Overview

Dataset statistics

Number of variables4
Number of observations42
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory1.5 KiB
Average record size in memory36.1 B

Variable types

Numeric1
Categorical1
Text2

Dataset

Description부산광역시북구_착한가격업소현황_20230615
Author부산광역시 북구
URLhttp://data.busan.go.kr/dataSet/detail.nm?contentId=10&publicdatapk=15005906

Alerts

연번 has unique valuesUnique
상호 has unique valuesUnique

Reproduction

Analysis started2023-12-10 17:21:00.459754
Analysis finished2023-12-10 17:21:01.376735
Duration0.92 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct42
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean21.5
Minimum1
Maximum42
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size510.0 B
2023-12-11T02:21:01.545870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3.05
Q111.25
median21.5
Q331.75
95-th percentile39.95
Maximum42
Range41
Interquartile range (IQR)20.5

Descriptive statistics

Standard deviation12.267844
Coefficient of variation (CV)0.5705974
Kurtosis-1.2
Mean21.5
Median Absolute Deviation (MAD)10.5
Skewness0
Sum903
Variance150.5
MonotonicityStrictly increasing
2023-12-11T02:21:01.855706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=42)
ValueCountFrequency (%)
1 1
 
2.4%
33 1
 
2.4%
25 1
 
2.4%
26 1
 
2.4%
27 1
 
2.4%
28 1
 
2.4%
29 1
 
2.4%
30 1
 
2.4%
31 1
 
2.4%
32 1
 
2.4%
Other values (32) 32
76.2%
ValueCountFrequency (%)
1 1
2.4%
2 1
2.4%
3 1
2.4%
4 1
2.4%
5 1
2.4%
6 1
2.4%
7 1
2.4%
8 1
2.4%
9 1
2.4%
10 1
2.4%
ValueCountFrequency (%)
42 1
2.4%
41 1
2.4%
40 1
2.4%
39 1
2.4%
38 1
2.4%
37 1
2.4%
36 1
2.4%
35 1
2.4%
34 1
2.4%
33 1
2.4%

업종
Categorical

Distinct8
Distinct (%)19.0%
Missing0
Missing (%)0.0%
Memory size468.0 B
한식
18 
이미용업
11 
중식
5 
기타음식업
3 
목욕업
2 
Other values (3)
3 

Length

Max length6
Median length2
Mean length2.9047619
Min length2

Unique

Unique3 ?
Unique (%)7.1%

Sample

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

Common Values

ValueCountFrequency (%)
한식 18
42.9%
이미용업 11
26.2%
중식 5
 
11.9%
기타음식업 3
 
7.1%
목욕업 2
 
4.8%
세탁업 1
 
2.4%
일식 1
 
2.4%
기타서비스업 1
 
2.4%

Length

2023-12-11T02:21:02.215658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T02:21:02.530077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
한식 18
42.9%
이미용업 11
26.2%
중식 5
 
11.9%
기타음식업 3
 
7.1%
목욕업 2
 
4.8%
세탁업 1
 
2.4%
일식 1
 
2.4%
기타서비스업 1
 
2.4%

상호
Text

UNIQUE 

Distinct42
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size468.0 B
2023-12-11T02:21:03.022328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length9.5
Mean length5.5952381
Min length3

Characters and Unicode

Total characters235
Distinct characters141
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

Unique42 ?
Unique (%)100.0%

Sample

1st row대박삼겹2900
2nd row이원화구포국시전문점
3rd row금곡추어탕
4th row상하이갤러리
5th row우정분식
ValueCountFrequency (%)
대박삼겹2900 1
 
2.2%
아주탕 1
 
2.2%
헤어스케치 1
 
2.2%
헤어톡 1
 
2.2%
양지미용실 1
 
2.2%
북구반점 1
 
2.2%
돈까스 1
 
2.2%
일번지 1
 
2.2%
홍천손칼국수 1
 
2.2%
어미당 1
 
2.2%
Other values (35) 35
77.8%
2023-12-11T02:21:03.861324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
어 8
 
