Overview

Dataset statistics

Number of variables5
Number of observations36
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.5 KiB
Average record size in memory43.7 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 (81.7%)Imbalance
업소명 has unique valuesUnique
주소 has unique valuesUnique
전화번호 has unique valuesUnique

Reproduction

Analysis started2023-12-11 00:33:10.868438
Analysis finished2023-12-11 00:33:11.297239
Duration0.43 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업소명
Text

UNIQUE 

Distinct36
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size420.0 B
2023-12-11T09:33:11.456041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length10
Mean length5.9444444
Min length2

Characters and Unicode

Total characters214
Distinct characters113
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique36 ?
Unique (%)100.0%

Sample

1st row북면자연농원
2nd row우포한우프라자
3rd row조선옥삼계탕
4th row화덕본가
5th row월남쌈샤브이야기
ValueCountFrequency (%)
북면자연농원 1
 
2.7%
우포늪식당 1
 
2.7%
귀촌마을 1
 
2.7%
부생밀면고기집 1
 
2.7%
도천진짜순대창녕점 1
 
2.7%
하나비 1
 
2.7%
창녕대가 1
 
2.7%
석정숯불갈비 1
 
2.7%
선하축산 1
 
2.7%
양반청국장 1
 
2.7%
Other values (27) 27
73.0%
2023-12-11T09:33:11.902510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
식 11
 
5.1%
당 7
 
3.3%
우 7
 
3.3%
한 6
 
2.8%
자 5
 
2.3%
가 5
 
2.3%
집 4
 
1.9%
산 4
 
1.9%
기 4
 
1.9%
면 4
 
1.9%
Other values (103) 157
73.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 212
99.1%
Other Symbol 1
 
0.5%
Space Separator 1
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
식 11
 
5.2%
당 7
 
3.3%
우 7
 
3.3%
한 6
 
2.8%
자 5
 
2.4%
가 5
 
2.4%
집 4
 
1.9%
산 4
 
1.9%
기 4
 
1.9%
면 4
 
1.9%
Other values (101) 155
73.1%
Other Symbol
ValueCountFrequency (%)
㈜ 1
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 213
99.5%
Common 1
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
식 11
 
5.2%
당 7
 
3.3%
우 7
 
3.3%
한 6
 
2.8%
자 5
 
2.3%
가 5
 
2.3%
집 4
 
1.9%
산 4
 
1.9%
기 4
 
1.9%
면 4
 
1.9%
Other values (102) 156
73.2%
Common
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 212
99.1%
None 1
 
0.5%
ASCII 1
 
0.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
식 11
 
5.2%
당 7
 
3.3%
우 7
 
3.3%
한 6
 
2.8%
자 5
 
2.4%
가 5
 
2.4%
집 4
 
1.9%
산 4
 
1.9%
기 4
 
1.9%
면 4
 
1.9%
Other values (101) 155
73.1%
None
ValueCountFrequency (%)
㈜ 1
100.0%
ASCII
ValueCountFrequency (%)
1
100.0%

주소
Text

UNIQUE 

Distinct36
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size420.0 B
2023-12-11T09:33:12.140271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length14
Mean length12.138889
Min length10

Characters and Unicode

Total characters437
Distinct characters70
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

Unique36 ?
Unique (%)100.0%

Sample

1st row계성면 영산계성로 397-5
2nd row계성면 영산계성로 547
3rd row남지읍 남지리 981-8
4th row남지읍 남지중앙1길 17-1
5th row남지읍 남지중앙로 83-1
ValueCountFrequency (%)
창녕읍 15
 
13.9%
영산면 5
 
4.6%
도천면 5
 
4.6%
남지읍 4
 
3.7%
부곡면 3
 
2.8%
온천로 3
 
2.8%
말흘리 3
 
2.8%
화왕산로 2
 
1.9%
우포2로 2
 
1.9%
계성면 2
 
1.9%
Other values (63) 64
59.3%
2023-12-11T09:33:12.572900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
72
 
16.5%
1 24
 
5.5%
읍 19
 
4.3%
- 17
 
3.9%
면 17
 
3.9%
8 16
 
3.7%
2 16
 
3.7%
녕 16
 
3.7%
창 16
 
3.7%
길 14
 
3.2%
Other values (60) 210
48.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 238
54.5%
Decimal Number 110
25.2%
Space Separator 72
 
16.5%
Dash Punctuation 17
 
3.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
읍 19
 
8.0%
면 17
 
7.1%
녕 16
 
6.7%
창 16
 
6.7%
길 14
 
5.9%
로 14
 
5.9%
천 11
 
4.6%
산 10
 
4.2%
리 9
 
3.8%
영 8
 
3.4%
Other values (48) 104
43.7%
Decimal Number
ValueCountFrequency (%)
1 24
21.8%
8 16
14.5%
2 16
14.5%
9 10
9.1%
6 10
9.1%
4 9
 
