Overview

Dataset statistics

Number of variables5
Number of observations31
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.3 KiB
Average record size in memory44.3 B

Variable types

Text4
Categorical1

Dataset

Description경상남도 창녕군 음식점에 대한 데이터를 포함하고 있습니다.(모범음식점 업소명, 주소, 전화번호, 주메뉴, 분류)
Author경상남도 창녕군
URLhttps://bigdata.gyeongnam.go.kr/index.gn?menuCd=DOM_000000114002001000&publicdatapk=15007289

Alerts

분류 is highly imbalanced (79.4%)Imbalance
업소명 has unique valuesUnique
주소 has unique valuesUnique
전화번호 has unique valuesUnique

Reproduction

Analysis started2023-12-11 00:33:14.946432
Analysis finished2023-12-11 00:33:15.390488
Duration0.44 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업소명
Text

UNIQUE 

Distinct31
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size380.0 B
2023-12-11T09:33:15.532580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length9
Mean length5.9032258
Min length2

Characters and Unicode

Total characters183
Distinct characters106
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

Unique31 ?
Unique (%)100.0%

Sample

1st row서울식육식당
2nd row황부자숯불갈비
3rd row하나비
4th row풀무원식품(주)영산휴게소 한식당
5th row고궁
ValueCountFrequency (%)
서울식육식당 1
 
3.0%
진짜순대집 1
 
3.0%
선하축산 1
 
3.0%
북면자연농원 1
 
3.0%
월남쌈샤브이야기 1
 
3.0%
우포한우프라자 1
 
3.0%
통일냉면 1
 
3.0%
석정숯불갈비 1
 
3.0%
양평해장국 1
 
3.0%
로타리식육식당 1
 
3.0%
Other values (23) 23
69.7%
2023-12-11T09:33:15.877166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
식 8
 
4.4%
우 6
 
3.3%
당 5
 
2.7%
한 5
 
2.7%
집 4
 
2.2%
면 4
 
2.2%
자 4
 
2.2%
비 4
 
2.2%
녕 3
 
1.6%
기 3
 
1.6%
Other values (96) 137
74.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 179
97.8%
Space Separator 2
 
1.1%
Close Punctuation 1
 
0.5%
Open Punctuation 1
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
식 8
 
4.5%
우 6
 
3.4%
당 5
 
2.8%
한 5
 
2.8%
집 4
 
2.2%
면 4
 
2.2%
자 4
 
2.2%
비 4
 
2.2%
녕 3
 
1.7%
기 3
 
1.7%
Other values (93) 133
74.3%
Space Separator
ValueCountFrequency (%)
2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 179
97.8%
Common 4
 
2.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
식 8
 
4.5%
우 6
 
3.4%
당 5
 
2.8%
한 5
 
2.8%
집 4
 
2.2%
면 4
 
2.2%
자 4
 
2.2%
비 4
 
2.2%
녕 3
 
1.7%
기 3
 
1.7%
Other values (93) 133
74.3%
Common
ValueCountFrequency (%)
2
50.0%
) 1
25.0%
( 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 179
97.8%
ASCII 4
 
2.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
식 8
 
4.5%
우 6
 
3.4%
당 5
 
2.8%
한 5
 
2.8%
집 4
 
2.2%
면 4
 
2.2%
자 4
 
2.2%
비 4
 
2.2%
녕 3
 
1.7%
기 3
 
1.7%
Other values (93) 133
74.3%
ASCII
ValueCountFrequency (%)
2
50.0%
) 1
25.0%
( 1
25.0%

주소
Text

UNIQUE 

Distinct31
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size380.0 B
2023-12-11T09:33:16.094165image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length45
Median length30
Mean length23.032258
Min length19

Characters and Unicode

Total characters714
Distinct characters79
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

Unique31 ?
Unique (%)100.0%

Sample

1st row경상남도 창녕군 부곡면 온천1길 65
2nd row경상남도 창녕군 부곡면 원앙로 49 (외1필지)
3rd row경상남도 창녕군 창녕읍 화왕산로 88
4th row경상남도 창녕군 영산면 장척호수길 56-110
5th row경상남도 창녕군 창녕읍 탑금당길 16
ValueCountFrequency (%)
경상남도 31
19.0%
창녕군 31
19.0%
창녕읍 13
 
8.0%
화왕산로 5
 
3.1%
도천면 4
 
2.5%
영산면 4
 
2.5%
부곡면 3
 
1.8%
남지읍 3
 
1.8%
영산계성로 2
 
1.2%
69 2
 
1.2%
Other values (61) 65
39.9%
2023-12-11T09:33:16.493487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
132
18.5%
창 45
 
6.3%
녕 45
 
6.3%
남 37
 
5.2%
도 36
 
5.0%
경 33
 
4.6%
군 32
 
4.5%
상 31
 
4.3%
1 28
 
3.9%
로 17
 
2.4%
Other values (69) 278
38.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 453
63.4%
Space Separator 132
 
