Overview

Dataset statistics

Number of variables14
Number of observations314
Missing cells351
Missing cells (%)8.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory34.8 KiB
Average record size in memory113.4 B

Variable types

Numeric1
Categorical5
Text8

Alerts

공개여부 has constant value ""Constant
작성일 has constant value ""Constant
갱신주기 has constant value ""Constant
순번 is highly overall correlated with 시군명High correlation
시군명 is highly overall correlated with 순번High correlation
업종 is highly imbalanced (58.6%)Imbalance
대표자 has 6 (1.9%) missing valuesMissing
전화번호 has 8 (2.5%) missing valuesMissing
품목2 has 80 (25.5%) missing valuesMissing
품목3 has 196 (62.4%) missing valuesMissing
영업시간 has 61 (19.4%) missing valuesMissing
순번 has unique valuesUnique

Reproduction

Analysis started2024-03-14 00:54:45.673714
Analysis finished2024-03-14 00:54:47.035703
Duration1.36 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct314
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean157.5
Minimum1
Maximum314
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size2.9 KiB
2024-03-14T09:54:47.098982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile16.65
Q179.25
median157.5
Q3235.75
95-th percentile298.35
Maximum314
Range313
Interquartile range (IQR)156.5

Descriptive statistics

Standard deviation90.788215
Coefficient of variation (CV)0.57643311
Kurtosis-1.2
Mean157.5
Median Absolute Deviation (MAD)78.5
Skewness0
Sum49455
Variance8242.5
MonotonicityStrictly increasing
2024-03-14T09:54:47.208270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.3%
208 1
 
0.3%
215 1
 
0.3%
214 1
 
0.3%
213 1
 
0.3%
212 1
 
0.3%
211 1
 
0.3%
210 1
 
0.3%
209 1
 
0.3%
207 1
 
0.3%
Other values (304) 304
96.8%
ValueCountFrequency (%)
1 1
0.3%
2 1
0.3%
3 1
0.3%
4 1
0.3%
5 1
0.3%
6 1
0.3%
7 1
0.3%
8 1
0.3%
9 1
0.3%
10 1
0.3%
ValueCountFrequency (%)
314 1
0.3%
313 1
0.3%
312 1
0.3%
311 1
0.3%
310 1
0.3%
309 1
0.3%
308 1
0.3%
307 1
0.3%
306 1
0.3%
305 1
0.3%

시군명
Categorical

HIGH CORRELATION 

Distinct14
Distinct (%)4.5%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
전주시
42 
정읍시
33 
고창군
31 
완주군
31 
무주군
30 
Other values (9)
147 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
전주시 42
13.4%
정읍시 33
10.5%
고창군 31
9.9%
완주군 31
9.9%
무주군 30
9.6%
군산시 29
9.2%
남원시 23
7.3%
김제시 20
6.4%
장수군 19
6.1%
익산시 17
5.4%
Other values (4) 39
12.4%

Length

2024-03-14T09:54:47.321564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
전주시 42
13.4%
정읍시 33
10.5%
고창군 31
9.9%
완주군 31
9.9%
무주군 30
9.6%
군산시 29
9.2%
남원시 23
7.3%
김제시 20
6.4%
장수군 19
6.1%
익산시 17
5.4%
Other values (4) 39
12.4%

업소명
Text

Distinct310
Distinct (%)98.7%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
2024-03-14T09:54:47.647152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length11
Mean length4.7675159
Min length2

Characters and Unicode

Total characters1497
Distinct characters313
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

Unique306 ?
Unique (%)97.5%

Sample

1st row이래면옥
2nd row제일크리너스샵
3rd row중본이쟁반짜장
4th row만나별미
5th row기린로가정식백반
ValueCountFrequency (%)
전주식당 2
 
0.6%
전원식당 2
 
0.6%
미용실 2
 
0.6%
지리산 2
 
0.6%
전주식토속콩나물해장국 2
 
0.6%
목살집 2
 
0.6%
행복한농부 1
 
0.3%
이래면옥 1
 
0.3%
청산 1
 
0.3%
부자회관 1
 
0.3%
Other values (311) 311
95.1%
2024-03-14T09:54:48.042982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
식 66
 
