Overview

Dataset statistics

Number of variables5
Number of observations963
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory37.7 KiB
Average record size in memory40.1 B

Variable types

Categorical2
Text3

Dataset

Description한국문화예술위원회에서 제공하는 문화누리카드 홈페이지입니다.
Author한국문화예술위원회
URLhttps://www.data.go.kr/data/15045193/fileData.do

Reproduction

Analysis started2023-12-12 01:42:09.158835
Analysis finished2023-12-12 01:42:10.017757
Duration0.86 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

지역
Categorical

Distinct16
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Memory size7.7 KiB
서울
253 
경기
174 
경북
88 
강원
64 
경남
59 
Other values (11)
325 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row전북
2nd row대구
3rd row서울
4th row서울
5th row서울

Common Values

ValueCountFrequency (%)
서울 253
26.3%
경기 174
18.1%
경북 88
 
9.1%
강원 64
 
6.6%
경남 59
 
6.1%
전남 47
 
4.9%
전북 44
 
4.6%
충남 42
 
4.4%
충북 39
 
4.0%
부산 27
 
2.8%
Other values (6) 126
13.1%

Length

2023-12-12T10:42:10.083326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
서울 253
26.3%
경기 174
18.1%
경북 88
 
9.1%
강원 64
 
6.6%
경남 59
 
6.1%
전남 47
 
4.9%
전북 44
 
4.6%
충남 42
 
4.4%
충북 39
 
4.0%
부산 27
 
2.8%
Other values (6) 126
13.1%

가맹점명
Text

Distinct960
Distinct (%)99.7%
Missing0
Missing (%)0.0%
Memory size7.7 KiB
2023-12-12T10:42:10.373029image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length43
Median length29
Mean length13.103842
Min length2

Characters and Unicode

Total characters12619
Distinct characters598
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique957 ?
Unique (%)99.4%

Sample

1st row헐리우드민박(팬션)
2nd row(주)삼성여행사
3rd row정보화마을 농촌체험
4th row(주)하나투어
5th row하나프리티켓
ValueCountFrequency (%)
롯데컬처웍스㈜롯데시네마 93
 
4.7%
강원 50
 
2.5%
경북 43
 
2.2%
롯데시네마 42
 
2.1%
경기 39
 
2.0%
전남 38
 
1.9%
전북 28
 
1.4%
경남 28
 
1.4%
충남 23
 
1.2%
제주 22
 
1.1%
Other values (1276) 1569
79.4%
2023-12-12T10:42:10.866421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1015
 
8.0%
마 462
 
3.7%
( 449
 
3.6%
) 448
 
3.6%
을 297
 
2.4%
스 238
 
1.9%
데 237
 
1.9%
롯 235
 
1.9%
시 232
 
1.8%
주 209
 
1.7%
Other values (588) 8797
69.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 10202
80.8%
Space Separator 1015
 
8.0%
Open Punctuation 449
 
3.6%
Close Punctuation 448
 
3.6%
Uppercase Letter 246
 
1.9%
Other Symbol 115
 
0.9%
Lowercase Letter 100
 
0.8%
Decimal Number 38
 
0.3%
Other Punctuation 4
 
< 0.1%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
마 462
 
4.5%
을 297
 
2.9%
스 238
 
2.3%
데 237
 
2.3%
롯 235
 
2.3%
시 232
 
2.3%
주 209
 
2.0%
인 204
 
2.0%
라 163
 
1.6%
산 152
 
1.5%
Other values (527) 7773
76.2%
Uppercase Letter
ValueCountFrequency (%)
S 27
 
11.0%
O 22
 
8.9%
K 20
 
8.1%
C 19
 
7.7%
E 19
 
7.7%
A 17
 
6.9%
T 13
 
5.3%
G 12
 
4.9%
L 11
 
4.5%
B 10
 
4.1%
Other values (14) 76
30.9%
Lowercase Letter
ValueCountFrequency (%)
e 16
16.0%
i 11
11.0%
l 9
9.0%
t 8
 
