letter
ValueCountFrequency (%)
자 2
40.0%
대 1
20.0%
표 1
20.0%
택 1
20.0%
Dash Punctuation
ValueCountFrequency (%)
- 235
100.0%
Open Punctuation
ValueCountFrequency (%)
( 32
100.0%
Close Punctuation
ValueCountFrequency (%)
) 32
100.0%
Other Symbol
ValueCountFrequency (%)
№ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 20081
79.7%
Common 5108
 
20.3%
Hangul 5
 
< 0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
A 2548
12.7%
I 1720
 
8.6%
N 1699
 
8.5%
O 1462
 
7.3%
E 1458
 
7.3%
R 1271
 
6.3%
T 1239
 
6.2%
S 1045
 
5.2%
L 820
 
4.1%
D 788
 
3.9%
Other values (17) 6031
30.0%
Common
ValueCountFrequency (%)
, 1364
26.7%
0 601
11.8%
1 577
11.3%
2 380
 
7.4%
3 307
 
6.0%
. 299
 
5.9%
5 257
 
5.0%
- 235
 
4.6%
4 227
 
4.4%
6 200
 
3.9%
Other values (12) 661
12.9%
Hangul
ValueCountFrequency (%)
자 2
40.0%
대 1
20.0%
표 1
20.0%
택 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 25180
99.9%
None 8
 
< 0.1%
Hangul 5
 
< 0.1%
Letterlike Symbols 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
A 2548
 
10.1%
I 1720
 
6.8%
N 1699
 
6.7%
O 1462
 
5.8%
E 1458
 
5.8%
, 1364
 
5.4%
R 1271
 
5.0%
T 1239
 
4.9%
S 1045
 
4.2%
L 820
 
3.3%
Other values (36) 10554
41.9%
None
ValueCountFrequency (%)
¡ 4
50.0%
Æ 4
50.0%
Hangul
ValueCountFrequency (%)
자 2
40.0%
대 1
20.0%
표 1
20.0%
택 1
20.0%
Letterlike Symbols
ValueCountFrequency (%)
№ 1
100.0%

전화번호
Text

MISSING 

Distinct341
Distinct (%)99.7%
Missing44
Missing (%)11.4%
Memory size3.1 KiB
2023-12-12T17:40:35.362459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length15
Mean length12.596491
Min length8

Characters and Unicode

Total characters4308
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

Unique340 ?
Unique (%)99.4%

Sample

1st row234-1279-3000
2nd row271-1922-8800
3rd row271-1579-0000
4th row271-1454-5020
5th row47-4145-2727
ValueCountFrequency (%)
194-0898-7500 2
 
0.6%
8620-8221-8828 1
 
0.3%
234-1279-3000 1
 
0.3%
35-957-7335 1
 
0.3%
36-416-8555 1
 
0.3%
36-821-1519 1
 
0.3%
34-577-8515 1
 
0.3%
54-261-9191 1
 
0.3%
35-796-3340 1
 
0.3%
36-709-9840 1
 
0.3%
Other values (331) 331
96.8%
2023-12-12T17:40:35.863655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 672
15.6%
2 483
11.2%
1 409
9.5%
6 402
9.3%
8 381
8.8%
0 372
8.6%
5 342
7.9%
7 341
7.9%
3 314
7.3%
9 301
7.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3636
84.4%
Dash Punctuation 672
 
15.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 483
13.3%
1 409
11.2%
6 402
11.1%
8 381
10.5%
0 372
10.2%
5 342
9.4%
7 341
9.4%
3 314
8.6%
9 301
8.3%
4 291
8.0%
Dash Punctuation
ValueCountFrequency (%)
- 672
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4308
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 672
15.6%
2 483
11.2%
1 409
9.5%
6 402
9.3%
8 381
8.8%
0 372
8.6%
5 342
7.9%
7 341
7.9%
3 314
7.3%
9 301
7.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4308
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 672
15.6%
2 483
11.2%
1 409
9.5%
6 402
9.3%
8 381
8.8%
0 372
8.6%
5 342
7.9%
7 341
7.9%
3 314
7.3%
9 301
7.0%