4.4%
당 52
 
3.5%
미 44
 
2.9%
용 35
 
2.3%
이 33
 
2.2%
원 26
 
1.7%
실 26
 
1.7%
가 25
 
1.7%
국 24
 
1.6%
관 23
 
1.5%
Other values (303) 1143
76.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1475
98.5%
Space Separator 14
 
0.9%
Decimal Number 6
 
0.4%
Open Punctuation 1
 
0.1%
Close Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
식 66
 
4.5%
당 52
 
3.5%
미 44
 
3.0%
용 35
 
2.4%
이 33
 
2.2%
원 26
 
1.8%
실 26
 
1.8%
가 25
 
1.7%
국 24
 
1.6%
관 23
 
1.6%
Other values (296) 1121
76.0%
Decimal Number
ValueCountFrequency (%)
0 2
33.3%
2 2
33.3%
5 1
16.7%
1 1
16.7%
Space Separator
ValueCountFrequency (%)
14
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1475
98.5%
Common 22
 
1.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
식 66
 
4.5%
당 52
 
3.5%
미 44
 
3.0%
용 35
 
2.4%
이 33
 
2.2%
원 26
 
1.8%
실 26
 
1.8%
가 25
 
1.7%
국 24
 
1.6%
관 23
 
1.6%
Other values (296) 1121
76.0%
Common
ValueCountFrequency (%)
14
63.6%
0 2
 
9.1%
2 2
 
9.1%
( 1
 
4.5%
) 1
 
4.5%
5 1
 
4.5%
1 1
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1475
98.5%
ASCII 22
 
1.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
식 66
 
4.5%
당 52
 
3.5%
미 44
 
3.0%
용 35
 
2.4%
이 33
 
2.2%
원 26
 
1.8%
실 26
 
1.8%
가 25
 
1.7%
국 24
 
1.6%
관 23
 
1.6%
Other values (296) 1121
76.0%
ASCII
ValueCountFrequency (%)
14
63.6%
0 2
 
9.1%
2 2
 
9.1%
( 1
 
4.5%
) 1
 
4.5%
5 1
 
4.5%
1 1
 
4.5%

대표자
Text

MISSING 

Distinct300
Distinct (%)97.4%
Missing6
Missing (%)1.9%
Memory size2.6 KiB
2024-03-14T09:54:48.343768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length3
Mean length3.012987
Min length2

Characters and Unicode

Total characters928
Distinct characters148
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

Unique293 ?
Unique (%)95.1%

Sample

1st row최정희
2nd row권기호
3rd row김종복
4th row김혜숙
5th row강정자
ValueCountFrequency (%)
김영숙 3
 
1.0%
김순자 2
 
0.6%
박영애 2
 
0.6%
김민희 2
 
0.6%
이미화 2
 
0.6%
정현자 2
 
0.6%
이영자 2
 
0.6%
한재순 1
 
0.3%
임장미 1
 
0.3%
조순옥 1
 
0.3%
Other values (291) 291
94.2%
2024-03-14T09:54:48.742428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
김 69
 
7.4%
이 56
 
6.0%
순 43
 
4.6%
자 38
 
4.1%
영 38
 
4.1%
정 31
 
3.3%
숙 29
 
3.1%
박 25
 
2.7%
희 23
 
2.5%
옥 17
 
1.8%
Other values (138) 559
60.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 927
99.9%
Space Separator 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 69
 
7.4%
이 56
 
6.0%
순 43
 
4.6%
자 38
 
4.1%
영 38
 
4.1%
정 31
 
3.3%
숙 29
 
3.1%
박 25
 
2.7%
희 23
 
2.5%
옥 17
 
1.8%
Other values (137) 558
60.2%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 927
99.9%
Common 1
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 69
 
7.4%
이 56
 
6.0%
순 43
 
4.6%
자 38
 
4.1%
영 38
 
4.1%
정 31
 
3.3%
숙 29
 
3.1%
박 25
 
2.7%
희 23
 
2.5%
옥 17
 
1.8%
Other values (137) 558
60.2%
Common
ValueCountFrequency (%)
1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 927
99.9%
ASCII 1
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
김 69
 
