Overview

Dataset statistics

Number of variables11
Number of observations25
Missing cells15
Missing cells (%)5.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.4 KiB
Average record size in memory96.3 B

Variable types

Numeric3
Text6
Categorical2

Dataset

Description부산광역시동구_착한가격업소정보_20230314
Author부산광역시 동구
URLhttp://data.busan.go.kr/dataSet/detail.nm?contentId=10&publicdatapk=3057420

Alerts

가격(원)1 is highly overall correlated with 가격(원)2High correlation
가격(원)2 is highly overall correlated with 가격(원)1High correlation
업소구분 is highly imbalanced (54.1%)Imbalance
대표전화 has 1 (4.0%) missing valuesMissing
메뉴2 has 7 (28.0%) missing valuesMissing
가격(원)2 has 7 (28.0%) missing valuesMissing
번호 has unique valuesUnique
업소명 has unique valuesUnique
주소 has unique valuesUnique
착한가격업소 소개 has unique valuesUnique

Reproduction

Analysis started2023-12-10 16:12:46.899915
Analysis finished2023-12-10 16:12:49.151822
Duration2.25 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct25
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13
Minimum1
Maximum25
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2023-12-11T01:12:49.233132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.2
Q17
median13
Q319
95-th percentile23.8
Maximum25
Range24
Interquartile range (IQR)12

Descriptive statistics

Standard deviation7.3598007
Coefficient of variation (CV)0.56613852
Kurtosis-1.2
Mean13
Median Absolute Deviation (MAD)6
Skewness0
Sum325
Variance54.166667
MonotonicityStrictly increasing
2023-12-11T01:12:49.398536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
1 1
 
4.0%
2 1
 
4.0%
25 1
 
4.0%
24 1
 
4.0%
23 1
 
4.0%
22 1
 
4.0%
21 1
 
4.0%
20 1
 
4.0%
19 1
 
4.0%
18 1
 
4.0%
Other values (15) 15
60.0%
ValueCountFrequency (%)
1 1
4.0%
2 1
4.0%
3 1
4.0%
4 1
4.0%
5 1
4.0%
6 1
4.0%
7 1
4.0%
8 1
4.0%
9 1
4.0%
10 1
4.0%
ValueCountFrequency (%)
25 1
4.0%
24 1
4.0%
23 1
4.0%
22 1
4.0%
21 1
4.0%
20 1
4.0%
19 1
4.0%
18 1
4.0%
17 1
4.0%
16 1
4.0%

업소명
Text

UNIQUE 

Distinct25
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
2023-12-11T01:12:49.668116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length8
Mean length5.36
Min length2

Characters and Unicode

Total characters134
Distinct characters92
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique25 ?
Unique (%)100.0%

Sample

1st row초량영동밀면
2nd row문출래된장
3rd row양지추어탕
4th row원조콩나물비빔밥
5th row범일동양푼이동태백반
ValueCountFrequency (%)
초량영동밀면 1
 
3.8%
문출래된장 1
 
3.8%
명작미용실 1
 
3.8%
정아밀면돼지국밥 1
 
3.8%
풍전칼국수 1
 
3.8%
엄마손칼국수 1
 
3.8%
수림 1
 
3.8%
중앙충무김밥 1
 
3.8%
은혜식당 1
 
3.8%
대갓집 1
 
3.8%
Other values (16) 16
61.5%
2023-12-11T01:12:50.173240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
국 5
 
3.7%
수 5
 
3.7%
지 5
 
3.7%
밥 4
 
3.0%
장 3
 
2.2%
동 3
 
2.2%
돼 3
 
2.2%
식 3
 
2.2%
정 3
 
2.2%
미 3
 
2.2%
Other values (82) 97
72.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 133
99.3%
Space Separator 1
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
국 5
 
3.8%
수 5
 
3.8%
지 5
 
3.8%
밥 4
 
3.0%
장 3
 
2.3%
동 3
 
2.3%
돼 3
 
2.3%
식 3
 
2.3%
정 3
 
2.3%
미 3
 
2.3%
Other values (81) 96
72.2%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 133
99.3%
Common 1
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
국 5
 
