Overview

Dataset statistics

Number of variables5
Number of observations59
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.5 KiB
Average record size in memory43.2 B

Variable types

Text4
Numeric1

Dataset

Description사상구 관내 착한가격업소(업소명, 소재지, 연락처, 품목) 안내사항으로 물가안정에 기여하는 착한 가게를 소개하여 소비자 물가 안정에 기여하기 위함
URLhttps://www.data.go.kr/data/15001641/fileData.do

Alerts

업소명 has unique valuesUnique
새 주소 has unique valuesUnique

Reproduction

Analysis started2023-12-12 10:22:02.588554
Analysis finished2023-12-12 10:22:03.239168
Duration0.65 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업소명
Text

UNIQUE 

Distinct59
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size604.0 B
2023-12-12T19:22:03.462853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length8
Mean length4.9661017
Min length1

Characters and Unicode

Total characters293
Distinct characters154
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

Unique59 ?
Unique (%)100.0%

Sample

1st row예진할매칼국수
2nd row원산갈비
3rd row촌칼국수
4th row강촌칼국수
5th row합천돼지국밥
ValueCountFrequency (%)
예진할매칼국수 1
 
1.6%
만복밀면 1
 
1.6%
밥을 1
 
1.6%
짓다 1
 
1.6%
산에산에 1
 
1.6%
오대양횟집 1
 
1.6%
로뎀국수칼국수 1
 
1.6%
문화관 1
 
1.6%
옌닌쌀국수 1
 
1.6%
송림시골밥상 1
 
1.6%
Other values (51) 51
83.6%
2023-12-12T19:22:03.907129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
국 16
 
5.5%
수 12
 
4.1%
밥 8
 
2.7%
칼 8
 
2.7%
리 6
 
2.0%
산 5
 
1.7%
오 5
 
1.7%
정 5
 
1.7%
장 5
 
1.7%
지 4
 
1.4%
Other values (144) 219
74.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 291
99.3%
Space Separator 2
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
국 16
 
5.5%
수 12
 
4.1%
밥 8
 
2.7%
칼 8
 
2.7%
리 6
 
2.1%
산 5
 
1.7%
오 5
 
1.7%
정 5
 
1.7%
장 5
 
1.7%
지 4
 
1.4%
Other values (143) 217
74.6%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 291
99.3%
Common 2
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
국 16
 
5.5%
수 12
 
4.1%
밥 8
 
2.7%
칼 8
 
2.7%
리 6
 
2.1%
산 5
 
1.7%
오 5
 
1.7%
정 5
 
1.7%
장 5
 
1.7%
지 4
 
1.4%
Other values (143) 217
74.6%
Common
ValueCountFrequency (%)
2
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 291
99.3%
ASCII 2
 
0.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
국 16
 
5.5%
수 12
 
4.1%
밥 8
 
2.7%
칼 8
 
2.7%
리 6
 
2.1%
산 5
 
1.7%
오 5
 
1.7%
정 5
 
1.7%
장 5
 
1.7%
지 4
 
1.4%
Other values (143) 217
74.6%
ASCII
ValueCountFrequency (%)
2
100.0%

새 주소
Text

UNIQUE 

Distinct59
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size604.0 B
2023-12-12T19:22:04.197389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length43
Median length33
Mean length25.762712
Min length20

Characters and Unicode

Total characters1520
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

Unique59 ?
Unique (%)100.0%

Sample

1st row부산광역시 사상구 학장로 324(주례동)
2nd row부산광역시 사상구 광장로81번길 27(괘법동)
3rd row부산광역시 사상구 모라로110번길 40-13(모라동)
4th row부산광역시 사상구 백양대로 916, 1-112(모라동, 우성상가)
5th row부산광역시 사상구 사상로309번길7(덕포동)
ValueCountFrequency (%)
부산광역시 59
23.9%
사상구 59
23.9%
사상로 7
 
2.8%
백양대로 5
 
2.0%
학감대로 3
 
1.2%
대동로 2
 
0.8%
괘감로 2
 
0.8%
새벽시장로 2
 
0.8%
1층(주례동 2
 
0.8%
사상로342번길 2
 
0.8%
Other values (101) 104
42.1%
2023-12-12T19:22:04.634836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
188
 
