Overview

Dataset statistics

Number of variables5
Number of observations46
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.0 KiB
Average record size in memory43.9 B

Variable types

Numeric1
Categorical1
Text3

Dataset

Description부산광역시_부산진구_착한가격업소현황_20230912
Author부산광역시 부산진구
URLhttp://data.busan.go.kr/dataSet/detail.nm?contentId=10&publicdatapk=15055848

Alerts

업종 is highly imbalanced (62.6%)Imbalance
연번 has unique valuesUnique
업소명 has unique valuesUnique
소재지(도로명주소) has unique valuesUnique
연락처 has unique valuesUnique

Reproduction

Analysis started2023-12-10 17:12:51.378175
Analysis finished2023-12-10 17:12:52.612007
Duration1.23 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct46
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean23.5
Minimum1
Maximum46
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size546.0 B
2023-12-11T02:12:53.011142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3.25
Q112.25
median23.5
Q334.75
95-th percentile43.75
Maximum46
Range45
Interquartile range (IQR)22.5

Descriptive statistics

Standard deviation13.422618
Coefficient of variation (CV)0.57117522
Kurtosis-1.2
Mean23.5
Median Absolute Deviation (MAD)11.5
Skewness0
Sum1081
Variance180.16667
MonotonicityStrictly increasing
2023-12-11T02:12:53.811765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=46)
ValueCountFrequency (%)
1 1
 
2.2%
36 1
 
2.2%
27 1
 
2.2%
28 1
 
2.2%
29 1
 
2.2%
30 1
 
2.2%
31 1
 
2.2%
32 1
 
2.2%
33 1
 
2.2%
34 1
 
2.2%
Other values (36) 36
78.3%
ValueCountFrequency (%)
1 1
2.2%
2 1
2.2%
3 1
2.2%
4 1
2.2%
5 1
2.2%
6 1
2.2%
7 1
2.2%
8 1
2.2%
9 1
2.2%
10 1
2.2%
ValueCountFrequency (%)
46 1
2.2%
45 1
2.2%
44 1
2.2%
43 1
2.2%
42 1
2.2%
41 1
2.2%
40 1
2.2%
39 1
2.2%
38 1
2.2%
37 1
2.2%

업종
Categorical

IMBALANCE 

Distinct5
Distinct (%)10.9%
Missing0
Missing (%)0.0%
Memory size500.0 B
한식
39 
미용업
4 
중식
 
1
기타요식업
 
1
세탁업
 
1

Length

Max length5
Median length2
Mean length2.173913
Min length2

Unique

Unique3 ?
Unique (%)6.5%

Sample

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

Common Values

ValueCountFrequency (%)
한식 39
84.8%
미용업 4
 
8.7%
중식 1
 
2.2%
기타요식업 1
 
2.2%
세탁업 1
 
2.2%

Length

2023-12-11T02:12:54.609918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T02:12:55.078271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
한식 39
84.8%
미용업 4
 
8.7%
중식 1
 
2.2%
기타요식업 1
 
2.2%
세탁업 1
 
2.2%

업소명
Text

UNIQUE 

Distinct46
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size500.0 B
2023-12-11T02:12:55.964838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length8
Mean length4.9782609
Min length3

Characters and Unicode

Total characters229
Distinct characters133
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique46 ?
Unique (%)100.0%

Sample

1st row금복식당
2nd row좋은식당
3rd row서울식당
4th row하동재첩
5th row우정분식
ValueCountFrequency (%)
금복식당 1
 
2.1%
굿맨헤어 1
 
2.1%
정성담은 1
 
2.1%
나라소머리곰탕 1
 
2.1%
팔팔대패 1
 
2.1%
우성숯불갈비 1
 
2.1%
동두천부대찌개 1
 
2.1%
황금이네 1
 
2.1%
장고방 1
 
2.1%
삼삼오오 1
 
2.1%
Other values (37) 37
78.7%
2023-12-11T02:12:57.456583image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
식 8
 
3.5%
국 7
 
3.1%
수 6
 
2.6%
가 5
 
2.2%
당 5
 
2.2%
정 5
 
2.2%
어 4
 
1.7%
면 4
 
1.7%
대 4
 
1.7%
우 4
 
1.7%
Other values (123) 177
77.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 222
96.9%
Decimal Number 4
 
1.7%
Open Punctuation 1
 
0.4%
Space Separator 1
 
0.4%
Close Punctuation 1
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
식 8
 
3.6%
국 7
 
3.2%
수 6
 
2.7%
가 5
 
2.3%
당 5
 
2.3%
정 5
 
2.3%
어 4
 
1.8%
면 4
 
1.8%
대 4
 
1.8%
우 4
 
1.8%
Other values (116) 170
76.6%
Decimal Number
ValueCountFrequency (%)
4 1
25.0%
7 1
25.0%
9 1
25.0%
1 1
25.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 222
96.9%
Common 7
 