3.8%
수 5
 
3.8%
지 5
 
3.8%
밥 4
 
3.0%
장 3
 
2.3%
동 3
 
2.3%
돼 3
 
2.3%
식 3
 
2.3%
정 3
 
2.3%
미 3
 
2.3%
Other values (81) 96
72.2%
Common
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 133
99.3%
ASCII 1
 
0.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
국 5
 
3.8%
수 5
 
3.8%
지 5
 
3.8%
밥 4
 
3.0%
장 3
 
2.3%
동 3
 
2.3%
돼 3
 
2.3%
식 3
 
2.3%
정 3
 
2.3%
미 3
 
2.3%
Other values (81) 96
72.2%
ASCII
ValueCountFrequency (%)
1
100.0%

업소구분
Categorical

IMBALANCE 

Distinct6
Distinct (%)24.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
한식
20 
중식
 
1
경양식
 
1
분식
 
1
미용
 
1

Length

Max length3
Median length2
Mean length2.08
Min length2

Unique

Unique5 ?
Unique (%)20.0%

Sample

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

Common Values

ValueCountFrequency (%)
한식 20
80.0%
중식 1
 
4.0%
경양식 1
 
4.0%
분식 1
 
4.0%
미용 1
 
4.0%
이미용 1
 
4.0%

Length

2023-12-11T01:12:50.358113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:12:50.526823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
한식 20
80.0%
중식 1
 
4.0%
경양식 1
 
4.0%
분식 1
 
4.0%
미용 1
 
4.0%
이미용 1
 
4.0%

지역
Categorical

Distinct5
Distinct (%)20.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
수정2동
9 
초량3동
6 
범일2동
6 
초량2동
3 
초량1동
1 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique1 ?
Unique (%)4.0%

Sample

1st row초량2동
2nd row초량3동
3rd row수정2동
4th row수정2동
5th row범일2동

Common Values

ValueCountFrequency (%)
수정2동 9
36.0%
초량3동 6
24.0%
범일2동 6
24.0%
초량2동 3
 
12.0%
초량1동 1
 
4.0%

Length

2023-12-11T01:12:50.693129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:12:50.858479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
수정2동 9
36.0%
초량3동 6
24.0%
범일2동 6
24.0%
초량2동 3
 
12.0%
초량1동 1
 
4.0%

주소
Text

UNIQUE 

Distinct25
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
2023-12-11T01:12:51.130084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length37
Median length23
Mean length20.24
Min length15

Characters and Unicode

Total characters506
Distinct characters50
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

Unique25 ?
Unique (%)100.0%

Sample

1st row부산광역시 동구 중앙대로221번길 10
2nd row부산광역시 동구 중앙대로214번길 3-6
3rd row부산광역시 동구 중앙대로371번길 70-4
4th row부산광역시 동구 중앙대로361번길
5th row부산광역시 동구 자성공원로 1-16
ValueCountFrequency (%)
부산광역시 25
25.0%
동구 25
25.0%
자성공원로 4
 
4.0%
중앙대로221번길 2
 
2.0%
중앙대로371번길 2
 
2.0%
23-3 1
 
1.0%
3동상가(범일동 1
 
1.0%
한양아파트 1
 
1.0%
범일로102번길 1
 
1.0%
9 1
 
1.0%
Other values (37) 37
37.0%
2023-12-11T01:12:51.772608image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
78
 
15.4%
동 29
 
5.7%
1 27
 
5.3%
로 25
 
4.9%
구 25
 
4.9%
부 25
 
4.9%
시 25
 
4.9%
광 25
 
4.9%
역 25
 
4.9%
산 25
 
4.9%
Other values (40) 197
38.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 312
61.7%
Decimal Number 99
 
19.6%
Space Separator 78
 
15.4%
Dash Punctuation 13
 
2.6%
Other Punctuation 2
 
0.4%
Close Punctuation 1
 
0.2%
Open Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 29
 
9.3%
로 25
 
8.0%
구 25
 
8.0%
부 25
 
8.0%
시 25
 
8.0%
광 25
 
8.0%
역 25
 
8.0%
산 25
 
8.0%
번 14
 
4.5%
길 14
 
4.5%
Other values (25) 80
25.6%
Decimal Number
ValueCountFrequency (%)
1 27
27.3%
2 20
20.2%
3 15
15.2%
7 8
 