8.0%
c 8
 
8.0%
a 7
 
7.0%
v 7
 
7.0%
n 5
 
5.0%
o 4
 
4.0%
s 4
 
4.0%
Other values (10) 21
21.0%
Decimal Number
ValueCountFrequency (%)
2 9
23.7%
4 9
23.7%
1 7
18.4%
9 4
10.5%
0 4
10.5%
5 2
 
5.3%
3 2
 
5.3%
8 1
 
2.6%
Other Punctuation
ValueCountFrequency (%)
/ 2
50.0%
. 1
25.0%
# 1
25.0%
Space Separator
ValueCountFrequency (%)
1015
100.0%
Open Punctuation
ValueCountFrequency (%)
( 449
100.0%
Close Punctuation
ValueCountFrequency (%)
) 448
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 115
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 10317
81.8%
Common 1956
 
15.5%
Latin 346
 
2.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
마 462
 
4.5%
을 297
 
2.9%
스 238
 
2.3%
데 237
 
2.3%
롯 235
 
2.3%
시 232
 
2.2%
주 209
 
2.0%
인 204
 
2.0%
라 163
 
1.6%
산 152
 
1.5%
Other values (528) 7888
76.5%
Latin
ValueCountFrequency (%)
S 27
 
7.8%
O 22
 
6.4%
K 20
 
5.8%
C 19
 
5.5%
E 19
 
5.5%
A 17
 
4.9%
e 16
 
4.6%
T 13
 
3.8%
G 12
 
3.5%
L 11
 
3.2%
Other values (34) 170
49.1%
Common
ValueCountFrequency (%)
1015
51.9%
( 449
23.0%
) 448
22.9%
2 9
 
0.5%
4 9
 
0.5%
1 7
 
0.4%
9 4
 
0.2%
0 4
 
0.2%
5 2
 
0.1%
3 2
 
0.1%
Other values (6) 7
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 10202
80.8%
ASCII 2302
 
18.2%
None 115
 
0.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1015
44.1%
( 449
19.5%
) 448
19.5%
S 27
 
1.2%
O 22
 
1.0%
K 20
 
0.9%
C 19
 
0.8%
E 19
 
0.8%
A 17
 
0.7%
e 16
 
0.7%
Other values (50) 250
 
10.9%
Hangul
ValueCountFrequency (%)
마 462
 
4.5%
을 297
 
2.9%
스 238
 
2.3%
데 237
 
2.3%
롯 235
 
2.3%
시 232
 
2.3%
주 209
 
2.0%
인 204
 
2.0%
라 163
 
1.6%
산 152
 
1.5%
Other values (527) 7773
76.2%
None
ValueCountFrequency (%)
㈜ 115
100.0%

분류
Categorical

Distinct13
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size7.7 KiB
관광지
402 
영상
160 
공연
71 
체육시설
67 
체육용품
43 
Other values (8)
220 

Length

Max length5
Median length4
Mean length2.8296989
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row숙박
2nd row여행사
3rd row관광지
4th row여행사
5th row공연

Common Values

ValueCountFrequency (%)
관광지 402
41.7%
영상 160
 
16.6%
공연 71
 
7.4%
체육시설 67
 
7.0%
체육용품 43
 
4.5%
미술 42
 
4.4%
도서 42
 
4.4%
음악 33
 
3.4%
여행사 25
 
2.6%
스포츠관람 24
 
2.5%
Other values (3) 54
 
5.6%

Length

2023-12-12T10:42:11.008435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
관광지 402
41.7%
영상 160
 
16.6%
공연 71
 
7.4%
체육시설 67
 
7.0%
체육용품 43
 
4.5%
미술 42
 
4.4%
도서 42
 
4.4%
음악 33
 
3.4%
여행사 25
 
2.6%
스포츠관람 24
 
2.5%
Other values (3) 54
 
5.6%

주소
Text

Distinct931
Distinct (%)96.7%
Missing0
Missing (%)0.0%
Memory size7.7 KiB
2023-12-12T10:42:11.349379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length57
Median length45
Mean length25.05296
Min length12

Characters and Unicode

Total characters24126
Distinct characters533
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique910 ?
Unique (%)94.5%

