Overview

Dataset statistics

Number of variables5
Number of observations30
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.3 KiB
Average record size in memory45.4 B

Variable types

Numeric1
Text4

Dataset

Description대구광역시 동구에서 추천하는 대구광역시 동구 맛집 현황입니다. 이 데이터는 업소명, 주소, 전화번호, 주메뉴 항목을 제공합니다.
Author대구광역시 동구
URLhttps://www.data.go.kr/data/15052653/fileData.do

Alerts

연번 has unique valuesUnique
업소명 has unique valuesUnique
전화번호 has unique valuesUnique
주메뉴 has unique valuesUnique

Reproduction

Analysis started2024-04-06 08:10:01.069933
Analysis finished2024-04-06 08:10:02.265046
Duration1.2 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean15.5
Minimum1
Maximum30
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2024-04-06T17:10:02.405274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.45
Q18.25
median15.5
Q322.75
95-th percentile28.55
Maximum30
Range29
Interquartile range (IQR)14.5

Descriptive statistics

Standard deviation8.8034084
Coefficient of variation (CV)0.56796183
Kurtosis-1.2
Mean15.5
Median Absolute Deviation (MAD)7.5
Skewness0
Sum465
Variance77.5
MonotonicityStrictly increasing
2024-04-06T17:10:02.708572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
1 1
 
3.3%
17 1
 
3.3%
30 1
 
3.3%
29 1
 
3.3%
28 1
 
3.3%
27 1
 
3.3%
26 1
 
3.3%
25 1
 
3.3%
24 1
 
3.3%
23 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
1 1
3.3%
2 1
3.3%
3 1
3.3%
4 1
3.3%
5 1
3.3%
6 1
3.3%
7 1
3.3%
8 1
3.3%
9 1
3.3%
10 1
3.3%
ValueCountFrequency (%)
30 1
3.3%
29 1
3.3%
28 1
3.3%
27 1
3.3%
26 1
3.3%
25 1
3.3%
24 1
3.3%
23 1
3.3%
22 1
3.3%
21 1
3.3%

업소명
Text

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
2024-04-06T17:10:03.122660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length9
Mean length5.9
Min length2

Characters and Unicode

Total characters177
Distinct characters111
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique30 ?
Unique (%)100.0%

Sample

1st row거송복어식당
2nd row고향집칼국수.재바우
3rd row고향차밭골식당
4th row더기네장어
5th row만수정
ValueCountFrequency (%)
거송복어식당 1
 
3.1%
고향집칼국수.재바우 1
 
3.1%
원조어탕 1
 
3.1%
팔공은가비 1
 
3.1%
팔도웰빙쌈밥 1
 
3.1%
55온족발동촌유원지점 1
 
3.1%
행복한맛고을 1
 
3.1%
황토시골집 1
 
3.1%
화우정식당 1
 
3.1%
해아래숲 1
 
3.1%
Other values (22) 22
68.8%
2024-04-06T17:10:03.813561image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
식 6
 
3.4%
당 6
 
3.4%
수 5
 
2.8%
리 4
 
2.3%
재 3
 
1.7%
오 3
 
1.7%
토 3
 
1.7%
미 3
 
1.7%
가 3
 
1.7%
정 3
 
1.7%
Other values (101) 138
78.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 172
97.2%
Decimal Number 2
 
1.1%
Space Separator 2
 
1.1%
Other Punctuation 1
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
식 6
 
3.5%
당 6
 
3.5%
수 5
 
2.9%
리 4
 
2.3%
재 3
 
1.7%
오 3
 
1.7%
토 3
 
1.7%
미 3
 
1.7%
가 3
 
1.7%
정 3
 
1.7%
Other values (98) 133
77.3%
Decimal Number
ValueCountFrequency (%)
5 2
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 172
97.2%
Common 5
 
2.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
식 6
 
3.5%
당 6
 
3.5%
수 5
 
2.9%
리 4
 
2.3%
재 3
 
1.7%
오 3
 
1.7%
토 3
 
1.7%
미 3
 
1.7%
가 3
 
1.7%
정 3
 
1.7%
Other values (98) 133
77.3%
Common
ValueCountFrequency (%)
5 2
40.0%
2
40.0%
. 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 172
97.2%
ASCII 5
 
