Overview

Dataset statistics

Number of variables7
Number of observations907
Missing cells2039
Missing cells (%)32.1%
Duplicate rows62
Duplicate rows (%)6.8%
Total size in memory49.7 KiB
Average record size in memory56.1 B

Variable types

Text7

Dataset

DescriptionJDC지정면세점_입점업체 정보(2002-2015년)
Author제주국제자유도시개발센터
URLhttps://www.data.go.kr/data/15052278/fileData.do

Alerts

Dataset has 62 (6.8%) duplicate rowsDuplicates
최초 입점일자 has 55 (6.1%) missing valuesMissing
입점일자 has 20 (2.2%) missing valuesMissing
퇴점일자 has 652 (71.9%) missing valuesMissing
연락처 1 has 639 (70.5%) missing valuesMissing
연락처 2 has 664 (73.2%) missing valuesMissing

Reproduction

Analysis started2023-12-12 12:19:22.785754
Analysis finished2023-12-12 12:19:23.709817
Duration0.92 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

협력업체명
Text

Distinct157
Distinct (%)17.5%
Missing8
Missing (%)0.9%
Memory size7.2 KiB
2023-12-12T21:19:23.970887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length21
Mean length6.5517241
Min length2

Characters and Unicode

Total characters5890
Distinct characters219
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

Unique33 ?
Unique (%)3.7%

Sample

1st row다린앤컴퍼니
2nd row다린앤컴퍼니
3rd row다린앤컴퍼니
4th row다린앤컴퍼니
5th row다린앤컴퍼니
ValueCountFrequency (%)
인비트윈 34
 
3.6%
다리인터내셔널 29
 
3.0%
주)강남에스비 26
 
2.7%
브랜디포 22
 
2.3%
재키상사 19
 
2.0%
룩옵틱스 19
 
2.0%
엘코잉크 19
 
2.0%
주)삼풍인터내셔널 18
 
1.9%
부루벨코리아(co 17
 
1.8%
ys물산 16
 
1.7%
Other values (155) 732
77.0%
2023-12-12T21:19:24.458776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
) 250
 
4.2%
( 250
 
4.2%
인 178
 
3.0%
주 169
 
2.9%
이 162
 
2.8%
코 155
 
2.6%
리 149
 
2.5%
a 137
 
2.3%
터 134
 
2.3%
스 133
 
2.3%
Other values (209) 4173
70.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4066
69.0%
Uppercase Letter 636
 
10.8%
Lowercase Letter 425
 
7.2%
Close Punctuation 250
 
4.2%
Open Punctuation 250
 
4.2%
Other Punctuation 190
 
3.2%
Space Separator 52
 
0.9%
Other Symbol 21
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
인 178
 
4.4%
주 169
 
4.2%
이 162
 
4.0%
코 155
 
3.8%
리 149
 
3.7%
터 134
 
3.3%
스 133
 
3.3%
셔 132
 
3.2%
내 124
 
3.0%
널 119
 
2.9%
Other values (174) 2611
64.2%
Uppercase Letter
ValueCountFrequency (%)
T 101
15.9%
K 78
12.3%
N 45
 
7.1%
B 42
 
6.6%
L 41
 
6.4%
F 40
 
6.3%
C 40
 
6.3%
G 38
 
6.0%
A 35
 
5.5%
I 32
 
5.0%
Other values (10) 144
22.6%
Lowercase Letter
ValueCountFrequency (%)
a 137
32.2%
p 123
28.9%
m 123
28.9%
r 14
 
3.3%
e 10
 
2.4%
o 10
 
2.4%
u 4
 
0.9%
l 4
 
0.9%
Other Punctuation
ValueCountFrequency (%)
; 123
64.7%
& 53
27.9%
. 14
 
7.4%
Close Punctuation
ValueCountFrequency (%)
) 250
100.0%
Open Punctuation
ValueCountFrequency (%)
( 250
100.0%
Space Separator
ValueCountFrequency (%)
52
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 21
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4087
69.4%
Latin 1061
 
