Overview

Dataset statistics

Number of variables5
Number of observations89
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.6 KiB
Average record size in memory41.5 B

Variable types

Text4
Categorical1

Dataset

Description대구광역시_수성구 모범음식점 현황_20231211
Author대구광역시 수성구
URLhttp://data.daegu.go.kr/open/data/dataView.do?dataSetId=15054680&dataSetDetailId=150546801a5c23ee02440&provdMethod=FILE

Alerts

소재지(도로명) has unique valuesUnique
소재지전화번호 has unique valuesUnique

Reproduction

Analysis started2023-12-16 05:09:39.625861
Analysis finished2023-12-16 05:09:50.237555
Duration10.61 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업소명
Text

Distinct88
Distinct (%)98.9%
Missing0
Missing (%)0.0%
Memory size844.0 B
2023-12-16T05:09:50.805577image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length11
Mean length6.4382022
Min length2

Characters and Unicode

Total characters573
Distinct characters222
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 (%)97.8%

Sample

1st row가리산삼계탕
2nd row가창제일횟집
3rd row가츠라수성못본점
4th row감나무집
5th row감포은정복어횟집
ValueCountFrequency (%)
아주특별한해장국 2
 
1.9%
닭불백 1
 
1.0%
에스파냐 1
 
1.0%
어부네코다리조림대구점 1
 
1.0%
양포수산 1
 
1.0%
양곱화 1
 
1.0%
안동국시 1
 
1.0%
서울칡냉면 1
 
1.0%
예전애 1
 
1.0%
아트리움 1
 
1.0%
Other values (93) 93
89.4%
2023-12-16T05:09:52.179312image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
점 23
 
4.0%
15
 
2.6%
지 12
 
2.1%
한 11
 
1.9%
대 11
 
1.9%
산 10
 
1.7%
성 10
 
1.7%
수 10
 
1.7%
가 9
 
1.6%
리 9
 
1.6%
Other values (212) 453
79.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 523
91.3%
Space Separator 15
 
2.6%
Lowercase Letter 11
 
1.9%
Uppercase Letter 10
 
1.7%
Close Punctuation 7
 
1.2%
Open Punctuation 7
 
1.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
점 23
 
4.4%
지 12
 
2.3%
한 11
 
2.1%
대 11
 
2.1%
산 10
 
1.9%
성 10
 
1.9%
수 10
 
1.9%
가 9
 
1.7%
리 9
 
1.7%
식 8
 
1.5%
Other values (193) 410
78.4%
Uppercase Letter
ValueCountFrequency (%)
H 2
20.0%
I 2
20.0%
B 1
10.0%
A 1
10.0%
L 1
10.0%
Y 1
10.0%
N 1
10.0%
C 1
10.0%
Lowercase Letter
ValueCountFrequency (%)
e 2
18.2%
o 2
18.2%
r 2
18.2%
t 1
9.1%
s 1
9.1%
b 1
9.1%
k 1
9.1%
w 1
9.1%
Space Separator
ValueCountFrequency (%)
15
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7
100.0%
Open Punctuation
ValueCountFrequency (%)
( 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 523
91.3%
Common 29
 
5.1%
Latin 21
 
3.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
점 23
 
4.4%
지 12
 
2.3%
한 11
 
2.1%
대 11
 
2.1%
산 10
 
1.9%
성 10
 
1.9%
수 10
 
1.9%
가 9
 
1.7%
리 9
 
1.7%
식 8
 
1.5%
Other values (193) 410
78.4%
Latin
ValueCountFrequency (%)
H 2
 
9.5%
I 2
 
9.5%
e 2
 
9.5%
o 2
 
9.5%
r 2
 
9.5%
B 1
 
4.8%
A 1
 
4.8%
t 1
 
4.8%
s 1
 
4.8%
b 1
 
4.8%
Other values (6) 6
28.6%
Common
ValueCountFrequency (%)
15
51.7%
) 7
24.1%
( 7
24.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 523
91.3%
ASCII 50
 
