Overview

Dataset statistics

Number of variables14
Number of observations45
Missing cells88
Missing cells (%)14.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.1 KiB
Average record size in memory116.9 B

Variable types

Categorical3
Text9
Numeric1
Unsupported1

Dataset

Description경기도 안산시에 있는 착한가격업소 현황으로 업종,업소명,대표자,연락처,주소,품목,가격등을 제공합니다..
URLhttps://www.data.go.kr/data/15036759/fileData.do

Alerts

관리부서명 has constant value ""Constant
데이터기준일자 has constant value ""Constant
연락처 has 7 (15.6%) missing valuesMissing
품목2 has 5 (11.1%) missing valuesMissing
가격2 has 5 (11.1%) missing valuesMissing
품목3 has 13 (28.9%) missing valuesMissing
가격3 has 13 (28.9%) missing valuesMissing
특이사항 has 45 (100.0%) missing valuesMissing
업소명 has unique valuesUnique
대표자 has unique valuesUnique
소재지도로명주소 has unique valuesUnique
특이사항 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2023-12-12 03:21:18.133114
Analysis finished2023-12-12 03:21:19.684295
Duration1.55 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업종
Categorical

Distinct7
Distinct (%)15.6%
Missing0
Missing (%)0.0%
Memory size492.0 B
한식
30 
미용업
6 
기타요식업
 
3
기타비요식업
 
2
양식
 
2
Other values (2)
 
2

Length

Max length6
Median length2
Mean length2.5333333
Min length2

Unique

Unique2 ?
Unique (%)4.4%

Sample

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

Common Values

ValueCountFrequency (%)
한식 30
66.7%
미용업 6
 
13.3%
기타요식업 3
 
6.7%
기타비요식업 2
 
4.4%
양식 2
 
4.4%
중식 1
 
2.2%
세탁업 1
 
2.2%

Length

2023-12-12T12:21:19.803332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T12:21:20.000848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
한식 30
66.7%
미용업 6
 
13.3%
기타요식업 3
 
6.7%
기타비요식업 2
 
4.4%
양식 2
 
4.4%
중식 1
 
2.2%
세탁업 1
 
2.2%

업소명
Text

UNIQUE 

Distinct45
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size492.0 B
2023-12-12T12:21:20.321364image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length5.0888889
Min length2

Characters and Unicode

Total characters229
Distinct characters135
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

Unique45 ?
Unique (%)100.0%

Sample

1st row강원도청국장
2nd row고은미용실
3rd row고잔숯불갈비
4th row고향밥상
5th row구포멸치국수
ValueCountFrequency (%)
강원도청국장 1
 
2.1%
고은미용실 1
 
2.1%
장군만두 1
 
2.1%
장지영헤어샵 1
 
2.1%
장터통닭 1
 
2.1%
진미식당 1
 
2.1%
칠갑산생고기 1
 
2.1%
카페산책 1
 
2.1%
큐당구장 1
 
2.1%
한나헤어아트 1
 
2.1%
Other values (38) 38
79.2%
2023-12-12T12:21:20.745326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
장 8
 
3.5%
고 7
 
3.1%
식 7
 
3.1%
당 7
 
3.1%
한 4
 
1.7%
집 4
 
1.7%
이 4
 
1.7%
국 4
 
1.7%
드 4
 
1.7%
도 4
 
1.7%
Other values (125) 176
76.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 224
97.8%
Space Separator 3
 
1.3%
Open Punctuation 1
 
0.4%
Close Punctuation 1
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
장 8
 
3.6%
고 7
 
3.1%
식 7
 
3.1%
당 7
 
3.1%
한 4
 
1.8%
집 4
 
1.8%
이 4
 
1.8%
국 4
 
1.8%
드 4
 
1.8%
도 4
 
1.8%
Other values (122) 171
76.3%
Space Separator
ValueCountFrequency (%)
3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 224
97.8%
Common 5
 