18.0%
Common 742
 
12.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
인 178
 
4.4%
주 169
 
4.1%
이 162
 
4.0%
코 155
 
3.8%
리 149
 
3.6%
터 134
 
3.3%
스 133
 
3.3%
셔 132
 
3.2%
내 124
 
3.0%
널 119
 
2.9%
Other values (175) 2632
64.4%
Latin
ValueCountFrequency (%)
a 137
12.9%
p 123
11.6%
m 123
11.6%
T 101
 
9.5%
K 78
 
7.4%
N 45
 
4.2%
B 42
 
4.0%
L 41
 
3.9%
F 40
 
3.8%
C 40
 
3.8%
Other values (18) 291
27.4%
Common
ValueCountFrequency (%)
) 250
33.7%
( 250
33.7%
; 123
16.6%
& 53
 
7.1%
52
 
7.0%
. 14
 
1.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4066
69.0%
ASCII 1803
30.6%
None 21
 
0.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
) 250
13.9%
( 250
13.9%
a 137
 
7.6%
p 123
 
6.8%
m 123
 
6.8%
; 123
 
6.8%
T 101
 
5.6%
K 78
 
4.3%
& 53
 
2.9%
52
 
2.9%
Other values (24) 513
28.5%
Hangul
ValueCountFrequency (%)
인 178
 
4.4%
주 169
 
4.2%
이 162
 
4.0%
코 155
 
3.8%
리 149
 
3.7%
터 134
 
3.3%
스 133
 
3.3%
셔 132
 
3.2%
내 124
 
3.0%
널 119
 
2.9%
Other values (174) 2611
64.2%
None
ValueCountFrequency (%)
㈜ 21
100.0%

브랜드명
Text

Distinct405
Distinct (%)44.7%
Missing1
Missing (%)0.1%
Memory size7.2 KiB
2023-12-12T21:19:24.818383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length19
Mean length8.2075055
Min length1

Characters and Unicode

Total characters7436
Distinct characters144
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique147 ?
Unique (%)16.2%

Sample

1st rowCourvoisier
2nd rowCourvoisier
3rd rowBallantines
4th rowJack Daniel
5th row천년정성
ValueCountFrequency (%)
anna 15
 
1.3%
sui 15
 
1.3%
givenchy 11
 
1.0%
h.boss 9
 
0.8%
prada 9
 
0.8%
burberry 8
 
0.7%
lancome 8
 
0.7%
e.armani 8
 
0.7%
guerlain 8
 
0.7%
chloe 8
 
0.7%
Other values (466) 1025
91.2%
2023-12-12T21:19:25.433019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
a 416
 
5.6%
e 354
 
4.8%
A 346
 
4.7%
i 311
 
4.2%
E 282
 
3.8%
r 272
 
3.7%
S 269
 
3.6%
I 253
 
3.4%
n 251
 
3.4%
o 227
 
3.1%
Other values (134) 4455
59.9%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 3502
47.1%
Lowercase Letter 3149
42.3%
Other Letter 282
 
3.8%
Space Separator 218
 
2.9%
Other Punctuation 164
 
2.2%
Close Punctuation 51
 
0.7%
Open Punctuation 51
 
0.7%
Dash Punctuation 9
 
0.1%
Decimal Number 9
 
0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 27
 
9.6%
트 26
 
9.2%
나 24
 
8.5%
베 24
 
8.5%
라 23
 
8.2%
디 14
 
5.0%
브 14
 
5.0%
포 13
 
4.6%
랜 12
 
4.3%
스 5
 
1.8%
Other values (66) 100
35.5%
Lowercase Letter
ValueCountFrequency (%)
a 416
13.2%
e 354
11.2%
i 311
9.9%
r 272
 
