Overview

Dataset statistics

Number of variables9
Number of observations162
Missing cells11
Missing cells (%)0.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory11.8 KiB
Average record size in memory74.8 B

Variable types

Text5
Numeric2
Categorical2

Dataset

Description식품위생법 제47조(위생등급), 식품위생법 시행규칙 제61조(우수업소·모범업소 지정 등)에 따른 전주시 내 모범음식점 현황을 제공합니다항목 : 업소명, 전화번호, 도로명주소, 지번주소, 위도, 경도 등제공부서 : 환경위생과
Author전북특별자치도 전주시
URLhttps://www.data.go.kr/data/3079790/fileData.do

Alerts

영업상태명 has constant value ""Constant
음식의유형 is highly imbalanced (62.3%)Imbalance
전화번호 has 11 (6.8%) missing valuesMissing
업소명 has unique valuesUnique
도로명주소 has unique valuesUnique
지번주소 has unique valuesUnique
위도 has unique valuesUnique
경도 has unique valuesUnique

Reproduction

Analysis started2024-03-14 20:49:46.436186
Analysis finished2024-03-14 20:49:48.343713
Duration1.91 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업소명
Text

UNIQUE 

Distinct162
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
2024-03-15T05:49:49.110218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length13
Mean length6.037037
Min length1

Characters and Unicode

Total characters978
Distinct characters268
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

Unique162 ?
Unique (%)100.0%

Sample

1st row가족회관
2nd row감로헌
3rd row감성9091돼지전주아중점
4th row건지산도토리
5th row겐돈소바
ValueCountFrequency (%)
가족회관 1
 
0.6%
전동떡갈비앤브리즈 1
 
0.6%
정통중화요리백두산 1
 
0.6%
전주메밀 1
 
0.6%
전주부븸온 1
 
0.6%
전주어죽본가 1
 
0.6%
전주옥정호 1
 
0.6%
정가네양평해장국아중2호점 1
 
0.6%
정든집 1
 
0.6%
김여사네 1
 
0.6%
Other values (157) 157
94.0%
2024-03-15T05:49:50.446650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
점 41
 
4.2%
가 22
 
2.2%
한 20
 
2.0%
전 18
 
1.8%
아 15
 
1.5%
주 15
 
1.5%
리 14
 
1.4%
정 14
 
1.4%
장 13
 
1.3%
우 13
 
1.3%
Other values (258) 793
81.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 955
97.6%
Open Punctuation 6
 
0.6%
Close Punctuation 6
 
0.6%
Decimal Number 6
 
0.6%
Space Separator 5
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
점 41
 
4.3%
가 22
 
2.3%
한 20
 
2.1%
전 18
 
1.9%
아 15
 
1.6%
주 15
 
1.6%
리 14
 
1.5%
정 14
 
1.5%
장 13
 
1.4%
우 13
 
1.4%
Other values (251) 770
80.6%
Decimal Number
ValueCountFrequency (%)
1 2
33.3%
9 2
33.3%
2 1
16.7%
0 1
16.7%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%
Space Separator
ValueCountFrequency (%)
5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 955
97.6%
Common 23
 
2.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
점 41
 
4.3%
가 22
 
2.3%
한 20
 
2.1%
전 18
 
1.9%
아 15
 
1.6%
주 15
 
1.6%
리 14
 
1.5%
정 14
 
1.5%
장 13
 
1.4%
우 13
 
1.4%
Other values (251) 770
80.6%
Common
ValueCountFrequency (%)
( 6
26.1%
) 6
26.1%
5
21.7%
1 2
 
8.7%
9 2
 
8.7%
2 1
 
4.3%
0 1
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 955
97.6%
ASCII 23
 
2.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
점 41
 
4.3%
가 22
 
2.3%
한 20
 
2.1%
전 18
 
1.9%
아 15
 
1.6%
주 15
 
1.6%
리 14
 
1.5%
정 14
 
1.5%
장 13
 
1.4%
우 13
 
1.4%
Other values (251) 770
80.6%
ASCII
ValueCountFrequency (%)
( 6
26.1%
) 6
26.1%
5
21.7%
1 2
 