Sample

1st row전북 부안군 변산면 도청리162-1
2nd row대구광역시 중구 국채보상로 515
3rd row서울특별시 강남구 테헤란로25길 50 304호
4th row서울특별시 종로구 인사동5길 41 하나빌딩
5th row서울특별시 종로구 인사동5길 41 하나빌딩
ValueCountFrequency (%)
서울특별시 192
 
3.7%
경기도 99
 
1.9%
경기 75
 
1.4%
서울 60
 
1.1%
경북 57
 
1.1%
강원 54
 
1.0%
정보화마을 47
 
0.9%
경남 46
 
0.9%
중구 46
 
0.9%
전남 42
 
0.8%
Other values (2509) 4521
86.3%
2023-12-12T10:42:11.980421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5409
 
22.4%
1 779
 
3.2%
로 752
 
3.1%
시 710
 
2.9%
구 568
 
2.4%
2 531
 
2.2%
서 392
 
1.6%
길 387
 
1.6%
경 371
 
1.5%
3 354
 
1.5%
Other values (523) 13873
57.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 14616
60.6%
Space Separator 5409
 
22.4%
Decimal Number 3573
 
14.8%
Dash Punctuation 177
 
0.7%
Uppercase Letter 124
 
0.5%
Other Punctuation 73
 
0.3%
Open Punctuation 61
 
0.3%
Close Punctuation 61
 
0.3%
Math Symbol 19
 
0.1%
Lowercase Letter 13
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 752
 
5.1%
시 710
 
4.9%
구 568
 
3.9%
서 392
 
2.7%
길 387
 
2.6%
경 371
 
2.5%
울 305
 
2.1%
남 292
 
2.0%
동 289
 
2.0%
면 282
 
1.9%
Other values (470) 10268
70.3%
Uppercase Letter
ValueCountFrequency (%)
C 17
13.7%
N 13
10.5%
D 12
 
9.7%
M 12
 
9.7%
A 8
 
6.5%
E 7
 
5.6%
B 6
 
4.8%
T 6
 
4.8%
H 6
 
4.8%
K 5
 
4.0%
Other values (13) 32
25.8%
Lowercase Letter
ValueCountFrequency (%)
i 2
15.4%
u 2
15.4%
g 1
7.7%
n 1
7.7%
d 1
7.7%
l 1
7.7%
c 1
7.7%
e 1
7.7%
t 1
7.7%
r 1
7.7%
Decimal Number
ValueCountFrequency (%)
1 779
21.8%
2 531
14.9%
3 354
9.9%
0 332
9.3%
5 305
 
8.5%
4 305
 
8.5%
6 279
 
7.8%
8 263
 
7.4%
7 233
 
6.5%
9 192
 
5.4%
Other Punctuation
ValueCountFrequency (%)
, 67
91.8%
. 4
 
5.5%
· 1
 
1.4%
& 1
 
1.4%
Space Separator
ValueCountFrequency (%)
5409
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 177
100.0%
Open Punctuation
ValueCountFrequency (%)
( 61
100.0%
Close Punctuation
ValueCountFrequency (%)
) 61
100.0%
Math Symbol
ValueCountFrequency (%)
~ 19
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 14616
60.6%
Common 9373
38.9%
Latin 137
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 752
 
5.1%
시 710
 
4.9%
구 568
 
3.9%
서 392
 
2.7%
길 387
 
2.6%
경 371
 
2.5%
울 305
 
2.1%
남 292
 
2.0%
동 289
 
2.0%
면 282
 
1.9%
Other values (470) 10268
70.3%
Latin
ValueCountFrequency (%)
C 17
 
12.4%
N 13
 
9.5%
D 12
 
8.8%
M 12
 
8.8%
A 8
 
5.8%
E 7
 
5.1%
B 6
 
4.4%
T 6
 
4.4%
H 6
 
4.4%
K 5
 
3.6%
Other values (24) 45
32.8%
Common
ValueCountFrequency (%)
5409
57.7%
1 779
 
8.3%
2 531
 
5.7%
3 354
 
3.8%
0 332
 
3.5%
5 305
 
3.3%
4 305
 
3.3%
6 279
 
3.0%
8 263
 
2.8%
7 233
 
2.5%
Other values (9) 583
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 14616
60.6%
ASCII 9509
39.4%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5409
56.9%
1 779
 