8.6%
n 251
 
8.0%
o 227
 
7.2%
l 178
 
5.7%
s 150
 
4.8%
c 136
 
4.3%
u 129
 
4.1%
Other values (16) 725
23.0%
Uppercase Letter
ValueCountFrequency (%)
A 346
 
9.9%
E 282
 
8.1%
S 269
 
7.7%
I 253
 
7.2%
L 225
 
6.4%
N 210
 
6.0%
O 210
 
6.0%
R 202
 
5.8%
M 181
 
5.2%
C 176
 
5.0%
Other values (16) 1148
32.8%
Other Punctuation
ValueCountFrequency (%)
. 83
50.6%
; 37
22.6%
& 24
 
14.6%
' 15
 
9.1%
/ 3
 
1.8%
: 2
 
1.2%
Decimal Number
ValueCountFrequency (%)
5 3
33.3%
7 3
33.3%
3 1
 
11.1%
2 1
 
11.1%
9 1
 
11.1%
Space Separator
ValueCountFrequency (%)
218
100.0%
Close Punctuation
ValueCountFrequency (%)
) 51
100.0%
Open Punctuation
ValueCountFrequency (%)
( 51
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 9
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 6651
89.4%
Common 503
 
6.8%
Hangul 282
 
3.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 27
 
9.6%
트 26
 
9.2%
나 24
 
8.5%
베 24
 
8.5%
라 23
 
8.2%
디 14
 
5.0%
브 14
 
5.0%
포 13
 
4.6%
랜 12
 
4.3%
스 5
 
1.8%
Other values (66) 100
35.5%
Latin
ValueCountFrequency (%)
a 416
 
6.3%
e 354
 
5.3%
A 346
 
5.2%
i 311
 
4.7%
E 282
 
4.2%
r 272
 
4.1%
S 269
 
4.0%
I 253
 
3.8%
n 251
 
3.8%
o 227
 
3.4%
Other values (42) 3670
55.2%
Common
ValueCountFrequency (%)
218
43.3%
. 83
 
16.5%
) 51
 
10.1%
( 51
 
10.1%
; 37
 
7.4%
& 24
 
4.8%
' 15
 
3.0%
- 9
 
1.8%
/ 3
 
0.6%
5 3
 
0.6%
Other values (6) 9
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 7154
96.2%
Hangul 282
 
3.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
a 416
 
5.8%
e 354
 
4.9%
A 346
 
4.8%
i 311
 
4.3%
E 282
 
3.9%
r 272
 
3.8%
S 269
 
3.8%
I 253
 
3.5%
n 251
 
3.5%
o 227
 
3.2%
Other values (58) 4173
58.3%
Hangul
ValueCountFrequency (%)
리 27
 
9.6%
트 26
 
9.2%
나 24
 
8.5%
베 24
 
8.5%
라 23
 
8.2%
디 14
 
5.0%
브 14
 
5.0%
포 13
 
4.6%
랜 12
 
4.3%
스 5
 
1.8%
Other values (66) 100
35.5%

최초 입점일자
Text

MISSING 

Distinct218
Distinct (%)25.6%
Missing55
Missing (%)6.1%
Memory size7.2 KiB
2023-12-12T21:19:25.851202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length10
Mean length9.9870892
Min length7

Characters and Unicode

Total characters8509
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique61 ?
Unique (%)7.2%

Sample

1st row2002-12-24
2nd row2002-12-24
3rd row2002-12-24
4th row2003-02-12
5th row2011-12-17
ValueCountFrequency (%)
2002-12-24 225
26.4%
2011-12-17 33
 
3.9%
2003-11-29 19
 
2.2%
2008-08-30 18
 
2.1%
2013-07-16 13
 
1.5%
2011-11-11 11
 
1.3%
2003-11-25 10
 
1.2%
2003-09-06 10
 
1.2%
2006-09-01 10
 
1.2%
2003-06-28 9
 
1.1%
Other values (208) 494
58.0%
2023-12-12T21:19:26.448924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2246
26.4%
2 1908
22.4%
- 1694
19.9%
1 1129
13.3%
4 423
 