팩스번호
Text

MISSING 

Distinct137
Distinct (%)100.0%
Missing249
Missing (%)64.5%
Memory size3.1 KiB
2023-12-12T17:40:36.179313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length13
Mean length12.846715
Min length8

Characters and Unicode

Total characters1760
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

Unique137 ?
Unique (%)100.0%

Sample

1st row271-1974-7447
2nd row271-1608-0601
3rd row8862-2221-6234
4th row8862-8698-1066
5th row8862-2388-2159
ValueCountFrequency (%)
4053-0366-9799 1
 
0.7%
8621-6128-0186 1
 
0.7%
8621-2420-8276 1
 
0.7%
8620-8603-1038 1
 
0.7%
8610-5718-7823 1
 
0.7%
8621-6031-8715 1
 
0.7%
8620-8518-6134 1
 
0.7%
4584-1163 1
 
0.7%
6221-2980-9501 1
 
0.7%
971-4363-5662 1
 
0.7%
Other values (127) 127
92.7%
2023-12-12T17:40:36.639515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 270
15.3%
2 222
12.6%
6 179
10.2%
8 161
9.1%
1 160
9.1%
5 141
8.0%
3 135
7.7%
9 134
7.6%
7 130
7.4%
4 116
6.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1490
84.7%
Dash Punctuation 270
 
15.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 222
14.9%
6 179
12.0%
8 161
10.8%
1 160
10.7%
5 141
9.5%
3 135
9.1%
9 134
9.0%
7 130
8.7%
4 116
7.8%
0 112
7.5%
Dash Punctuation
ValueCountFrequency (%)
- 270
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1760
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 270
15.3%
2 222
12.6%
6 179
10.2%
8 161
9.1%
1 160
9.1%
5 141
8.0%
3 135
7.7%
9 134
7.6%
7 130
7.4%
4 116
6.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1760
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 270
15.3%
2 222
12.6%
6 179
10.2%
8 161
9.1%
1 160
9.1%
5 141
8.0%
3 135
7.7%
9 134
7.6%
7 130
7.4%
4 116
6.6%

이메일
Text

MISSING 

Distinct213
Distinct (%)99.5%
Missing172
Missing (%)44.6%
Memory size3.1 KiB
2023-12-12T17:40:36.961370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length36
Median length31
Mean length21.102804
Min length12

Characters and Unicode

Total characters4516
Distinct characters59
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique212 ?
Unique (%)99.1%

Sample

1st rowconsumercare.nigeria@unilever.com
2nd rowaccpayza@iff.com
3rd rowabel.b@permark.co.za
4th roworders@proactivesa.co.za
5th rowventas@grupoledu.com
ValueCountFrequency (%)
info@ptn-global.com 2
 
0.9%
support@bloomigo.com 1
 
0.5%
consumercare.nigeria@unilever.com 1
 
0.5%
vinayj.msl@gmail.com 1
 
0.5%
ayman.makram@lunapac.com 1
 
0.5%
info@huwell.it 1
 
0.5%
info@mavive.com 1
 
0.5%
info@fabyline.it 1
 
0.5%
krishnan.d@suntara-india.com 1
 
0.5%
sales.saiwellness@gmail.com 1
 
0.5%
Other values (203) 203
94.9%
2023-12-12T17:40:37.446171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
o 425
 
9.4%
a 377
 
8.3%
i 307
 
6.8%
m 301
 
6.7%
c 291
 
6.4%
. 285
 
6.3%
e 275
 
6.1%
n 239
 
5.3%
r 221
 
4.9%
@ 214
 
4.7%
Other values (49) 1581
35.0%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 3863
85.5%
Other Punctuation 499
 