2.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
식 6
 
3.5%
당 6
 
3.5%
수 5
 
2.9%
리 4
 
2.3%
재 3
 
1.7%
오 3
 
1.7%
토 3
 
1.7%
미 3
 
1.7%
가 3
 
1.7%
정 3
 
1.7%
Other values (98) 133
77.3%
ASCII
ValueCountFrequency (%)
5 2
40.0%
2
40.0%
. 1
20.0%

주소
Text

Distinct29
Distinct (%)96.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
2024-04-06T17:10:04.253394image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length46
Median length26
Mean length23.866667
Min length20

Characters and Unicode

Total characters716
Distinct characters74
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique28 ?
Unique (%)93.3%

Sample

1st row대구광역시 동구 동촌로 263(방촌동)
2nd row대구광역시 동구 송라로 93(신천동)
3rd row대구광역시 동구 팔공산로 339(송정동)
4th row대구광역시 동구 팔공산로2길 88(덕곡동)
5th row대구광역시 동구 단산길 7-13(봉무동)
ValueCountFrequency (%)
대구광역시 30
23.4%
동구 30
23.4%
갓바위로 3
 
2.3%
효동로6길 2
 
1.6%
1층 2
 
1.6%
파계로 2
 
1.6%
효동로2길 2
 
1.6%
2층(효목동 2
 
1.6%
93(신천동 2
 
1.6%
송라로 2
 
1.6%
Other values (51) 51
39.8%
2024-04-06T17:10:05.028259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
98
 
13.7%
동 66
 
9.2%
구 60
 
8.4%
대 35
 
4.9%
( 30
 
4.2%
광 30
 
4.2%
역 30
 
4.2%
시 30
 
4.2%
) 30
 
4.2%
로 30
 
4.2%
Other values (64) 277
38.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 421
58.8%
Decimal Number 119
 
16.6%
Space Separator 98
 
13.7%
Open Punctuation 30
 
4.2%
Close Punctuation 30
 
4.2%
Dash Punctuation 10
 
1.4%
Other Punctuation 8
 
1.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 66
15.7%
구 60
14.3%
대 35
 
8.3%
광 30
 
7.1%
역 30
 
7.1%
시 30
 
7.1%
로 30
 
7.1%
길 14
 
3.3%
효 9
 
2.1%
목 5
 
1.2%
Other values (48) 112
26.6%
Decimal Number
ValueCountFrequency (%)
1 19
16.0%
2 18
15.1%
3 17
14.3%
5 15
12.6%
6 14
11.8%
4 9
7.6%
8 9
7.6%
0 8
6.7%
9 6
 
5.0%
7 4
 
3.4%
Other Punctuation
ValueCountFrequency (%)
, 7
87.5%
. 1
 
12.5%
Space Separator
ValueCountFrequency (%)
98
100.0%
Open Punctuation
ValueCountFrequency (%)
( 30
100.0%
Close Punctuation
ValueCountFrequency (%)
) 30
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 421
58.8%
Common 295
41.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 66
15.7%
구 60
14.3%
대 35
 
8.3%
광 30
 
7.1%
역 30
 
7.1%
시 30
 
7.1%
로 30
 
7.1%
길 14
 
3.3%
효 9
 
2.1%
목 5
 
1.2%
Other values (48) 112
26.6%
Common
ValueCountFrequency (%)
98
33.2%
( 30
 
10.2%
) 30
 
10.2%
1 19
 
6.4%
2 18
 
6.1%
3 17
 
5.8%
5 15
 
5.1%
6 14
 
4.7%
- 10
 
3.4%
4 9
 
3.1%
Other values (6) 35
 
11.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 421
58.8%
ASCII 295
41.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
98
33.2%
( 30
 