5.0%
3 348
 
4.1%
8 186
 
2.2%
7 171
 
2.0%
6 139
 
1.6%
5 130
 
1.5%
Other values (2) 135
 
1.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6809
80.0%
Dash Punctuation 1694
 
19.9%
Other Punctuation 6
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2246
33.0%
2 1908
28.0%
1 1129
16.6%
4 423
 
6.2%
3 348
 
5.1%
8 186
 
2.7%
7 171
 
2.5%
6 139
 
2.0%
5 130
 
1.9%
9 129
 
1.9%
Dash Punctuation
ValueCountFrequency (%)
- 1694
100.0%
Other Punctuation
ValueCountFrequency (%)
. 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 8509
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2246
26.4%
2 1908
22.4%
- 1694
19.9%
1 1129
13.3%
4 423
 
5.0%
3 348
 
4.1%
8 186
 
2.2%
7 171
 
2.0%
6 139
 
1.6%
5 130
 
1.5%
Other values (2) 135
 
1.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 8509
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2246
26.4%
2 1908
22.4%
- 1694
19.9%
1 1129
13.3%
4 423
 
5.0%
3 348
 
4.1%
8 186
 
2.2%
7 171
 
2.0%
6 139
 
1.6%
5 130
 
1.5%
Other values (2) 135
 
1.6%

입점일자
Text

MISSING 

Distinct283
Distinct (%)31.9%
Missing20
Missing (%)2.2%
Memory size7.2 KiB
2023-12-12T21:19:26.835876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length9.6583991
Min length3

Characters and Unicode

Total characters8567
Distinct characters18
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique87 ?
Unique (%)9.8%

Sample

1st row2002-12-24
2nd row2002-12-24
3rd row2002-12-24
4th row2003-02-12
5th row2011-12-17
ValueCountFrequency (%)
2002-12-24 169
 
19.1%
2011-12-17 48
 
5.4%
2002.12 18
 
2.0%
2008-08-30 14
 
1.6%
2010-08-01 14
 
1.6%
2014-01-01 12
 
1.4%
2011-11-11 12
 
1.4%
2003-11-29 11
 
1.2%
2003-06-28 9
 
1.0%
2012-10-19 9
 
1.0%
Other values (273) 571
64.4%
2023-12-12T21:19:27.377648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 2283
26.6%
2 1838
21.5%
- 1588
18.5%
1 1319
15.4%
4 370
 
4.3%
3 301
 
3.5%
8 214
 
2.5%
7 172
 
2.0%
9 137
 
1.6%
6 119
 
1.4%
Other values (8) 226
 
2.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6871
80.2%
Dash Punctuation 1588
 
18.5%
Other Punctuation 90
 
1.1%
Lowercase Letter 8
 
0.1%
Other Letter 6
 
0.1%
Uppercase Letter 4
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 2283
33.2%
2 1838
26.8%
1 1319
19.2%
4 370
 
5.4%
3 301
 
4.4%
8 214
 
3.1%
7 172
 
2.5%
9 137
 
2.0%
6 119
 
1.7%
5 118
 
1.7%
Other Letter
ValueCountFrequency (%)
미 2
33.3%
입 2
33.3%
점 2
33.3%
Lowercase Letter
ValueCountFrequency (%)
u 4
50.0%
l 4
50.0%
Dash Punctuation
ValueCountFrequency (%)
- 1588
100.0%
Other Punctuation
ValueCountFrequency (%)
. 90
100.0%
Uppercase Letter
ValueCountFrequency (%)
J 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 8549
99.8%
Latin 12
 
0.1%
Hangul 6
 
0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 2283
26.7%
2 1838
21.5%
- 1588
18.6%
1 1319
15.4%
4 370
 