11.0%
Uppercase Letter 94
 
2.1%
Decimal Number 33
 
0.7%
Dash Punctuation 19
 
0.4%
Connector Punctuation 8
 
0.2%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
o 425
11.0%
a 377
 
9.8%
i 307
 
7.9%
m 301
 
7.8%
c 291
 
7.5%
e 275
 
7.1%
n 239
 
6.2%
r 221
 
5.7%
s 186
 
4.8%
l 183
 
4.7%
Other values (16) 1058
27.4%
Uppercase Letter
ValueCountFrequency (%)
O 13
13.8%
E 10
10.6%
M 10
10.6%
I 9
9.6%
C 8
 
8.5%
N 7
 
7.4%
T 5
 
5.3%
R 5
 
5.3%
F 4
 
4.3%
B 3
 
3.2%
Other values (10) 20
21.3%
Decimal Number
ValueCountFrequency (%)
1 8
24.2%
0 6
18.2%
7 4
12.1%
5 4
12.1%
9 3
 
9.1%
6 3
 
9.1%
2 2
 
6.1%
4 2
 
6.1%
8 1
 
3.0%
Other Punctuation
ValueCountFrequency (%)
. 285
57.1%
@ 214
42.9%
Dash Punctuation
ValueCountFrequency (%)
- 19
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 3957
87.6%
Common 559
 
12.4%

Most frequent character per script

Latin
ValueCountFrequency (%)
o 425
 
10.7%
a 377
 
9.5%
i 307
 
7.8%
m 301
 
7.6%
c 291
 
7.4%
e 275
 
6.9%
n 239
 
6.0%
r 221
 
5.6%
s 186
 
4.7%
l 183
 
4.6%
Other values (36) 1152
29.1%
Common
ValueCountFrequency (%)
. 285
51.0%
@ 214
38.3%
- 19
 
3.4%
1 8
 
1.4%
_ 8
 
1.4%
0 6
 
1.1%
7 4
 
0.7%
5 4
 
0.7%
9 3
 
0.5%
6 3
 
0.5%
Other values (3) 5
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4516
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
o 425
 
9.4%
a 377
 
8.3%
i 307
 
6.8%
m 301
 
6.7%
c 291
 
6.4%
. 285
 
6.3%
e 275
 
6.1%
n 239
 
5.3%
r 221
 
4.9%
@ 214
 
4.7%
Other values (49) 1581
35.0%

홈페이지
Text

MISSING 

Distinct235
Distinct (%)99.2%
Missing149
Missing (%)38.6%
Memory size3.1 KiB
2023-12-12T17:40:37.770056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length40
Median length30
Mean length20.388186
Min length10

Characters and Unicode

Total characters4832
Distinct characters56
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique233 ?
Unique (%)98.3%

Sample

1st rowwww.unilevernigeria.com
2nd rowhttp://www.iff.com
3rd rowhttp://www.proactivesa.co.za
4th rowhttps://www.drcyjhcc.com.tw
5th rowhttp://www.cloversmedtech.com/
ValueCountFrequency (%)
www.symrise.com 2
 
0.8%
http://www.cosmobeauty.co.jp 2
 
0.8%
www.pg.com 2
 
0.8%
www.advancedcosmeceuticals.com.au 1
 
0.4%
www.fabindo.com 1
 
0.4%
https://www.mtg.gr.jp 1
 
0.4%
www.inoherb.com 1
 
0.4%
http://www.kcinnerbella.com 1
 
0.4%
www.unilevernigeria.com 1
 
0.4%
www.avenirpacific.com.au 1
 
0.4%
Other values (224) 224
94.5%
2023-12-12T17:40:38.231060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
w 626
 
13.0%
. 494
 
10.2%
o 332
 
6.9%
t 323
 
6.7%
c 258
 
5.3%
/ 241
 
5.0%
m 238
 
4.9%
e 226
 
4.7%
a 220
 
4.6%
i 187
 
3.9%
Other values (46) 1687
34.9%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 3849
79.7%
Other Punctuation 832
 
