Overview

Dataset statistics

Number of variables9
Number of observations61
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.5 KiB
Average record size in memory76.1 B

Variable types

Numeric2
Categorical3
Text3
Boolean1

Dataset

Description전북특별자치도의 시군별 향토 음식점 데이터전북특별자치도 향토 음식점 및 대형 음식점 안내전북특별자치도 향토 음식점이 있는 시와 군의 이름전북특별자치도 향토 음식점 업소의 이름전북특별자치도 지정 향토 음식점에 대한 자료의 공개여부 등
Author전북특별자치도
URLhttps://www.data.go.kr/data/3081263/fileData.do

Alerts

자료출처 has constant value ""Constant
공개여부 has constant value ""Constant
순번 is highly overall correlated with 갱신주기(년) and 2 other fieldsHigh correlation
갱신주기(년) is highly overall correlated with 순번High correlation
시군명 is highly overall correlated with 순번 and 1 other fieldsHigh correlation
향토음식명 is highly overall correlated with 순번 and 1 other fieldsHigh correlation
순번 has unique valuesUnique
업소명 has unique valuesUnique
주소 has unique valuesUnique
전화번호 has unique valuesUnique

Reproduction

Analysis started2024-03-14 20:03:59.041890
Analysis finished2024-03-14 20:04:01.110734
Duration2.07 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct61
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean31
Minimum1
Maximum61
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size677.0 B
2024-03-15T05:04:01.261044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile4
Q116
median31
Q346
95-th percentile58
Maximum61
Range60
Interquartile range (IQR)30

Descriptive statistics

Standard deviation17.752934
Coefficient of variation (CV)0.57267529
Kurtosis-1.2
Mean31
Median Absolute Deviation (MAD)15
Skewness0
Sum1891
Variance315.16667
MonotonicityStrictly increasing
2024-03-15T05:04:01.533049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.6%
47 1
 
1.6%
34 1
 
1.6%
35 1
 
1.6%
36 1
 
1.6%
37 1
 
1.6%
38 1
 
1.6%
39 1
 
1.6%
40 1
 
1.6%
41 1
 
1.6%
Other values (51) 51
83.6%
ValueCountFrequency (%)
1 1
1.6%
2 1
1.6%
3 1
1.6%
4 1
1.6%
5 1
1.6%
6 1
1.6%
7 1
1.6%
8 1
1.6%
9 1
1.6%
10 1
1.6%
ValueCountFrequency (%)
61 1
1.6%
60 1
1.6%
59 1
1.6%
58 1
1.6%
57 1
1.6%
56 1
1.6%
55 1
1.6%
54 1
1.6%
53 1
1.6%
52 1
1.6%

시군명
Categorical

HIGH CORRELATION 

Distinct14
Distinct (%)23.0%
Missing0
Missing (%)0.0%
Memory size616.0 B
전주시
22 
익산시
6 
김제시
5 
부안군
5 
완주군
4 
Other values (9)
19 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique3 ?
Unique (%)4.9%

Sample

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

Common Values

ValueCountFrequency (%)
전주시 22
36.1%
익산시 6
 
9.8%
김제시 5
 
8.2%
부안군 5
 
8.2%
완주군 4
 
6.6%
고창군 4
 
6.6%
정읍시 3
 
4.9%
무주군 3
 
4.9%
군산시 2
 
3.3%
남원시 2
 
3.3%
Other values (4) 5
 
8.2%

Length

2024-03-15T05:04:01.973005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
전주시 22
36.1%
익산시 6
 
9.8%
김제시 5
 
8.2%
부안군 5
 
8.2%
완주군 4
 
6.6%
고창군 4
 
6.6%
정읍시 3
 
4.9%
무주군 3
 
4.9%
군산시 2
 
3.3%
남원시 2
 
3.3%
Other values (4) 5
 
8.2%

향토음식명
Categorical

HIGH CORRELATION 

Distinct30
Distinct (%)49.2%
Missing0
Missing (%)0.0%
Memory size616.0 B
전주비빔밥
8 
콩나물국밥
7 
민물장어구이
4 
순두부찌개
4 
바지락죽
 
3
Other values (25)
35 

Length

Max length9
Median length8
Mean length5.1147541
Min length3

Unique

Unique16 ?
Unique (%)26.2%

Sample

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

Common Values

ValueCountFrequency (%)
전주비빔밥 8
 
13.1%
콩나물국밥 7
 
11.5%
민물장어구이 4
 
6.6%
순두부찌개 4
 
6.6%
바지락죽 3
 
4.9%
한정식 3
 
4.9%
민물고기 매운탕 2
 
3.3%
돌솥밥 2
 
3.3%
육회비빔밥 2
 
3.3%
추어탕(숙회) 2
 
3.3%
Other values (20) 24
39.3%

Length

2024-03-15T05:04:02.480844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
전주비빔밥 8
 