10.2%
) 30
 
10.2%
1 19
 
6.4%
2 18
 
6.1%
3 17
 
5.8%
5 15
 
5.1%
6 14
 
4.7%
- 10
 
3.4%
4 9
 
3.1%
Other values (6) 35
 
11.9%
Hangul
ValueCountFrequency (%)
동 66
15.7%
구 60
14.3%
대 35
 
8.3%
광 30
 
7.1%
역 30
 
7.1%
시 30
 
7.1%
로 30
 
7.1%
길 14
 
3.3%
효 9
 
2.1%
목 5
 
1.2%
Other values (48) 112
26.6%

전화번호
Text

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
2024-04-06T17:10:05.449228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters360
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

Unique30 ?
Unique (%)100.0%

Sample

1st row053-984-6755
2nd row053-751-6850
3rd row053-981-5883
4th row053-982-2537
5th row053-985-1814
ValueCountFrequency (%)
053-984-6755 1
 
3.3%
053-751-6850 1
 
3.3%
053-983-8886 1
 
3.3%
053-985-0124 1
 
3.3%
053-939-5568 1
 
3.3%
053-964-8225 1
 
3.3%
053-982-1001 1
 
3.3%
053-986-5900 1
 
3.3%
053-985-8052 1
 
3.3%
053-957-2356 1
 
3.3%
Other values (20) 20
66.7%
2024-04-06T17:10:06.047441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 60
16.7%
5 57
15.8%
0 53
14.7%
3 40
11.1%
9 39
10.8%
8 35
9.7%
6 18
 
5.0%
1 17
 
4.7%
2 17
 
4.7%
7 13
 
3.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 300
83.3%
Dash Punctuation 60
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 57
19.0%
0 53
17.7%
3 40
13.3%
9 39
13.0%
8 35
11.7%
6 18
 
6.0%
1 17
 
5.7%
2 17
 
5.7%
7 13
 
4.3%
4 11
 
3.7%
Dash Punctuation
ValueCountFrequency (%)
- 60
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 360
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 60
16.7%
5 57
15.8%
0 53
14.7%
3 40
11.1%
9 39
10.8%
8 35
9.7%
6 18
 
5.0%
1 17
 
4.7%
2 17
 
4.7%
7 13
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 360
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 60
16.7%
5 57
15.8%
0 53
14.7%
3 40
11.1%
9 39
10.8%
8 35
9.7%
6 18
 
5.0%
1 17
 
4.7%
2 17
 
4.7%
7 13
 
3.6%

주메뉴
Text

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
2024-04-06T17:10:06.466079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length14
Mean length8.5
Min length3

Characters and Unicode

Total characters255
Distinct characters107
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique30 ?
Unique (%)100.0%

Sample

1st row복어찜+탕
2nd row칼국수
3rd row차밭골 정식
4th row장어숯불구이+곤드레장어탕
5th row장어탕
ValueCountFrequency (%)
복어찜+탕 1
 
2.8%
칼국수 1
 
2.8%
연요리정찬 1
 
2.8%
한방편육+메밀면 1
 
2.8%
직화쭈꾸미 1
 
2.8%
백숙 1
 
2.8%
냉면 1
 
2.8%
영양오리백숙 1
 
2.8%
닭백숙 1
 
2.8%
버섯만두전골 1
 
2.8%
Other values (26) 26
72.2%
2024-04-06T17:10:07.167053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
+ 19
 
7.5%
리 9
 
3.5%
이 8
 
3.1%
8
 
3.1%
오 8
 
3.1%
탕 7
 
2.7%
어 6
 
2.4%
숙 6
 
2.4%
국 6
 
2.4%
백 6
 
2.4%
Other values (97) 172
67.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 222
87.1%
Math Symbol 19
 
7.5%
Space Separator 8
 
3.1%
Other Punctuation 4
 
1.6%
Close Punctuation 1
 
0.4%
Open Punctuation 1
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 9
 
4.1%
이 8
 
3.6%
오 8
 
3.6%
탕 7
 
3.2%
어 6
 
2.7%
숙 6
 
2.7%
국 6
 
2.7%
백 6
 
2.7%
수 5
 
2.3%
미 5
 
2.3%
Other values (91) 156
70.3%
Other Punctuation
ValueCountFrequency (%)
, 3
75.0%
/ 1
 