8.7%
9 2
 
8.7%
2 1
 
4.3%
0 1
 
4.3%

전화번호
Text

MISSING 

Distinct151
Distinct (%)100.0%
Missing11
Missing (%)6.8%
Memory size1.4 KiB
2024-03-15T05:49:51.493290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters1812
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

Unique151 ?
Unique (%)100.0%

Sample

1st row063-284-0982
2nd row063-275-8811
3rd row063-246-0592
4th row063-255-1415
5th row063-246-2585
ValueCountFrequency (%)
063-212-1475 1
 
0.7%
063-241-5000 1
 
0.7%
063-273-3392 1
 
0.7%
063-285-3838 1
 
0.7%
063-241-4447 1
 
0.7%
063-224-2999 1
 
0.7%
063-227-8052 1
 
0.7%
063-288-4578 1
 
0.7%
063-254-7986 1
 
0.7%
063-251-9207 1
 
0.7%
Other values (141) 141
93.4%
2024-03-15T05:49:53.065026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 302
16.7%
2 290
16.0%
0 242
13.4%
3 238
13.1%
6 205
11.3%
8 104
 
5.7%
5 99
 
5.5%
1 95
 
5.2%
4 84
 
4.6%
7 82
 
4.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1510
83.3%
Dash Punctuation 302
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 290
19.2%
0 242
16.0%
3 238
15.8%
6 205
13.6%
8 104
 
6.9%
5 99
 
6.6%
1 95
 
6.3%
4 84
 
5.6%
7 82
 
5.4%
9 71
 
4.7%
Dash Punctuation
ValueCountFrequency (%)
- 302
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1812
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 302
16.7%
2 290
16.0%
0 242
13.4%
3 238
13.1%
6 205
11.3%
8 104
 
5.7%
5 99
 
5.5%
1 95
 
5.2%
4 84
 
4.6%
7 82
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1812
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 302
16.7%
2 290
16.0%
0 242
13.4%
3 238
13.1%
6 205
11.3%
8 104
 
5.7%
5 99
 
5.5%
1 95
 
5.2%
4 84
 
4.6%
7 82
 
4.5%

도로명주소
Text

UNIQUE 

Distinct162
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
2024-03-15T05:49:54.592110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length26
Mean length23.975309
Min length21

Characters and Unicode

Total characters3884
Distinct characters149
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

Unique162 ?
Unique (%)100.0%

Sample

1st row전북특별자치도 전주시 완산구 전라감영5길 17
2nd row전북특별자치도 전주시 덕진구 권삼득로 247
3rd row전북특별자치도 전주시 덕진구 건산로 223
4th row전북특별자치도 전주시 덕진구 동부대로 1051
5th row전북특별자치도 전주시 덕진구 동가재미3길 50
ValueCountFrequency (%)
전북특별자치도 162
20.0%
전주시 162
20.0%
완산구 88
 
10.9%
덕진구 74
 
9.1%
동부대로 8
 
1.0%
백제대로 7
 
0.9%
홍산남로 6
 
0.7%
기린대로 6
 
0.7%
송천중앙로 6
 
0.7%
5 4
 
0.5%
Other values (236) 287
35.4%
2024-03-15T05:49:56.538748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
648
16.7%
전 336
 
8.7%
북 166
 
4.3%
자 164
 
4.2%
주 164
 
4.2%
구 163
 
4.2%
시 163
 
4.2%
특 162
 
4.2%
별 162
 
4.2%
치 162
 
4.2%
Other values (139) 1594
41.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2702
69.6%
Space Separator 648
 
16.7%
Decimal Number 488
 
12.6%
Dash Punctuation 46
 
1.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
전 336
 
12.4%
북 166
 
6.1%
자 164
 
6.1%
주 164
 
6.1%
구 163
 
6.0%
시 163
 
6.0%
특 162
 
6.0%
별 162
 
6.0%
치 162
 
6.0%
도 162
 
6.0%
Other values (127) 898
33.2%
Decimal Number
ValueCountFrequency (%)
1 111
22.7%
2 77
15.8%
3 62
12.7%
5 42
 
8.6%
4 40
 
8.2%
6 36
 
7.4%
0 33
 
6.8%
7 31
 
6.4%
9 29
 
5.9%
8 27
 
5.5%
Space Separator
ValueCountFrequency (%)
648
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 46
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2702
69.6%
Common 1182
30.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
전 336
 