11.0%
콩나물국밥 7
 
9.6%
민물장어구이 4
 
5.5%
순두부찌개 4
 
5.5%
바지락죽 3
 
4.1%
한정식 3
 
4.1%
탕 3
 
4.1%
지평선한우비빔밥 2
 
2.7%
산채정식 2
 
2.7%
궁 2
 
2.7%
Other values (28) 35
47.9%

업소명
Text

UNIQUE 

Distinct61
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size616.0 B
2024-03-15T05:04:03.720288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length11
Mean length6.2459016
Min length1

Characters and Unicode

Total characters381
Distinct characters131
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

Unique61 ?
Unique (%)100.0%

Sample

1st row종 로 회 관
2nd row한 국 관
3rd row한 국 집
4th row가 족 회 관
5th row고 궁
ValueCountFrequency (%)
관 8
 
5.6%
당 5
 
3.5%
집 5
 
3.5%
회 5
 
3.5%
가 4
 
2.8%
식 4
 
2.8%
한 3
 
2.1%
일 3
 
2.1%
신 3
 
2.1%
산 3
 
2.1%
Other values (86) 100
69.9%
2024-03-15T05:04:05.496548image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
82
 
21.5%
관 12
 
3.1%
산 9
 
2.4%
당 8
 
2.1%
식 7
 
1.8%
한 7
 
1.8%
집 7
 
1.8%
가 7
 
1.8%
전 7
 
1.8%
회 6
 
1.6%
Other values (121) 229
60.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 295
77.4%
Space Separator 82
 
21.5%
Close Punctuation 2
 
0.5%
Open Punctuation 2
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
관 12
 
4.1%
산 9
 
3.1%
당 8
 
2.7%
식 7
 
2.4%
한 7
 
2.4%
집 7
 
2.4%
가 7
 
2.4%
전 7
 
2.4%
회 6
 
2.0%
국 6
 
2.0%
Other values (118) 219
74.2%
Space Separator
ValueCountFrequency (%)
82
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 295
77.4%
Common 86
 
22.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
관 12
 
4.1%
산 9
 
3.1%
당 8
 
2.7%
식 7
 
2.4%
한 7
 
2.4%
집 7
 
2.4%
가 7
 
2.4%
전 7
 
2.4%
회 6
 
2.0%
국 6
 
2.0%
Other values (118) 219
74.2%
Common
ValueCountFrequency (%)
82
95.3%
) 2
 
2.3%
( 2
 
2.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 295
77.4%
ASCII 86
 
22.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
82
95.3%
) 2
 
2.3%
( 2
 
2.3%
Hangul
ValueCountFrequency (%)
관 12
 
4.1%
산 9
 
3.1%
당 8
 
2.7%
식 7
 
2.4%
한 7
 
2.4%
집 7
 
2.4%
가 7
 
2.4%
전 7
 
2.4%
회 6
 
2.0%
국 6
 
2.0%
Other values (118) 219
74.2%

주소
Text

UNIQUE 

Distinct61
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size616.0 B
2024-03-15T05:04:06.876714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length17
Mean length15.114754
Min length10

Characters and Unicode

Total characters922
Distinct characters122
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

Unique61 ?
Unique (%)100.0%

Sample

1st row전주시 완산구 전동성당길 98
2nd row전주시 덕진구 기린대로 425
3rd row전주시 완산구 어진길 119
4th row전주시 완산구 전라감영 5길 17
5th row전주시 덕진구 송천중앙로 33
ValueCountFrequency (%)
전주시 22
 
9.2%
완산구 17
 
7.1%
익산시 6
 
2.5%
부안군 5
 
2.1%
김제시 5
 
2.1%
덕진구 4
 
1.7%
아산면 4
 
1.7%
고창군 4
 
1.7%
완주군 4
 
1.7%
17 3
 
1.3%
Other values (137) 165
69.0%
2024-03-15T05:04:08.391402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
179
19.4%
산 48
 
5.2%
시 40
 
4.3%
로 40
 
4.3%
1 32
 
3.5%
주 32
 
3.5%
전 31
 
3.4%
면 29
 
3.1%
구 24
 
2.6%
2 24
 
2.6%
Other values (112) 443
48.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 565
61.3%
Space Separator 179
 