8.2%
2 531
 
5.6%
3 354
 
3.7%
0 332
 
3.5%
5 305
 
3.2%
4 305
 
3.2%
6 279
 
2.9%
8 263
 
2.8%
7 233
 
2.5%
Other values (42) 719
 
7.6%
Hangul
ValueCountFrequency (%)
로 752
 
5.1%
시 710
 
4.9%
구 568
 
3.9%
서 392
 
2.7%
길 387
 
2.6%
경 371
 
2.5%
울 305
 
2.1%
남 292
 
2.0%
동 289
 
2.0%
면 282
 
1.9%
Other values (470) 10268
70.3%
None
ValueCountFrequency (%)
· 1
100.0%

전화번호
Text

Distinct777
Distinct (%)80.7%
Missing0
Missing (%)0.0%
Memory size7.7 KiB
2023-12-12T10:42:12.348399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length11.2108
Min length9

Characters and Unicode

Total characters10796
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

Unique751 ?
Unique (%)78.0%

Sample

1st row063-583-7088
2nd row053-431-3000
3rd row1833-2990
4th row1577-1233
5th row1566-6668
ValueCountFrequency (%)
1544-8855 130
 
13.5%
1588-7890 13
 
1.3%
02-752-8041 9
 
0.9%
1670-9201 8
 
0.8%
1544-1555 4
 
0.4%
02-356-0273 4
 
0.4%
1833-2990 4
 
0.4%
1588-3820 3
 
0.3%
031-955-3333 3
 
0.3%
1661-2000 2
 
0.2%
Other values (767) 783
81.3%
2023-12-12T10:42:12.872594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 1671
15.5%
0 1601
14.8%
5 1184
11.0%
4 1030
9.5%
3 918
8.5%
1 894
8.3%
8 857
7.9%
2 818
7.6%
6 692
6.4%
7 665
 
6.2%
Other values (2) 466
 
4.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 9124
84.5%
Dash Punctuation 1671
 
15.5%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1601
17.5%
5 1184
13.0%
4 1030
11.3%
3 918
10.1%
1 894
9.8%
8 857
9.4%
2 818
9.0%
6 692
7.6%
7 665
7.3%
9 465
 
5.1%
Dash Punctuation
ValueCountFrequency (%)
- 1671
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 10796
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 1671
15.5%
0 1601
14.8%
5 1184
11.0%
4 1030
9.5%
3 918
8.5%
1 894
8.3%
8 857
7.9%
2 818
7.6%
6 692
6.4%
7 665
 
6.2%
Other values (2) 466
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 10796
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 1671
15.5%
0 1601
14.8%
5 1184
11.0%
4 1030
9.5%
3 918
8.5%
1 894
8.3%
8 857
7.9%
2 818
7.6%
6 692
6.4%
7 665
 
6.2%
Other values (2) 466
 
4.3%

Correlations

2023-12-12T10:42:13.013955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지역분류
지역1.0000.491
분류0.4911.000
2023-12-12T10:42:13.129966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지역분류
지역1.0000.197
분류0.1971.000
2023-12-12T10:42:13.243225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
지역분류
지역1.0000.197
분류0.1971.000

Missing values

2023-12-12T10:42:09.853858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T10:42:09.976195image/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.

Sample

지역가맹점명분류주소전화번호
0전북헐리우드민박(팬션)숙박전북 부안군 변산면 도청리162-1063-583-7088
1대구(주)삼성여행사여행사대구광역시 중구 국채보상로 515053-431-3000
2서울정보화마을 농촌체험관광지서울특별시 강남구 테헤란로25길 50 304호1833-2990
3서울(주)하나투어여행사서울특별시 종로구 인사동5길 41 하나빌딩1577-1233
4서울하나프리티켓공연서울특별시 종로구 인사동5길 41 하나빌딩1566-6668
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