3.4%
용 7
 
3.0%
미 7
 
3.0%
이 6
 
2.6%
실 6
 
2.6%
헤 5
 
2.1%
지 5
 
2.1%
국 5
 
2.1%
전 4
 
1.7%
탕 4
 
1.7%
Other values (131) 178
75.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 224
95.3%
Decimal Number 6
 
2.6%
Space Separator 3
 
1.3%
Close Punctuation 1
 
0.4%
Open Punctuation 1
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
어 8
 
3.6%
용 7
 
3.1%
미 7
 
3.1%
이 6
 
2.7%
실 6
 
2.7%
헤 5
 
2.2%
지 5
 
2.2%
국 5
 
2.2%
전 4
 
1.8%
탕 4
 
1.8%
Other values (124) 167
74.6%
Decimal Number
ValueCountFrequency (%)
0 3
50.0%
9 1
 
16.7%
2 1
 
16.7%
1 1
 
16.7%
Space Separator
ValueCountFrequency (%)
3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 224
95.3%
Common 11
 
4.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
어 8
 
3.6%
용 7
 
3.1%
미 7
 
3.1%
이 6
 
2.7%
실 6
 
2.7%
헤 5
 
2.2%
지 5
 
2.2%
국 5
 
2.2%
전 4
 
1.8%
탕 4
 
1.8%
Other values (124) 167
74.6%
Common
ValueCountFrequency (%)
3
27.3%
0 3
27.3%
9 1
 
9.1%
2 1
 
9.1%
) 1
 
9.1%
( 1
 
9.1%
1 1
 
9.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 224
95.3%
ASCII 11
 
4.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
어 8
 
3.6%
용 7
 
3.1%
미 7
 
3.1%
이 6
 
2.7%
실 6
 
2.7%
헤 5
 
2.2%
지 5
 
2.2%
국 5
 
2.2%
전 4
 
1.8%
탕 4
 
1.8%
Other values (124) 167
74.6%
ASCII
ValueCountFrequency (%)
3
27.3%
0 3
27.3%
9 1
 
9.1%
2 1
 
9.1%
) 1
 
9.1%
( 1
 
9.1%
1 1
 
9.1%

사업장 주소
Text

Distinct41
Distinct (%)97.6%
Missing0
Missing (%)0.0%
Memory size468.0 B
2023-12-11T02:21:04.397330image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length36
Median length17
Mean length14.452381
Min length6

Characters and Unicode

Total characters607
Distinct characters57
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

Unique40 ?
Unique (%)95.2%

Sample

1st row만덕2로 24
2nd row구포시장1길 6(구포동)
3rd row효열로275번길 43(금곡동)
4th row의성로115번길127(덕천동)
5th row만덕대로15번길9(덕천동)
ValueCountFrequency (%)
금곡대로20번길 3
 
3.8%
구포시장1길 2
 
2.6%
만덕대로 2
 
2.6%
의성로 2
 
2.6%
6(구포동 2
 
2.6%
68 1
 
1.3%
7-4(만덕동 1
 
1.3%
상학로 1
 
1.3%
5 1
 
1.3%
1층(만덕동 1
 
1.3%
Other values (62) 62
79.5%
2023-12-11T02:21:05.569493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 41
 
6.8%
로 39
 
6.4%
동 38
 
6.3%
덕 36
 
5.9%
36
 
5.9%
) 35
 
5.8%
( 34
 
5.6%
2 28
 
4.6%
길 27
 
4.4%
번 24
 
4.0%
Other values (47) 269
44.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 318
52.4%
Decimal Number 175
28.8%
Space Separator 36
 
5.9%
Close Punctuation 35
 
5.8%
Open Punctuation 34
 
5.6%
Dash Punctuation 6
 
1.0%
Other Punctuation 3
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 39
12.3%
동 38
11.9%
덕 36
11.3%
길 27
 