8.1%
4 6
 
6.1%
6 6
 
6.1%
9 5
 
5.1%
0 5
 
5.1%
8 4
 
4.0%
5 3
 
3.0%
Space Separator
ValueCountFrequency (%)
78
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 13
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 312
61.7%
Common 194
38.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 29
 
9.3%
로 25
 
8.0%
구 25
 
8.0%
부 25
 
8.0%
시 25
 
8.0%
광 25
 
8.0%
역 25
 
8.0%
산 25
 
8.0%
번 14
 
4.5%
길 14
 
4.5%
Other values (25) 80
25.6%
Common
ValueCountFrequency (%)
78
40.2%
1 27
 
13.9%
2 20
 
10.3%
3 15
 
7.7%
- 13
 
6.7%
7 8
 
4.1%
4 6
 
3.1%
6 6
 
3.1%
9 5
 
2.6%
0 5
 
2.6%
Other values (5) 11
 
5.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 312
61.7%
ASCII 194
38.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
78
40.2%
1 27
 
13.9%
2 20
 
10.3%
3 15
 
7.7%
- 13
 
6.7%
7 8
 
4.1%
4 6
 
3.1%
6 6
 
3.1%
9 5
 
2.6%
0 5
 
2.6%
Other values (5) 11
 
5.7%
Hangul
ValueCountFrequency (%)
동 29
 
9.3%
로 25
 
8.0%
구 25
 
8.0%
부 25
 
8.0%
시 25
 
8.0%
광 25
 
8.0%
역 25
 
8.0%
산 25
 
8.0%
번 14
 
4.5%
길 14
 
4.5%
Other values (25) 80
25.6%

대표전화
Text

MISSING 

Distinct24
Distinct (%)100.0%
Missing1
Missing (%)4.0%
Memory size332.0 B
2023-12-11T01:12:52.170389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters288
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

Unique24 ?
Unique (%)100.0%

Sample

1st row051-442-5537
2nd row051-469-9609
3rd row051-467-3924
4th row051-464-2386
5th row051-631-4613
ValueCountFrequency (%)
051-442-5537 1
 
4.2%
051-469-9609 1
 
4.2%
051-441-1001 1
 
4.2%
051-462-7617 1
 
4.2%
051-463-6393 1
 
4.2%
051-442-5535 1
 
4.2%
051-644-6666 1
 
4.2%
051-466-1010 1
 
4.2%
051-441-0086 1
 
4.2%
051-633-9285 1
 
4.2%
Other values (14) 14
58.3%
2023-12-11T01:12:52.811593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 48
16.7%
6 39
13.5%
1 36
12.5%
4 36
12.5%
0 35
12.2%
5 34
11.8%
3 18
 
6.2%
9 14
 
4.9%
7 11
 
3.8%
2 10
 
3.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 240
83.3%
Dash Punctuation 48
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
6 39
16.2%
1 36
15.0%
4 36
15.0%
0 35
14.6%
5 34
14.2%
3 18
7.5%
9 14
 
5.8%
7 11
 
4.6%
2 10
 
4.2%
8 7
 
2.9%
Dash Punctuation
ValueCountFrequency (%)
- 48
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 288
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 48
16.7%
6 39
13.5%
1 36
12.5%
4 36
12.5%
0 35
12.2%
5 34
11.8%
3 18
 
6.2%
9 14
 
4.9%
7 11
 
3.8%
2 10
 
3.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 288
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 48
16.7%
6 39
13.5%
1 36
12.5%
4 36
12.5%
0 35
12.2%
5 34
11.8%
3 18
 
6.2%
9 14
 
4.9%
7 11
 
3.8%
2 10
 
3.5%

메뉴1
Text

Distinct23
Distinct (%)92.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
2023-12-11T01:12:53.080260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length9
Mean length4.44
Min length2

Characters and Unicode

Total characters111
Distinct characters64
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