12.4%
상 82
 
5.4%
사 77
 
5.1%
동 66
 
4.3%
시 64
 
4.2%
광 62
 
4.1%
산 60
 
3.9%
부 59
 
3.9%
역 59
 
3.9%
구 59
 
3.9%
Other values (62) 744
48.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 943
62.0%
Decimal Number 248
 
16.3%
Space Separator 188
 
12.4%
Open Punctuation 58
 
3.8%
Close Punctuation 58
 
3.8%
Other Punctuation 14
 
0.9%
Dash Punctuation 11
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
상 82
 
8.7%
사 77
 
8.2%
동 66
 
7.0%
시 64
 
6.8%
광 62
 
6.6%
산 60
 
6.4%
부 59
 
6.3%
역 59
 
6.3%
구 59
 
6.3%
로 59
 
6.3%
Other values (47) 296
31.4%
Decimal Number
ValueCountFrequency (%)
1 37
14.9%
2 36
14.5%
3 33
13.3%
6 24
9.7%
7 23
9.3%
4 20
8.1%
0 20
8.1%
5 19
7.7%
8 19
7.7%
9 17
6.9%
Space Separator
ValueCountFrequency (%)
188
100.0%
Open Punctuation
ValueCountFrequency (%)
( 58
100.0%
Close Punctuation
ValueCountFrequency (%)
) 58
100.0%
Other Punctuation
ValueCountFrequency (%)
, 14
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 943
62.0%
Common 577
38.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
상 82
 
8.7%
사 77
 
8.2%
동 66
 
7.0%
시 64
 
6.8%
광 62
 
6.6%
산 60
 
6.4%
부 59
 
6.3%
역 59
 
6.3%
구 59
 
6.3%
로 59
 
6.3%
Other values (47) 296
31.4%
Common
ValueCountFrequency (%)
188
32.6%
( 58
 
10.1%
) 58
 
10.1%
1 37
 
6.4%
2 36
 
6.2%
3 33
 
5.7%
6 24
 
4.2%
7 23
 
4.0%
4 20
 
3.5%
0 20
 
3.5%
Other values (5) 80
13.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 943
62.0%
ASCII 577
38.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
188
32.6%
( 58
 
10.1%
) 58
 
10.1%
1 37
 
6.4%
2 36
 
6.2%
3 33
 
5.7%
6 24
 
4.2%
7 23
 
4.0%
4 20
 
3.5%
0 20
 
3.5%
Other values (5) 80
13.9%
Hangul
ValueCountFrequency (%)
상 82
 
8.7%
사 77
 
8.2%
동 66
 
7.0%
시 64
 
6.8%
광 62
 
6.6%
산 60
 
6.4%
부 59
 
6.3%
역 59
 
6.3%
구 59
 
6.3%
로 59
 
6.3%
Other values (47) 296
31.4%

연락처
Text

Distinct55
Distinct (%)93.2%
Missing0
Missing (%)0.0%
Memory size604.0 B
2023-12-12T19:22:04.884613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length11.271186
Min length1

Characters and Unicode

Total characters665
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

Unique53 ?
Unique (%)89.8%

Sample

1st row051-322-5465
2nd row051-327-2127
3rd row051-317-6594
4th row051-313-6572
5th row051-302-2350
ValueCountFrequency (%)
4
 
6.8%
051-327-9463 2
 
3.4%
051-314-5353 1
 
1.7%
051-310-7200 1
 
1.7%
051-315-7005 1
 
1.7%
051-317-3287 1
 
1.7%
051-322-5465 1
 
1.7%
051-323-2370 1
 
1.7%
051-305-7258 1
 
1.7%
051-324-9903 1
 
1.7%
Other values (45) 45
76.3%
2023-12-12T19:22:05.282436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 114
17.1%
5 96
14.4%
3 96
14.4%
0 93
14.0%
1 92
13.8%
2 49
7.4%
7 36
 
5.4%
8 29
 
4.4%
6 26
 
3.9%
4 22
 
3.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 551
82.9%
Dash Punctuation 114
 
17.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 96
17.4%
3 96
17.4%
0 93
16.9%
1 92
16.7%
2 49
8.9%
7 36
 
6.5%
8 29
 
5.3%
6 26
 
4.7%
4 22
 
4.0%
9 12
 
2.2%
Dash Punctuation
ValueCountFrequency (%)
- 114
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 665
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 114
17.1%
5 96
14.4%
3 96
14.4%
0 93
14.0%
1 92
13.8%
2 49
7.4%
7 36
 
