Overview

Dataset statistics

Number of variables8
Number of observations677
Missing cells735
Missing cells (%)13.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory42.4 KiB
Average record size in memory64.2 B

Variable types

Text5
Categorical3

Dataset

Description키,분류1,명칭,도로명 주소,전화번호,홈페이지주소,분류2,분류3
Author중구
URLhttps://data.seoul.go.kr/dataList/OA-12959/S/1/datasetView.do

Alerts

분류1 is highly overall correlated with 분류2 and 1 other fieldsHigh correlation
분류3 is highly overall correlated with 분류1 and 1 other fieldsHigh correlation
분류2 is highly overall correlated with 분류1 and 1 other fieldsHigh correlation
도로명 주소 has 12 (1.8%) missing valuesMissing
전화번호 has 232 (34.3%) missing valuesMissing
홈페이지주소 has 491 (72.5%) missing valuesMissing
키 has unique valuesUnique

Reproduction

Analysis started2023-12-11 08:53:33.605919
Analysis finished2023-12-11 08:53:36.324738
Duration2.72 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

키
Text

UNIQUE 

Distinct677
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size5.4 KiB
2023-12-11T17:53:36.527206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters8124
Distinct characters16
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

Unique677 ?
Unique (%)100.0%

Sample

1st rowBE_IW12-0209
2nd rowBE_IW12-0210
3rd rowBE_IW12-0211
4th rowBE_IW12-0212
5th rowBE_IW12-0213
ValueCountFrequency (%)
be_iw12-0209 1
 
0.1%
be_iw12-0490 1
 
0.1%
be_iw12-0500 1
 
0.1%
be_iw12-0435 1
 
0.1%
be_iw12-0436 1
 
0.1%
be_iw12-0437 1
 
0.1%
be_iw12-0438 1
 
0.1%
be_iw12-0487 1
 
0.1%
be_iw12-0488 1
 
0.1%
be_iw12-0489 1
 
0.1%
Other values (667) 667
98.5%
2023-12-11T17:53:36.943900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 915
11.3%
2 915
11.3%
0 912
11.2%
B 677
8.3%
E 677
8.3%
_ 677
8.3%
I 677
8.3%
W 677
8.3%
- 677
8.3%
5 238
 
2.9%
Other values (6) 1082
13.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4062
50.0%
Uppercase Letter 2708
33.3%
Connector Punctuation 677
 
8.3%
Dash Punctuation 677
 
8.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 915
22.5%
2 915
22.5%
0 912
22.5%
5 238
 
5.9%
3 238
 
5.9%
4 238
 
5.9%
6 216
 
5.3%
7 136
 
3.3%
9 127
 
3.1%
8 127
 
3.1%
Uppercase Letter
ValueCountFrequency (%)
B 677
25.0%
E 677
25.0%
I 677
25.0%
W 677
25.0%
Connector Punctuation
ValueCountFrequency (%)
_ 677
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 677
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5416
66.7%
Latin 2708
33.3%

Most frequent character per script

Common
ValueCountFrequency (%)
1 915
16.9%
2 915
16.9%
0 912
16.8%
_ 677
12.5%
- 677
12.5%
5 238
 
4.4%
3 238
 
4.4%
4 238
 
4.4%
6 216
 
4.0%
7 136
 
2.5%
Other values (2) 254
 
4.7%
Latin
ValueCountFrequency (%)
B 677
25.0%
E 677
25.0%
I 677
25.0%
W 677
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 8124
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 915
11.3%
2 915
11.3%
0 912
11.2%
B 677
8.3%
E 677
8.3%
_ 677
8.3%
I 677
8.3%
W 677
8.3%
- 677
8.3%
5 238
 
2.9%
Other values (6) 1082
13.3%

분류1
Categorical

HIGH CORRELATION 

Distinct6
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size5.4 KiB
맛집
247 
문화재
182 
문화공간(볼거리)
117 
쇼핑(살거리)
85 
숙박(호텔)
34 

Length

Max length12
Median length9
Mean length4.4844904
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
맛집 247
36.5%
문화재 182
26.9%
문화공간(볼거리) 117
17.3%
쇼핑(살거리) 85
 