Unique21 ?
Unique (%)84.0%

Sample

1st row물밀면
2nd row차돌박이된장찌개
3rd row추어탕
4th row콩나물비빔밥
5th row동태탕
ValueCountFrequency (%)
추어탕 2
 
8.0%
된장찌개 2
 
8.0%
멸치국수 1
 
4.0%
물밀면 1
 
4.0%
한정식 1
 
4.0%
파마 1
 
4.0%
밀면 1
 
4.0%
칼국수 1
 
4.0%
돌솥우동국밥 1
 
4.0%
충무김밥 1
 
4.0%
Other values (13) 13
52.0%
2023-12-11T01:12:53.891167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
밥 5
 
4.5%
장 4
 
3.6%
국 4
 
3.6%
0 3
 
2.7%
탕 3
 
2.7%
된 3
 
2.7%
찌 3
 
2.7%
개 3
 
2.7%
면 3
 
2.7%
겹 3
 
2.7%
Other values (54) 77
69.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 95
85.6%
Decimal Number 6
 
5.4%
Close Punctuation 3
 
2.7%
Open Punctuation 3
 
2.7%
Lowercase Letter 2
 
1.8%
Space Separator 2
 
1.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
밥 5
 
5.3%
장 4
 
4.2%
국 4
 
4.2%
탕 3
 
3.2%
된 3
 
3.2%
찌 3
 
3.2%
개 3
 
3.2%
면 3
 
3.2%
겹 3
 
3.2%
수 3
 
3.2%
Other values (47) 61
64.2%
Decimal Number
ValueCountFrequency (%)
0 3
50.0%
1 2
33.3%
3 1
 
16.7%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Lowercase Letter
ValueCountFrequency (%)
g 2
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 95
85.6%
Common 14
 
12.6%
Latin 2
 
1.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
밥 5
 
5.3%
장 4
 
4.2%
국 4
 
4.2%
탕 3
 
3.2%
된 3
 
3.2%
찌 3
 
3.2%
개 3
 
3.2%
면 3
 
3.2%
겹 3
 
3.2%
수 3
 
3.2%
Other values (47) 61
64.2%
Common
ValueCountFrequency (%)
0 3
21.4%
) 3
21.4%
( 3
21.4%
1 2
14.3%
2
14.3%
3 1
 
7.1%
Latin
ValueCountFrequency (%)
g 2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 95
85.6%
ASCII 16
 
14.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
밥 5
 
5.3%
장 4
 
4.2%
국 4
 
4.2%
탕 3
 
3.2%
된 3
 
3.2%
찌 3
 
3.2%
개 3
 
3.2%
면 3
 
3.2%
겹 3
 
3.2%
수 3
 
3.2%
Other values (47) 61
64.2%
ASCII
ValueCountFrequency (%)
0 3
18.8%
) 3
18.8%
( 3
18.8%
1 2
12.5%
g 2
12.5%
2
12.5%
3 1
 
6.2%

가격(원)1
Real number (ℝ)

HIGH CORRELATION 

Distinct10
Distinct (%)40.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7136
Minimum3500
Maximum18000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2023-12-11T01:12:54.047290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3500
5-th percentile4300
Q16000
median7000
Q38000
95-th percentile8980
Maximum18000
Range14500
Interquartile range (IQR)2000

Descriptive statistics

Standard deviation2613.2483
Coefficient of variation (CV)0.36620632
Kurtosis12.935412
Mean7136
Median Absolute Deviation (MAD)1000
Skewness3.0499409
Sum178400
Variance6829066.7
MonotonicityNot monotonic
2023-12-11T01:12:54.222563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
6000 8
32.0%
7000 6
24.0%
8000 4
16.0%
3500 1
 
4.0%
7500 1
 
4.0%
5500 1
 
4.0%
9000 1
 
4.0%
4000 1
 
4.0%
8900 1
 
4.0%
18000 1
 
4.0%
ValueCountFrequency (%)
3500 1
 
4.0%
4000 1
 
4.0%
5500 1
 
4.0%
6000 8
32.0%
7000 6
24.0%
7500 1
 
4.0%
8000 4
16.0%
8900 1
 
4.0%
9000 1
 
4.0%
18000 1
 
4.0%
ValueCountFrequency (%)
18000 1
 
4.0%
9000 1
 
4.0%
8900 1
 
4.0%
8000 4
16.0%
7500 1
 
4.0%
7000 6
24.0%
6000 8
32.0%
5500 1
 
4.0%
4000 1
 
4.0%
3500 1
 
4.0%

메뉴2
Text

MISSING 

Distinct17
Distinct (%)94.4%
Missing7
Missing (%)28.0%
Memory size332.0 B
2023-12-11T01:12:54.460802image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length6
Mean length4
Min length2