7.4%
이 56
 
6.0%
순 43
 
4.6%
자 38
 
4.1%
영 38
 
4.1%
정 31
 
3.3%
숙 29
 
3.1%
박 25
 
2.7%
희 23
 
2.5%
옥 17
 
1.8%
Other values (137) 558
60.2%
ASCII
ValueCountFrequency (%)
1
100.0%

업종
Categorical

IMBALANCE 

Distinct18
Distinct (%)5.7%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
한식
219 
이미용업
40 
중식
22 
분식
 
5
미용업
 
5
Other values (13)
23 

Length

Max length6
Median length2
Mean length2.3343949
Min length2

Unique

Unique8 ?
Unique (%)2.5%

Sample

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

Common Values

ValueCountFrequency (%)
한식 219
69.7%
이미용업 40
 
12.7%
중식 22
 
7.0%
분식 5
 
1.6%
미용업 5
 
1.6%
세탁업 5
 
1.6%
목욕업 4
 
1.3%
기타양식 2
 
0.6%
미용 2
 
0.6%
숙박업 2
 
0.6%
Other values (8) 8
 
2.5%

Length

2024-03-14T09:54:48.877537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
한식 219
69.7%
이미용업 40
 
12.7%
중식 22
 
7.0%
분식 5
 
1.6%
미용업 5
 
1.6%
세탁업 5
 
1.6%
목욕업 4
 
1.3%
미용 2
 
0.6%
숙박업 2
 
0.6%
기타양식 2
 
0.6%
Other values (8) 8
 
2.5%

도로명주소
Text

Distinct309
Distinct (%)98.4%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
2024-03-14T09:54:49.150894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length35
Median length23
Mean length14.659236
Min length9

Characters and Unicode

Total characters4603
Distinct characters200
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

Unique305 ?
Unique (%)97.1%

Sample

1st row전주시 완산구 동문길 103
2nd row전주시 덕진구 쪽구름로 19
3rd row전주시 완산구 공북로71
4th row전주시 완산구 거마평로 122
5th row전주시 완산구 기린대로 222
ValueCountFrequency (%)
전주시 42
 
3.7%
완산구 36
 
3.1%
정읍시 33
 
2.9%
완주군 31
 
2.7%
고창군 31
 
2.7%
무주군 30
 
2.6%
군산시 29
 
2.5%
남원시 23
 
2.0%
김제시 20
 
1.7%
장수군 19
 
1.7%
Other values (532) 856
74.4%
2024-03-14T09:54:49.517347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
846
 
18.4%
1 223
 
4.8%
로 204
 
4.4%
군 180
 
3.9%
시 177
 
3.8%
주 137
 
3.0%
2 120
 
2.6%
길 120
 
2.6%
산 116
 
2.5%
읍 114
 
2.5%
Other values (190) 2366
51.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2736
59.4%
Decimal Number 892
 
19.4%
Space Separator 846
 
18.4%
Dash Punctuation 76
 
1.7%
Open Punctuation 24
 
0.5%
Close Punctuation 24
 
0.5%
Other Punctuation 5
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 204
 
7.5%
군 180
 
6.6%
시 177
 
6.5%
주 137
 
5.0%
길 120
 
4.4%
산 116
 
4.2%
읍 114
 
4.2%
면 89
 
3.3%
무 74
 
2.7%
동 73
 
2.7%
Other values (174) 1452
53.1%
Decimal Number
ValueCountFrequency (%)
1 223
25.0%
2 120
13.5%
3 100
11.2%
4 91
10.2%
6 68
 
7.6%
7 65
 
7.3%
9 63
 
7.1%
8 61
 
6.8%
5 58
 
6.5%
0 43
 
4.8%
Other Punctuation
ValueCountFrequency (%)
, 3
60.0%
* 2
40.0%
Space Separator
ValueCountFrequency (%)
846
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 76
100.0%
Open Punctuation
ValueCountFrequency (%)
( 24
100.0%
Close Punctuation
ValueCountFrequency (%)
) 24
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2736
59.4%
Common 1867
40.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 204
 
7.5%
군 180
 
6.6%
시 177
 
6.5%
주 137
 
5.0%
길 120
 
4.4%
산 116
 
4.2%
읍 114
 
4.2%
면 89
 
3.3%
무 74
 
2.7%
동 73
 
2.7%
Other values (174) 1452
53.1%
Common
ValueCountFrequency (%)
846
45.3%
1 223
 