12.6%
숙박(호텔) 34
 
5.0%
중구 어디까지 가봤니? 12
 
1.8%

Length

2023-12-11T17:53:37.106088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T17:53:37.257514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
맛집 247
35.2%
문화재 182
26.0%
문화공간(볼거리 117
16.7%
쇼핑(살거리 85
 
12.1%
숙박(호텔 34
 
4.9%
중구 12
 
1.7%
어디까지 12
 
1.7%
가봤니 12
 
1.7%

명칭
Text

Distinct603
Distinct (%)89.1%
Missing0
Missing (%)0.0%
Memory size5.4 KiB
2023-12-11T17:53:37.595913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length25
Mean length7.9497784
Min length2

Characters and Unicode

Total characters5382
Distinct characters707
Distinct categories9 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique534 ?
Unique (%)78.9%

Sample

1st row전주중앙회관
2nd row전주풍남회관
3rd row정성본샤브수끼
4th row정통삼계탕
5th row제일가든
ValueCountFrequency (%)
구 11
 
1.1%
상 10
 
1.0%
터 10
 
1.0%
서울 9
 
0.9%
어린이공원 9
 
0.9%
기념관 9
 
0.9%
공원 7
 
0.7%
미술관 6
 
0.6%
기념비 5
 
0.5%
호텔 5
 
0.5%
Other values (765) 958
92.2%
2023-12-11T17:53:38.044460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
496
 
9.2%
) 163
 
3.0%
( 163
 
3.0%
터 90
 
1.7%
동 88
 
1.6%
관 80
 
1.5%
장 73
 
1.4%
이 70
 
1.3%
시 65
 
1.2%
址 64
 
1.2%
Other values (697) 4030
74.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4490
83.4%
Space Separator 496
 
9.2%
Close Punctuation 164
 
3.0%
Open Punctuation 164
 
3.0%
Uppercase Letter 31
 
0.6%
Decimal Number 24
 
0.4%
Other Punctuation 10
 
0.2%
Dash Punctuation 2
 
< 0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
터 90
 
2.0%
동 88
 
2.0%
관 80
 
1.8%
장 73
 
1.6%
이 70
 
1.6%
시 65
 
1.4%
址 64
 
1.4%
원 62
 
1.4%
서 61
 
1.4%
화 54
 
1.2%
Other values (667) 3783
84.3%
Uppercase Letter
ValueCountFrequency (%)
E 4
12.9%
K 3
9.7%
C 3
9.7%
G 3
9.7%
V 3
9.7%
W 3
9.7%
O 2
6.5%
X 2
6.5%
T 2
6.5%
D 2
6.5%
Other values (3) 4
12.9%
Decimal Number
ValueCountFrequency (%)
0 8
33.3%
1 7
29.2%
3 4
16.7%
4 2
 
8.3%
5 2
 
8.3%
6 1
 
4.2%
Other Punctuation
ValueCountFrequency (%)
? 6
60.0%
: 2
 
20.0%
! 1
 
10.0%
. 1
 
10.0%
Close Punctuation
ValueCountFrequency (%)
) 163
99.4%
] 1
 
0.6%
Open Punctuation
ValueCountFrequency (%)
( 163
99.4%
[ 1
 
0.6%
Space Separator
ValueCountFrequency (%)
496
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3761
69.9%
Common 861
 
16.0%
Han 729
 
13.5%
Latin 31
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
터 90
 
2.4%
동 88
 
2.3%
관 80
 
2.1%
장 73
 
1.9%
이 70
 
1.9%
시 65
 
1.7%
원 62
 
1.6%
서 61
 
1.6%
화 54
 
1.4%
정 48
 
1.3%
Other values (404) 3070
81.6%
Han
ValueCountFrequency (%)
址 64
 
8.8%
館 18
 
2.5%
國 15
 
2.1%
堂 15
 
2.1%
家 14
 
1.9%
舊 13
 
1.8%
洞 13
 
1.8%
門 12
 
1.6%
聖 11
 
1.5%
廳 11
 
1.5%
Other values (253) 543
74.5%
Common
ValueCountFrequency (%)
496
57.6%
) 163
 
18.9%
( 163
 
18.9%
0 8
 
0.9%
1 7
 
0.8%
? 6
 
0.7%
3 4
 
0.5%
4 2
 
0.2%
- 2
 
0.2%
: 2
 
0.2%
Other values (7) 8
 
0.9%
Latin
ValueCountFrequency (%)
E 4
12.9%
K 3
9.7%
C 3
9.7%
G 3
9.7%
V 3
9.7%
W 3
9.7%
O 2
6.5%
X 2
6.5%
T 2
6.5%
D 2
6.5%
Other values (3) 4
12.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3759
69.8%
ASCII 892
 