Characters and Unicode

Total characters72
Distinct characters51
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique16 ?
Unique (%)88.9%

Sample

1st row비빔밀면
2nd row추어국수
3rd row광어미역국
4th row짬뽕
5th row돈까스정식
ValueCountFrequency (%)
우동 2
 
11.1%
추어탕 1
 
5.6%
비빔밀면 1
 
5.6%
한돈삼겹살(130g 1
 
5.6%
염색 1
 
5.6%
돼지국밥 1
 
5.6%
수제비 1
 
5.6%
돌솥얼큰우동 1
 
5.6%
생오겹 1
 
5.6%
추어국수 1
 
5.6%
Other values (7) 7
38.9%
2023-12-11T01:12:54.876896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
국 4
 
5.6%
수 4
 
5.6%
우 3
 
4.2%
비 3
 
4.2%
동 3
 
4.2%
어 3
 
4.2%
겹 2
 
2.8%
돈 2
 
2.8%
) 2
 
2.8%
빔 2
 
2.8%
Other values (41) 44
61.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 64
88.9%
Decimal Number 3
 
4.2%
Close Punctuation 2
 
2.8%
Open Punctuation 2
 
2.8%
Lowercase Letter 1
 
1.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
국 4
 
6.2%
수 4
 
6.2%
우 3
 
4.7%
비 3
 
4.7%
동 3
 
4.7%
어 3
 
4.7%
겹 2
 
3.1%
돈 2
 
3.1%
빔 2
 
3.1%
추 2
 
3.1%
Other values (35) 36
56.2%
Decimal Number
ValueCountFrequency (%)
3 1
33.3%
1 1
33.3%
0 1
33.3%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Lowercase Letter
ValueCountFrequency (%)
g 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 64
88.9%
Common 7
 
9.7%
Latin 1
 
1.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
국 4
 
6.2%
수 4
 
6.2%
우 3
 
4.7%
비 3
 
4.7%
동 3
 
4.7%
어 3
 
4.7%
겹 2
 
3.1%
돈 2
 
3.1%
빔 2
 
3.1%
추 2
 
3.1%
Other values (35) 36
56.2%
Common
ValueCountFrequency (%)
) 2
28.6%
( 2
28.6%
3 1
14.3%
1 1
14.3%
0 1
14.3%
Latin
ValueCountFrequency (%)
g 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 64
88.9%
ASCII 8
 
11.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
국 4
 
6.2%
수 4
 
6.2%
우 3
 
4.7%
비 3
 
4.7%
동 3
 
4.7%
어 3
 
4.7%
겹 2
 
3.1%
돈 2
 
3.1%
빔 2
 
3.1%
추 2
 
3.1%
Other values (35) 36
56.2%
ASCII
ValueCountFrequency (%)
) 2
25.0%
( 2
25.0%
3 1
12.5%
1 1
12.5%
0 1
12.5%
g 1
12.5%

가격(원)2
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct10
Distinct (%)55.6%
Missing7
Missing (%)28.0%
Infinite0
Infinite (%)0.0%
Mean7522.2222
Minimum4500
Maximum20000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size357.0 B
2023-12-11T01:12:55.053298image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4500
5-th percentile4925
Q16000
median7000
Q37875
95-th percentile11500
Maximum20000
Range15500
Interquartile range (IQR)1875

Descriptive statistics

Standard deviation3416.6643
Coefficient of variation (CV)0.45420943
Kurtosis11.445457
Mean7522.2222
Median Absolute Deviation (MAD)1000
Skewness3.1217928
Sum135400
Variance11673595
MonotonicityNot monotonic
2023-12-11T01:12:55.229087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
7000 5
20.0%
6000 3
12.0%
5000 2
 