8.2%
7 8
 
7.3%
5 8
 
7.3%
3 5
 
4.5%
0 4
 
3.6%
Space Separator
ValueCountFrequency (%)
72
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 17
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 238
54.5%
Common 199
45.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
읍 19
 
8.0%
면 17
 
7.1%
녕 16
 
6.7%
창 16
 
6.7%
길 14
 
5.9%
로 14
 
5.9%
천 11
 
4.6%
산 10
 
4.2%
리 9
 
3.8%
영 8
 
3.4%
Other values (48) 104
43.7%
Common
ValueCountFrequency (%)
72
36.2%
1 24
 
12.1%
- 17
 
8.5%
8 16
 
8.0%
2 16
 
8.0%
9 10
 
5.0%
6 10
 
5.0%
4 9
 
4.5%
7 8
 
4.0%
5 8
 
4.0%
Other values (2) 9
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 238
54.5%
ASCII 199
45.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
72
36.2%
1 24
 
12.1%
- 17
 
8.5%
8 16
 
8.0%
2 16
 
8.0%
9 10
 
5.0%
6 10
 
5.0%
4 9
 
4.5%
7 8
 
4.0%
5 8
 
4.0%
Other values (2) 9
 
4.5%
Hangul
ValueCountFrequency (%)
읍 19
 
8.0%
면 17
 
7.1%
녕 16
 
6.7%
창 16
 
6.7%
길 14
 
5.9%
로 14
 
5.9%
천 11
 
4.6%
산 10
 
4.2%
리 9
 
3.8%
영 8
 
3.4%
Other values (48) 104
43.7%

전화번호
Text

UNIQUE 

Distinct36
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size420.0 B
2023-12-11T09:33:12.811858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters432
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

Unique36 ?
Unique (%)100.0%

Sample

1st row055-521-8858
2nd row055-536-4114
3rd row055-526-1044
4th row055-521-8592
5th row055-526-4296
ValueCountFrequency (%)
055-521-8858 1
 
2.8%
055-536-4114 1
 
2.8%
055-533-9966 1
 
2.8%
055-533-9600 1
 
2.8%
055-533-0392 1
 
2.8%
055-532-4388 1
 
2.8%
055-532-0074 1
 
2.8%
055-532-3301 1
 
2.8%
055-533-1180 1
 
2.8%
055-533-0503 1
 
2.8%
Other values (26) 26
72.2%
2023-12-11T09:33:13.147072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 122
28.2%
- 72
16.7%
0 58
13.4%
3 52
12.0%
2 30
 
6.9%
6 24
 
5.6%
1 20
 
4.6%
9 18
 
4.2%
8 16
 
3.7%
4 13
 
3.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 360
83.3%
Dash Punctuation 72
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 122
33.9%
0 58
16.1%
3 52
14.4%
2 30
 
8.3%
6 24
 
6.7%
1 20
 
5.6%
9 18
 
5.0%
8 16
 
4.4%
4 13
 
3.6%
7 7
 
1.9%
Dash Punctuation
ValueCountFrequency (%)
- 72
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 432
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 122
28.2%
- 72
16.7%
0 58
13.4%
3 52
12.0%
2 30
 
6.9%
6 24
 
5.6%
1 20
 
4.6%
9 18
 
4.2%
8 16
 
3.7%
4 13
 
3.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 432
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 122
28.2%
- 72
16.7%
0 58
13.4%
3 52
12.0%
2 30
 
6.9%
6 24
 
5.6%
1 20
 
4.6%
9 18
 
4.2%
8 16
 
3.7%
4 13
 
3.0%

주메뉴
Text

Distinct35
Distinct (%)97.2%
Missing0
Missing (%)0.0%
Memory size420.0 B
2023-12-11T09:33:13.389065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length9
Mean length7.9166667
Min length2

Characters and Unicode

Total characters285
Distinct characters96
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

Unique34 ?
Unique (%)94.4%

Sample

1st row오리불고기,오리탕
2nd row한우숯불구이,갈비탕
3rd row삼계탕,석쇠불고기
4th row돼지갈비
5th row월남쌈샤브
ValueCountFrequency (%)
순대전골 2
 
4.4%
청국장 2
 
4.4%
돼지고기 2
 
4.4%
모듬순대 2
 
4.4%
아구찜,추어탕 1
 
2.2%
돼지갈비,소갈비 1
 
2.2%
오리불고기,오리탕 1
 
2.2%
칡냉면 1
 
2.2%
인동초한우전문점 1
 
2.2%
돼지갈비,판메밀 1
 
2.2%
Other values (31) 31
68.9%
2023-12-11T09:33:13.741747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
, 28
 