11.9%
2 120
 
6.4%
3 100
 
5.4%
4 91
 
4.9%
- 76
 
4.1%
6 68
 
3.6%
7 65
 
3.5%
9 63
 
3.4%
8 61
 
3.3%
Other values (6) 154
 
8.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2736
59.4%
ASCII 1867
40.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
846
45.3%
1 223
 
11.9%
2 120
 
6.4%
3 100
 
5.4%
4 91
 
4.9%
- 76
 
4.1%
6 68
 
3.6%
7 65
 
3.5%
9 63
 
3.4%
8 61
 
3.3%
Other values (6) 154
 
8.2%
Hangul
ValueCountFrequency (%)
로 204
 
7.5%
군 180
 
6.6%
시 177
 
6.5%
주 137
 
5.0%
길 120
 
4.4%
산 116
 
4.2%
읍 114
 
4.2%
면 89
 
3.3%
무 74
 
2.7%
동 73
 
2.7%
Other values (174) 1452
53.1%

전화번호
Text

MISSING 

Distinct306
Distinct (%)100.0%
Missing8
Missing (%)2.5%
Memory size2.6 KiB
2024-03-14T09:54:49.801430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length8
Mean length9.748366
Min length8

Characters and Unicode

Total characters2983
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique306 ?
Unique (%)100.0%

Sample

1st row288-6644
2nd row211-2177
3rd row271-2223
4th row224-9529
5th row285-1005
ValueCountFrequency (%)
287-5589 1
 
0.3%
351-5520 1
 
0.3%
351-7533 1
 
0.3%
353-0102 1
 
0.3%
352-2862 1
 
0.3%
352-1318 1
 
0.3%
352-0068 1
 
0.3%
353-5777 1
 
0.3%
353-5292 1
 
0.3%
351-2296 1
 
0.3%
Other values (296) 296
96.7%
2024-03-14T09:54:50.157528image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 438
14.7%
3 431
14.4%
6 363
12.2%
2 322
10.8%
5 302
10.1%
0 289
9.7%
4 225
7.5%
8 197
6.6%
1 168
 
5.6%
7 128
 
4.3%
Other values (2) 120
 
4.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2535
85.0%
Dash Punctuation 438
 
14.7%
Space Separator 10
 
0.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 431
17.0%
6 363
14.3%
2 322
12.7%
5 302
11.9%
0 289
11.4%
4 225
8.9%
8 197
7.8%
1 168
 
6.6%
7 128
 
5.0%
9 110
 
4.3%
Dash Punctuation
ValueCountFrequency (%)
- 438
100.0%
Space Separator
ValueCountFrequency (%)
10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2983
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 438
14.7%
3 431
14.4%
6 363
12.2%
2 322
10.8%
5 302
10.1%
0 289
9.7%
4 225
7.5%
8 197
6.6%
1 168
 
5.6%
7 128
 
4.3%
Other values (2) 120
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2983
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 438
14.7%
3 431
14.4%
6 363
12.2%
2 322
10.8%
5 302
10.1%
0 289
9.7%
4 225
7.5%
8 197
6.6%
1 168
 
5.6%
7 128
 
4.3%
Other values (2) 120
 
4.0%

품목1
Text

Distinct139
Distinct (%)44.3%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
2024-03-14T09:54:50.397772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length12
Mean length3.9681529
Min length1

Characters and Unicode

Total characters1246
Distinct characters172
Distinct categories8 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique95 ?
Unique (%)30.3%

Sample

1st row갈비탕
2nd row양복
3rd row짜장면
4th row백반
5th row비빔밥
ValueCountFrequency (%)
백반 33
 
10.2%
커트 22
 
6.8%
김치찌개 17
 
5.3%
삼겹살(200g 13
 
4.0%
짜장면 8
 
2.5%
삼겹살 8
 
2.5%
자장면 7
 
2.2%
국수 7
 
2.2%
컷트 6
 
1.9%
이발 5
 
1.5%
Other values (130) 197
61.0%
2024-03-14T09:54:50.743324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
국 53
 