12.4%
북 166
 
6.1%
자 164
 
6.1%
주 164
 
6.1%
구 163
 
6.0%
시 163
 
6.0%
특 162
 
6.0%
별 162
 
6.0%
치 162
 
6.0%
도 162
 
6.0%
Other values (127) 898
33.2%
Common
ValueCountFrequency (%)
648
54.8%
1 111
 
9.4%
2 77
 
6.5%
3 62
 
5.2%
- 46
 
3.9%
5 42
 
3.6%
4 40
 
3.4%
6 36
 
3.0%
0 33
 
2.8%
7 31
 
2.6%
Other values (2) 56
 
4.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2702
69.6%
ASCII 1182
30.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
648
54.8%
1 111
 
9.4%
2 77
 
6.5%
3 62
 
5.2%
- 46
 
3.9%
5 42
 
3.6%
4 40
 
3.4%
6 36
 
3.0%
0 33
 
2.8%
7 31
 
2.6%
Other values (2) 56
 
4.7%
Hangul
ValueCountFrequency (%)
전 336
 
12.4%
북 166
 
6.1%
자 164
 
6.1%
주 164
 
6.1%
구 163
 
6.0%
시 163
 
6.0%
특 162
 
6.0%
별 162
 
6.0%
치 162
 
6.0%
도 162
 
6.0%
Other values (127) 898
33.2%

지번주소
Text

UNIQUE 

Distinct162
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
2024-03-15T05:49:58.062296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length29
Mean length26.895062
Min length22

Characters and Unicode

Total characters4357
Distinct characters66
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

Unique162 ?
Unique (%)100.0%

Sample

1st row전북특별자치도 전주시 완산구 중앙동3가 80
2nd row전북특별자치도 전주시 덕진구 금암동 728-215
3rd row전북특별자치도 전주시 덕진구 인후동1가 401-1
4th row전북특별자치도 전주시 덕진구 송천동2가 산 23-3
5th row전북특별자치도 전주시 덕진구 인후동1가 850-1
ValueCountFrequency (%)
전북특별자치도 162
20.0%
전주시 162
20.0%
완산구 88
 
10.9%
덕진구 74
 
9.1%
효자동3가 20
 
2.5%
송천동2가 14
 
1.7%
중화산동2가 11
 
1.4%
효자동2가 11
 
1.4%
인후동1가 10
 
1.2%
금암동 7
 
0.9%
Other values (201) 252
31.1%
2024-03-15T05:50:01.132961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
649
 
14.9%
전 331
 
7.6%
자 194
 
4.5%
1 174
 
4.0%
북 163
 
3.7%
동 163
 
3.7%
특 162
 
3.7%
별 162
 
3.7%
치 162
 
3.7%
도 162
 
3.7%
Other values (56) 2035
46.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2731
62.7%
Decimal Number 826
 
19.0%
Space Separator 649
 
14.9%
Dash Punctuation 151
 
3.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
전 331
 
12.1%
자 194
 
7.1%
북 163
 
6.0%
동 163
 
6.0%
특 162
 
5.9%
별 162
 
5.9%
치 162
 
5.9%
도 162
 
5.9%
주 162
 
5.9%
시 162
 
5.9%
Other values (44) 908
33.2%
Decimal Number
ValueCountFrequency (%)
1 174
21.1%
2 161
19.5%
3 109
13.2%
4 70
8.5%
5 68
 
8.2%
7 58
 
7.0%
9 55
 
6.7%
6 52
 
6.3%
8 49
 
5.9%
0 30
 
3.6%
Space Separator
ValueCountFrequency (%)
649
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 151
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2731
62.7%
Common 1626
37.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
전 331
 
12.1%
자 194
 
7.1%
북 163
 
6.0%
동 163
 
6.0%
특 162
 
5.9%
별 162
 
5.9%
치 162
 
5.9%
도 162
 
5.9%
주 162
 
5.9%
시 162
 
5.9%
Other values (44) 908
33.2%
Common
ValueCountFrequency (%)
649
39.9%
1 174
 
10.7%
2 161
 
9.9%
- 151
 
9.3%
3 109
 
6.7%
4 70
 
4.3%
5 68
 
4.2%
7 58
 
3.6%
9 55
 
3.4%
6 52
 
3.2%
Other values (2) 79
 
4.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2731
62.7%
ASCII 1626
37.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
649
39.9%
1 174
 
