Overview

Dataset statistics

Number of variables6
Number of observations70
Missing cells1
Missing cells (%)0.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.5 KiB
Average record size in memory50.9 B

Variable types

Categorical2
Text3
Numeric1

Dataset

Description울산광역시의 일반 음식점의 품목별 가격 동향 정보(업소명, 품목별, 소재지, 가격, 전화번호 등)를 제공하고 있음.
Author울산광역시
URLhttps://www.data.go.kr/data/15065101/fileData.do

Alerts

기준 is highly overall correlated with 품목별High correlation
품목별 is highly overall correlated with 기준High correlation
가격 has 1 (1.4%) missing valuesMissing

Reproduction

Analysis started2023-12-12 04:49:40.743314
Analysis finished2023-12-12 04:49:41.718940
Duration0.98 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

품목별
Categorical

HIGH CORRELATION 

Distinct14
Distinct (%)20.0%
Missing0
Missing (%)0.0%
Memory size692.0 B
냉 면
5 
비 빔 밥
5 
갈 비 탕
5 
삼 계 탕
5 
칼 국 수
5 
Other values (9)
45 

Length

Max length6
Median length5.5
Mean length4.8571429
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row냉 면
2nd row냉 면
3rd row냉 면
4th row냉 면
5th row냉 면

Common Values

ValueCountFrequency (%)
냉 면 5
 
7.1%
비 빔 밥 5
 
7.1%
갈 비 탕 5
 
7.1%
삼 계 탕 5
 
7.1%
칼 국 수 5
 
7.1%
자 장 면 5
 
7.1%
짬 뽕 5
 
7.1%
김치찌개 5
 
7.1%
된장찌개 5
 
7.1%
돼지갈비 5
 
7.1%
Other values (4) 20
28.6%

Length

2023-12-12T13:49:41.828807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
비 10
 
6.7%
김 10
 
6.7%
밥 10
 
6.7%
탕 10
 
6.7%
면 10
 
6.7%
냉 5
 
3.3%
뽕 5
 
3.3%
튀 5
 
3.3%
삼겹살 5
 
3.3%
심 5
 
3.3%
Other values (15) 75
50.0%

기준
Categorical

HIGH CORRELATION 

Distinct9
Distinct (%)12.9%
Missing0
Missing (%)0.0%
Memory size692.0 B
1 그릇
15 
중화요리점 1그릇
10 
대중식당 1그릇
10 
1인분 130g 기준(다를 시 환산 요망)
10 
1그릇(1마리)
5 
Other values (4)
20 

Length

Max length23
Median length10
Mean length9.1428571
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1 그릇
2nd row1 그릇
3rd row1 그릇
4th row1 그릇
5th row1 그릇

Common Values

ValueCountFrequency (%)
1 그릇 15
21.4%
중화요리점 1그릇 10
14.3%
대중식당 1그릇 10
14.3%
1인분 130g 기준(다를 시 환산 요망) 10
14.3%
1그릇(1마리) 5
 
7.1%
분식점 1그릇 5
 
7.1%
1인분 200g 기준 5
 
7.1%
튀김통닭 1마리 5
 
7.1%
1줄 5
 
7.1%

Length

2023-12-12T13:49:42.020652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T13:49:42.191067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1그릇 25
14.3%
1 15
 
8.6%
그릇 15
 
8.6%
1인분 15
 
8.6%
기준(다를 10
 
5.7%
요망 10
 
5.7%
시 10
 
5.7%
환산 10
 
5.7%
130g 10
 
5.7%
대중식당 10
 
5.7%
Other values (8) 45
25.7%

업소명
Text

Distinct55
Distinct (%)78.6%
Missing0
Missing (%)0.0%
Memory size692.0 B
2023-12-12T13:49:42.555786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length12
Mean length5.2428571
Min length3

Characters and Unicode

Total characters367
Distinct characters131
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

Unique44 ?
Unique (%)62.9%

Sample

1st row김밥나라
2nd row시골여행
3rd row참진앓이
4th row무돌삼
5th row숙이네분식
ValueCountFrequency (%)
김밥천국 4
 
5.2%
김밥나라 3
 
3.9%
촌당숯불갈비 3
 
3.9%
숙이네분식 2
 
2.6%
삼미식당 2
 
2.6%
북경반점 2
 
2.6%
산동만두 2
 
2.6%
꼬맹이김밥천국 2
 
2.6%
동산분식 2
 
2.6%
최가네밥 2
 
2.6%
Other values (51) 53
68.8%
2023-12-12T13:49:43.043562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
밥 17
 