8.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
점 23
 
4.4%
지 12
 
2.3%
한 11
 
2.1%
대 11
 
2.1%
산 10
 
1.9%
성 10
 
1.9%
수 10
 
1.9%
가 9
 
1.7%
리 9
 
1.7%
식 8
 
1.5%
Other values (193) 410
78.4%
ASCII
ValueCountFrequency (%)
15
30.0%
) 7
14.0%
( 7
14.0%
H 2
 
4.0%
I 2
 
4.0%
e 2
 
4.0%
o 2
 
4.0%
r 2
 
4.0%
B 1
 
2.0%
A 1
 
2.0%
Other values (9) 9
18.0%

소재지(도로명)
Text

UNIQUE 

Distinct89
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size844.0 B
2023-12-16T05:09:53.494791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length53
Median length37
Mean length25.865169
Min length20

Characters and Unicode

Total characters2302
Distinct characters90
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

Unique89 ?
Unique (%)100.0%

Sample

1st row대구광역시 수성구 들안로 61 (상동)
2nd row대구광역시 수성구 파동로 3 (파동)
3rd row대구광역시 수성구 용학로 138, 1층 (두산동)
4th row대구광역시 수성구 동대구로80길 24, 2,3층 (범어동)
5th row대구광역시 수성구 국채보상로180길 13 (범어동)
ValueCountFrequency (%)
대구광역시 89
19.2%
수성구 89
19.2%
들안로 20
 
4.3%
두산동 15
 
3.2%
달구벌대로 14
 
3.0%
범어동 12
 
2.6%
동대구로 9
 
1.9%
만촌동 8
 
1.7%
상동 8
 
1.7%
중동 8
 
1.7%
Other values (150) 192
41.4%
2023-12-16T05:09:55.244272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
375
16.3%
구 207
 
9.0%
대 117
 
5.1%
동 109
 
4.7%
수 105
 
4.6%
성 105
 
4.6%
( 95
 
4.1%
) 95
 
4.1%
시 90
 
3.9%
광 89
 
3.9%
Other values (80) 915
39.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1359
59.0%
Space Separator 375
 
16.3%
Decimal Number 338
 
14.7%
Open Punctuation 95
 
4.1%
Close Punctuation 95
 
4.1%
Other Punctuation 29
 
1.3%
Dash Punctuation 10
 
0.4%
Uppercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 207
15.2%
대 117
 
8.6%
동 109
 
8.0%
수 105
 
7.7%
성 105
 
7.7%
시 90
 
6.6%
광 89
 
6.5%
역 89
 
6.5%
로 88
 
6.5%
산 22
 
1.6%
Other values (64) 338
24.9%
Decimal Number
ValueCountFrequency (%)
1 73
21.6%
2 65
19.2%
3 44
13.0%
4 36
10.7%
6 23
 
6.8%
9 23
 
6.8%
7 21
 
6.2%
8 21
 
6.2%
0 20
 
5.9%
5 12
 
3.6%
Space Separator
ValueCountFrequency (%)
375
100.0%
Open Punctuation
ValueCountFrequency (%)
( 95
100.0%
Close Punctuation
ValueCountFrequency (%)
) 95
100.0%
Other Punctuation
ValueCountFrequency (%)
, 29
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 10
100.0%
Uppercase Letter
ValueCountFrequency (%)
A 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1359
59.0%
Common 942
40.9%
Latin 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 207
15.2%
대 117
 
8.6%
동 109
 
8.0%
수 105
 
7.7%
성 105
 
7.7%
시 90
 
6.6%
광 89
 
6.5%
역 89
 
6.5%
로 88
 
6.5%
산 22
 
1.6%
Other values (64) 338
24.9%
Common
ValueCountFrequency (%)
375
39.8%
( 95
 
10.1%
) 95
 
10.1%
1 73
 
7.7%
2 65
 
6.9%
3 44
 
4.7%
4 36
 
3.8%
, 29
 
3.1%
6 23
 
2.4%
9 23
 
2.4%
Other values (5) 84
 
8.9%
Latin
ValueCountFrequency (%)
A 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1359
59.0%
ASCII 943
41.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
375
39.8%
( 95
 