4.3%
3 301
 
3.5%
8 214
 
2.5%
7 172
 
2.0%
9 137
 
1.6%
6 119
 
1.4%
Other values (2) 208
 
2.4%
Latin
ValueCountFrequency (%)
J 4
33.3%
u 4
33.3%
l 4
33.3%
Hangul
ValueCountFrequency (%)
미 2
33.3%
입 2
33.3%
점 2
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 8561
99.9%
Hangul 6
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 2283
26.7%
2 1838
21.5%
- 1588
18.5%
1 1319
15.4%
4 370
 
4.3%
3 301
 
3.5%
8 214
 
2.5%
7 172
 
2.0%
9 137
 
1.6%
6 119
 
1.4%
Other values (5) 220
 
2.6%
Hangul
ValueCountFrequency (%)
미 2
33.3%
입 2
33.3%
점 2
33.3%

퇴점일자
Text

MISSING 

Distinct204
Distinct (%)80.0%
Missing652
Missing (%)71.9%
Memory size7.2 KiB
2023-12-12T21:19:27.727524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length9.5058824
Min length6

Characters and Unicode

Total characters2424
Distinct characters31
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique175 ?
Unique (%)68.6%

Sample

1st row2006-04-15
2nd row2007-01-24
3rd rowDec-07
4th row2012-09-04
5th row2013-05-15
ValueCountFrequency (%)
2010-07-31 8
 
3.1%
2011-12-16 8
 
3.1%
aug-08 4
 
1.6%
2013-07-15 4
 
1.6%
2014-03-31 4
 
1.6%
2013-09-25 3
 
1.2%
jan-11 3
 
1.2%
may-09 3
 
1.2%
nov-10 3
 
1.2%
jul-10 2
 
0.8%
Other values (194) 213
83.5%
2023-12-12T21:19:28.227874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 577
23.8%
- 479
19.8%
1 419
17.3%
2 400
16.5%
3 120
 
5.0%
7 66
 
2.7%
5 62
 
2.6%
4 60
 
2.5%
6 51
 
2.1%
9 49
 
2.0%
Other values (21) 141
 
5.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1852
76.4%
Dash Punctuation 479
 
19.8%
Lowercase Letter 62
 
2.6%
Uppercase Letter 31
 
1.3%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
u 11
17.7%
a 9
14.5%
g 7
11.3%
n 6
9.7%
e 6
9.7%
l 3
 
4.8%
r 3
 
4.8%
p 3
 
4.8%
v 3
 
4.8%
o 3
 
4.8%
Other values (3) 8
12.9%
Decimal Number
ValueCountFrequency (%)
0 577
31.2%
1 419
22.6%
2 400
21.6%
3 120
 
6.5%
7 66
 
3.6%
5 62
 
3.3%
4 60
 
3.2%
6 51
 
2.8%
9 49
 
2.6%
8 48
 
2.6%
Uppercase Letter
ValueCountFrequency (%)
J 9
29.0%
A 9
29.0%
M 4
12.9%
F 3
 
9.7%
N 3
 
9.7%
D 2
 
6.5%
S 1
 
3.2%
Dash Punctuation
ValueCountFrequency (%)
- 479
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2331
96.2%
Latin 93
 
3.8%

Most frequent character per script

Latin
ValueCountFrequency (%)
u 11
11.8%
J 9
 
9.7%
a 9
 
9.7%
A 9
 
9.7%
g 7
 
7.5%
n 6
 
6.5%
e 6
 
6.5%
M 4
 
4.3%
F 3
 
3.2%
l 3
 
3.2%
Other values (10) 26
28.0%
Common
ValueCountFrequency (%)
0 577
24.8%
- 479
20.5%
1 419
18.0%
2 400
17.2%
3 120
 
5.1%
7 66
 
2.8%
5 62
 
2.7%
4 60
 
2.6%
6 51
 
2.2%
9 49
 
2.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2424
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 577
23.8%
- 479
19.8%
1 419
17.3%
2 400
16.5%
3 120
 