10.7%
2 161
 
9.9%
- 151
 
9.3%
3 109
 
6.7%
4 70
 
4.3%
5 68
 
4.2%
7 58
 
3.6%
9 55
 
3.4%
6 52
 
3.2%
Other values (2) 79
 
4.9%
Hangul
ValueCountFrequency (%)
전 331
 
12.1%
자 194
 
7.1%
북 163
 
6.0%
동 163
 
6.0%
특 162
 
5.9%
별 162
 
5.9%
치 162
 
5.9%
도 162
 
5.9%
주 162
 
5.9%
시 162
 
5.9%
Other values (44) 908
33.2%

위도
Real number (ℝ)

UNIQUE 

Distinct162
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.829166
Minimum35.779246
Maximum35.893639
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2024-03-15T05:50:01.692131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.779246
5-th percentile35.790892
Q135.815986
median35.825515
Q335.844729
95-th percentile35.869742
Maximum35.893639
Range0.11439369
Interquartile range (IQR)0.02874297

Descriptive statistics

Standard deviation0.023871114
Coefficient of variation (CV)0.0006662481
Kurtosis-0.44025828
Mean35.829166
Median Absolute Deviation (MAD)0.011049865
Skewness0.25814393
Sum5804.3249
Variance0.00056983006
MonotonicityNot monotonic
2024-03-15T05:50:02.461971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35.81707161 1
 
0.6%
35.81995016 1
 
0.6%
35.8205657 1
 
0.6%
35.82626755 1
 
0.6%
35.78600197 1
 
0.6%
35.82564697 1
 
0.6%
35.81772973 1
 
0.6%
35.81725609 1
 
0.6%
35.87104162 1
 
0.6%
35.81497375 1
 
0.6%
Other values (152) 152
93.8%
ValueCountFrequency (%)
35.77924562 1
0.6%
35.77972804 1
0.6%
35.78187341 1
0.6%
35.78289563 1
0.6%
35.78600197 1
0.6%
35.78617072 1
0.6%
35.7896153 1
0.6%
35.78970222 1
0.6%
35.79084288 1
0.6%
35.7918315 1
0.6%
ValueCountFrequency (%)
35.89363931 1
0.6%
35.87464848 1
0.6%
35.87229994 1
0.6%
35.87153472 1
0.6%
35.87104162 1
0.6%
35.87099678 1
0.6%
35.870617 1
0.6%
35.87011417 1
0.6%
35.869781 1
0.6%
35.86900238 1
0.6%

경도
Real number (ℝ)

UNIQUE 

Distinct162
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.12879
Minimum127.07061
Maximum127.19394
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2024-03-15T05:50:02.815375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum127.07061
5-th percentile127.10105
Q1127.10975
median127.12289
Q3127.14823
95-th percentile127.17145
Maximum127.19394
Range0.1233333
Interquartile range (IQR)0.038475125

Descriptive statistics

Standard deviation0.024346942
Coefficient of variation (CV)0.00019151399
Kurtosis-0.35072891
Mean127.12879
Median Absolute Deviation (MAD)0.0177329
Skewness0.25717975
Sum20594.864
Variance0.00059277357
MonotonicityNot monotonic
2024-03-15T05:50:03.306087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.145947 1
 
0.6%
127.1046969 1
 
0.6%
127.1482307 1
 
0.6%
127.1458471 1
 
0.6%
127.1115668 1
 
0.6%
127.1656486 1
 
0.6%
127.1176458 1
 
0.6%
127.1175872 1
 
0.6%
127.1588161 1
 
0.6%
127.1487324 1
 
0.6%
Other values (152) 152
93.8%
ValueCountFrequency (%)
127.0706092 1
0.6%
127.0707817 1
0.6%
127.0745372 1
0.6%
127.0751568 1
0.6%
127.0802609 1
0.6%
127.0921333 1
0.6%
127.0933118 1
0.6%
127.09989 1
0.6%
127.1009283 1
0.6%
127.1033699 1
0.6%
ValueCountFrequency (%)
127.1939425 1
0.6%
127.1837559 1
0.6%
127.1769809 1
0.6%
127.1752865 1
0.6%
127.1748982 1
0.6%
127.1741448 1
0.6%
127.1738028 1
0.6%
127.172616 1
0.6%
127.171476 1
0.6%
127.1709802 1
0.6%