2.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
장 8
 
3.6%
고 7
 
3.1%
식 7
 
3.1%
당 7
 
3.1%
한 4
 
1.8%
집 4
 
1.8%
이 4
 
1.8%
국 4
 
1.8%
드 4
 
1.8%
도 4
 
1.8%
Other values (122) 171
76.3%
Common
ValueCountFrequency (%)
3
60.0%
( 1
 
20.0%
) 1
 
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 224
97.8%
ASCII 5
 
2.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
장 8
 
3.6%
고 7
 
3.1%
식 7
 
3.1%
당 7
 
3.1%
한 4
 
1.8%
집 4
 
1.8%
이 4
 
1.8%
국 4
 
1.8%
드 4
 
1.8%
도 4
 
1.8%
Other values (122) 171
76.3%
ASCII
ValueCountFrequency (%)
3
60.0%
( 1
 
20.0%
) 1
 
20.0%

대표자
Text

UNIQUE 

Distinct45
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size492.0 B
2023-12-12T12:21:21.003302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters135
Distinct characters67
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique45 ?
Unique (%)100.0%

Sample

1st row박형남
2nd row노경자
3rd row이상혁
4th row전숙자
5th row김순옥
ValueCountFrequency (%)
박형남 1
 
2.2%
장연석 1
 
2.2%
박공임 1
 
2.2%
한정란 1
 
2.2%
황상구 1
 
2.2%
주은정 1
 
2.2%
신정화 1
 
2.2%
최정숙 1
 
2.2%
이갑주 1
 
2.2%
김혜란 1
 
2.2%
Other values (35) 35
77.8%
2023-12-12T12:21:21.400709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
김 9
 
6.7%
정 8
 
5.9%
박 8
 
5.9%
이 6
 
4.4%
미 5
 
3.7%
현 3
 
2.2%
옥 3
 
2.2%
석 3
 
2.2%
선 3
 
2.2%
한 3
 
2.2%
Other values (57) 84
62.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 135
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 9
 
6.7%
정 8
 
5.9%
박 8
 
5.9%
이 6
 
4.4%
미 5
 
3.7%
현 3
 
2.2%
옥 3
 
2.2%
석 3
 
2.2%
선 3
 
2.2%
한 3
 
2.2%
Other values (57) 84
62.2%

Most occurring scripts

ValueCountFrequency (%)
Hangul 135
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 9
 
6.7%
정 8
 
5.9%
박 8
 
5.9%
이 6
 
4.4%
미 5
 
3.7%
현 3
 
2.2%
옥 3
 
2.2%
석 3
 
2.2%
선 3
 
2.2%
한 3
 
2.2%
Other values (57) 84
62.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 135
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
김 9
 
6.7%
정 8
 
5.9%
박 8
 
5.9%
이 6
 
4.4%
미 5
 
3.7%
현 3
 
2.2%
옥 3
 
2.2%
석 3
 
2.2%
선 3
 
2.2%
한 3
 
2.2%
Other values (57) 84
62.2%

연락처
Text

MISSING 

Distinct38
Distinct (%)100.0%
Missing7
Missing (%)15.6%
Memory size492.0 B
2023-12-12T12:21:21.681702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.052632
Min length12

Characters and Unicode

Total characters458
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

Unique38 ?
Unique (%)100.0%

Sample

1st row031-405-0227
2nd row031-438-8676
3rd row031-403-9991
4th row031-415-9239
5th row031-502-7779
ValueCountFrequency (%)
031-411-0027 1
 
2.6%
031-480-9992 1
 
2.6%
031-410-9888 1
 
2.6%
031-406-0373 1
 
2.6%
031-406-3989 1
 
2.6%
031-414-7992 1
 
2.6%
031-406-1739 1
 
2.6%
031-402-6158 1
 
2.6%
070-4791-9382 1
 
2.6%
031-405-6265 1
 
2.6%
Other values (28) 28
73.7%
2023-12-12T12:21:22.174656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 76
16.6%
0 74
16.2%
1 69
15.1%
3 53
11.6%
4 42
9.2%
8 32
7.0%
5 25
 
5.5%
2 24
 
5.2%
7 24
 
5.2%
9 23
 
5.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 382
83.4%
Dash Punctuation 76
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 74
19.4%
1 69
18.1%
3 53
13.9%
4 42
11.0%
8 32
8.4%
5 25
 
6.5%
2 24
 
6.3%
7 24
 
6.3%
9 23
 
6.0%
6 16
 
4.2%
Dash Punctuation
ValueCountFrequency (%)
- 76
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 458
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 76
16.6%
0 74
16.2%
1 69
15.1%
3 53
11.6%
4 42
9.2%
8 32
7.0%
5 25
 
5.5%
2 24
 
5.2%
7 24
 
5.2%
9 23
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 458
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 76
16.6%
0 74
16.2%
1 69
15.1%
3 53
11.6%
4 42
9.2%
8 32
7.0%
5 25
 