4.3%
반 47
 
3.8%
0 46
 
3.7%
백 45
 
3.6%
밥 40
 
3.2%
장 37
 
3.0%
트 34
 
2.7%
개 33
 
2.6%
찌 32
 
2.6%
삼 30
 
2.4%
Other values (162) 849
68.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1067
85.6%
Decimal Number 76
 
6.1%
Close Punctuation 30
 
2.4%
Open Punctuation 29
 
2.3%
Lowercase Letter 24
 
1.9%
Space Separator 12
 
1.0%
Other Punctuation 6
 
0.5%
Math Symbol 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
국 53
 
5.0%
반 47
 
4.4%
백 45
 
4.2%
밥 40
 
3.7%
장 37
 
3.5%
트 34
 
3.2%
개 33
 
3.1%
찌 32
 
3.0%
삼 30
 
2.8%
커 27
 
2.5%
Other values (150) 689
64.6%
Decimal Number
ValueCountFrequency (%)
0 46
60.5%
2 22
28.9%
3 3
 
3.9%
1 2
 
2.6%
5 2
 
2.6%
8 1
 
1.3%
Close Punctuation
ValueCountFrequency (%)
) 30
100.0%
Open Punctuation
ValueCountFrequency (%)
( 29
100.0%
Lowercase Letter
ValueCountFrequency (%)
g 24
100.0%
Space Separator
ValueCountFrequency (%)
12
100.0%
Other Punctuation
ValueCountFrequency (%)
, 6
100.0%
Math Symbol
ValueCountFrequency (%)
+ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1066
85.6%
Common 155
 
12.4%
Latin 24
 
1.9%
Han 1
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
국 53
 
5.0%
반 47
 
4.4%
백 45
 
4.2%
밥 40
 
3.8%
장 37
 
3.5%
트 34
 
3.2%
개 33
 
3.1%
찌 32
 
3.0%
삼 30
 
2.8%
커 27
 
2.5%
Other values (149) 688
64.5%
Common
ValueCountFrequency (%)
0 46
29.7%
) 30
19.4%
( 29
18.7%
2 22
14.2%
12
 
7.7%
, 6
 
3.9%
3 3
 
1.9%
+ 2
 
1.3%
1 2
 
1.3%
5 2
 
1.3%
Latin
ValueCountFrequency (%)
g 24
100.0%
Han
ValueCountFrequency (%)
大 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1066
85.6%
ASCII 179
 
14.4%
CJK 1
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
국 53
 
5.0%
반 47
 
4.4%
백 45
 
4.2%
밥 40
 
3.8%
장 37
 
3.5%
트 34
 
3.2%
개 33
 
3.1%
찌 32
 
3.0%
삼 30
 
2.8%
커 27
 
2.5%
Other values (149) 688
64.5%
ASCII
ValueCountFrequency (%)
0 46
25.7%
) 30
16.8%
( 29
16.2%
g 24
13.4%
2 22
12.3%
12
 
6.7%
, 6
 
3.4%
3 3
 
1.7%
+ 2
 
1.1%
1 2
 
1.1%
Other values (2) 3
 
1.7%
CJK
ValueCountFrequency (%)
大 1
100.0%

품목2
Text

MISSING 

Distinct120
Distinct (%)51.3%
Missing80
Missing (%)25.5%
Memory size2.6 KiB
2024-03-14T09:54:50.961752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length11
Mean length3.9487179
Min length2

Characters and Unicode

Total characters924
Distinct characters172
Distinct categories7 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique90 ?
Unique (%)38.5%

Sample

1st row비빔냉면
2nd row바지
3rd row짬뽕
4th row콩나물국밥
5th row김치찌개
ValueCountFrequency (%)
파마 18
 
7.5%
짬뽕 14
 
5.9%
김치찌개 11
 
4.6%
된장찌개 8
 
3.3%
청국장 7
 
2.9%
삼겹살(200g 6
 
2.5%
국수 6
 
2.5%
갈비탕 6
 
2.5%
삼겹살 6
 
2.5%
백반 5
 
2.1%
Other values (106) 152
63.6%
2024-03-14T09:54:51.265079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
국 47
 
5.1%
비 31
 
3.4%
밥 26
 
2.8%
0 26
 
2.8%
26
 
2.8%
개 25
 
2.7%
( 23
 
2.5%
) 23
 
2.5%
장 23
 
2.5%
수 22
 
2.4%
Other values (162) 652
70.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 790
85.5%
Decimal Number 46
 