4.6%
김 15
 
4.1%
이 11
 
3.0%
국 9
 
2.5%
숯 8
 
2.2%
비 8
 
2.2%
식 8
 
2.2%
8
 
2.2%
가 8
 
2.2%
불 7
 
1.9%
Other values (121) 268
73.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 359
97.8%
Space Separator 8
 
2.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
밥 17
 
4.7%
김 15
 
4.2%
이 11
 
3.1%
국 9
 
2.5%
숯 8
 
2.2%
비 8
 
2.2%
식 8
 
2.2%
가 8
 
2.2%
불 7
 
1.9%
갈 7
 
1.9%
Other values (120) 261
72.7%
Space Separator
ValueCountFrequency (%)
8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 359
97.8%
Common 8
 
2.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
밥 17
 
4.7%
김 15
 
4.2%
이 11
 
3.1%
국 9
 
2.5%
숯 8
 
2.2%
비 8
 
2.2%
식 8
 
2.2%
가 8
 
2.2%
불 7
 
1.9%
갈 7
 
1.9%
Other values (120) 261
72.7%
Common
ValueCountFrequency (%)
8
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 359
97.8%
ASCII 8
 
2.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
밥 17
 
4.7%
김 15
 
4.2%
이 11
 
3.1%
국 9
 
2.5%
숯 8
 
2.2%
비 8
 
2.2%
식 8
 
2.2%
가 8
 
2.2%
불 7
 
1.9%
갈 7
 
1.9%
Other values (120) 261
72.7%
ASCII
ValueCountFrequency (%)
8
100.0%

소재지
Text

Distinct59
Distinct (%)84.3%
Missing0
Missing (%)0.0%
Memory size692.0 B
2023-12-12T13:49:43.412565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length21
Mean length17.414286
Min length6

Characters and Unicode

Total characters1219
Distinct characters92
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

Unique48 ?
Unique (%)68.6%

Sample

1st row울산광역시 중구 유곡로 27
2nd row울산광역시 남구 수암로 116번길 14
3rd row울산광역시 동구 명덕 5길 8
4th row울산광역시 북구 당수골15길 5-1
5th row울산광역시 울주군 천상2길 6-3
ValueCountFrequency (%)
울산광역시 70
24.1%
남구 14
 
4.8%
울주군 14
 
4.8%
동구 14
 
4.8%
중구 13
 
4.5%
북구 13
 
4.5%
수암로 4
 
1.4%
청량읍 4
 
1.4%
12 3
 
1.0%
1층 3
 
1.0%
Other values (103) 138
47.6%
2023-12-12T13:49:44.015565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
222
18.2%
울 85
 
7.0%
시 76
 
6.2%
산 74
 
6.1%
광 70
 
5.7%
역 70
 
5.7%
구 55
 
4.5%
1 52
 
4.3%
길 41
 
3.4%
로 30
 
2.5%
Other values (82) 444
36.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 783
64.2%
Space Separator 222
 
18.2%
Decimal Number 197
 
16.2%
Dash Punctuation 11
 
0.9%
Other Punctuation 4
 
0.3%
Open Punctuation 1
 
0.1%
Close Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
울 85
 
10.9%
시 76
 
9.7%
산 74
 
9.5%
광 70
 
8.9%
역 70
 
8.9%
구 55
 
7.0%
길 41
 
5.2%
로 30
 
3.8%
동 21
 
2.7%
남 19
 
2.4%
Other values (67) 242
30.9%
Decimal Number
ValueCountFrequency (%)
1 52
26.4%
2 29
14.7%
5 25
12.7%
3 22
11.2%
0 19
 
9.6%
4 15
 
7.6%
6 11
 
5.6%
7 10
 
5.1%
9 10
 
5.1%
8 4
 
2.0%
Space Separator
ValueCountFrequency (%)
222
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 11
100.0%
Other Punctuation
ValueCountFrequency (%)
, 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 783
64.2%
Common 436
35.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
울 85
 