5.5%
2 24
 
5.2%
7 24
 
5.2%
9 23
 
5.0%

소재지도로명주소
Text

UNIQUE 

Distinct45
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size492.0 B
2023-12-12T12:21:22.609673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length38
Median length32
Mean length26.044444
Min length17

Characters and Unicode

Total characters1172
Distinct characters106
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

Unique45 ?
Unique (%)100.0%

Sample

1st row경기도 안산시 단원구 광덕대로 146, 일번지프라자 125호
2nd row경기도 안산시 상록구 건건로 67
3rd row경기도 안산시 단원구 광덕4로 102 신원프라자
4th row경기도 안산시 상록구 일동로 13-1
5th row경기도 안산시 상록구 장화2길 37-1
ValueCountFrequency (%)
경기도 45
 
16.4%
안산시 45
 
16.4%
단원구 23
 
8.4%
상록구 21
 
7.6%
1층 6
 
2.2%
광덕동로 5
 
1.8%
104호 4
 
1.5%
3층 3
 
1.1%
광덕3로 3
 
1.1%
선진4길 2
 
0.7%
Other values (107) 118
42.9%
2023-12-12T12:21:23.120500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
232
19.8%
1 54
 
4.6%
산 48
 
4.1%
안 46
 
3.9%
경 45
 
3.8%
도 45
 
3.8%
시 45
 
3.8%
구 45
 
3.8%
기 45
 
3.8%
로 37
 
3.2%
Other values (96) 530
45.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 692
59.0%
Space Separator 232
 
19.8%
Decimal Number 197
 
16.8%
Other Punctuation 30
 
2.6%
Open Punctuation 6
 
0.5%
Close Punctuation 6
 
0.5%
Dash Punctuation 6
 
0.5%
Uppercase Letter 3
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 48
 
6.9%
안 46
 
6.6%
경 45
 
6.5%
도 45
 
6.5%
시 45
 
6.5%
구 45
 
6.5%
기 45
 
6.5%
로 37
 
5.3%
원 28
 
4.0%
호 25
 
3.6%
Other values (79) 283
40.9%
Decimal Number
ValueCountFrequency (%)
1 54
27.4%
3 28
14.2%
0 23
11.7%
2 19
 
9.6%
4 18
 
9.1%
5 13
 
6.6%
6 12
 
6.1%
7 12
 
6.1%
9 10
 
5.1%
8 8
 
4.1%
Uppercase Letter
ValueCountFrequency (%)
A 2
66.7%
B 1
33.3%
Space Separator
ValueCountFrequency (%)
232
100.0%
Other Punctuation
ValueCountFrequency (%)
, 30
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 692
59.0%
Common 477
40.7%
Latin 3
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 48
 
6.9%
안 46
 
6.6%
경 45
 
6.5%
도 45
 
6.5%
시 45
 
6.5%
구 45
 
6.5%
기 45
 
6.5%
로 37
 
5.3%
원 28
 
4.0%
호 25
 
3.6%
Other values (79) 283
40.9%
Common
ValueCountFrequency (%)
232
48.6%
1 54
 
11.3%
, 30
 
6.3%
3 28
 
5.9%
0 23
 
4.8%
2 19
 
4.0%
4 18
 
3.8%
5 13
 
2.7%
6 12
 
2.5%
7 12
 
2.5%
Other values (5) 36
 
7.5%
Latin
ValueCountFrequency (%)
A 2
66.7%
B 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 692
59.0%
ASCII 480
41.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
232
48.3%
1 54
 
11.2%
, 30
 
6.2%
3 28
 
5.8%
0 23
 
4.8%
2 19
 
4.0%
4 18
 
3.8%
5 13
 
2.7%
6 12
 
2.5%
7 12
 
2.5%
Other values (7) 39
 
8.1%
Hangul
ValueCountFrequency (%)
산 48
 
6.9%
안 46
 
6.6%
경 45
 
6.5%
도 45
 
6.5%
시 45
 
6.5%
구 45
 
6.5%
기 45
 
6.5%
로 37
 
5.3%
원 28
 
4.0%
호 25
 
3.6%
Other values (79) 283
40.9%

품목1
Text

Distinct35
Distinct (%)77.8%
Missing0
Missing (%)0.0%
Memory size492.0 B
2023-12-12T12:21:23.406480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length9
Mean length4
Min length1

Characters and Unicode

Total characters180
Distinct characters97
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique28 ?
Unique (%)62.2%