16.6%
CJK 729
 
13.5%
Compat Jamo 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
496
55.6%
) 163
 
18.3%
( 163
 
18.3%
0 8
 
0.9%
1 7
 
0.8%
? 6
 
0.7%
E 4
 
0.4%
3 4
 
0.4%
K 3
 
0.3%
C 3
 
0.3%
Other values (20) 35
 
3.9%
Hangul
ValueCountFrequency (%)
터 90
 
2.4%
동 88
 
2.3%
관 80
 
2.1%
장 73
 
1.9%
이 70
 
1.9%
시 65
 
1.7%
원 62
 
1.6%
서 61
 
1.6%
화 54
 
1.4%
정 48
 
1.3%
Other values (402) 3068
81.6%
CJK
ValueCountFrequency (%)
址 64
 
8.8%
館 18
 
2.5%
國 15
 
2.1%
堂 15
 
2.1%
家 14
 
1.9%
舊 13
 
1.8%
洞 13
 
1.8%
門 12
 
1.6%
聖 11
 
1.5%
廳 11
 
1.5%
Other values (253) 543
74.5%
Compat Jamo
ValueCountFrequency (%)
ㅣ 1
50.0%
ㆍ 1
50.0%

도로명 주소
Text

MISSING 

Distinct567
Distinct (%)85.3%
Missing12
Missing (%)1.8%
Memory size5.4 KiB
2023-12-11T17:53:38.421281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length53
Median length41
Mean length24.640602
Min length11

Characters and Unicode

Total characters16386
Distinct characters295
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

Unique493 ?
Unique (%)74.1%

Sample

1st row서울 중구 명동8나길 19 (충무로1가)
2nd row서울 중구 태평로1가 62-7 광안빌딩 2
3rd row서울 중구 을지로43길 30 (을지로6가) 미진빌딩
4th row서울 중구 수표동 35-12
5th row중구 무교로 17-17(무교동 31)
ValueCountFrequency (%)
중구 658
 
20.3%
서울 124
 
3.8%
52
 
1.6%
앞 36
 
1.1%
2가 30
 
0.9%
장충단로 29
 
0.9%
퇴계로 29
 
0.9%
동호로 28
 
0.9%
서울시 28
 
0.9%
을지로 25
 
0.8%
Other values (1140) 2195
67.9%
2023-12-11T17:53:38.897538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2712
 
16.6%
1 1056
 
6.4%
2 753
 
4.6%
구 689
 
4.2%
( 674
 
4.1%
) 672
 
4.1%
중 667
 
4.1%
로 664
 
4.1%
동 628
 
3.8%
- 494
 
3.0%
Other values (285) 7377
45.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7562
46.1%
Decimal Number 4139
25.3%
Space Separator 2712
 
16.6%
Open Punctuation 674
 
4.1%
Close Punctuation 672
 
4.1%
Dash Punctuation 494
 
3.0%
Other Punctuation 77
 
0.5%
Uppercase Letter 45
 
0.3%
Lowercase Letter 7
 
< 0.1%
Math Symbol 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 689
 
9.1%
중 667
 
8.8%
로 664
 
8.8%
동 628
 
8.3%
가 371
 
4.9%
길 284
 
3.8%
서 224
 
3.0%
울 179
 
2.4%
장 174
 
2.3%
대 162
 
2.1%
Other values (243) 3520
46.5%
Uppercase Letter
ValueCountFrequency (%)
O 7
15.6%
T 4
 
