Overview

Dataset statistics

Number of variables4
Number of observations61
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.0 KiB
Average record size in memory34.2 B

Variable types

Text4

Dataset

Description인천광역시 미추홀구의 맛있는집 선정업소 현황에 대한 데이터로 업소명, 주소,전화번호 등의 정보를 제공하고 있습니다.
Author인천광역시 미추홀구
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=15102062&srcSe=7661IVAWM27C61E190

Alerts

업소명 has unique valuesUnique
전화번호 has unique valuesUnique

Reproduction

Analysis started2024-03-18 05:03:10.429347
Analysis finished2024-03-18 05:03:12.560221
Duration2.13 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업소명
Text

UNIQUE 

Distinct61
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size620.0 B
2024-03-18T14:03:12.736969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length11
Mean length5.9508197
Min length2

Characters and Unicode

Total characters363
Distinct characters180
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique61 ?
Unique (%)100.0%

Sample

1st row가마솥순두부
2nd row경복궁학익점(주)엔타스시스템
3rd row계절식당
4th row고려한방삼계탕
5th row곤드레愛찬
ValueCountFrequency (%)
가마솥순두부 1
 
1.6%
경복궁학익점(주)엔타스시스템 1
 
1.6%
신포횟집 1
 
1.6%
약선당감자탕 1
 
1.6%
양반집 1
 
1.6%
어가싱싱회종합어시장 1
 
1.6%
오향왕족발육족 1
 
1.6%
신기본점 1
 
1.6%
옥경이네생태찌개 1
 
1.6%
옹진냉면집 1
 
1.6%
Other values (54) 54
84.4%
2024-03-18T14:03:13.125022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
탕 9
 
2.5%
원 9
 
2.5%
가 8
 
2.2%
기 7
 
1.9%
어 7
 
1.9%
물 6
 
1.7%
지 6
 
1.7%
추 5
 
1.4%
삼 5
 
1.4%
갈 5
 
1.4%
Other values (170) 296
81.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 353
97.2%
Open Punctuation 3
 
0.8%
Close Punctuation 3
 
0.8%
Space Separator 3
 
0.8%
Other Punctuation 1
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
탕 9
 
2.5%
원 9
 
2.5%
가 8
 
2.3%
기 7
 
2.0%
어 7
 
2.0%
물 6
 
1.7%
지 6
 
1.7%
추 5
 
1.4%
삼 5
 
1.4%
갈 5
 
1.4%
Other values (166) 286
81.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Space Separator
ValueCountFrequency (%)
3
100.0%
Other Punctuation
ValueCountFrequency (%)
& 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 351
96.7%
Common 10
 
2.8%
Han 2
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
탕 9
 
2.6%
원 9
 
2.6%
가 8
 
2.3%
기 7
 
2.0%
어 7
 
2.0%
물 6
 
1.7%
지 6
 
1.7%
추 5
 
1.4%
삼 5
 
1.4%
갈 5
 
1.4%
Other values (164) 284
80.9%
Common
ValueCountFrequency (%)
( 3
30.0%
) 3
30.0%
3
30.0%
& 1
 
10.0%
Han
ValueCountFrequency (%)
愛 1
50.0%
林 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 351
96.7%
ASCII 10
 
2.8%
CJK 2
 
0.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
탕 9
 
2.6%
원 9
 
2.6%
가 8
 
2.3%
기 7
 
2.0%
어 7
 
2.0%
물 6
 
1.7%
지 6
 
1.7%
추 5
 
1.4%
삼 5
 
1.4%
갈 5
 
1.4%
Other values (164) 284
80.9%
ASCII
ValueCountFrequency (%)
( 3
30.0%
) 3
30.0%
3
30.0%
& 1
 
10.0%
CJK
ValueCountFrequency (%)
愛 1
50.0%
林 1
50.0%

주소
Text

Distinct60
Distinct (%)98.4%
Missing0
Missing (%)0.0%
Memory size620.0 B
2024-03-18T14:03:13.371731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length34
Median length29
Mean length25.098361
Min length21

Characters and Unicode

Total characters1531
Distinct characters74
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

Unique59 ?
Unique (%)96.7%

Sample

1st row인천광역시 미추홀구 소성로 326(문학동)
2nd row인천광역시 미추홀구 매소홀로 378(학익동)
3rd row인천광역시 미추홀구 낙섬서로10번길 28(용현동)
4th row인천광역시 미추홀구 인주대로 404(주안동)
5th row인천광역시 미추홀구 매소홀로 407(학익동)
ValueCountFrequency (%)
인천광역시 62
24.8%
미추홀구 61
24.4%
매소홀로 6
 
2.4%
미추홀대로 4
 
1.6%
소성로 3
 
1.2%
독배로 3
 
1.2%
숭의동 3
 
1.2%
미추로 2
 
0.8%
석정로 2
 
0.8%
석바위로 2
 
0.8%
Other values (97) 102
40.8%
2024-03-18T14:03:13.780835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
190
 