10.9%
시 76
 
9.7%
산 74
 
9.5%
광 70
 
8.9%
역 70
 
8.9%
구 55
 
7.0%
길 41
 
5.2%
로 30
 
3.8%
동 21
 
2.7%
남 19
 
2.4%
Other values (67) 242
30.9%
Common
ValueCountFrequency (%)
222
50.9%
1 52
 
11.9%
2 29
 
6.7%
5 25
 
5.7%
3 22
 
5.0%
0 19
 
4.4%
4 15
 
3.4%
- 11
 
2.5%
6 11
 
2.5%
7 10
 
2.3%
Other values (5) 20
 
4.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 783
64.2%
ASCII 436
35.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
222
50.9%
1 52
 
11.9%
2 29
 
6.7%
5 25
 
5.7%
3 22
 
5.0%
0 19
 
4.4%
4 15
 
3.4%
- 11
 
2.5%
6 11
 
2.5%
7 10
 
2.3%
Other values (5) 20
 
4.6%
Hangul
ValueCountFrequency (%)
울 85
 
10.9%
시 76
 
9.7%
산 74
 
9.5%
광 70
 
8.9%
역 70
 
8.9%
구 55
 
7.0%
길 41
 
5.2%
로 30
 
3.8%
동 21
 
2.7%
남 19
 
2.4%
Other values (67) 242
30.9%

가격
Real number (ℝ)

MISSING 

Distinct24
Distinct (%)34.8%
Missing1
Missing (%)1.4%
Infinite0
Infinite (%)0.0%
Mean7159.1304
Minimum2000
Maximum33800
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size762.0 B
2023-12-12T13:49:44.186812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2000
5-th percentile2200
Q15000
median6000
Q38000
95-th percentile14000
Maximum33800
Range31800
Interquartile range (IQR)3000

Descriptive statistics

Standard deviation4570.9008
Coefficient of variation (CV)0.63847151
Kurtosis16.818775
Mean7159.1304
Median Absolute Deviation (MAD)1990
Skewness3.3564686
Sum493980
Variance20893135
MonotonicityNot monotonic
2023-12-12T13:49:44.383324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
6000 10
14.3%
7000 9
12.9%
5000 7
 
10.0%
8000 5
 
7.1%
4000 4
 
5.7%
2000 4
 
5.7%
10000 4
 
5.7%
11000 3
 
4.3%
5500 3
 
4.3%
3900 2
 
2.9%
Other values (14) 18
25.7%
ValueCountFrequency (%)
2000 4
5.7%
2500 1
 
1.4%
3000 2
 
2.9%
3500 1
 
1.4%
3900 2
 
2.9%
4000 4
5.7%
4500 1
 
1.4%
5000 7
10.0%
5500 3
4.3%
5990 1
 
1.4%
ValueCountFrequency (%)
33800 1
 
1.4%
19500 1
 
1.4%
15600 1
 
1.4%
14000 2
 
2.9%
11000 3
4.3%
10010 1
 
1.4%
10000 4
5.7%
9000 1
 
1.4%
8000 5
7.1%
7990 2
 
2.9%

전화번호
Text

Distinct55
Distinct (%)78.6%
Missing0
Missing (%)0.0%
Memory size692.0 B
2023-12-12T13:49:44.731423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length14
Mean length12.814286
Min length9

Characters and Unicode

Total characters897
Distinct characters20
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

Unique43 ?
Unique (%)61.4%

Sample

1st row 052-211-4529
2nd row 052-258-5954
3rd row 052-975-0092
4th row052-287-8884
5th row052-242-0884
ValueCountFrequency (%)
개인정보로 5
 
6.7%
미기재 5
 
6.7%
052-248-5000 2
 
2.7%
052-251-6000 2
 
2.7%
052-252-1150 2
 
2.7%
052-252-1155 2
 
2.7%
052-266-7459 2
 
2.7%
052-237-5522 2
 
2.7%
052-294-1455 2
 
2.7%
052-227-3990 2
 
2.7%
Other values (45) 49
65.3%
2023-12-12T13:49:45.289119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 175
19.5%
- 130
14.5%
5 125
13.9%
0 107
11.9%
75
8.4%
9 46
 
5.1%
8 42
 
4.7%
1 39
 
4.3%
4 34
 
3.8%
3 32
 
3.6%
Other values (10) 92
10.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 652
72.7%
Dash Punctuation 130
 
14.5%
Space Separator 75
 
8.4%
Other Letter 40
 
4.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 175
26.8%
5 125
19.2%
0 107
16.4%
9 46
 