5.0%
Space Separator 26
 
2.8%
Open Punctuation 23
 
2.5%
Close Punctuation 23
 
2.5%
Lowercase Letter 14
 
1.5%
Math Symbol 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
국 47
 
5.9%
비 31
 
3.9%
밥 26
 
3.3%
개 25
 
3.2%
장 23
 
2.9%
수 22
 
2.8%
찌 22
 
2.8%
탕 22
 
2.8%
파 18
 
2.3%
마 18
 
2.3%
Other values (150) 536
67.8%
Decimal Number
ValueCountFrequency (%)
0 26
56.5%
2 13
28.3%
1 2
 
4.3%
5 2
 
4.3%
4 1
 
2.2%
3 1
 
2.2%
6 1
 
2.2%
Space Separator
ValueCountFrequency (%)
26
100.0%
Open Punctuation
ValueCountFrequency (%)
( 23
100.0%
Close Punctuation
ValueCountFrequency (%)
) 23
100.0%
Lowercase Letter
ValueCountFrequency (%)
g 14
100.0%
Math Symbol
ValueCountFrequency (%)
+ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 789
85.4%
Common 120
 
13.0%
Latin 14
 
1.5%
Han 1
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
국 47
 
6.0%
비 31
 
3.9%
밥 26
 
3.3%
개 25
 
3.2%
장 23
 
2.9%
수 22
 
2.8%
찌 22
 
2.8%
탕 22
 
2.8%
파 18
 
2.3%
마 18
 
2.3%
Other values (149) 535
67.8%
Common
ValueCountFrequency (%)
0 26
21.7%
26
21.7%
( 23
19.2%
) 23
19.2%
2 13
10.8%
1 2
 
1.7%
5 2
 
1.7%
+ 2
 
1.7%
4 1
 
0.8%
3 1
 
0.8%
Latin
ValueCountFrequency (%)
g 14
100.0%
Han
ValueCountFrequency (%)
大 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 789
85.4%
ASCII 134
 
14.5%
CJK 1
 
0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
국 47
 
6.0%
비 31
 
3.9%
밥 26
 
3.3%
개 25
 
3.2%
장 23
 
2.9%
수 22
 
2.8%
찌 22
 
2.8%
탕 22
 
2.8%
파 18
 
2.3%
마 18
 
2.3%
Other values (149) 535
67.8%
ASCII
ValueCountFrequency (%)
0 26
19.4%
26
19.4%
( 23
17.2%
) 23
17.2%
g 14
10.4%
2 13
9.7%
1 2
 
1.5%
5 2
 
1.5%
+ 2
 
1.5%
4 1
 
0.7%
Other values (2) 2
 
1.5%
CJK
ValueCountFrequency (%)
大 1
100.0%

품목3
Text

MISSING 

Distinct79
Distinct (%)66.9%
Missing196
Missing (%)62.4%
Memory size2.6 KiB
2024-03-14T09:54:51.488183image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length10
Mean length3.9830508
Min length2

Characters and Unicode

Total characters470
Distinct characters125
Distinct categories6 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique59 ?
Unique (%)50.0%

Sample

1st row돼지불고기
2nd row티셔츠
3rd row간짜장
4th row시래기감자탕
5th row새알팥죽
ValueCountFrequency (%)
김치찌개 8
 
6.7%
염색 7
 
5.8%
된장찌개 6
 
5.0%
우동 4
 
3.3%
간짜장 4
 
3.3%
청국장 4
 
3.3%
백반 3
 
2.5%
드라이 3
 
2.5%
티셔츠 2
 
1.7%
새알팥죽 2
 
1.7%
Other values (68) 77
64.2%
2024-03-14T09:54:51.783905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
장 22
 
4.7%
21
 
4.5%
개 19
 
4.0%
국 18
 
3.8%
찌 17
 
3.6%
밥 16
 
3.4%
탕 13
 
2.8%
우 12
 
2.6%
치 11
 
2.3%
비 10
 
2.1%
Other values (115) 311
66.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 418
88.9%
Space Separator 21
 