5.0%
7 66
 
2.7%
5 62
 
2.6%
4 60
 
2.5%
6 51
 
2.1%
9 49
 
2.0%
Other values (21) 141
 
5.8%

연락처 1
Text

MISSING 

Distinct123
Distinct (%)45.9%
Missing639
Missing (%)70.5%
Memory size7.2 KiB
2023-12-12T21:19:28.489265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length11.697761
Min length9

Characters and Unicode

Total characters3135
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

Unique65 ?
Unique (%)24.3%

Sample

1st row02-3445-2818
2nd row02-3445-2818
3rd row02-3445-2818
4th row02-3445-2818
5th row02-3448-3001
ValueCountFrequency (%)
064-751-0399 13
 
4.9%
02-3218-8314 10
 
3.7%
02-569-3931 8
 
3.0%
02-2055-2312 8
 
3.0%
02-365-2900 7
 
2.6%
02-2658-0013 6
 
2.2%
02-6712-0812 6
 
2.2%
02-2198-5304 5
 
1.9%
02-2230-0284 5
 
1.9%
02-3016-8221 5
 
1.9%
Other values (113) 195
72.8%
2023-12-12T21:19:28.872542image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 520
16.6%
0 499
15.9%
2 494
15.8%
1 292
9.3%
3 251
8.0%
4 209
6.7%
5 195
 
6.2%
8 187
 
6.0%
7 186
 
5.9%
6 175
 
5.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2615
83.4%
Dash Punctuation 520
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 499
19.1%
2 494
18.9%
1 292
11.2%
3 251
9.6%
4 209
8.0%
5 195
 
7.5%
8 187
 
7.2%
7 186
 
7.1%
6 175
 
6.7%
9 127
 
4.9%
Dash Punctuation
ValueCountFrequency (%)
- 520
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3135
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 520
16.6%
0 499
15.9%
2 494
15.8%
1 292
9.3%
3 251
8.0%
4 209
6.7%
5 195
 
6.2%
8 187
 
6.0%
7 186
 
5.9%
6 175
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3135
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 520
16.6%
0 499
15.9%
2 494
15.8%
1 292
9.3%
3 251
8.0%
4 209
6.7%
5 195
 
6.2%
8 187
 
6.0%
7 186
 
5.9%
6 175
 
5.6%

연락처 2
Text

MISSING 

Distinct89
Distinct (%)36.6%
Missing664
Missing (%)73.2%
Memory size7.2 KiB
2023-12-12T21:19:29.121703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length11.592593
Min length9

Characters and Unicode

Total characters2817
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

Unique39 ?
Unique (%)16.0%

Sample

1st row02-3445-6417
2nd row02-3445-6417
3rd row02-3445-6417
4th row02-3445-6417
5th row02-3448-4001
ValueCountFrequency (%)
064-722-2428 13
 
5.3%
02-517-5205 13
 
5.3%
02-3444-5477 11
 
4.5%
02-3446-8553 10
 
4.1%
02-2055-2316 8
 
3.3%
02-3440-2790 8
 
3.3%
02-365-1900 7
 
2.9%
02-3284-1319 7
 
2.9%
02-2658-0631 6
 
2.5%
02-2230-0288 5
 
2.1%
Other values (79) 155
63.8%
2023-12-12T21:19:29.527503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 484
17.2%
0 433
15.4%
2 429
15.2%
5 248
8.8%
4 230
8.2%
3 205
7.3%
1 191
 
6.8%
8 162
 
5.8%
6 157
 
5.6%
7 155
 
5.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2333
82.8%
Dash Punctuation 484
 
17.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 433
18.6%
2 429
18.4%
5 248
10.6%
4 230
9.9%
3 205
8.8%
1 191
8.2%
8 162
 
6.9%
6 157
 
6.7%
7 155
 
6.6%
9 123
 
5.3%
Dash Punctuation
ValueCountFrequency (%)
- 484
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2817
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 484
17.2%
0 433
15.4%
2 429
15.2%
5 248
8.8%
4 230
8.2%
3 205
7.3%
1 191
 