7.1%
8 42
 
6.4%
1 39
 
6.0%
4 34
 
5.2%
3 32
 
4.9%
7 30
 
4.6%
6 22
 
3.4%
Other Letter
ValueCountFrequency (%)
인 5
12.5%
재 5
12.5%
기 5
12.5%
미 5
12.5%
로 5
12.5%
보 5
12.5%
정 5
12.5%
개 5
12.5%
Dash Punctuation
ValueCountFrequency (%)
- 130
100.0%
Space Separator
ValueCountFrequency (%)
75
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 857
95.5%
Hangul 40
 
4.5%

Most frequent character per script

Common
ValueCountFrequency (%)
2 175
20.4%
- 130
15.2%
5 125
14.6%
0 107
12.5%
75
8.8%
9 46
 
5.4%
8 42
 
4.9%
1 39
 
4.6%
4 34
 
4.0%
3 32
 
3.7%
Other values (2) 52
 
6.1%
Hangul
ValueCountFrequency (%)
인 5
12.5%
재 5
12.5%
기 5
12.5%
미 5
12.5%
로 5
12.5%
보 5
12.5%
정 5
12.5%
개 5
12.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 857
95.5%
Hangul 40
 
4.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 175
20.4%
- 130
15.2%
5 125
14.6%
0 107
12.5%
75
8.8%
9 46
 
5.4%
8 42
 
4.9%
1 39
 
4.6%
4 34
 
4.0%
3 32
 
3.7%
Other values (2) 52
 
6.1%
Hangul
ValueCountFrequency (%)
인 5
12.5%
재 5
12.5%
기 5
12.5%
미 5
12.5%
로 5
12.5%
보 5
12.5%
정 5
12.5%
개 5
12.5%

Interactions

2023-12-12T13:49:41.306085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T13:49:45.448018image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
품목별기준업소명소재지가격전화번호
품목별1.0001.0000.0000.3660.6600.000
기준1.0001.0000.9310.9710.5340.916
업소명0.0000.9311.0000.9980.9450.999
소재지0.3660.9710.9981.0000.9970.999
가격0.6600.5340.9450.9971.0000.990
전화번호0.0000.9160.9990.9990.9901.000
2023-12-12T13:49:45.597787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
기준품목별
기준1.0000.958
품목별0.9581.000
2023-12-12T13:49:45.735414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
가격품목별기준
가격1.0000.3230.341
품목별0.3231.0000.958
기준0.3410.9581.000

Missing values

2023-12-12T13:49:41.494761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T13:49:41.663504image/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

품목별기준업소명소재지가격전화번호
0냉 면1 그릇김밥나라울산광역시 중구 유곡로 277000052-211-4529
1냉 면1 그릇시골여행울산광역시 남구 수암로 116번길 146500052-258-5954
2냉 면1 그릇참진앓이울산광역시 동구 명덕 5길 84000052-975-0092
3냉 면1 그릇무돌삼울산광역시 북구 당수골15길 5-16000052-287-8884
4냉 면1 그릇숙이네분식울산광역시 울주군 천상2길 6-36000052-242-0884
5비 빔 밥1 그릇고봉민김밥울산광역시 중구 번영로 5807000052-294-3655
6비 빔 밥1 그릇강산손수제비울산광역시 남구 중앙로 64번길 237000052-261-5292
7비 빔 밥1 그릇경주식당울산광역시 동구 전하동 동울산시장 상가5000개인정보로 미기재
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9비 빔 밥1 그릇숙이네분식울산광역시 울주군 천상2길 6-36000052-242-0884
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60튀 김 닭튀김통닭 1마리성아모듬통닭울산광역시 중구 화진길 1711000052-211-7000
61튀 김 닭튀김통닭 1마리조선의옛날통닭울산광역시 남구 월평로 507000052-911-9989
62튀 김 닭튀김통닭 1마리다가치통닭울산광역시 동구 명덕3길 408000052-234-8100
63튀 김 닭튀김통닭 1마리가마치통닭울산광역시 북구 천곡남로 34, 115호8000052-281-7292
64튀 김 닭튀김통닭 1마리가마치교동울산광역시 울주군 언양읍 헌양길219000052-254-8292
65김 밥1줄김밥나라울산광역시 중구 유곡로 273000052-211-4529
66김 밥1줄김밥천국울산광역시 남구 수암로 310-12500052-265-7110
67김 밥1줄이모집울산광역시 동구 명덕 2길 명덕시장2000052-235-9864
68김 밥1줄동산분식울산광역시 북구 호계3길 17-112000052-282-3882
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