12.4%
인 73
 
4.8%
홀 73
 
4.8%
미 68
 
4.4%
추 68
 
4.4%
천 64
 
4.2%
구 63
 
4.1%
역 62
 
4.0%
시 62
 
4.0%
광 62
 
4.0%
Other values (64) 746
48.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 998
65.2%
Decimal Number 212
 
13.8%
Space Separator 190
 
12.4%
Open Punctuation 60
 
3.9%
Close Punctuation 60
 
3.9%
Dash Punctuation 11
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
인 73
 
7.3%
홀 73
 
7.3%
미 68
 
6.8%
추 68
 
6.8%
천 64
 
6.4%
구 63
 
6.3%
역 62
 
6.2%
시 62
 
6.2%
광 62
 
6.2%
동 61
 
6.1%
Other values (50) 342
34.3%
Decimal Number
ValueCountFrequency (%)
2 31
14.6%
1 28
13.2%
3 22
10.4%
4 22
10.4%
8 21
9.9%
5 20
9.4%
6 18
8.5%
9 18
8.5%
7 17
8.0%
0 15
7.1%
Space Separator
ValueCountFrequency (%)
190
100.0%
Open Punctuation
ValueCountFrequency (%)
( 60
100.0%
Close Punctuation
ValueCountFrequency (%)
) 60
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 998
65.2%
Common 533
34.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
인 73
 
7.3%
홀 73
 
7.3%
미 68
 
6.8%
추 68
 
6.8%
천 64
 
6.4%
구 63
 
6.3%
역 62
 
6.2%
시 62
 
6.2%
광 62
 
6.2%
동 61
 
6.1%
Other values (50) 342
34.3%
Common
ValueCountFrequency (%)
190
35.6%
( 60
 
11.3%
) 60
 
11.3%
2 31
 
5.8%
1 28
 
5.3%
3 22
 
4.1%
4 22
 
4.1%
8 21
 
3.9%
5 20
 
3.8%
6 18
 
3.4%
Other values (4) 61
 
11.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 998
65.2%
ASCII 533
34.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
190
35.6%
( 60
 
11.3%
) 60
 
11.3%
2 31
 
5.8%
1 28
 
5.3%
3 22
 
4.1%
4 22
 
4.1%
8 21
 
3.9%
5 20
 
3.8%
6 18
 
3.4%
Other values (4) 61
 
11.4%
Hangul
ValueCountFrequency (%)
인 73
 
7.3%
홀 73
 
7.3%
미 68
 
6.8%
추 68
 
6.8%
천 64
 
6.4%
구 63
 
6.3%
역 62
 
6.2%
시 62
 
6.2%
광 62
 
6.2%
동 61
 
6.1%
Other values (50) 342
34.3%

전화번호
Text

UNIQUE 

Distinct61
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size620.0 B
2024-03-18T14:03:14.007131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters732
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

Unique61 ?
Unique (%)100.0%

Sample

1st row032-426-7270
2nd row032-873-2000
3rd row032-888-7419
4th row032-431-1133
5th row032-876-6322
ValueCountFrequency (%)
032-426-7270 1
 
1.6%
032-881-7076 1
 
1.6%
032-888-7700 1
 
1.6%
032-867-4286 1
 
1.6%
032-891-0777 1
 
1.6%
032-883-1889 1
 
1.6%
032-875-1300 1
 
1.6%
032-875-0589 1
 
1.6%
032-466-1676 1
 
1.6%
032-875-0410 1
 
1.6%
Other values (51) 51
83.6%
2024-03-18T14:03:14.406929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 122
16.7%
0 106
14.5%
2 103
14.1%
3 101
13.8%
8 88
12.0%
7 46
 
6.3%
6 40
 
5.5%
4 38
 
5.2%
5 35
 
4.8%
1 28
 
3.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 610
83.3%
Dash Punctuation 122
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 106
17.4%
2 103
16.9%
3 101
16.6%
8 88
14.4%
7 46
7.5%
6 40
 
6.6%
4 38
 
6.2%
5 35
 
5.7%
1 28
 
4.6%
9 25
 
4.1%
Dash Punctuation
ValueCountFrequency (%)
- 122
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 732
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 122
16.7%
0 106
14.5%
2 103
14.1%
3 101
13.8%
8 88
12.0%
7 46
 
6.3%
6 40
 
5.5%
4 38
 
5.2%
5 35
 
4.8%
1 28
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 732
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 122
16.7%
0 106
14.5%
2 103
14.1%
3 101
13.8%
8 88
12.0%
7 46
 
6.3%
6 40
 
5.5%
4 38
 
5.2%
5 35
 
4.8%
1 28
 
3.8%

메뉴
Text

Distinct57
Distinct (%)93.4%
Missing0
Missing (%)0.0%
Memory size620.0 B
2024-03-18T14:03:14.660548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length13
Mean length5.7213115
Min length2

Characters and Unicode

Total characters349
Distinct characters149
Distinct categories4 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique53 ?
Unique (%)86.9%

Sample

1st row두부보쌈
2nd row양념갈비
3rd row산문어연포탕
4th row한방삼계탕
5th row곤드레나물밥
ValueCountFrequency (%)
탕 3
 