25.0%
Math Symbol
ValueCountFrequency (%)
+ 19
100.0%
Space Separator
ValueCountFrequency (%)
8
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 222
87.1%
Common 33
 
12.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 9
 
4.1%
이 8
 
3.6%
오 8
 
3.6%
탕 7
 
3.2%
어 6
 
2.7%
숙 6
 
2.7%
국 6
 
2.7%
백 6
 
2.7%
수 5
 
2.3%
미 5
 
2.3%
Other values (91) 156
70.3%
Common
ValueCountFrequency (%)
+ 19
57.6%
8
24.2%
, 3
 
9.1%
) 1
 
3.0%
( 1
 
3.0%
/ 1
 
3.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 222
87.1%
ASCII 33
 
12.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
+ 19
57.6%
8
24.2%
, 3
 
9.1%
) 1
 
3.0%
( 1
 
3.0%
/ 1
 
3.0%
Hangul
ValueCountFrequency (%)
리 9
 
4.1%
이 8
 
3.6%
오 8
 
3.6%
탕 7
 
3.2%
어 6
 
2.7%
숙 6
 
2.7%
국 6
 
2.7%
백 6
 
2.7%
수 5
 
2.3%
미 5
 
2.3%
Other values (91) 156
70.3%

Interactions

2024-04-06T17:10:01.623105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-06T17:10:07.337093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번업소명주소전화번호주메뉴
연번1.0001.0000.9271.0001.000
업소명1.0001.0001.0001.0001.000
주소0.9271.0001.0001.0001.000
전화번호1.0001.0001.0001.0001.000
주메뉴1.0001.0001.0001.0001.000

Missing values

2024-04-06T17:10:01.861336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-06T17:10:02.152245image/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

연번업소명주소전화번호주메뉴
01거송복어식당대구광역시 동구 동촌로 263(방촌동)053-984-6755복어찜+탕
12고향집칼국수.재바우대구광역시 동구 송라로 93(신천동)053-751-6850칼국수
23고향차밭골식당대구광역시 동구 팔공산로 339(송정동)053-981-5883차밭골 정식
34더기네장어대구광역시 동구 팔공산로2길 88(덕곡동)053-982-2537장어숯불구이+곤드레장어탕
45만수정대구광역시 동구 단산길 7-13(봉무동)053-985-1814장어탕
56명산가대구광역시 동구 공항로 140(불로동)053-984-3550곤드레/연잎밥정식+섬나물비빔밥
67미소명가미역대구광역시 동구 효동로6길 47-5(효목동)053-956-9657가자미미역국+꼬막정찬
78백림정대구광역시 동구 도평로 249(도동)053-986-0032옻닭+옻오리
89블루문레스토랑대구광역시 동구 파계로685(중대동)053-981-8088안심스테이크류
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2021천서리원조메밀면대구광역시 동구 갓바위로 243-3(진인동)053-981-6001한방편육+메밀면
2122춤추는 아양쭈꾸미대구광역시 동구 효동로2길 13-3, 2층(효목동)053-957-2356직화쭈꾸미
2223해아래숲대구광역시 동구 파계로138길 26(중대동)053-985-8052백숙+ 냉면
2324화우정식당대구광역시 동구 서촌로23길 13-1(덕곡동)053-986-5900영양오리백숙
2425황토시골집대구광역시 동구 파계로 604(중대동)053-982-1001닭백숙
2526행복한맛고을대구광역시 동구 이노밸리로54길 3-12, 1층 (신서동)053-964-8225버섯만두전골+ 만두국
262755온족발동촌유원지점대구광역시 동구 효동로2길 45(효목동)053-939-5568온족발+불족발
2728팔도웰빙쌈밥대구광역시 동구 팔공로 31길 6-3, 104호,105호,109호,110호(불로동)053-985-0124쌈+제육+생선구이
2829팔공은가비대구광역시 동구 용천로 58 (미곡동)053-983-8886능이한방백숙(오리, 닭), 닭볶음탕
2930원조어탕 팔공산점대구광역시 동구 파계로 569, 1층 (중대동)053-981-5299어탕수제비, 어탕칼국수