19.4%
Decimal Number 170
 
18.4%
Dash Punctuation 8
 
0.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 48
 
8.5%
시 40
 
7.1%
로 40
 
7.1%
주 32
 
5.7%
전 31
 
5.5%
면 29
 
5.1%
구 24
 
4.2%
군 23
 
4.1%
길 21
 
3.7%
완 21
 
3.7%
Other values (100) 256
45.3%
Decimal Number
ValueCountFrequency (%)
1 32
18.8%
2 24
14.1%
3 20
11.8%
5 18
10.6%
7 15
8.8%
8 14
8.2%
4 14
8.2%
9 13
7.6%
6 11
 
6.5%
0 9
 
5.3%
Space Separator
ValueCountFrequency (%)
179
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 565
61.3%
Common 357
38.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 48
 
8.5%
시 40
 
7.1%
로 40
 
7.1%
주 32
 
5.7%
전 31
 
5.5%
면 29
 
5.1%
구 24
 
4.2%
군 23
 
4.1%
길 21
 
3.7%
완 21
 
3.7%
Other values (100) 256
45.3%
Common
ValueCountFrequency (%)
179
50.1%
1 32
 
9.0%
2 24
 
6.7%
3 20
 
5.6%
5 18
 
5.0%
7 15
 
4.2%
8 14
 
3.9%
4 14
 
3.9%
9 13
 
3.6%
6 11
 
3.1%
Other values (2) 17
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 565
61.3%
ASCII 357
38.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
179
50.1%
1 32
 
9.0%
2 24
 
6.7%
3 20
 
5.6%
5 18
 
5.0%
7 15
 
4.2%
8 14
 
3.9%
4 14
 
3.9%
9 13
 
3.6%
6 11
 
3.1%
Other values (2) 17
 
4.8%
Hangul
ValueCountFrequency (%)
산 48
 
8.5%
시 40
 
7.1%
로 40
 
7.1%
주 32
 
5.7%
전 31
 
5.5%
면 29
 
5.1%
구 24
 
4.2%
군 23
 
4.1%
길 21
 
3.7%
완 21
 
3.7%
Other values (100) 256
45.3%

전화번호
Text

UNIQUE 

Distinct61
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size616.0 B
2024-03-15T05:04:09.407074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters732
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

Unique61 ?
Unique (%)100.0%

Sample

1st row063-288-4578
2nd row063-272-9229
3rd row063-284-2224
4th row063-284-2884
5th row063-251-3211
ValueCountFrequency (%)
063-288-4578 1
 
1.6%
063-538-8131 1
 
1.6%
063-625-2443 1
 
1.6%
063-625-3356 1
 
1.6%
063-548-5557 1
 
1.6%
063-542-0431 1
 
1.6%
063-543-0076 1
 
1.6%
063-548-9595 1
 
1.6%
063-545-0666 1
 
1.6%
063-262-2602 1
 
1.6%
Other values (51) 51
83.6%
2024-03-15T05:04:11.177920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 122
16.7%
3 106
14.5%
6 104
14.2%
0 89
12.2%
2 76
10.4%
8 59
8.1%
5 53
7.2%
4 43
 
5.9%
1 39
 
5.3%
7 22
 
3.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 610
83.3%
Dash Punctuation 122
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 106
17.4%
6 104
17.0%
0 89
14.6%
2 76
12.5%
8 59
9.7%
5 53
8.7%
4 43
7.0%
1 39
 
6.4%
7 22
 
3.6%
9 19
 
3.1%
Dash Punctuation
ValueCountFrequency (%)
- 122
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 732
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 122
16.7%
3 106
14.5%
6 104
14.2%
0 89
12.2%
2 76
10.4%
8 59
8.1%
5 53
7.2%
4 43
 
5.9%
1 39
 
5.3%
7 22
 
3.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 732
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 122
16.7%
3 106
14.5%
6 104
14.2%
0 89
12.2%
2 76
10.4%
8 59
8.1%
5 53
7.2%
4 43
 
5.9%
1 39
 
5.3%
7 22
 
3.0%

자료출처
Categorical

CONSTANT 

Distinct1
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size616.0 B
건강안전과
61 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
건강안전과 61
100.0%

Length

2024-03-15T05:04:11.696918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T05:04:12.073651image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
건강안전과 61
100.0%

공개여부
Boolean

CONSTANT 

Distinct1
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size189.0 B
True
61 
ValueCountFrequency (%)
True 61
100.0%
2024-03-15T05:04:12.615748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

갱신주기(년)
Real number (ℝ)