Sample

1st row청국장
2nd row커트
3rd row갈비탕
4th row백반
5th row멸치국수
ValueCountFrequency (%)
한식부페 3
 
5.9%
된장찌개 3
 
5.9%
컷트 3
 
5.9%
중대 2
 
3.9%
아메리카노 2
 
3.9%
뷔페성인 2
 
3.9%
청국장 2
 
3.9%
1kg 1
 
2.0%
오늘의 1
 
2.0%
메뉴 1
 
2.0%
Other values (31) 31
60.8%
2023-12-12T12:21:23.891523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
장 6
 
3.3%
6
 
3.3%
한 5
 
2.8%
페 5
 
2.8%
트 5
 
2.8%
리 4
 
2.2%
컷 4
 
2.2%
1 4
 
2.2%
비 4
 
2.2%
국 4
 
2.2%
Other values (87) 133
73.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 160
88.9%
Space Separator 6
 
3.3%
Decimal Number 6
 
3.3%
Lowercase Letter 3
 
1.7%
Open Punctuation 2
 
1.1%
Close Punctuation 2
 
1.1%
Modifier Symbol 1
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
장 6
 
3.8%
한 5
 
3.1%
페 5
 
3.1%
트 5
 
3.1%
리 4
 
2.5%
컷 4
 
2.5%
비 4
 
2.5%
국 4
 
2.5%
식 3
 
1.9%
탕 3
 
1.9%
Other values (78) 117
73.1%
Decimal Number
ValueCountFrequency (%)
1 4
66.7%
8 1
 
16.7%
0 1
 
16.7%
Lowercase Letter
ValueCountFrequency (%)
g 2
66.7%
k 1
33.3%
Space Separator
ValueCountFrequency (%)
6
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Modifier Symbol
ValueCountFrequency (%)
˙ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 160
88.9%
Common 17
 
9.4%
Latin 3
 
1.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
장 6
 
3.8%
한 5
 
3.1%
페 5
 
3.1%
트 5
 
3.1%
리 4
 
2.5%
컷 4
 
2.5%
비 4
 
2.5%
국 4
 
2.5%
식 3
 
1.9%
탕 3
 
1.9%
Other values (78) 117
73.1%
Common
ValueCountFrequency (%)
6
35.3%
1 4
23.5%
( 2
 
11.8%
) 2
 
11.8%
˙ 1
 
5.9%
8 1
 
5.9%
0 1
 
5.9%
Latin
ValueCountFrequency (%)
g 2
66.7%
k 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 160
88.9%
ASCII 19
 
10.6%
Modifier Letters 1
 
0.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
장 6
 
3.8%
한 5
 
3.1%
페 5
 
3.1%
트 5
 
3.1%
리 4
 
2.5%
컷 4
 
2.5%
비 4
 
2.5%
국 4
 
2.5%
식 3
 
1.9%
탕 3
 
1.9%
Other values (78) 117
73.1%
ASCII
ValueCountFrequency (%)
6
31.6%
1 4
21.1%
g 2
 
10.5%
( 2
 
10.5%
) 2
 
10.5%
k 1
 
5.3%
8 1
 
5.3%
0 1
 
5.3%
Modifier Letters
ValueCountFrequency (%)
˙ 1
100.0%

가격1
Text

Distinct24
Distinct (%)53.3%
Missing0
Missing (%)0.0%
Memory size492.0 B
2023-12-12T12:21:24.155777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length4
Mean length4.4888889
Min length4

Characters and Unicode

Total characters202
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique15 ?
Unique (%)33.3%

Sample

1st row7000
2nd row8000
3rd row9000
4th row6000
5th row5000
ValueCountFrequency (%)
8000 7
15.6%
7000 6
13.3%
10000 3
 
6.7%
9000 3
 
6.7%
12000 3
 
6.7%
3000 2
 
4.4%
8400 2
 
4.4%
5000 2
 
4.4%
6500 2
 
4.4%
8900 1
 
2.2%
Other values (14) 14
31.1%
2023-12-12T12:21:24.630671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 136
67.3%
1 13
 
6.4%
8 11
 
5.4%
5 9
 
4.5%
3 8
 
4.0%
7 6
 
3.0%
6 5
 
2.5%
9 4
 
2.0%
2 4
 
2.0%
4 4
 
2.0%
Other values (2) 2
 
1.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 200
99.0%
Other Punctuation 1
 