4.1%
추어탕 3
 
4.1%
모듬초밥 2
 
2.7%
아귀찜 2
 
2.7%
생태전골 2
 
2.7%
생선회정식 1
 
1.4%
찹쌀순대국 1
 
1.4%
포두부황토구이보쌈 1
 
1.4%
민물파장어쌈 1
 
1.4%
냉면 1
 
1.4%
Other values (56) 56
76.7%
2024-03-18T14:03:15.058517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
탕 18
 
5.2%
12
 
3.4%
, 10
 
2.9%
찜 10
 
2.9%
어 10
 
2.9%
리 7
 
2.0%
비 7
 
2.0%
갈 7
 
2.0%
선 5
 
1.4%
추 5
 
1.4%
Other values (139) 258
73.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 324
92.8%
Space Separator 12
 
3.4%
Other Punctuation 10
 
2.9%
Uppercase Letter 3
 
0.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
탕 18
 
5.6%
찜 10
 
3.1%
어 10
 
3.1%
리 7
 
2.2%
비 7
 
2.2%
갈 7
 
2.2%
선 5
 
1.5%
추 5
 
1.5%
이 5
 
1.5%
장 5
 
1.5%
Other values (134) 245
75.6%
Uppercase Letter
ValueCountFrequency (%)
P 1
33.3%
I 1
33.3%
V 1
33.3%
Space Separator
ValueCountFrequency (%)
12
100.0%
Other Punctuation
ValueCountFrequency (%)
, 10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 324
92.8%
Common 22
 
6.3%
Latin 3
 
0.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
탕 18
 
5.6%
찜 10
 
3.1%
어 10
 
3.1%
리 7
 
2.2%
비 7
 
2.2%
갈 7
 
2.2%
선 5
 
1.5%
추 5
 
1.5%
이 5
 
1.5%
장 5
 
1.5%
Other values (134) 245
75.6%
Latin
ValueCountFrequency (%)
P 1
33.3%
I 1
33.3%
V 1
33.3%
Common
ValueCountFrequency (%)
12
54.5%
, 10
45.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 324
92.8%
ASCII 25
 
7.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
탕 18
 
5.6%
찜 10
 
3.1%
어 10
 
3.1%
리 7
 
2.2%
비 7
 
2.2%
갈 7
 
2.2%
선 5
 
1.5%
추 5
 
1.5%
이 5
 
1.5%
장 5
 
1.5%
Other values (134) 245
75.6%
ASCII
ValueCountFrequency (%)
12
48.0%
, 10
40.0%
P 1
 
4.0%
I 1
 
4.0%
V 1
 
4.0%

Correlations

2024-03-18T14:03:15.175607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업소명주소전화번호메뉴
업소명1.0001.0001.0001.000
주소1.0001.0001.0000.991
전화번호1.0001.0001.0001.000
메뉴1.0000.9911.0001.000

Missing values

2024-03-18T14:03:12.422893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-18T14:03:12.521557image/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

업소명주소전화번호메뉴
0가마솥순두부인천광역시 미추홀구 소성로 326(문학동)032-426-7270두부보쌈
1경복궁학익점(주)엔타스시스템인천광역시 미추홀구 매소홀로 378(학익동)032-873-2000양념갈비
2계절식당인천광역시 미추홀구 낙섬서로10번길 28(용현동)032-888-7419산문어연포탕
3고려한방삼계탕인천광역시 미추홀구 인주대로 404(주안동)032-431-1133한방삼계탕
4곤드레愛찬인천광역시 미추홀구 매소홀로 407(학익동)032-876-6322곤드레나물밥
5광명갈비탕인천광역시 미추홀구 인하로262번길 20(주안동)032-863-2225갈비탕
6권가네전주비빔밥인천광역시 미추홀구 문학길 9-37(문학동)032-431-2973비빔밥
7금산식당인천광역시 미추홀구 매소홀로488번길 6-29(학익동)032-864-3003벤뎅이회무침
8김가네볼테기아구찜인천광역시 미추홀구 미추로 55(숭의동)032-884-8850대구볼테기탕
9나삼보해물가인천광역시 미추홀구 미추홀대로 661(주안동)032-439-7900해물탕
업소명주소전화번호메뉴
51평창곤드레추어탕인천광역시 미추홀구 경원대로628번길 5(관교동)032-426-7424추어탕, 매콤곤드레코다리찜
52함흥관인천광역시 미추홀구 인중로 1(숭의동)032-889-4004전복갈비찜
53화진원인천광역시 미추홀구 인주대로128번길 30(용현동)032-763-1818갈빗살버섯전골, 새우간장조림
54황금게장인천광역시 미추홀구 석바위로 49(주안동)032-873-6868꽃게장
55황금오리인천광역시 미추홀구 석정로 428(주안동)032-861-2020웰빙한방오리백숙
56장재은오리집인천광역시 미추홀구 소성로185번길 16-9(학익동)032-435-5282한방노루궁뎅이오리백숙
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