HIGH CORRELATION 

Distinct7
Distinct (%)11.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.3442623
Minimum1
Maximum7
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size677.0 B
2024-03-15T05:04:12.887139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median1
Q31
95-th percentile4
Maximum7
Range6
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.1815984
Coefficient of variation (CV)0.87899396
Kurtosis13.190339
Mean1.3442623
Median Absolute Deviation (MAD)0
Skewness3.6766494
Sum82
Variance1.3961749
MonotonicityIncreasing
2024-03-15T05:04:13.229049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
1 55
90.2%
2 1
 
1.6%
3 1
 
1.6%
4 1
 
1.6%
5 1
 
1.6%
6 1
 
1.6%
7 1
 
1.6%
ValueCountFrequency (%)
1 55
90.2%
2 1
 
1.6%
3 1
 
1.6%
4 1
 
1.6%
5 1
 
1.6%
6 1
 
1.6%
7 1
 
1.6%
ValueCountFrequency (%)
7 1
 
1.6%
6 1
 
1.6%
5 1
 
1.6%
4 1
 
1.6%
3 1
 
1.6%
2 1
 
1.6%
1 55
90.2%

Interactions

2024-03-15T05:04:00.180428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:03:59.668339image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:04:00.430302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:03:59.917428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-15T05:04:13.489995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번시군명향토음식명업소명주소전화번호갱신주기(년)
순번1.0000.9170.9761.0001.0001.0000.288
시군명0.9171.0000.9971.0001.0001.0000.000
향토음식명0.9760.9971.0001.0001.0001.0000.663
업소명1.0001.0001.0001.0001.0001.0001.000
주소1.0001.0001.0001.0001.0001.0001.000
전화번호1.0001.0001.0001.0001.0001.0001.000
갱신주기(년)0.2880.0000.6631.0001.0001.0001.000
2024-03-15T05:04:13.770872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
향토음식명시군명
향토음식명1.0000.787
시군명0.7871.000
2024-03-15T05:04:14.010945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번갱신주기(년)시군명향토음식명
순번1.0000.5170.6350.619
갱신주기(년)0.5171.0000.0000.250
시군명0.6350.0001.0000.787
향토음식명0.6190.2500.7871.000

Missing values

2024-03-15T05:04:00.755736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-15T05:04:00.991946image/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

순번시군명향토음식명업소명주소전화번호자료출처공개여부갱신주기(년)
01전주시전주비빔밥종 로 회 관전주시 완산구 전동성당길 98063-288-4578건강안전과Y1
12전주시전주비빔밥한 국 관전주시 덕진구 기린대로 425063-272-9229건강안전과Y1
23전주시전주비빔밥한 국 집전주시 완산구 어진길 119063-284-2224건강안전과Y1
34전주시전주비빔밥가 족 회 관전주시 완산구 전라감영 5길 17063-284-2884건강안전과Y1
45전주시전주비빔밥고 궁전주시 덕진구 송천중앙로 33063-251-3211건강안전과Y1
56전주시전주비빔밥풍 남 정전주시 완산구 태조로 52063-285-7782건강안전과Y1
67전주시전주비빔밥전주부븸온전주시 오나산구 현무1길 20063-284-0982건강안전과Y1
78전주시전주비빔밥(유)갑기원전주시 덕진구 상리로 50063-212-5766건강안전과Y1
89전주시콩나물국밥삼 백 집전주시 완산구 전주객사2길 22063-284-2227건강안전과Y1
910전주시콩나물국밥삼 일 관전주시 완산구 전주객사2길 20063-284-8964건강안전과Y1
순번시군명향토음식명업소명주소전화번호자료출처공개여부갱신주기(년)
5152순창군민물고기매운탕화탄매운탕순창군 유등면 화탄길 1063-652-2956건강안전과Y1
5253고창군민물장어구이신 덕 식 당고창군 아산면 선운사로 8063-562-1533건강안전과Y1
5354고창군민물장어구이유 신 식 당고창군 아산면 선운사로 25063-562-1566건강안전과Y1
5455고창군민물장어구이연 기 식 당고창군 아산면 선운대로 2727063-561-3815건강안전과Y1
5556고창군민물장어구이청림가든정 금자할매집고창군 아산면 인천강서길 12063-564-1406건강안전과Y2
5657부안군백합죽계 화 회 관부안군 행안면 변산로 95063-584-8100건강안전과Y3
5758부안군바지락죽변산 온천산장부안군 변산면 묵정길 83-6063-584-4874건강안전과Y4
5859부안군바지락죽원조 바지락죽부안군 변산면 묵정길 18063-583-9763건강안전과Y5
5960부안군바지락죽변산 명인바지락죽부안군 변산면 변산해변로 794063-584-7171건강안전과Y6
6061부안군오디영양밥당 산 마 루부안군 부안읍 당산로 71063-581-1626건강안전과Y7