10.1%
) 95
 
10.1%
1 73
 
7.7%
2 65
 
6.9%
3 44
 
4.7%
4 36
 
3.8%
, 29
 
3.1%
6 23
 
2.4%
9 23
 
2.4%
Other values (6) 85
 
9.0%
Hangul
ValueCountFrequency (%)
구 207
15.2%
대 117
 
8.6%
동 109
 
8.0%
수 105
 
7.7%
성 105
 
7.7%
시 90
 
6.6%
광 89
 
6.5%
역 89
 
6.5%
로 88
 
6.5%
산 22
 
1.6%
Other values (64) 338
24.9%

소재지전화번호
Text

UNIQUE 

Distinct89
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size844.0 B
2023-12-16T05:09:56.156943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters1068
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

Unique89 ?
Unique (%)100.0%

Sample

1st row053-762-3939
2nd row053-766-2232
3rd row053-761-2611
4th row053-756-7755
5th row053-752-5271
ValueCountFrequency (%)
053-762-3939 1
 
1.1%
053-795-4100 1
 
1.1%
053-764-5321 1
 
1.1%
053-763-5988 1
 
1.1%
053-622-2295 1
 
1.1%
053-763-4831 1
 
1.1%
053-567-6602 1
 
1.1%
053-753-3107 1
 
1.1%
053-763-6633 1
 
1.1%
053-754-3111 1
 
1.1%
Other values (79) 79
88.8%
2023-12-16T05:09:57.729298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 178
16.7%
5 148
13.9%
0 146
13.7%
3 135
12.6%
7 116
10.9%
6 84
7.9%
1 59
 
5.5%
2 57
 
5.3%
4 51
 
4.8%
8 49
 
4.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 890
83.3%
Dash Punctuation 178
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 148
16.6%
0 146
16.4%
3 135
15.2%
7 116
13.0%
6 84
9.4%
1 59
 
6.6%
2 57
 
6.4%
4 51
 
5.7%
8 49
 
5.5%
9 45
 
5.1%
Dash Punctuation
ValueCountFrequency (%)
- 178
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1068
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 178
16.7%
5 148
13.9%
0 146
13.7%
3 135
12.6%
7 116
10.9%
6 84
7.9%
1 59
 
5.5%
2 57
 
5.3%
4 51
 
4.8%
8 49
 
4.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1068
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 178
16.7%
5 148
13.9%
0 146
13.7%
3 135
12.6%
7 116
10.9%
6 84
7.9%
1 59
 
5.5%
2 57
 
5.3%
4 51
 
4.8%
8 49
 
4.6%

업태명
Categorical

Distinct12
Distinct (%)13.5%
Missing0
Missing (%)0.0%
Memory size844.0 B
한식
40 
식육(숯불구이)
21 
일식
6 
복어취급
5 
횟집
 
4
Other values (7)
13 

Length

Max length15
Median length2
Mean length3.9438202
Min length2

Unique

Unique2 ?
Unique (%)2.2%

Sample

1st row한식
2nd row횟집
3rd row일식
4th row한식
5th row복어취급

Common Values

ValueCountFrequency (%)
한식 40
44.9%
식육(숯불구이) 21
23.6%
일식 6
 
6.7%
복어취급 5
 
5.6%
횟집 4
 
4.5%
중국식 3
 
3.4%
경양식 2
 
2.2%
분식 2
 
2.2%
기타 2
 
2.2%
외국음식전문점(인도,태국등) 2
 
2.2%
Other values (2) 2
 
2.2%

Length

2023-12-16T05:09:58.430552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
한식 40
44.9%
식육(숯불구이 21
23.6%
일식 6
 