8.0%
8000 2
 
8.0%
7500 1
 
4.0%
4500 1
 
4.0%
20000 1
 
4.0%
8900 1
 
4.0%
5500 1
 
4.0%
10000 1
 
4.0%
(Missing) 7
28.0%
ValueCountFrequency (%)
4500 1
 
4.0%
5000 2
 
8.0%
5500 1
 
4.0%
6000 3
12.0%
7000 5
20.0%
7500 1
 
4.0%
8000 2
 
8.0%
8900 1
 
4.0%
10000 1
 
4.0%
20000 1
 
4.0%
ValueCountFrequency (%)
20000 1
 
4.0%
10000 1
 
4.0%
8900 1
 
4.0%
8000 2
 
8.0%
7500 1
 
4.0%
7000 5
20.0%
6000 3
12.0%
5500 1
 
4.0%
5000 2
 
8.0%
4500 1
 
4.0%

착한가격업소 소개
Text

UNIQUE 

Distinct25
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size332.0 B
2023-12-11T01:12:55.570017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length98
Median length53
Mean length49.08
Min length17

Characters and Unicode

Total characters1227
Distinct characters248
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

Unique25 ?
Unique (%)100.0%

Sample

1st row부산역 역세권에 위치하여 주인이 면을 뽑고 부산을 찾는 관광객이 부산의 별미인 밀면을 저렴한 가격으로 맛볼수 있음.
2nd row부산역주변 사무실밀집지역에 위치하여 저렴한 가격으로 집된장의 맛을 제공
3rd row건물 임대료가 없고 부부가 직접 운영하여 지출을 줄임. 2009년부터 가격동결하였고 주택1층이 식당이라 내집같은 아늑함이 느껴짐. 국내산미꾸라지만을 사용하여 건강식으로 좋음
4th row20년동안 한결같은 맛으로 꾸준히 손님들의 사랑을 받아옴. 식자재 모두 인근 수정재래시장을 이용하여 구입, 업주 혼자 운영하며 점심시간에 시간제도우미를 고용하여 인건비를 최소화
5th row엄마의 손맛이 느껴지는 깔끔한 밑반찬
ValueCountFrequency (%)
저렴한 13
 
4.7%
있음 8
 
2.9%
가격으로 7
 
2.6%
제공 6
 
2.2%
구입 5
 
1.8%
가격에 4
 
1.5%
부부가 4
 
1.5%
수 4
 
1.5%
식자재 3
 
1.1%
맛볼 3
 
1.1%
Other values (194) 217
79.2%
2023-12-11T01:12:56.155570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
252
 
20.5%
이 29
 
2.4%
한 26
 
2.1%
가 22
 
1.8%
하 22
 
1.8%
로 20
 
1.6%
수 17
 
1.4%
, 16
 
1.3%
인 16
 
1.3%
부 15
 
1.2%
Other values (238) 792
64.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 919
74.9%
Space Separator 252
 
20.5%
Decimal Number 27
 
2.2%
Other Punctuation 25
 
2.0%
Close Punctuation 2
 
0.2%
Open Punctuation 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 29
 
3.2%
한 26
 
2.8%
가 22
 
2.4%
하 22
 
2.4%
로 20
 
2.2%
수 17
 
1.8%
인 16
 
1.7%
부 15
 
1.6%
고 15
 
1.6%
제 15
 
1.6%
Other values (226) 722
78.6%
Decimal Number
ValueCountFrequency (%)
0 12
44.4%
2 6
22.2%
1 4
 
14.8%
5 2
 
7.4%
4 1
 
3.7%
9 1
 
3.7%
8 1
 
3.7%
Other Punctuation
ValueCountFrequency (%)
, 16
64.0%
. 9
36.0%
Space Separator
ValueCountFrequency (%)
252
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 919
74.9%
Common 308
 