5.4%
8 29
 
4.4%
6 26
 
3.9%
4 22
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 665
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 114
17.1%
5 96
14.4%
3 96
14.4%
0 93
14.0%
1 92
13.8%
2 49
7.4%
7 36
 
5.4%
8 29
 
4.4%
6 26
 
3.9%
4 22
 
3.3%

메뉴
Text

Distinct36
Distinct (%)61.0%
Missing0
Missing (%)0.0%
Memory size604.0 B
2023-12-12T19:22:05.521441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length11
Mean length4.1864407
Min length2

Characters and Unicode

Total characters247
Distinct characters96
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique26 ?
Unique (%)44.1%

Sample

1st row칼국수
2nd row육개장
3rd row칼국수
4th row칼국수
5th row순대국밥
ValueCountFrequency (%)
칼국수 7
 
11.9%
자장면 6
 
10.2%
커트 4
 
6.8%
남성커트 4
 
6.8%
재첩국 2
 
3.4%
돼지국밥 2
 
3.4%
김밥(1줄 2
 
3.4%
짜장면 2
 
3.4%
회덮밥 2
 
3.4%
된장찌개 2
 
3.4%
Other values (26) 26
44.1%
2023-12-12T19:22:05.957535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
국 18
 
7.3%
장 13
 
5.3%
수 10
 
4.0%
( 10
 
4.0%
) 10
 
4.0%
밥 9
 
3.6%
면 9
 
3.6%
커 8
 
3.2%
트 8
 
3.2%
칼 7
 
2.8%
Other values (86) 145
58.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 214
86.6%
Open Punctuation 10
 
4.0%
Close Punctuation 10
 
4.0%
Decimal Number 9
 
3.6%
Math Symbol 1
 
0.4%
Other Symbol 1
 
0.4%
Lowercase Letter 1
 
0.4%
Space Separator 1
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
국 18
 
8.4%
장 13
 
6.1%
수 10
 
4.7%
밥 9
 
4.2%
면 9
 
4.2%
커 8
 
3.7%
트 8
 
3.7%
칼 7
 
3.3%
자 6
 
2.8%
산 4
 
1.9%
Other values (76) 122
57.0%
Decimal Number
ValueCountFrequency (%)
1 5
55.6%
2 2
 
22.2%
0 1
 
11.1%
5 1
 
11.1%
Open Punctuation
ValueCountFrequency (%)
( 10
100.0%
Close Punctuation
ValueCountFrequency (%)
) 10
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%
Other Symbol
ValueCountFrequency (%)
㎏ 1
100.0%
Lowercase Letter
ValueCountFrequency (%)
g 1
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 214
86.6%
Common 32
 
13.0%
Latin 1
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
국 18
 
8.4%
장 13
 
6.1%
수 10
 
4.7%
밥 9
 
4.2%
면 9
 
4.2%
커 8
 
3.7%
트 8
 
3.7%
칼 7
 
3.3%
자 6
 
2.8%
산 4
 
1.9%
Other values (76) 122
57.0%
Common
ValueCountFrequency (%)
( 10
31.2%
) 10
31.2%
1 5
15.6%
2 2
 
6.2%
+ 1
 
3.1%
0 1
 
3.1%
㎏ 1
 
3.1%
5 1
 
3.1%
1
 
3.1%
Latin
ValueCountFrequency (%)
g 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 214
86.6%
ASCII 32
 
13.0%
CJK Compat 1
 
0.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
국 18
 
8.4%
장 13
 
6.1%
수 10
 
4.7%
밥 9
 
4.2%
면 9
 
4.2%
커 8
 
3.7%
트 8
 
3.7%
칼 7
 
3.3%
자 6
 
2.8%
산 4
 
1.9%
Other values (76) 122
57.0%
ASCII
ValueCountFrequency (%)
( 10
31.2%
) 10
31.2%
1 5
15.6%
2 2
 
6.2%
+ 1
 
3.1%
0 1
 
3.1%
5 1
 
3.1%
g 1
 
3.1%
1
 
3.1%
CJK Compat
ValueCountFrequency (%)
㎏ 1
100.0%

가격
Real number (ℝ)