영업상태명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
영업
162 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업 162
100.0%

Length

2024-03-15T05:50:03.748484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T05:50:04.161415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업 162
100.0%

음식의유형
Categorical

IMBALANCE 

Distinct7
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
한식
134 
일식
 
10
중식
 
8
양식
 
3
경양식
 
3
Other values (2)
 
4

Length

Max length3
Median length2
Mean length2.0308642
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
한식 134
82.7%
일식 10
 
6.2%
중식 8
 
4.9%
양식 3
 
1.9%
경양식 3
 
1.9%
기타 2
 
1.2%
뷔페식 2
 
1.2%

Length

2024-03-15T05:50:04.540068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T05:50:04.944830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
한식 134
82.7%
일식 10
 
6.2%
중식 8
 
4.9%
양식 3
 
1.9%
경양식 3
 
1.9%
기타 2
 
1.2%
뷔페식 2
 
1.2%

주된음식종류
Text

Distinct111
Distinct (%)68.5%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
2024-03-15T05:50:06.852022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length9
Mean length4.2901235
Min length1

Characters and Unicode

Total characters695
Distinct characters139
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique93 ?
Unique (%)57.4%

Sample

1st row비빔밥
2nd row약선음식
3rd row돼지고기 등
4th row도토리묵밥
5th row소바
ValueCountFrequency (%)
비빔밥 10
 
5.6%
냉면 7
 
3.9%
갈비탕 6
 
3.3%
한정식 6
 
3.3%
콩나물국밥 6
 
3.3%
소고기구이 5
 
2.8%
돼지갈비 5
 
2.8%
소고기 5
 
2.8%
짜장면 4
 
2.2%
삼겹살 4
 
2.2%
Other values (99) 122
67.8%
2024-03-15T05:50:08.259397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
비 33
 
4.7%
탕 33
 
4.7%
, 29
 
4.2%
밥 28
 
4.0%
갈 19
 
2.7%
구 19
 
2.7%
18
 
2.6%
이 18
 
2.6%
고 17
 
2.4%
기 17
 
2.4%
Other values (129) 464
66.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 648
93.2%
Other Punctuation 29
 
4.2%
Space Separator 18
 
2.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
비 33
 
5.1%
탕 33
 
5.1%
밥 28
 
4.3%
갈 19
 
2.9%
구 19
 
2.9%
이 18
 
2.8%
고 17
 
2.6%
기 17
 
2.6%
장 15
 
2.3%
빔 14
 
2.2%
Other values (127) 435
67.1%
Other Punctuation
ValueCountFrequency (%)
, 29
100.0%
Space Separator
ValueCountFrequency (%)
18
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 648
93.2%
Common 47
 
6.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
비 33
 
5.1%
탕 33
 
5.1%
밥 28
 
4.3%
갈 19
 
2.9%
구 19
 
2.9%
이 18
 
2.8%
고 17
 
2.6%
기 17
 
2.6%
장 15
 
2.3%
빔 14
 
2.2%
Other values (127) 435
67.1%
Common
ValueCountFrequency (%)
, 29
61.7%
18
38.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 648
93.2%
ASCII 47
 
6.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
비 33
 
5.1%
탕 33
 
5.1%
밥 28
 
4.3%
갈 19
 
2.9%
구 19
 
2.9%
이 18
 
2.8%
고 17
 
2.6%
기 17
 
2.6%
장 15
 
2.3%
빔 14
 
2.2%
Other values (127) 435
67.1%
ASCII
ValueCountFrequency (%)
, 29
61.7%
18
38.3%

Interactions

2024-03-15T05:49:47.499360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:49:47.092313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:49:47.651587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T05:49:47.342026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-15T05:50:08.420880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도음식의유형
위도1.0000.6880.000
경도0.6881.0000.000
음식의유형0.0000.0001.000
2024-03-15T05:50:08.570998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도음식의유형
위도1.0000.1920.000
경도0.1921.0000.000
음식의유형0.0000.0001.000

Missing values

2024-03-15T05:49:47.881615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-15T05:49:48.164593image/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