0.5%
Math Symbol 1
 
0.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 136
68.0%
1 13
 
6.5%
8 11
 
5.5%
5 9
 
4.5%
3 8
 
4.0%
7 6
 
3.0%
6 5
 
2.5%
9 4
 
2.0%
2 4
 
2.0%
4 4
 
2.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 202
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 136
67.3%
1 13
 
6.4%
8 11
 
5.4%
5 9
 
4.5%
3 8
 
4.0%
7 6
 
3.0%
6 5
 
2.5%
9 4
 
2.0%
2 4
 
2.0%
4 4
 
2.0%
Other values (2) 2
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 202
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 136
67.3%
1 13
 
6.4%
8 11
 
5.4%
5 9
 
4.5%
3 8
 
4.0%
7 6
 
3.0%
6 5
 
2.5%
9 4
 
2.0%
2 4
 
2.0%
4 4
 
2.0%
Other values (2) 2
 
1.0%

품목2
Text

MISSING 

Distinct37
Distinct (%)92.5%
Missing5
Missing (%)11.1%
Memory size492.0 B
2023-12-12T12:21:24.918702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length4.575
Min length2

Characters and Unicode

Total characters183
Distinct characters101
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique34 ?
Unique (%)85.0%

Sample

1st row김치찌개
2nd row퍼머
3rd row김치전골
4th row김치찌개
5th row비빔국수
ValueCountFrequency (%)
김치찌개 3
 
6.0%
청국장 2
 
4.0%
파마 2
 
4.0%
중 1
 
2.0%
왕만두 1
 
2.0%
부대찌개 1
 
2.0%
순대곱창 1
 
2.0%
어묵탕 1
 
2.0%
2인분 1
 
2.0%
기준 1
 
2.0%
Other values (36) 36
72.0%
2023-12-12T12:21:25.371920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
10
 
5.5%
개 6
 
3.3%
김 5
 
2.7%
치 5
 
2.7%
찌 5
 
2.7%
국 5
 
2.7%
비 5
 
2.7%
페 4
 
2.2%
이 4
 
2.2%
밥 3
 
1.6%
Other values (91) 131
71.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 156
85.2%
Space Separator 10
 
5.5%
Decimal Number 7
 
3.8%
Open Punctuation 3
 
1.6%
Close Punctuation 3
 
1.6%
Lowercase Letter 3
 
1.6%
Math Symbol 1
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
개 6
 
3.8%
김 5
 
3.2%
치 5
 
3.2%
찌 5
 
3.2%
국 5
 
3.2%
비 5
 
3.2%
페 4
 
2.6%
이 4
 
2.6%
밥 3
 
1.9%
미 3
 
1.9%
Other values (80) 111
71.2%
Decimal Number
ValueCountFrequency (%)
1 3
42.9%
3 1
 
14.3%
0 1
 
14.3%
2 1
 
14.3%
8 1
 
14.3%
Lowercase Letter
ValueCountFrequency (%)
g 2
66.7%
k 1
33.3%
Space Separator
ValueCountFrequency (%)
10
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 156
85.2%
Common 24
 
13.1%
Latin 3
 
1.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
개 6
 
3.8%
김 5
 
3.2%
치 5
 
3.2%
찌 5
 
3.2%
국 5
 
3.2%
비 5
 
3.2%
페 4
 
2.6%
이 4
 
2.6%
밥 3
 
1.9%
미 3
 
1.9%
Other values (80) 111
71.2%
Common
ValueCountFrequency (%)
10
41.7%
( 3
 
12.5%
1 3
 
12.5%
) 3
 
12.5%
3 1
 
4.2%
0 1
 
4.2%
2 1
 
4.2%
8 1
 
4.2%
+ 1
 
4.2%
Latin
ValueCountFrequency (%)
g 2
66.7%
k 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 156
85.2%
ASCII 27
 
14.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
10
37.0%
( 3
 
11.1%
1 3
 
11.1%
) 3
 
11.1%
g 2
 
7.4%
3 1
 
3.7%
k 1
 
3.7%
0 1
 
3.7%
2 1
 
3.7%
8 1
 
3.7%
Hangul
ValueCountFrequency (%)
개 6
 
3.8%
김 5
 
3.2%
치 5
 
3.2%
찌 5
 
3.2%
국 5
 
3.2%
비 5
 
3.2%
페 4
 
2.6%
이 4
 
2.6%
밥 3
 
1.9%
미 3
 
1.9%
Other values (80) 111
71.2%

가격2
Text

MISSING 

Distinct23
Distinct (%)57.5%
Missing5
Missing (%)11.1%
Memory size492.0 B
2023-12-12T12:21:25.618648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length4
Mean length4.625
Min length4