17.2%
Uppercase Letter 109
 
2.3%
Dash Punctuation 33
 
0.7%
Decimal Number 5
 
0.1%
Open Punctuation 2
 
< 0.1%
Close Punctuation 2
 
< 0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
w 626
16.3%
o 332
 
8.6%
t 323
 
8.4%
c 258
 
6.7%
m 238
 
6.2%
e 226
 
5.9%
a 220
 
5.7%
i 187
 
4.9%
p 183
 
4.8%
s 162
 
4.2%
Other values (16) 1094
28.4%
Uppercase Letter
ValueCountFrequency (%)
W 18
16.5%
M 13
11.9%
O 12
11.0%
E 10
9.2%
C 9
 
8.3%
I 7
 
6.4%
N 6
 
5.5%
T 4
 
3.7%
R 4
 
3.7%
Y 3
 
2.8%
Other values (10) 23
21.1%
Other Punctuation
ValueCountFrequency (%)
. 494
59.4%
/ 241
29.0%
: 96
 
11.5%
' 1
 
0.1%
Decimal Number
ValueCountFrequency (%)
1 2
40.0%
8 2
40.0%
5 1
20.0%
Dash Punctuation
ValueCountFrequency (%)
- 33
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 3958
81.9%
Common 874
 
18.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
w 626
15.8%
o 332
 
8.4%
t 323
 
8.2%
c 258
 
6.5%
m 238
 
6.0%
e 226
 
5.7%
a 220
 
5.6%
i 187
 
4.7%
p 183
 
4.6%
s 162
 
4.1%
Other values (36) 1203
30.4%
Common
ValueCountFrequency (%)
. 494
56.5%
/ 241
27.6%
: 96
 
11.0%
- 33
 
3.8%
1 2
 
0.2%
( 2
 
0.2%
) 2
 
0.2%
8 2
 
0.2%
5 1
 
0.1%
' 1
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4832
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
w 626
 
13.0%
. 494
 
10.2%
o 332
 
6.9%
t 323
 
6.7%
c 258
 
5.3%
/ 241
 
5.0%
m 238
 
4.9%
e 226
 
4.7%
a 220
 
4.6%
i 187
 
3.9%
Other values (46) 1687
34.9%

Correlations

2023-12-12T17:40:38.325637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업종코드업종한글명
업종코드1.0001.000
업종한글명1.0001.000
2023-12-12T17:40:38.414357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업종한글명업종코드
업종한글명1.0001.000
업종코드1.0001.000
2023-12-12T17:40:38.510613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업종코드업종한글명
업종코드1.0001.000
업종한글명1.0001.000

Missing values

2023-12-12T17:40:32.560816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T17:40:32.678271image/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.
2023-12-12T17:40:32.776799image/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