8.9%
S 4
 
8.9%
B 4
 
8.9%
P 3
 
6.7%
M 3
 
6.7%
E 3
 
6.7%
C 3
 
6.7%
W 2
 
4.4%
R 2
 
4.4%
Other values (9) 10
22.2%
Decimal Number
ValueCountFrequency (%)
1 1056
25.5%
2 753
18.2%
3 411
 
9.9%
4 341
 
8.2%
5 325
 
7.9%
6 280
 
6.8%
0 268
 
6.5%
8 259
 
6.3%
7 233
 
5.6%
9 213
 
5.1%
Lowercase Letter
ValueCountFrequency (%)
i 2
28.6%
l 1
14.3%
n 1
14.3%
g 1
14.3%
d 1
14.3%
u 1
14.3%
Other Punctuation
ValueCountFrequency (%)
, 74
96.1%
. 3
 
3.9%
Space Separator
ValueCountFrequency (%)
2712
100.0%
Open Punctuation
ValueCountFrequency (%)
( 674
100.0%
Close Punctuation
ValueCountFrequency (%)
) 672
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 494
100.0%
Math Symbol
ValueCountFrequency (%)
~ 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 8772
53.5%
Hangul 7562
46.1%
Latin 52
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 689
 
9.1%
중 667
 
8.8%
로 664
 
8.8%
동 628
 
8.3%
가 371
 
4.9%
길 284
 
3.8%
서 224
 
3.0%
울 179
 
2.4%
장 174
 
2.3%
대 162
 
2.1%
Other values (243) 3520
46.5%
Latin
ValueCountFrequency (%)
O 7
13.5%
T 4
 
7.7%
S 4
 
7.7%
B 4
 
7.7%
P 3
 
5.8%
M 3
 
5.8%
E 3
 
5.8%
C 3
 
5.8%
W 2
 
3.8%
R 2
 
3.8%
Other values (15) 17
32.7%
Common
ValueCountFrequency (%)
2712
30.9%
1 1056
 
12.0%
2 753
 
8.6%
( 674
 
7.7%
) 672
 
7.7%
- 494
 
5.6%
3 411
 
4.7%
4 341
 
3.9%
5 325
 
3.7%
6 280
 
3.2%
Other values (7) 1054
 
12.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 8824
53.9%
Hangul 7562
46.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2712
30.7%
1 1056
 
12.0%
2 753
 
8.5%
( 674
 
7.6%
) 672
 
7.6%
- 494
 
5.6%
3 411
 
4.7%
4 341
 
3.9%
5 325
 
3.7%
6 280
 
3.2%
Other values (32) 1106
12.5%
Hangul
ValueCountFrequency (%)
구 689
 
9.1%
중 667
 
8.8%
로 664
 
8.8%
동 628
 
8.3%
가 371
 
4.9%
길 284
 
3.8%
서 224
 
3.0%
울 179
 
2.4%
장 174
 
2.3%
대 162
 
2.1%
Other values (243) 3520
46.5%

전화번호
Text

MISSING 

Distinct383
Distinct (%)86.1%
Missing232
Missing (%)34.3%
Memory size5.4 KiB
2023-12-11T17:53:39.206476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length19
Mean length11.862921
Min length5

Characters and Unicode

Total characters5279
Distinct characters14
Distinct categories5 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique326 ?
Unique (%)73.3%

Sample

1st row02-776-3525
2nd row02-736-2144
3rd row02-2269-5270
4th row02-2272-6900
5th row02-777-1137
ValueCountFrequency (%)
02-2232-2000 4
 
0.9%
02-752-6800 3
 
0.7%
02-3396-5855 3
 
0.7%
02-3455-8341~2 3
 
0.7%
042-481-4650 3
 
0.7%
02-2268-0592 3
 
0.7%
02-2290-1234 3
 
0.7%
02-2265-0220 3
 
0.7%
02-2048-5100 3
 
0.7%
1544-1122 3
 
0.7%
Other values (348) 418
93.1%
2023-12-11T17:53:39.709005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 1091
20.7%
- 882
16.7%
0 798
15.1%
7 466
8.8%
3 373
 
7.1%
5 350
 
6.6%
1 310
 
5.9%
6 289
 
5.5%
8 223
 
4.2%
4 195
 
3.7%
Other values (4) 302
 
5.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4271
80.9%
Dash Punctuation 882
 