Characters and Unicode

Total characters185
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

Unique16 ?
Unique (%)40.0%

Sample

1st row7000
2nd row25000
3rd row8000
4th row7000
5th row6000
ValueCountFrequency (%)
6000 5
 
12.5%
9000 4
 
10.0%
7000 4
 
10.0%
8000 3
 
7.5%
4000 3
 
7.5%
25000 3
 
7.5%
10000 2
 
5.0%
11000 1
 
2.5%
1500 1
 
2.5%
30000 1
 
2.5%
Other values (13) 13
32.5%
2023-12-12T12:21:26.003939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 126
68.1%
1 10
 
5.4%
5 9
 
4.9%
2 7
 
3.8%
7 6
 
3.2%
6 5
 
2.7%
9 5
 
2.7%
8 5
 
2.7%
4 5
 
2.7%
3 5
 
2.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 183
98.9%
Math Symbol 2
 
1.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 126
68.9%
1 10
 
5.5%
5 9
 
4.9%
2 7
 
3.8%
7 6
 
3.3%
6 5
 
2.7%
9 5
 
2.7%
8 5
 
2.7%
4 5
 
2.7%
3 5
 
2.7%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 185
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 126
68.1%
1 10
 
5.4%
5 9
 
4.9%
2 7
 
3.8%
7 6
 
3.2%
6 5
 
2.7%
9 5
 
2.7%
8 5
 
2.7%
4 5
 
2.7%
3 5
 
2.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 185
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 126
68.1%
1 10
 
5.4%
5 9
 
4.9%
2 7
 
3.8%
7 6
 
3.2%
6 5
 
2.7%
9 5
 
2.7%
8 5
 
2.7%
4 5
 
2.7%
3 5
 
2.7%

품목3
Text

MISSING 

Distinct30
Distinct (%)93.8%
Missing13
Missing (%)28.9%
Memory size492.0 B
2023-12-12T12:21:26.250311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length6
Mean length3.90625
Min length2

Characters and Unicode

Total characters125
Distinct characters87
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

Unique28 ?
Unique (%)87.5%

Sample

1st row콩비지
2nd row염색
3rd row한우등심
4th row된장찌개
5th row칼국수
ValueCountFrequency (%)
청국장 2
 
5.9%
염색 2
 
5.9%
차돌박이된장찌개 1
 
2.9%
생두부김치 1
 
2.9%
초코라떼 1
 
2.9%
드라이 1
 
2.9%
소보루 1
 
2.9%
야채곱창 1
 
2.9%
콩비지 1
 
2.9%
감자튀김 1
 
2.9%
Other values (22) 22
64.7%
2023-12-12T12:21:26.693640image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
장 6
 
4.8%
치 4
 
3.2%
개 4
 
3.2%
3
 
2.4%
염 3
 
2.4%
색 3
 
2.4%
이 3
 
2.4%
김 3
 
2.4%
찌 3
 
2.4%
국 3
 
2.4%
Other values (77) 90
72.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 117
93.6%
Space Separator 3
 
2.4%
Lowercase Letter 2
 
1.6%
Decimal Number 1
 
0.8%
Open Punctuation 1
 
0.8%
Close Punctuation 1
 
0.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
장 6
 
5.1%
치 4
 
3.4%
개 4
 
3.4%
염 3
 
2.6%
색 3
 
2.6%
이 3
 
2.6%
김 3
 
2.6%
찌 3
 
2.6%
국 3
 
2.6%
청 2
 
1.7%
Other values (71) 83
70.9%
Lowercase Letter
ValueCountFrequency (%)
g 1
50.0%
k 1
50.0%
Space Separator
ValueCountFrequency (%)
3
100.0%
Decimal Number
ValueCountFrequency (%)
1 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 117
93.6%
Common 6
 
4.8%
Latin 2
 
1.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
장 6
 
5.1%
치 4
 
3.4%
개 4
 
3.4%
염 3
 
2.6%
색 3
 
2.6%
이 3
 
2.6%
김 3
 
2.6%
찌 3
 
2.6%
국 3
 
2.6%
청 2
 
1.7%
Other values (71) 83
70.9%
Common
ValueCountFrequency (%)
3
50.0%
1 1
 
16.7%
( 1
 
16.7%
) 1
 
16.7%
Latin
ValueCountFrequency (%)
g 1
50.0%
k 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 117
93.6%
ASCII 8
 