Distinct18
Distinct (%)30.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11301.695
Minimum1200
Maximum220000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size663.0 B
2023-12-12T19:22:06.125555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1200
5-th percentile3850
Q15000
median6000
Q38000
95-th percentile25900
Maximum220000
Range218800
Interquartile range (IQR)3000

Descriptive statistics

Standard deviation28341.894
Coefficient of variation (CV)2.507756
Kurtosis53.084356
Mean11301.695
Median Absolute Deviation (MAD)1000
Skewness7.1456384
Sum666800
Variance8.0326293 × 108
MonotonicityNot monotonic
2023-12-12T19:22:06.270689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
6000 11
18.6%
8000 11
18.6%
5000 10
16.9%
7000 6
10.2%
10000 4
 
6.8%
4000 3
 
5.1%
5500 2
 
3.4%
4500 2
 
3.4%
25000 1
 
1.7%
39000 1
 
1.7%
Other values (8) 8
13.6%
ValueCountFrequency (%)
1200 1
 
1.7%
1800 1
 
1.7%
2500 1
 
1.7%
4000 3
 
5.1%
4500 2
 
3.4%
5000 10
16.9%
5500 2
 
3.4%
6000 11
18.6%
6500 1
 
1.7%
7000 6
10.2%
ValueCountFrequency (%)
220000 1
 
1.7%
39000 1
 
1.7%
34000 1
 
1.7%
25000 1
 
1.7%
10000 4
 
6.8%
9800 1
 
1.7%
9000 1
 
1.7%
8000 11
18.6%
7000 6
10.2%
6500 1
 
1.7%

Interactions

2023-12-12T19:22:02.973992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T19:22:06.373486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업소명새 주소연락처메뉴가격
업소명1.0001.0001.0001.0001.000
새 주소1.0001.0001.0001.0001.000
연락처1.0001.0001.0000.9181.000
메뉴1.0001.0000.9181.0001.000
가격1.0001.0001.0001.0001.000

Missing values

2023-12-12T19:22:03.085757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T19:22:03.191499image/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

업소명새 주소연락처메뉴가격
0예진할매칼국수부산광역시 사상구 학장로 324(주례동)051-322-5465칼국수5000
1원산갈비부산광역시 사상구 광장로81번길 27(괘법동)051-327-2127육개장8000
2촌칼국수부산광역시 사상구 모라로110번길 40-13(모라동)051-317-6594칼국수5000
3강촌칼국수부산광역시 사상구 백양대로 916, 1-112(모라동, 우성상가)051-313-6572칼국수5000
4합천돼지국밥부산광역시 사상구 사상로309번길7(덕포동)051-302-2350순대국밥8000
5만포장식당부산광역시 사상구 새벽시장로 58(감전동)051-317-0557삼겹살(국산150g)10000
6뿅가네장수돼지국밥부산광역시 사상구 괘감로 105(감전동)051-326-6624돼지국밥8000
7주례칼국수부산광역시 사상구 가야대로284번길 7-6(주례동)051-311-4628칼국수5000
8최가국밥부산광역시 사상구 가야대로366번길 43, 2층(주례동)051-314-3063돼지국밥7000
9박현헤어클럽부산광역시 사상구 백양대로 915(모라동)051-315-1137남성커트5000
업소명새 주소연락처메뉴가격
49까꼬뽀꼬부산광역시 사상구 새벽시장로46번길 29(감전동)051-322-8734커트6000
50진주네부산광역시 사상구 낙동대로766-8(엄궁동)051-324-3391회덮밥4500
51정다옥설렁탕부산광역시 사상구 농산물시장로22,103호(엄궁동)051-623-1233설렁탕10000
52후차이부산광역시 사상구 엄궁로206, 섬진아파트 4차상가 203호051-328-6000짜장면6000
53오륙도낙지부산광역시 사상구 모라로64(모라동)051-301-5253낙지볶음10000
54삼락하동재첩국부산광역시 사상구 낙동대로1518번길33(삼락동)051-310-7200재첩국8000
55가온미용실부산광역시 사상구 사상로 218(괘법동) 3층051-314-5353남성커트6000
56감전재첩국부산광역시 사상구 사상로123번길 17(감전동)051-317-3287재첩국8000
57냉정실내운전연습장부산광역시 사상구 가야대로 350(주례동) 2층051-315-7005장내+도로(2종)220000
58중국관부산광역시 사상구 사상로481번길 28(모라동)051-302-8775짜장면4000