16.7%
Space Separator 108
 
2.0%
Math Symbol 17
 
0.3%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 1091
25.5%
0 798
18.7%
7 466
10.9%
3 373
 
8.7%
5 350
 
8.2%
1 310
 
7.3%
6 289
 
6.8%
8 223
 
5.2%
4 195
 
4.6%
9 176
 
4.1%
Dash Punctuation
ValueCountFrequency (%)
- 882
100.0%
Space Separator
ValueCountFrequency (%)
108
100.0%
Math Symbol
ValueCountFrequency (%)
~ 17
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5279
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 1091
20.7%
- 882
16.7%
0 798
15.1%
7 466
8.8%
3 373
 
7.1%
5 350
 
6.6%
1 310
 
5.9%
6 289
 
5.5%
8 223
 
4.2%
4 195
 
3.7%
Other values (4) 302
 
5.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5279
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 1091
20.7%
- 882
16.7%
0 798
15.1%
7 466
8.8%
3 373
 
7.1%
5 350
 
6.6%
1 310
 
5.9%
6 289
 
5.5%
8 223
 
4.2%
4 195
 
3.7%
Other values (4) 302
 
5.7%

홈페이지주소
Text

MISSING 

Distinct167
Distinct (%)89.8%
Missing491
Missing (%)72.5%
Memory size5.4 KiB
2023-12-11T17:53:40.010196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length121
Median length62
Mean length32.290323
Min length14

Characters and Unicode

Total characters6006
Distinct characters65
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

Unique150 ?
Unique (%)80.6%

Sample

1st rowhttp://www.02-777-6661.kti114.net/
2nd rowhttp://jihwajafood.co.kr
3rd rowhttp://www.cathedral.or.kr/
4th rowhttp://www.dutyfree24.com/?Domain=Naver3
5th rowhttp://www.dutyfree24.com/?Domain=Naver3
ValueCountFrequency (%)
http://art-plaza.co.kr 4
 
2.2%
http://www.outback.co.kr 3
 
1.6%
http://www.veneziamegamall.net 3
 
1.6%
http://emart.shinsegae.com/branch/floor/floor.jsp?id=951 3
 
1.6%
http://www.myungbo.com 2
 
1.1%
http://www.cmah.or.kr 2
 
1.1%
http://www.ktxcinema.co.kr 2
 
1.1%
http://www.daehancinema.co.kr 2
 
1.1%
http://www.megabox.co.kr/theaters/main_dongdaemun.aspx?theatercode=12 2
 
1.1%
http://cinema.ani.seoul.kr 2
 
1.1%
Other values (132) 161
86.6%
2023-12-11T17:53:40.557606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
/ 582
 
9.7%
t 528
 
8.8%
. 498
 
8.3%
w 430
 
7.2%
o 388
 
6.5%
h 291
 
4.8%
p 279
 
4.6%
e 278
 
4.6%
a 277
 
4.6%
r 260
 
4.3%
Other values (55) 2195
36.5%

Most occurring categories

ValueCountFrequency (%)
Lowercase Letter 4427
73.7%
Other Punctuation 1292
 
21.5%
Decimal Number 101
 
1.7%
Space Separator 56
 
0.9%
Uppercase Letter 55
 
0.9%
Connector Punctuation 30
 
0.5%
Math Symbol 27
 
0.4%
Dash Punctuation 12
 
0.2%
Other Letter 6
 
0.1%

Most frequent character per category

Lowercase Letter
ValueCountFrequency (%)
t 528
11.9%
w 430
 
9.7%
o 388
 
8.8%
h 291
 
6.6%
p 279
 
6.3%
e 278
 
6.3%
a 277
 
6.3%
r 260
 
5.9%
n 218
 
4.9%
c 202
 
4.6%
Other values (15) 1276
28.8%
Uppercase Letter
ValueCountFrequency (%)
C 14
25.5%
S 7
12.7%
D 4
 
7.3%
F 4
 
7.3%
T 4
 
7.3%
M 4
 
7.3%
N 3
 
5.5%
H 3
 
5.5%
V 3
 
5.5%
L 2
 
3.6%
Other values (5) 7
12.7%
Decimal Number
ValueCountFrequency (%)
0 30
29.7%
1 30
29.7%
2 14
13.9%
4 6
 