6.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
장 6
 
5.1%
치 4
 
3.4%
개 4
 
3.4%
염 3
 
2.6%
색 3
 
2.6%
이 3
 
2.6%
김 3
 
2.6%
찌 3
 
2.6%
국 3
 
2.6%
청 2
 
1.7%
Other values (71) 83
70.9%
ASCII
ValueCountFrequency (%)
3
37.5%
g 1
 
12.5%
k 1
 
12.5%
1 1
 
12.5%
( 1
 
12.5%
) 1
 
12.5%

가격3
Real number (ℝ)

MISSING 

Distinct19
Distinct (%)59.4%
Missing13
Missing (%)28.9%
Infinite0
Infinite (%)0.0%
Mean13640.625
Minimum1500
Maximum90000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size537.0 B
2023-12-12T12:21:26.855813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1500
5-th percentile3275
Q16750
median8000
Q311250
95-th percentile38050
Maximum90000
Range88500
Interquartile range (IQR)4500

Descriptive statistics

Standard deviation16886.831
Coefficient of variation (CV)1.2379808
Kurtosis13.603966
Mean13640.625
Median Absolute Deviation (MAD)2000
Skewness3.4063673
Sum436500
Variance2.8516507 × 108
MonotonicityNot monotonic
2023-12-12T12:21:26.998313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
8000 5
 
11.1%
7000 5
 
11.1%
6000 3
 
6.7%
3500 2
 
4.4%
8500 2
 
4.4%
10000 2
 
4.4%
11000 1
 
2.2%
12000 1
 
2.2%
32000 1
 
2.2%
34000 1
 
2.2%
Other values (9) 9
20.0%
(Missing) 13
28.9%
ValueCountFrequency (%)
1500 1
 
2.2%
3000 1
 
2.2%
3500 2
 
4.4%
4000 1
 
2.2%
6000 3
6.7%
7000 5
11.1%
8000 5
11.1%
8500 2
 
4.4%
9000 1
 
2.2%
10000 2
 
4.4%
ValueCountFrequency (%)
90000 1
2.2%
43000 1
2.2%
34000 1
2.2%
32000 1
2.2%
25000 1
2.2%
20000 1
2.2%
15000 1
2.2%
12000 1
2.2%
11000 1
2.2%
10000 2
4.4%

특이사항
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing45
Missing (%)100.0%
Memory size537.0 B

관리부서명
Categorical

CONSTANT 

Distinct1
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size492.0 B
소상공인지원과
45 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
소상공인지원과 45
100.0%

Length

2023-12-12T12:21:27.502740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T12:21:27.626642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
소상공인지원과 45
100.0%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Memory size492.0 B
2023-08-07
45 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-08-07
2nd row2023-08-07
3rd row2023-08-07
4th row2023-08-07
5th row2023-08-07

Common Values

ValueCountFrequency (%)
2023-08-07 45
100.0%

Length

2023-12-12T12:21:27.760184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T12:21:27.886749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-08-07 45
100.0%

Interactions

2023-12-12T12:21:18.971729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T12:21:27.992559image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업종업소명대표자연락처소재지도로명주소품목1가격1품목2가격2품목3가격3
업종1.0001.0001.0001.0001.0001.0000.9181.0000.3031.0000.000
업소명1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
대표자1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
연락처1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
소재지도로명주소1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
품목11.0001.0001.0001.0001.0001.0000.9840.9870.9410.9700.913
가격10.9181.0001.0001.0001.0000.9841.0000.8660.9260.9890.698
품목21.0001.0001.0001.0001.0000.9870.8661.0000.9970.9540.855
가격20.3031.0001.0001.0001.0000.9410.9260.9971.0000.9940.895
품목31.0001.0001.0001.0001.0000.9700.9890.9540.9941.0001.000
가격30.0001.0001.0001.0001.0000.9130.6980.8550.8951.0001.000
2023-12-12T12:21:28.167558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
가격3업종
가격31.0000.000
업종0.0001.000

Missing values

2023-12-12T12:21:19.130538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T12:21:19.418906image/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.
2023-12-12T12:21:19.595837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