18.5%
Decimal Number 103
 
14.4%
Dash Punctuation 10
 
1.4%
Open Punctuation 6
 
0.8%
Close Punctuation 6
 
0.8%
Other Punctuation 4
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
창 45
 
9.9%
녕 45
 
9.9%
남 37
 
8.2%
도 36
 
7.9%
경 33
 
7.3%
군 32
 
7.1%
상 31
 
6.8%
로 17
 
3.8%
읍 16
 
3.5%
면 15
 
3.3%
Other values (54) 146
32.2%
Decimal Number
ValueCountFrequency (%)
1 28
27.2%
8 13
12.6%
6 11
 
10.7%
2 10
 
9.7%
9 9
 
8.7%
7 8
 
7.8%
0 7
 
6.8%
5 6
 
5.8%
4 6
 
5.8%
3 5
 
4.9%
Space Separator
ValueCountFrequency (%)
132
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 10
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 453
63.4%
Common 261
36.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
창 45
 
9.9%
녕 45
 
9.9%
남 37
 
8.2%
도 36
 
7.9%
경 33
 
7.3%
군 32
 
7.1%
상 31
 
6.8%
로 17
 
3.8%
읍 16
 
3.5%
면 15
 
3.3%
Other values (54) 146
32.2%
Common
ValueCountFrequency (%)
132
50.6%
1 28
 
10.7%
8 13
 
5.0%
6 11
 
4.2%
- 10
 
3.8%
2 10
 
3.8%
9 9
 
3.4%
7 8
 
3.1%
0 7
 
2.7%
5 6
 
2.3%
Other values (5) 27
 
10.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 453
63.4%
ASCII 261
36.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
132
50.6%
1 28
 
10.7%
8 13
 
5.0%
6 11
 
4.2%
- 10
 
3.8%
2 10
 
3.8%
9 9
 
3.4%
7 8
 
3.1%
0 7
 
2.7%
5 6
 
2.3%
Other values (5) 27
 
10.3%
Hangul
ValueCountFrequency (%)
창 45
 
9.9%
녕 45
 
9.9%
남 37
 
8.2%
도 36
 
7.9%
경 33
 
7.3%
군 32
 
7.1%
상 31
 
6.8%
로 17
 
3.8%
읍 16
 
3.5%
면 15
 
3.3%
Other values (54) 146
32.2%

전화번호
Text

UNIQUE 

Distinct31
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size380.0 B
2023-12-11T09:33:16.697573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters372
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

Unique31 ?
Unique (%)100.0%

Sample

1st row055-536-6369
2nd row055-536-5103
3rd row055-532-0074
4th row055-521-2978
5th row055-532-0335
ValueCountFrequency (%)
055-536-6369 1
 
3.2%
055-536-4388 1
 
3.2%
055-533-0503 1
 
3.2%
055-521-8858 1
 
3.2%
055-526-4296 1
 
3.2%
055-536-4114 1
 
3.2%
055-521-8852 1
 
3.2%
055-533-1180 1
 
3.2%
055-526-0118 1
 
3.2%
055-536-3551 1
 
3.2%
Other values (21) 21
67.7%
2023-12-11T09:33:16.996107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 104
28.0%
- 62
16.7%
0 48
12.9%
3 46
12.4%
2 28
 
7.5%
6 21
 
5.6%
1 19
 
5.1%
9 14
 
3.8%
8 14
 
3.8%
4 10
 
2.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 310
83.3%
Dash Punctuation 62
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 104
33.5%
0 48
15.5%
3 46
14.8%
2 28
 
9.0%
6 21
 
6.8%
1 19
 
6.1%
9 14
 
4.5%
8 14
 
4.5%
4 10
 
3.2%
7 6
 
1.9%
Dash Punctuation
ValueCountFrequency (%)
- 62
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 372
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 104
28.0%
- 62
16.7%
0 48
12.9%
3 46
12.4%
2 28
 
7.5%
6 21
 
5.6%
1 19
 
5.1%
9 14
 
3.8%
8 14
 
3.8%
4 10
 
2.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 372
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 104
28.0%
- 62
16.7%
0 48
12.9%
3 46
12.4%
2 28
 
7.5%
6 21
 
5.6%
1 19
 
5.1%
9 14
 
3.8%
8 14
 
3.8%
4 10
 
2.7%

주메뉴
Text

Distinct29
Distinct (%)93.5%
Missing0
Missing (%)0.0%
Memory size380.0 B
2023-12-11T09:33:17.196335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length15
Mean length11.032258
Min length3

Characters and Unicode

Total characters342
Distinct characters97
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

Unique27 ?
Unique (%)87.1%

Sample

1st row소갈비살+꽃등심+버섯전골+소고기전골+꼬리곰탕
2nd row양념돼지갈비
3rd row우동정식+모밀정식+생선초밥+일식코스요리
4th row장터국밥+김치찌개
5th row오리불고기+오리탕+한방백숙
ValueCountFrequency (%)
등 3
 