5.9%
9 5
 
5.0%
6 4
 
4.0%
5 4
 
4.0%
7 4
 
4.0%
3 4
 
4.0%
Other Punctuation
ValueCountFrequency (%)
/ 582
45.0%
. 498
38.5%
: 183
 
14.2%
? 19
 
1.5%
& 8
 
0.6%
, 2
 
0.2%
Other Letter
ValueCountFrequency (%)
시 1
16.7%
장 1
16.7%
산 1
16.7%
합 1
16.7%
종 1
16.7%
방 1
16.7%
Space Separator
ValueCountFrequency (%)
56
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 30
100.0%
Math Symbol
ValueCountFrequency (%)
= 27
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Latin 4482
74.6%
Common 1518
 
25.3%
Hangul 6
 
0.1%

Most frequent character per script

Latin
ValueCountFrequency (%)
t 528
 
11.8%
w 430
 
9.6%
o 388
 
8.7%
h 291
 
6.5%
p 279
 
6.2%
e 278
 
6.2%
a 277
 
6.2%
r 260
 
5.8%
n 218
 
4.9%
c 202
 
4.5%
Other values (30) 1331
29.7%
Common
ValueCountFrequency (%)
/ 582
38.3%
. 498
32.8%
: 183
 
12.1%
56
 
3.7%
_ 30
 
2.0%
0 30
 
2.0%
1 30
 
2.0%
= 27
 
1.8%
? 19
 
1.3%
2 14
 
0.9%
Other values (9) 49
 
3.2%
Hangul
ValueCountFrequency (%)
시 1
16.7%
장 1
16.7%
산 1
16.7%
합 1
16.7%
종 1
16.7%
방 1
16.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6000
99.9%
Hangul 6
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
/ 582
 
9.7%
t 528
 
8.8%
. 498
 
8.3%
w 430
 
7.2%
o 388
 
6.5%
h 291
 
4.9%
p 279
 
4.7%
e 278
 
4.6%
a 277
 
4.6%
r 260
 
4.3%
Other values (49) 2189
36.5%
Hangul
ValueCountFrequency (%)
시 1
16.7%
장 1
16.7%
산 1
16.7%
합 1
16.7%
종 1
16.7%
방 1
16.7%

분류2
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size5.4 KiB
맛집
250 
문화재
184 
문화공간
123 
쇼핑
86 
숙박1
34 

Length

Max length4
Median length3
Mean length2.6853767
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
맛집 250
36.9%
문화재 184
27.2%
문화공간 123
18.2%
쇼핑 86
 
12.7%
숙박1 34
 
5.0%

Length

2023-12-11T17:53:40.766588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T17:53:40.903627image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
맛집 250
36.9%
문화재 184
27.2%
문화공간 123
18.2%
쇼핑 86
 
12.7%
숙박1 34
 
5.0%

분류3
Categorical

HIGH CORRELATION 

Distinct21
Distinct (%)3.1%
Missing0
Missing (%)0.0%
Memory size5.4 KiB
한식
174 
문화유적/동상
109 
공연장
42 
쇼핑타운
40 
전통시장
35 
Other values (16)
277 

Length

Max length10
Median length9
Mean length3.9778434
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
한식 174
25.7%
문화유적/동상 109
16.1%
공연장 42
 
6.2%
쇼핑타운 40
 
5.9%
전통시장 35
 
5.2%
일식 35
 
5.2%
호텔 34
 
5.0%
유형/등록문화재 33
 
4.9%
국보/사적 30
 
4.4%
공원 28
 
4.1%
Other values (11) 117
17.3%

Length

2023-12-11T17:53:41.053714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
한식 174
25.7%
문화유적/동상 109
16.1%
공연장 42
 