8.5%
번 24
 
7.5%
만 20
 
6.3%
대 15
 
4.7%
천 15
 
4.7%
포 9
 
2.8%
구 9
 
2.8%
Other values (32) 86
27.0%
Decimal Number
ValueCountFrequency (%)
1 41
23.4%
2 28
16.0%
3 22
12.6%
4 21
12.0%
0 19
10.9%
7 11
 
6.3%
5 10
 
5.7%
8 10
 
5.7%
6 7
 
4.0%
9 6
 
3.4%
Space Separator
ValueCountFrequency (%)
36
100.0%
Close Punctuation
ValueCountFrequency (%)
) 35
100.0%
Open Punctuation
ValueCountFrequency (%)
( 34
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%
Other Punctuation
ValueCountFrequency (%)
, 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 318
52.4%
Common 289
47.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 39
12.3%
동 38
11.9%
덕 36
11.3%
길 27
 
8.5%
번 24
 
7.5%
만 20
 
6.3%
대 15
 
4.7%
천 15
 
4.7%
포 9
 
2.8%
구 9
 
2.8%
Other values (32) 86
27.0%
Common
ValueCountFrequency (%)
1 41
14.2%
36
12.5%
) 35
12.1%
( 34
11.8%
2 28
9.7%
3 22
7.6%
4 21
7.3%
0 19
6.6%
7 11
 
3.8%
5 10
 
3.5%
Other values (5) 32
11.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 318
52.4%
ASCII 289
47.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 41
14.2%
36
12.5%
) 35
12.1%
( 34
11.8%
2 28
9.7%
3 22
7.6%
4 21
7.3%
0 19
6.6%
7 11
 
3.8%
5 10
 
3.5%
Other values (5) 32
11.1%
Hangul
ValueCountFrequency (%)
로 39
12.3%
동 38
11.9%
덕 36
11.3%
길 27
 
8.5%
번 24
 
7.5%
만 20
 
6.3%
대 15
 
4.7%
천 15
 
4.7%
포 9
 
2.8%
구 9
 
2.8%
Other values (32) 86
27.0%

Interactions

2023-12-11T02:21:00.881429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T02:21:06.058210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번업종상호사업장 주소
연번1.0000.5971.0000.940
업종0.5971.0001.0001.000
상호1.0001.0001.0001.000
사업장 주소0.9401.0001.0001.000
2023-12-11T02:21:06.963698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번업종
연번1.0000.318
업종0.3181.000

Missing values

2023-12-11T02:21:01.112818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T02:21:01.301767image/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

연번업종상호사업장 주소
01한식대박삼겹2900만덕2로 24
12한식이원화구포국시전문점구포시장1길 6(구포동)
23한식금곡추어탕효열로275번길 43(금곡동)
34중식상하이갤러리의성로115번길127(덕천동)
45한식우정분식만덕대로15번길9(덕천동)
56한식경주전통돼지국밥만덕2로44번길43(만덕동)
67중식떴다왕손짜장금곡대로303번길80(화명동)
78한식강대감손칼국수구포시장1길 6(구포동)
89한식밀양가마솥추어탕와석장터로13(화명동)
910이미용업남희헤어아트백양대로1048번가길13(구포동)
연번업종상호사업장 주소
3233한식돈갈비의성로 109번길 34-2(덕천동)
3334기타서비스업맘씨생활건강만덕3로 33번길 8(만덕동)
3435이미용업달팽이미용실의성로 115번길 3 1층(덕천동)
3536중식웁스차이나시랑로 48
3637한식거창숯불구이만덕1로24번길 7-4(만덕동)
3738한식하동돼지국밥만덕대로 68
3839한식신가야밀면만덕2로44번길40
3940한식합천왕갈비만덕1로35-2
4041이미용업헤어코롱미용실양달로80-11 상가105호
4142한식만덕고깃집덕천로247번길3 1층