25.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 29
 
3.2%
한 26
 
2.8%
가 22
 
2.4%
하 22
 
2.4%
로 20
 
2.2%
수 17
 
1.8%
인 16
 
1.7%
부 15
 
1.6%
고 15
 
1.6%
제 15
 
1.6%
Other values (226) 722
78.6%
Common
ValueCountFrequency (%)
252
81.8%
, 16
 
5.2%
0 12
 
3.9%
. 9
 
2.9%
2 6
 
1.9%
1 4
 
1.3%
) 2
 
0.6%
5 2
 
0.6%
( 2
 
0.6%
4 1
 
0.3%
Other values (2) 2
 
0.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 919
74.9%
ASCII 308
 
25.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
252
81.8%
, 16
 
5.2%
0 12
 
3.9%
. 9
 
2.9%
2 6
 
1.9%
1 4
 
1.3%
) 2
 
0.6%
5 2
 
0.6%
( 2
 
0.6%
4 1
 
0.3%
Other values (2) 2
 
0.6%
Hangul
ValueCountFrequency (%)
이 29
 
3.2%
한 26
 
2.8%
가 22
 
2.4%
하 22
 
2.4%
로 20
 
2.2%
수 17
 
1.8%
인 16
 
1.7%
부 15
 
1.6%
고 15
 
1.6%
제 15
 
1.6%
Other values (226) 722
78.6%

Interactions

2023-12-11T01:12:48.335977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:12:47.632414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:12:47.946226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:12:48.459671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:12:47.731334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:12:48.051487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:12:48.583899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:12:47.839923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:12:48.187157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T01:12:56.290530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호업소명업소구분지역주소대표전화메뉴1가격(원)1메뉴2가격(원)2착한가격업소 소개
번호1.0001.0000.0000.0001.0001.0000.8200.0000.9440.0001.000
업소명1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
업소구분0.0001.0001.0000.0001.0001.0001.0000.5301.0000.4291.000
지역0.0001.0000.0001.0001.0001.0000.0000.0000.8770.0001.000
주소1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
대표전화1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
메뉴10.8201.0001.0000.0001.0001.0001.0000.9480.9771.0001.000
가격(원)10.0001.0000.5300.0001.0001.0000.9481.0001.0000.9551.000
메뉴20.9441.0001.0000.8771.0001.0000.9771.0001.0001.0001.000
가격(원)20.0001.0000.4290.0001.0001.0001.0000.9551.0001.0001.000
착한가격업소 소개1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
2023-12-11T01:12:56.449069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업소구분지역
업소구분1.0000.000
지역0.0001.000
2023-12-11T01:12:56.547575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호가격(원)1가격(원)2업소구분지역
번호1.0000.0640.0030.0000.000
가격(원)10.0641.0000.8630.3870.000
가격(원)20.0030.8631.0000.2740.000
업소구분0.0000.3870.2741.0000.000
지역0.0000.0000.0000.0001.000

Missing values

2023-12-11T01:12:48.776587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T01:12:48.932638image/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.
2023-12-11T01:12:49.083659image/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