6.2%
쇼핑타운 40
 
5.9%
전통시장 35
 
5.2%
일식 35
 
5.2%
호텔 34
 
5.0%
유형/등록문화재 33
 
4.9%
국보/사적 30
 
4.4%
공원 28
 
4.1%
Other values (11) 117
17.3%

Correlations

2023-12-11T17:53:41.176039image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
분류1분류2분류3
분류11.0000.9840.978
분류20.9841.0001.000
분류30.9781.0001.000
2023-12-11T17:53:41.298417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
분류1분류3분류2
분류11.0000.8790.993
분류30.8791.0000.988
분류20.9930.9881.000
2023-12-11T17:53:41.427211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
분류1분류2분류3
분류11.0000.9930.879
분류20.9931.0000.988
분류30.8790.9881.000

Missing values

2023-12-11T17:53:35.899681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T17:53:36.112762image/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.
2023-12-11T17:53:36.261041image/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

키분류1명칭도로명 주소전화번호홈페이지주소분류2분류3
0BE_IW12-0209맛집전주중앙회관서울 중구 명동8나길 19 (충무로1가)02-776-3525<NA>맛집한식
1BE_IW12-0210맛집전주풍남회관서울 중구 태평로1가 62-7 광안빌딩 202-736-2144<NA>맛집한식
2BE_IW12-0211맛집정성본샤브수끼서울 중구 을지로43길 30 (을지로6가) 미진빌딩02-2269-5270<NA>맛집한식
3BE_IW12-0212맛집정통삼계탕서울 중구 수표동 35-1202-2272-6900<NA>맛집한식
4BE_IW12-0213맛집제일가든중구 무교로 17-17(무교동 31)02-777-1137http://www.02-777-6661.kti114.net/맛집한식
5BE_IW12-0214맛집제일냉면숯불갈비중구 남대문로1길 42(북창동 18 - 9)02-756-2166<NA>맛집한식
6BE_IW12-0215맛집조마루서울 중구 수표로 20-1 (충무로3가)02-2274-7933<NA>맛집한식
7BE_IW12-0216맛집주원산오리서울 중구 을지로6가 18-5902-2273-2703<NA>맛집한식
8BE_IW12-0217맛집중앙회관중구 명동8나길 19(충무로1가 24 - 11)02-776-3525<NA>맛집한식
9BE_IW12-0218맛집지이오서울 중구 봉래동1가 132-902-771-5731<NA>맛집한식
키분류1명칭도로명 주소전화번호홈페이지주소분류2분류3
667BE_IW12-0159맛집서울삼계탕(영양센터)중구 남대문로1길 57(태평로2가 58)02-775-4300<NA>맛집한식
668BE_IW12-0581쇼핑(살거리)롯데아울렛 서울역점용산구 한강대로 405(동자동 43-205)02-6965-2500http://store.lotteshopping.com쇼핑쇼핑타운
669BE_IW12-0582쇼핑(살거리)밀리오레서울특별시 중구 퇴계로 11502-3393-2802http://www.migliore.co.kr/쇼핑쇼핑타운
670BE_IW12-0365문화공간(볼거리)덕수궁 미술관중구 세종대로99(정동 5-1)02-2022-0600www.moca.go.kr/index.do?_method=main문화공간전시장
671BE_IW12-0366문화공간(볼거리)서울시립미술관중구 새문안로 45(서소문동 37)02-2124-8800http://seoulmoa.seoul.go.kr/index.jsp문화공간전시장
672BE_IW12-0367문화공간(볼거리)서울시립미술관중구 덕수궁길 61(서소문동 37)02-2124-8800http://seoulmoa.seoul.go.kr/index.jsp문화공간전시장
673BE_IW12-0368문화공간(볼거리)우표문화누리서울시 중구 반포로1 POST TOWER 지하2층02-6450-5600http://www.kstamp.go.kr/kstampworld/문화공간전시장
674BE_IW12-0369문화공간(볼거리)우표문화누리서울시 중구 반포로1 POST TOWER 지하2층02-6450-5600http://www.kstamp.go.kr/문화공간전시장
675BE_IW12-0370문화공간(볼거리)조선일보 미술관중구 세종대로21길 30(태평로1가 61)02-724-6322http://gallery.chosun.com/문화공간전시장
676BE_IW12-0371문화공간(볼거리)조선일보 미술관중구 세종대로 21길 30(태평로1가 61)<NA>http://gallery.chosun.com/문화공간전시장