3.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
식 8
 
3.6%
국 7
 
3.2%
수 6
 
2.7%
가 5
 
2.3%
당 5
 
2.3%
정 5
 
2.3%
어 4
 
1.8%
면 4
 
1.8%
대 4
 
1.8%
우 4
 
1.8%
Other values (116) 170
76.6%
Common
ValueCountFrequency (%)
( 1
14.3%
1
14.3%
) 1
14.3%
4 1
14.3%
7 1
14.3%
9 1
14.3%
1 1
14.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 222
96.9%
ASCII 7
 
3.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
식 8
 
3.6%
국 7
 
3.2%
수 6
 
2.7%
가 5
 
2.3%
당 5
 
2.3%
정 5
 
2.3%
어 4
 
1.8%
면 4
 
1.8%
대 4
 
1.8%
우 4
 
1.8%
Other values (116) 170
76.6%
ASCII
ValueCountFrequency (%)
( 1
14.3%
1
14.3%
) 1
14.3%
4 1
14.3%
7 1
14.3%
9 1
14.3%
1 1
14.3%

소재지(도로명주소)
Text

UNIQUE 

Distinct46
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size500.0 B
2023-12-11T02:12:58.388638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length29
Mean length26.173913
Min length22

Characters and Unicode

Total characters1204
Distinct characters72
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

Unique46 ?
Unique (%)100.0%

Sample

1st row부산광역시 부산진구 서면문화로5번길 13(부전동)
2nd row부산광역시 부산진구 전포대로176번길 15(전포동)
3rd row부산광역시 부산진구 가야대로703번길31(당감동)
4th row부산광역시 부산진구 중앙대로743번길 25(부전동)
5th row부산광역시 부산진구 동천로85번길 3(부전동)
ValueCountFrequency (%)
부산광역시 46
24.9%
부산진구 46
24.9%
부전로152번길 3
 
1.6%
당감로 2
 
1.1%
엄광로 2
 
1.1%
새싹로8번길 2
 
1.1%
48(부전동 2
 
1.1%
서면문화로 2
 
1.1%
백양순환로 2
 
1.1%
5(부전동 2
 
1.1%
Other values (76) 76
41.1%
2023-12-11T02:12:59.819027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
139
 
11.5%
부 116
 
9.6%
산 93
 
7.7%
동 54
 
4.5%
광 48
 
4.0%
시 46
 
3.8%
역 46
 
3.8%
진 46
 
3.8%
구 46
 
3.8%
( 46
 
3.8%
Other values (62) 524
43.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 781
64.9%
Decimal Number 179
 
14.9%
Space Separator 139
 
11.5%
Open Punctuation 46
 
3.8%
Close Punctuation 46
 
3.8%
Other Punctuation 7
 
0.6%
Dash Punctuation 6
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
부 116
14.9%
산 93
11.9%
동 54
 
6.9%
광 48
 
6.1%
시 46
 
5.9%
역 46
 
5.9%
진 46
 
5.9%
구 46
 
5.9%
로 45
 
5.8%
전 29
 
3.7%
Other values (46) 212
27.1%
Decimal Number
ValueCountFrequency (%)
1 37
20.7%
5 25
14.0%
4 24
13.4%
2 24
13.4%
3 17
9.5%
7 15
8.4%
8 15
8.4%
6 9
 
5.0%
0 8
 
4.5%
9 5
 
2.8%
Other Punctuation
ValueCountFrequency (%)
, 6
85.7%
. 1
 
14.3%
Space Separator
ValueCountFrequency (%)
139
100.0%
Open Punctuation
ValueCountFrequency (%)
( 46
100.0%
Close Punctuation
ValueCountFrequency (%)
) 46
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 781
64.9%
Common 423
35.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
부 116
14.9%
산 93
11.9%
동 54
 
6.9%
광 48
 
6.1%
시 46
 
5.9%
역 46
 
5.9%
진 46
 
5.9%
구 46
 
5.9%
로 45
 
5.8%
전 29
 
3.7%
Other values (46) 212
27.1%
Common
ValueCountFrequency (%)
139
32.9%
( 46
 
10.9%
) 46
 
10.9%
1 37
 
8.7%
5 25
 
5.9%
4 24
 
5.7%
2 24
 
5.7%
3 17
 
4.0%
7 15
 
3.5%
8 15
 
3.5%
Other values (6) 35
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 781
64.9%
ASCII 423
35.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
139
32.9%
( 46
 
10.9%
) 46
 
10.9%
1 37
 
8.7%
5 25
 
5.9%
4 24
 
5.7%
2 24
 
5.7%
3 17
 
4.0%
7 15
 
3.5%
8 15
 
3.5%
Other values (6) 35
 
8.3%
Hangul
ValueCountFrequency (%)
부 116
14.9%
산 93
11.9%
동 54
 
6.9%
광 48
 
6.1%
시 46
 
5.9%
역 46
 
5.9%
진 46
 
5.9%
구 46
 
5.9%
로 45
 
5.8%
전 29
 
3.7%
Other values (46) 212
27.1%

연락처
Text

UNIQUE 

Distinct46
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size500.0 B
2023-12-11T02:13:00.750788image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length12.065217
Min length12