8.6%
순대전골+모듬순대 2
 
5.7%
양념돼지갈비 2
 
5.7%
한우스페셜구이+한우모듬+육회 1
 
2.9%
소갈비살+꽃등심+버섯전골+소고기전골+꼬리곰탕 1
 
2.9%
잉어찜+붕어찜+메기찜+논고동무침+메기탕 1
 
2.9%
활어회+매운탕+회덮밥 1
 
2.9%
오리불고기+오리탕 1
 
2.9%
한우생고기+돼지고기 1
 
2.9%
한우숯불구이+갈비탕 1
 
2.9%
Other values (21) 21
60.0%
2023-12-11T09:33:17.516414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
+ 44
 
12.9%
비 13
 
3.8%
기 13
 
3.8%
고 12
 
3.5%
탕 11
 
3.2%
갈 10
 
2.9%
불 8
 
2.3%
전 8
 
2.3%
리 7
 
2.0%
한 7
 
2.0%
Other values (87) 209
61.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 294
86.0%
Math Symbol 44
 
12.9%
Space Separator 4
 
1.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
비 13
 
4.4%
기 13
 
4.4%
고 12
 
4.1%
탕 11
 
3.7%
갈 10
 
3.4%
불 8
 
2.7%
전 8
 
2.7%
리 7
 
2.4%
한 7
 
2.4%
찜 7
 
2.4%
Other values (85) 198
67.3%
Math Symbol
ValueCountFrequency (%)
+ 44
100.0%
Space Separator
ValueCountFrequency (%)
4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 294
86.0%
Common 48
 
14.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
비 13
 
4.4%
기 13
 
4.4%
고 12
 
4.1%
탕 11
 
3.7%
갈 10
 
3.4%
불 8
 
2.7%
전 8
 
2.7%
리 7
 
2.4%
한 7
 
2.4%
찜 7
 
2.4%
Other values (85) 198
67.3%
Common
ValueCountFrequency (%)
+ 44
91.7%
4
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 294
86.0%
ASCII 48
 
14.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
+ 44
91.7%
4
 
8.3%
Hangul
ValueCountFrequency (%)
비 13
 
4.4%
기 13
 
4.4%
고 12
 
4.1%
탕 11
 
3.7%
갈 10
 
3.4%
불 8
 
2.7%
전 8
 
2.7%
리 7
 
2.4%
한 7
 
2.4%
찜 7
 
2.4%
Other values (85) 198
67.3%

분류
Categorical

IMBALANCE 

Distinct2
Distinct (%)6.5%
Missing0
Missing (%)0.0%
Memory size380.0 B
한식
30 
일식
 
1

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique1 ?
Unique (%)3.2%

Sample

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

Common Values

ValueCountFrequency (%)
한식 30
96.8%
일식 1
 
3.2%

Length

2023-12-11T09:33:17.629594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:33:17.710930image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
한식 30
96.8%
일식 1
 
3.2%

Correlations

2023-12-11T09:33:17.760775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업소명주소전화번호주메뉴분류
업소명1.0001.0001.0001.0001.000
주소1.0001.0001.0001.0001.000
전화번호1.0001.0001.0001.0001.000
주메뉴1.0001.0001.0001.0001.000
분류1.0001.0001.0001.0001.000

Missing values

2023-12-11T09:33:15.270397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T09:33:15.357812image/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

업소명주소전화번호주메뉴분류
0서울식육식당경상남도 창녕군 부곡면 온천1길 65055-536-6369소갈비살+꽃등심+버섯전골+소고기전골+꼬리곰탕한식
1황부자숯불갈비경상남도 창녕군 부곡면 원앙로 49 (외1필지)055-536-5103양념돼지갈비한식
2하나비경상남도 창녕군 창녕읍 화왕산로 88055-532-0074우동정식+모밀정식+생선초밥+일식코스요리한식
3풀무원식품(주)영산휴게소 한식당경상남도 창녕군 영산면 장척호수길 56-110055-521-2978장터국밥+김치찌개한식
4고궁경상남도 창녕군 창녕읍 탑금당길 16055-532-0335오리불고기+오리탕+한방백숙한식
5부생밀면고기집경상남도 창녕군 창녕읍 군청길 26, 2동 1층055-533-0392물밀면+비빔밀면 등한식
6도리원경상남도 창녕군 영산면 온천로 103-25055-521-6116장아찌정식한식
7금별식당경상남도 창녕군 창녕읍 창녕대동길 39055-532-9393해물찜+꽃게찜+아구찜+추어탕한식
8조선옥삼계탕경상남도 창녕군 남지읍 동포7길 19-1055-526-1044삼계탕한식
9흥부네전골경상남도 창녕군 부곡면 온천2길 42 ((같은번지내 변경))055-536-0293버섯전골+불고기전골+돼지갈비+삼겹살한식
업소명주소전화번호주메뉴분류
21양반청국장경상남도 창녕군 창녕읍 화왕산로 64055-533-0066청국장 전문점한식
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