6.7%
복어취급 5
 
5.6%
횟집 4
 
4.5%
중국식 3
 
3.4%
경양식 2
 
2.2%
분식 2
 
2.2%
기타 2
 
2.2%
외국음식전문점(인도,태국등 2
 
2.2%
Other values (2) 2
 
2.2%

주된음식
Text

Distinct57
Distinct (%)64.0%
Missing0
Missing (%)0.0%
Memory size844.0 B
2023-12-16T05:09:59.277283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length7
Mean length3.6853933
Min length1

Characters and Unicode

Total characters328
Distinct characters108
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique43 ?
Unique (%)48.3%

Sample

1st row삼계탕
2nd row회
3rd row돈까스
4th row삼계탕
5th row복어매운탕
ValueCountFrequency (%)
갈비살 10
 
10.9%
복어매운탕 4
 
4.3%
회 4
 
4.3%
한정식 4
 
4.3%
삼계탕 3
 
3.3%
중화요리 3
 
3.3%
돼지갈비 3
 
3.3%
삼겹살 3
 
3.3%
낙지볶음 3
 
3.3%
국수 2
 
2.2%
Other values (48) 53
57.6%
2023-12-16T05:10:00.995147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
비 14
 
4.3%
갈 13
 
4.0%
살 13
 
4.0%
리 12
 
3.7%
탕 9
 
2.7%
회 8
 
2.4%
지 8
 
2.4%
, 7
 
2.1%
밥 7
 
2.1%
국 7
 
2.1%
Other values (98) 230
70.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 318
97.0%
Other Punctuation 7
 
2.1%
Space Separator 3
 
0.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
비 14
 
4.4%
갈 13
 
4.1%
살 13
 
4.1%
리 12
 
3.8%
탕 9
 
2.8%
회 8
 
2.5%
지 8
 
2.5%
밥 7
 
2.2%
국 7
 
2.2%
고 7
 
2.2%
Other values (96) 220
69.2%
Other Punctuation
ValueCountFrequency (%)
, 7
100.0%
Space Separator
ValueCountFrequency (%)
3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 318
97.0%
Common 10
 
3.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
비 14
 
4.4%
갈 13
 
4.1%
살 13
 
4.1%
리 12
 
3.8%
탕 9
 
2.8%
회 8
 
2.5%
지 8
 
2.5%
밥 7
 
2.2%
국 7
 
2.2%
고 7
 
2.2%
Other values (96) 220
69.2%
Common
ValueCountFrequency (%)
, 7
70.0%
3
30.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 318
97.0%
ASCII 10
 
3.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
비 14
 
4.4%
갈 13
 
4.1%
살 13
 
4.1%
리 12
 
3.8%
탕 9
 
2.8%
회 8
 
2.5%
지 8
 
2.5%
밥 7
 
2.2%
국 7
 
2.2%
고 7
 
2.2%
Other values (96) 220
69.2%
ASCII
ValueCountFrequency (%)
, 7
70.0%
3
30.0%

Correlations

2023-12-16T05:10:01.346000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업소명소재지(도로명)소재지전화번호업태명주된음식
업소명1.0001.0001.0001.0000.970
소재지(도로명)1.0001.0001.0001.0001.000
소재지전화번호1.0001.0001.0001.0001.000
업태명1.0001.0001.0001.0000.975
주된음식0.9701.0001.0000.9751.000

Missing values

2023-12-16T05:09:49.290107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-16T05:09:49.973785image/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

업소명소재지(도로명)소재지전화번호업태명주된음식
0가리산삼계탕대구광역시 수성구 들안로 61 (상동)053-762-3939한식삼계탕
1가창제일횟집대구광역시 수성구 파동로 3 (파동)053-766-2232횟집회
2가츠라수성못본점대구광역시 수성구 용학로 138, 1층 (두산동)053-761-2611일식돈까스
3감나무집대구광역시 수성구 동대구로80길 24, 2,3층 (범어동)053-756-7755한식삼계탕
4감포은정복어횟집대구광역시 수성구 국채보상로180길 13 (범어동)053-752-5271복어취급복어매운탕
5개정시지점대구광역시 수성구 달구벌대로 3188, 202호 (신매동, 아레나스포츠센터 )053-795-7050한식비빔밥
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