번호업소명업소구분지역주소대표전화메뉴1가격(원)1메뉴2가격(원)2착한가격업소 소개
01초량영동밀면한식초량2동부산광역시 동구 중앙대로221번길 10051-442-5537물밀면6000비빔밀면6000부산역 역세권에 위치하여 주인이 면을 뽑고 부산을 찾는 관광객이 부산의 별미인 밀면을 저렴한 가격으로 맛볼수 있음.
12문출래된장한식초량3동부산광역시 동구 중앙대로214번길 3-6051-469-9609차돌박이된장찌개8000<NA><NA>부산역주변 사무실밀집지역에 위치하여 저렴한 가격으로 집된장의 맛을 제공
23양지추어탕한식수정2동부산광역시 동구 중앙대로371번길 70-4051-467-3924추어탕7000추어국수7000건물 임대료가 없고 부부가 직접 운영하여 지출을 줄임. 2009년부터 가격동결하였고 주택1층이 식당이라 내집같은 아늑함이 느껴짐. 국내산미꾸라지만을 사용하여 건강식으로 좋음
34원조콩나물비빔밥한식수정2동부산광역시 동구 중앙대로361번길051-464-2386콩나물비빔밥7000광어미역국700020년동안 한결같은 맛으로 꾸준히 손님들의 사랑을 받아옴. 식자재 모두 인근 수정재래시장을 이용하여 구입, 업주 혼자 운영하며 점심시간에 시간제도우미를 고용하여 인건비를 최소화
45범일동양푼이동태백반한식범일2동부산광역시 동구 자성공원로 1-16051-631-4613동태탕6000<NA><NA>엄마의 손맛이 느껴지는 깔끔한 밑반찬
56자유관중식초량3동부산광역시 동구 중앙대로 324051-469-6646자장면6000짬뽕7000동구 모범업소이며 입소문으로 많은 손님들이 방문, 깨끗하고 화려한 내부시설에다 저렴한 가격, 주인의 친절함이 더욱더 돋보임
67초량낙지볶음한식초량3동부산광역시 동구 중앙대로236번길 7-6051-464-9978낙지볶음7000<NA><NA>20여년동안 한결같이 영업을 하고 있으며 비교적 오래된 건물이임에도 실내가 깨끗함. 인근 사무실 근무하는 직장인들이 주이용객
78부성식당한식범일2동부산광역시 동구 자성공원로 17-2051-643-1059정식7000<NA><NA>부부가 운영하며 새벽시장에서 식자재를 구입, 월2회 독거노인(20명) 무료식사 제공, 여주인의 친절함과 인자함이 돋보임
89명가한식범일2동부산광역시 동구 자성공원로 23-9051-644-0079삼겹살(100g)3500<NA><NA>일본관광객이 주 이용객일정도로 외국인 여행자의 이용이 많은. 점심시간대 식사류 1,000원 할인
910쇠가리수제돈까스경양식수정2동부산광역시 동구 망양로 735051-464-9232수제돈까스7500돈까스정식7500수제돈까스가 대체로 프렌차이즈로 운영되어 불필요한 경비가 부담이 되어 젊은 부부가 직접 운영, 경비를 줄이고 저렴한 수제 돈까스를 제공하고 있음
번호업소명업소구분지역주소대표전화메뉴1가격(원)1메뉴2가격(원)2착한가격업소 소개
1516제주암돼지 왕소금구이한식범일2동부산광역시 동구 범일로102번길 9051-633-9285제주오겹살(130g)8900한돈삼겹살(130g)8900저렴한 가격에 품질좋은 돼지고기를 맛볼수 있음
1617대갓집한식수정2동부산광역시 동구 수정로 28051-441-0086생삼겹8000생오겹8000저렴한 가격에 돼지고기를 맛볼수 있음
1718은혜식당한식초량2동부산광역시 동구 초량중로80번길 3051-466-1010된장찌개7000추어탕7000저렴한 가격으로 구수한 된장찌개와 추어탕 등을 맛볼 수 있음
1819중앙충무김밥한식범일2동부산광역시 동구 자성공원로 23-3051-644-6666충무김밥6000우동5500충무김밥과 떡볶이를 셋트메뉴로 저렴하게 제공하며 포장고객이 많이 찾음
1920수림분식초량3동부산광역시 동구 초량중로93번길 12-1051-442-5535돌솥우동국밥6000돌솥얼큰우동600010여년동안의 경험으로 저렴한 가격으로 식사를 제공
2021엄마손칼국수한식수정2동부산광역시 동구 수정중로 12051-463-6393칼국수6000수제비6000저렴한 가격으로 맛좋은 칼국수와 수제비를 맛볼 수 있음
2122풍전칼국수한식수정2동부산광역시 동구 중앙대로371번길 23-4051-462-7617추어탕8000<NA><NA>전통시장 주변의 업소로 저렴하고 신선한 식자재를 구입, 저렴한 가격으로 제공
2223정아밀면돼지국밥한식초량3동부산광역시 동구 중앙대로251번길 18051-441-1001밀면6000돼지국밥8000저렴한 가격으로 깔끔한 식사제공
2324명작미용실미용수정2동부산광역시 동구 수정동로 3-1051-465-9775파마18000염색10000오랜 경험과 다양한 노하우로 저렴한 가격에 커트, 파마, 염색 제공
2425두발할인점이미용초량2동부산광역시 동구 중앙대로221번길 14<NA>컷트(일반)6000커트(경로)5000경로,시각장애인,수급자에 할인혜택