Characters and Unicode

Total characters555
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

Unique46 ?
Unique (%)100.0%

Sample

1st row051-803-8790
2nd row051-818-4243
3rd row051-895-5885
4th row051-808-5668
5th row051-803-0303
ValueCountFrequency (%)
051-803-8790 1
 
2.2%
051-897-0301 1
 
2.2%
051-643-0074 1
 
2.2%
051-865-6336 1
 
2.2%
051-804-0810 1
 
2.2%
051-817-5432 1
 
2.2%
051-898-0279 1
 
2.2%
051-808-2707 1
 
2.2%
051-898-2488 1
 
2.2%
051-898-0010 1
 
2.2%
Other values (36) 36
78.3%
2023-12-11T02:13:01.784786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 97
17.5%
- 92
16.6%
1 73
13.2%
8 71
12.8%
5 64
11.5%
6 39
7.0%
9 29
 
5.2%
3 26
 
4.7%
7 24
 
4.3%
4 22
 
4.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 463
83.4%
Dash Punctuation 92
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 97
21.0%
1 73
15.8%
8 71
15.3%
5 64
13.8%
6 39
8.4%
9 29
 
6.3%
3 26
 
5.6%
7 24
 
5.2%
4 22
 
4.8%
2 18
 
3.9%
Dash Punctuation
ValueCountFrequency (%)
- 92
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 555
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 97
17.5%
- 92
16.6%
1 73
13.2%
8 71
12.8%
5 64
11.5%
6 39
7.0%
9 29
 
5.2%
3 26
 
4.7%
7 24
 
4.3%
4 22
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 555
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 97
17.5%
- 92
16.6%
1 73
13.2%
8 71
12.8%
5 64
11.5%
6 39
7.0%
9 29
 
5.2%
3 26
 
4.7%
7 24
 
4.3%
4 22
 
4.0%

Interactions

2023-12-11T02:12:51.980616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T02:13:02.017587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번업종업소명소재지(도로명주소)연락처
연번1.0000.0001.0001.0001.000
업종0.0001.0001.0001.0001.000
업소명1.0001.0001.0001.0001.000
소재지(도로명주소)1.0001.0001.0001.0001.000
연락처1.0001.0001.0001.0001.000
2023-12-11T02:13:02.219262image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번업종
연번1.0000.000
업종0.0001.000

Missing values

2023-12-11T02:12:52.229567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T02:12:52.450869image/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

연번업종업소명소재지(도로명주소)연락처
01한식금복식당부산광역시 부산진구 서면문화로5번길 13(부전동)051-803-8790
12한식좋은식당부산광역시 부산진구 전포대로176번길 15(전포동)051-818-4243
23한식서울식당부산광역시 부산진구 가야대로703번길31(당감동)051-895-5885
34한식하동재첩부산광역시 부산진구 중앙대로743번길 25(부전동)051-808-5668
45한식우정분식부산광역시 부산진구 동천로85번길 3(부전동)051-803-0303
56한식중앙숯불갈비부산광역시 부산진구 골드테마길 65(범천동)051-632-2008
67한식골목식당(1974골목)부산광역시 부산진구 가야대로784번길 46(부전동)051-803-3850
78한식도마위에 암소부산광역시 부산진구 서면문화로 48(부전동)051-805-0073
89미용업영신미용실부산광역시 부산진구 서전로67번길 27-5(전포동)051-804-1041
910한식영자면옥칼국수부산광역시 부산진구 새싹로8번길 29(부전동)051-809-2136
연번업종업소명소재지(도로명주소)연락처
3637세탁업창진세탁부산광역시 부산진구 엄광로 70(가야동)051-893-4167
3738한식분식휴게소부산광역시 부산진구 냉정로 225, 1층(개금동)051-891-7009
3839한식초원곰탕부산광역시 부산진구 부전로152번길 55, 1층(부전동)051-803-6652
3940한식부잣집밀면부산광역시 부산진구 새싹로8번길 32(부전동)051-867-0125
4041미용업가인헤어아트부산광역시 부산진구 엄광로 264(가야동)051-891-8366
4142한식논두렁부산광역시 부산진구 연지로 24, 1층(연지동)051-808-1966
4243한식엄마손팥칼국수부산광역시 부산진구 동평로44번길 62-14(당감동)051-805-6343
4344한식대박분식부산광역시 부산진구 가야대로482번길 14(개금동)070-4233-1654
4445한식정성담은부산광역시 부산진구 범일로 148(범천동)051-643-0074
4546미용업미짱헤어부산광역시 부산진구 백양산로53번길 103(담감동)051-896-0030