업종업소명대표자연락처소재지도로명주소품목1가격1품목2가격2품목3가격3특이사항관리부서명데이터기준일자
0한식강원도청국장박형남031-405-0227경기도 안산시 단원구 광덕대로 146, 일번지프라자 125호청국장7000김치찌개7000콩비지7000<NA>소상공인지원과2023-08-07
1미용업고은미용실노경자031-438-8676경기도 안산시 상록구 건건로 67커트8000퍼머25000염색20000<NA>소상공인지원과2023-08-07
2한식고잔숯불갈비이상혁031-403-9991경기도 안산시 단원구 광덕4로 102 신원프라자갈비탕9000김치전골8000한우등심43000<NA>소상공인지원과2023-08-07
3한식고향밥상전숙자031-415-9239경기도 안산시 상록구 일동로 13-1백반6000김치찌개7000된장찌개7000<NA>소상공인지원과2023-08-07
4한식구포멸치국수김순옥031-502-7779경기도 안산시 상록구 장화2길 37-1멸치국수5000비빔국수6000칼국수6000<NA>소상공인지원과2023-08-07
5중식국빈중화요리박정화031-484-7506경기도 안산시 상록구 예술광장1로 7, 지하짜장4000짬뽕6000탕수육10000<NA>소상공인지원과2023-08-07
6한식꽃빛공원휴게소 음식점이홍배031-403-6360경기도 안산시 단원구 순환로 390 A동국수5000비빔밥6000청국장6000<NA>소상공인지원과2023-08-07
7한식남도목포맛집박복심031-418-2728경기도 안산시 상록구 선진4길 39된장찌개6500청국장9000남도정식7000<NA>소상공인지원과2023-08-07
8한식남도한식부페조정희031-501-5959경기도 안산시 상록구 광덕3로 324, 1층뷔페성인7000뷔페미취학5000<NA><NA><NA>소상공인지원과2023-08-07
9한식남이네 집밥박이남031-403-3108경기도 안산시 단원구 화정로 53, 101호된장찌개8000우거지갈비탕9000청국장8000<NA>소상공인지원과2023-08-07
업종업소명대표자연락처소재지도로명주소품목1가격1품목2가격2품목3가격3특이사항관리부서명데이터기준일자
35한식육덕삼김태용<NA>경기도 안산시 상록구 선진4길 36 1층무한삼겹14000냉동삼겹13000<NA><NA><NA>소상공인지원과2023-08-07
36양식파스타픽신금섭<NA>경기도 안산시 상록수 예술광장로1, 다농마트 3층 청년몰 304호통새우로제8900베이컨크림8500통새우토마토8500<NA>소상공인지원과2023-08-07
37기타요식업카페마리스현행임<NA>경기도 안산시 단원구 광덕3로 167-18, 105호아메리카노3000카페라떼4000카푸치노4000<NA>소상공인지원과2023-08-07
38한식드레푸드홍덕순031-402-7122경기도 안산시 단원구 광덕서로 68, B102호한식부페7000<NA><NA><NA><NA><NA>소상공인지원과2023-08-07
39한식계장수전정옥031-505-4173경기도 안산시 상록구 영화6길 14, 1층 102호(사동)닭숯불구이 1kg33000양념 닭숯불구이 1kg35000반반 1kg34000<NA>소상공인지원과2023-08-07
40양식라냐고석봉<NA>경기도 안산시 상록구 예술광장로 1, 333호(월피동, 다농마트)라자냐11000미트로프10000빠에야8500<NA>소상공인지원과2023-08-07
41한식보약족발(고잔신도시점)김미옥031-402-5151경기도 안산시 단원구 광덕동로 41, 113호(고잔동, 로진프라자)족발 대36000족발 중32000족발 대(포장)32000<NA>소상공인지원과2023-08-07
42한식전주식당정흥선031-8042-7015경기도 안산시 단원구 풍전로 37-9, 316동(원곡동, 트리플렉스)한식부페6500<NA><NA><NA><NA><NA>소상공인지원과2023-08-07
43한식제주복집박미녀031-495-1157경기도 안산시 단원구 산단로 326, 에이동 지층 3호(원곡동)복어 지리˙매운탕12000복튀김30000쭈꾸미볶음12000<NA>소상공인지원과2023-08-07
44한식청국장이랑갈비찜엄태웅031-402-9276경기도 안산시 단원구 원포공원1로 70 127호(초지동, 키즈타운)청국장8000갈치탕14000<NA><NA><NA>소상공인지원과2023-08-07