6.8%
8 162
 
5.8%
6 157
 
5.6%
7 155
 
5.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2817
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 484
17.2%
0 433
15.4%
2 429
15.2%
5 248
8.8%
4 230
8.2%
3 205
7.3%
1 191
 
6.8%
8 162
 
5.8%
6 157
 
5.6%
7 155
 
5.5%

Missing values

2023-12-12T21:19:23.227321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T21:19:23.393635image/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.
2023-12-12T21:19:23.573522image/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

협력업체명브랜드명최초 입점일자입점일자퇴점일자연락처 1연락처 2
0다린앤컴퍼니Courvoisier2002-12-242002-12-242006-04-15<NA><NA>
1다린앤컴퍼니Courvoisier2002-12-242002-12-24<NA><NA><NA>
2다린앤컴퍼니Ballantines2002-12-242002-12-24<NA>02-3445-281802-3445-6417
3다린앤컴퍼니Jack Daniel2003-02-122003-02-12<NA>02-3445-281802-3445-6417
4다린앤컴퍼니천년정성2011-12-172011-12-17<NA>02-3445-281802-3445-6417
5다린앤컴퍼니한삼인2003-04-292012-03-29<NA>02-3445-281802-3445-6417
6TRS KoreaShui Jing Fang<NA>2002.12<NA>02-3448-300102-3448-4001
7TRS KoreaJ &amp; B<NA>2002.12<NA>02-3448-300102-3448-4001
8TRS KoreaJohnnie Walker<NA>2002.12<NA>02-3448-300102-3448-4001
9정우INTChivas Regal2002-12-242002-12-24<NA>02-2253-136302-2253-1368
협력업체명브랜드명최초 입점일자입점일자퇴점일자연락처 1연락처 2
897N&amp;amp;B인터네셔널Kipling2003-07-052003-07-05<NA><NA><NA>
898N&amp;amp;amp;B인터네셔널Kipling2003-07-052003-07-05Jan-09<NA><NA>
899유로코리아Dr.jart2008-08-302008-08-30Aug-11<NA><NA>
900유로코리아Dr.jart2008-08-302008-08-30<NA><NA><NA>
901인스컴(NH농협)한삼인2003-04-292003-04-29<NA><NA><NA>
902인스컴(NH농협)한삼인2003-04-292003-04-292012-03-29<NA><NA>
903모브컴퍼니LOVCAT2008-04-172008-04-17<NA><NA><NA>
904모브컴퍼니LOVCAT2008-04-172008-04-172011-12-16<NA><NA>
905(주)에이제이인터내셔널MCM2002-12-242002-12-24<NA><NA><NA>
906(주)에이제이인터내셔널MCM2002-12-242002-12-242009-03-23<NA><NA>

Duplicate rows

Most frequently occurring

협력업체명브랜드명최초 입점일자입점일자퇴점일자연락처 1연락처 2# duplicates
2(주)강남에스비Mars2005-08-312005-08-31<NA><NA><NA>3
3(주)강남에스비Swiss Delice2002-12-242002-12-24<NA><NA><NA>3
42인비트윈DAKS(L)(라베트리나)2013.12<NA><NA><NA><NA>3
61<NA>PRADA<NA><NA><NA><NA><NA>3
0(주)강남에스비Gold Kenn2002-12-242002-12-24<NA><NA><NA>2
1(주)강남에스비LEGO<NA><NA><NA><NA><NA>2
4(주)나자인Mandarina Duck2010-02-272010-02-27<NA>02-3496-803202-3496-80972
5(주)에스제이듀코S.T.DUPONT2013-03-012013-03-01<NA>02-2106-340602-549-13882
6(주)이데아코즈Anna Sui2002-12-242012.04<NA>02-6905-890102-6905-89592
7B&amp;F통상Elizabeth Arden2005-03-052005-03-05<NA><NA><NA>2