9.8%
기 12
 
4.2%
비 11
 
3.9%
고 10
 
3.5%
탕 9
 
3.2%
갈 9
 
3.2%
9
 
3.2%
한 8
 
2.8%
지 8
 
2.8%
우 8
 
2.8%
Other values (86) 173
60.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 248
87.0%
Other Punctuation 28
 
9.8%
Space Separator 9
 
3.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 12
 
4.8%
비 11
 
4.4%
고 10
 
4.0%
탕 9
 
3.6%
갈 9
 
3.6%
한 8
 
3.2%
지 8
 
3.2%
우 8
 
3.2%
돼 7
 
2.8%
장 7
 
2.8%
Other values (84) 159
64.1%
Other Punctuation
ValueCountFrequency (%)
, 28
100.0%
Space Separator
ValueCountFrequency (%)
9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 248
87.0%
Common 37
 
13.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 12
 
4.8%
비 11
 
4.4%
고 10
 
4.0%
탕 9
 
3.6%
갈 9
 
3.6%
한 8
 
3.2%
지 8
 
3.2%
우 8
 
3.2%
돼 7
 
2.8%
장 7
 
2.8%
Other values (84) 159
64.1%
Common
ValueCountFrequency (%)
, 28
75.7%
9
 
24.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 248
87.0%
ASCII 37
 
13.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
, 28
75.7%
9
 
24.3%
Hangul
ValueCountFrequency (%)
기 12
 
4.8%
비 11
 
4.4%
고 10
 
4.0%
탕 9
 
3.6%
갈 9
 
3.6%
한 8
 
3.2%
지 8
 
3.2%
우 8
 
3.2%
돼 7
 
2.8%
장 7
 
2.8%
Other values (84) 159
64.1%

분류
Categorical

IMBALANCE 

Distinct2
Distinct (%)5.6%
Missing0
Missing (%)0.0%
Memory size420.0 B
한식
35 
일식
 
1

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique1 ?
Unique (%)2.8%

Sample

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

Common Values

ValueCountFrequency (%)
한식 35
97.2%
일식 1
 
2.8%

Length

2023-12-11T09:33:13.868326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T09:33:13.979088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
한식 35
97.2%
일식 1
 
2.8%

Correlations

2023-12-11T09:33:14.044904image/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

2023-12-11T09:33:11.150477image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T09:33:11.264220image/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
0북면자연농원계성면 영산계성로 397-5055-521-8858오리불고기,오리탕한식
1우포한우프라자계성면 영산계성로 547055-536-4114한우숯불구이,갈비탕한식
2조선옥삼계탕남지읍 남지리 981-8055-526-1044삼계탕,석쇠불고기한식
3화덕본가남지읍 남지중앙1길 17-1055-521-8592돼지갈비한식
4월남쌈샤브이야기남지읍 남지중앙로 83-1055-526-4296월남쌈샤브한식
5연안바다횟집남지읍 남포1길 2055-536-4252모듬회,회덮밥한식
6가현한우생고기전문점대지면 효정리 328-1055-532-9259한우생고기한식
7향촌가든도천면 가마골2길 5055-536-4450촌닭,오리백숙,송이백숙한식
8통일냉면도천면 개울길 29-8055-521-8852냉면, 갈비탕한식
9양평해장국도천면 낙동로 811055-526-0118양평해장국, 소내장탕한식
업소명주소전화번호주메뉴분류
26금성칡냉면창녕읍 술정리 4-2055-533-9966칡냉면한식
27선하축산창녕읍 술정중앙길 18-6055-533-0503삼겹살, 목살한식
28가얏골감자탕창녕읍 우포2로 1179055-532-1770김치감자탕,시래기감자탕한식
29창녕한우창녕읍 우포2로 1200055-533-3338한우쇠고기, 돼지고기한식
30화왕산풀향기식당창녕읍 자하곡길 75055-533-9098수제비,버섯전골한식
31금별식당창녕읍 창녕대동길 39055-532-9393아구찜,추어탕한식
32고궁창녕읍 탑금당길 16055-532-0335청국장, 오리불고기한식
33화왕산갈비마을창녕읍 화왕산로 18055-532-9292돼지갈비,소갈비한식
34양반청국장창녕읍 화왕산로 64055-533-0066청국장한식
35풀무원식품㈜영산휴게소 한식당영산면 장척호수길 56-110055-521-2978장터국밥,김치찌개한식