업종코드업종한글명상호명주소전화번호팩스번호이메일홈페이지
020423화장품제조업UNILEVERNIGERIAPLC1,BILLINGSWAYOREGUNIKEJALAGOSNIGERIA234-1279-3000<NA>consumercare.nigeria@unilever.comwww.unilevernigeria.com
120423화장품제조업INTERNATIONALFLAVORSANDFRAGRANCESIFFSOUTHAFRICAPTYLTD34DIESELRD,ISANDO1600271-1922-8800271-1974-7447accpayza@iff.comhttp://www.iff.com
247813화장품,비누및방향제소매업PERMARKSUPPLYNETWORKPTYLTD50ANGUSCRES,MODDERFONTEINEDENVALE1609271-1579-0000271-1608-0601abel.b@permark.co.za<NA>
346443화장품및화장용품도매업PROACTIVESAPTYLTD301STAVENUEEDENVALEEDENVALE1609ZA271-1454-5020<NA>orders@proactivesa.co.zahttp://www.proactivesa.co.za
446443화장품및화장용품도매업NORCOSMETICSASASLAKVEIEN14E,0753,OSLO47-4145-2727<NA><NA><NA>
546443화장품및화장용품도매업CYJINTERNATIONALTAIWANINC4F-1,872,CHUNGCHENGRD.,CHUNGHEDIST.,NEWTAIPEICITY,23586,TAIWAN(R.O.C.)8862-2221-72428862-2221-6234<NA>https://www.drcyjhcc.com.tw
646443화장품및화장용품도매업CLOVERSBIOTECHNOLOGYCOLTD17F-5,16F-1,NO.75,XINTAI5THRD.,SEC.1,XIZHIDIST.,NEWTAIPEICITY,22101,TAIWAN(R.O.C.)8862-8698-10988862-8698-1066<NA>http://www.cloversmedtech.com/
746443화장품및화장용품도매업MIRACODECOLTD3F,7,ALLEY6,LANE170,CHUNGHSIAOE.RD.,SEC.4,DAANDIST,TAIPEICITY,TAIWANR.O.C.8862-2388-21588862-2388-2159<NA>www.miracode.com
820423화장품제조업KAOTAIWANCORPORATION10F,207,BEIXINGRD.,SEC.3,XINDIANDIST.,NEWTAIPEICITY,23143,TAIWAN(R.O.C.)8862-8665-19008862-8913-1156<NA>www.kao.com.tw
946443화장품및화장용품도매업KINGYUANTRADINGCOLTD10,LANE26,HSINYIRD.,PANCHIAODIST.,NEWTAIPEICITY,22061,TAIWAN(R.O.C.)8862-8967-10898862-8967-7668<NA>www.izumi.com.tw
업종코드업종한글명상호명주소전화번호팩스번호이메일홈페이지
37646443화장품및화장용품도매업TEHANONLINESTOREBARANGAYBAGONGPOOKROSARIO4225BATANGASPHILIPPINES<NA><NA><NA><NA>
37746443화장품및화장용품도매업OELPOOLAUSTRALIAPTYLTDANDTHEBIEDERMANNFAMILYTRUST38AUTOMOTIVEDRWANGARAWA606589-409-5433<NA>admin@advancedcosmeceuticals.com.auwww.advancedcosmeceuticals.com.au
37846443화장품및화장용품도매업AVENIRPACIFICPTYLTDUNIT374MURDOCHCIRCUITACACIARIDGEQLD411073-711-2390<NA>info@n01cosmetics.com.auwww.avenirpacific.com.au
37947813화장품,비누및방향제소매업INBPTYLTD60BLEVEL6'104BATHURSTSTREETSYDNEYNSW200029-283-2202<NA><NA>www.boniik.com
38046443화장품및화장용품도매업SINKICONCEPTUALWORLDLIMITEDRM5,N2/FKAISERESTPH3,11HOKYUENSTHUNGHOM,KOWLOONHONGKONG852-3596-3008852-3565-5690winkychan@kstarsgroup.com.hk<NA>
38147813화장품,비누및방향제소매업MINISOINTERNATIONALHONGKONGLIMITEDRMA12/FKIUFUCOMLBLDG,300LOCKHARTRDWANCHAI,HONGKONGISLANDHONGKONG852-3954-5109852-3954-5385<NA>www.miniso.hk
38246443화장품및화장용품도매업PETITBONHEURLIMITEDRM122112/FRADIOCITY,505HENNESSYRDCAUSEWAYBAY,HONGKONGISLANDHONGKONG<NA><NA>INFO@PETITBONHEUR.COM.HKWWW.PETITBONHEUR.COM.HK
38347813화장품,비누및방향제소매업YOUUPINTERNATIONALLIMITEDRMA24/FSUPERLUCKINDLCTRPH2,57SHATSUIRDTSUENWAN,NEWTERRITORIESHONGKONG852-3153-2768852-3153-2769<NA><NA>
38446443화장품및화장용품도매업OCEANMEDICALGROUPLIMITEDRMB10/FCHINAFENHINBLDG,5CHEUNGYUESTCHEUNGSHAWAN,KOWLOONHONGKONG852-3583-2797852-3188-9480carrie_fong@ymail.com<NA>
38546443화장품및화장용품도매업BEAUTYCONCEPTASIATRADINGCOLIMITEDRM170317/FMETROPLAZATWR2,223HINGFONGRDKWAICHUNG,NEWTERRITORIESHONGKONG852-2422-7323852-2422-7328<NA><NA>