업소명전화번호도로명주소지번주소위도경도영업상태명음식의유형주된음식종류
0가족회관063-284-0982전북특별자치도 전주시 완산구 전라감영5길 17전북특별자치도 전주시 완산구 중앙동3가 8035.817072127.145947영업한식비빔밥
1감로헌063-275-8811전북특별자치도 전주시 덕진구 권삼득로 247전북특별자치도 전주시 덕진구 금암동 728-21535.839425127.132826영업한식약선음식
2감성9091돼지전주아중점063-246-0592전북특별자치도 전주시 덕진구 건산로 223전북특별자치도 전주시 덕진구 인후동1가 401-135.834378127.161569영업한식돼지고기 등
3건지산도토리063-255-1415전북특별자치도 전주시 덕진구 동부대로 1051전북특별자치도 전주시 덕진구 송천동2가 산 23-335.869002127.132151영업한식도토리묵밥
4겐돈소바063-246-2585전북특별자치도 전주시 덕진구 동가재미3길 50전북특별자치도 전주시 덕진구 인후동1가 850-135.834783127.165835영업일식소바
5고궁063-251-3211전북특별자치도 전주시 덕진구 송천중앙로 33전북특별자치도 전주시 덕진구 덕진동2가 168-935.850102127.119419영업한식전주비빔밥
6고궁담063-228-3711전북특별자치도 전주시 완산구 유연로 170전북특별자치도 전주시 완산구 효자동3가 1627-135.824911127.10402영업한식비빔밥
7고귀063-275-9595전북특별자치도 전주시 덕진구 송천로 1전북특별자치도 전주시 덕진구 송천동1가 292-735.852983127.118903영업한식소고기 구이
8고기명가수라간063-212-1475전북특별자치도 전주시 덕진구 기린대로 1016전북특별자치도 전주시 덕진구 여의동 693-435.867692127.075157영업한식소고기구이
9고려옥063-245-5002전북특별자치도 전주시 덕진구 동부대로 429전북특별자치도 전주시 덕진구 우아동2가 932-435.830304127.174898영업한식콩나물국밥
업소명전화번호도로명주소지번주소위도경도영업상태명음식의유형주된음식종류
152해이루063-272-1829전북특별자치도 전주시 덕진구 명륜5길 9전북특별자치도 전주시 덕진구 덕진동1가 1277-1435.84371127.125311영업한식감자탕
153현대옥송천농수산시장점063-276-0099전북특별자치도 전주시 덕진구 송천중앙로 233-20전북특별자치도 전주시 덕진구 송천동2가 49335.868013127.119067영업한식콩나물국밥
154형제골뼈다귀순대국063-225-8880전북특별자치도 전주시 완산구 장승배기로 154전북특별자치도 전주시 완산구 평화동2가 842-935.794591127.129818영업한식순대국밥
155호림이네063-285-4007전북특별자치도 전주시 완산구 춘향로 5152전북특별자치도 전주시 완산구 색장동 42935.798513127.183756영업한식한정식
156호성갈비063-254-5293전북특별자치도 전주시 덕진구 초당길 11전북특별자치도 전주시 덕진구 호성동1가 564-135.866237127.149899영업한식오리코스요리
157호순이감자탕063-221-2489전북특별자치도 전주시 완산구 강변로 78전북특별자치도 전주시 완산구 삼천동1가 284-135.79851127.110049영업한식감자탕
158화심장어아중점063-245-6592전북특별자치도 전주시 덕진구 인교9길 21-14전북특별자치도 전주시 덕진구 우아동1가 1116-935.827026127.175286영업한식장어구이
159황씨네대가추어탕063-255-3773전북특별자치도 전주시 덕진구 송천로 47전북특별자치도 전주시 덕진구 송천동1가 326-235.857477127.118028영업한식추어탕
160효자동아귀찜063-236-4642전북특별자치도 전주시 완산구 바우배기2길 23전북특별자치도 전주시 완산구 효자동2가 1236-435.817005127.104292영업한식아구찜
161흑두부이야기063-273-2332전북특별자치도 전주시 완산구 서곡2길 30-19전북특별자치도 전주시 완산구 효자동3가 1470-135.833034127.103506영업한식흑두부보쌈, 전골