4.5%
Decimal Number 13
 
2.8%
Open Punctuation 7
 
1.5%
Close Punctuation 7
 
1.5%
Lowercase Letter 4
 
0.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
장 22
 
5.3%
개 19
 
4.5%
국 18
 
4.3%
찌 17
 
4.1%
밥 16
 
3.8%
탕 13
 
3.1%
우 12
 
2.9%
치 11
 
2.6%
비 10
 
2.4%
김 10
 
2.4%
Other values (108) 270
64.6%
Decimal Number
ValueCountFrequency (%)
0 8
61.5%
2 4
30.8%
6 1
 
7.7%
Space Separator
ValueCountFrequency (%)
21
100.0%
Open Punctuation
ValueCountFrequency (%)
( 7
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7
100.0%
Lowercase Letter
ValueCountFrequency (%)
g 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 416
88.5%
Common 48
 
10.2%
Latin 4
 
0.9%
Han 2
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
장 22
 
5.3%
개 19
 
4.6%
국 18
 
4.3%
찌 17
 
4.1%
밥 16
 
3.8%
탕 13
 
3.1%
우 12
 
2.9%
치 11
 
2.6%
비 10
 
2.4%
김 10
 
2.4%
Other values (106) 268
64.4%
Common
ValueCountFrequency (%)
21
43.8%
0 8
 
16.7%
( 7
 
14.6%
) 7
 
14.6%
2 4
 
8.3%
6 1
 
2.1%
Han
ValueCountFrequency (%)
小 1
50.0%
大 1
50.0%
Latin
ValueCountFrequency (%)
g 4
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 416
88.5%
ASCII 52
 
11.1%
CJK 2
 
0.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
장 22
 
5.3%
개 19
 
4.6%
국 18
 
4.3%
찌 17
 
4.1%
밥 16
 
3.8%
탕 13
 
3.1%
우 12
 
2.9%
치 11
 
2.6%
비 10
 
2.4%
김 10
 
2.4%
Other values (106) 268
64.4%
ASCII
ValueCountFrequency (%)
21
40.4%
0 8
 
15.4%
( 7
 
13.5%
) 7
 
13.5%
g 4
 
7.7%
2 4
 
7.7%
6 1
 
1.9%
CJK
ValueCountFrequency (%)
小 1
50.0%
大 1
50.0%

영업시간
Text

MISSING 

Distinct82
Distinct (%)32.4%
Missing61
Missing (%)19.4%
Memory size2.6 KiB
2024-03-14T09:54:52.064466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length11
Mean length11
Min length3

Characters and Unicode

Total characters2783
Distinct characters18
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique47 ?
Unique (%)18.6%

Sample

1st row11:00~21:00
2nd row09:00~20:30
3rd row10:30~20:30
4th row09:00~21:00
5th row11:30~18:30
ValueCountFrequency (%)
11:00~22:00 35
 
13.7%
11:00~21:00 21
 
8.2%
10:00~22:00 15
 
5.9%
10:00~20:00 15
 
5.9%
09:00~21:00 13
 
5.1%
10:00~21:00 13
 
5.1%
09:00~20:00 7
 
2.7%
09:00~22:00 6
 
2.3%
08:00~20:00 6
 
2.3%
07:00~20:00 6
 
2.3%
Other values (75) 119
46.5%
2024-03-14T09:54:52.433411image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1184
42.5%
: 502
18.0%
1 353
 
12.7%
2 274
 
9.8%
~ 249
 
8.9%
9 69
 
2.5%
3 56
 
2.0%
8 31
 
1.1%
7 20
 
0.7%
4 13
 
0.5%
Other values (8) 32
 
1.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2021
72.6%
Other Punctuation 503
 
18.1%
Math Symbol 253
 
9.1%
Space Separator 3
 
0.1%
Other Letter 3
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1184
58.6%
1 353
 
17.5%
2 274
 
13.6%
9 69
 
3.4%
3 56
 
2.8%
8 31
 
1.5%
7 20
 
1.0%
4 13
 
0.6%
6 11
 
0.5%
5 10
 
0.5%
Other Letter
ValueCountFrequency (%)
불 1
33.3%
가 1
33.3%
능 1
33.3%
Other Punctuation
ValueCountFrequency (%)
: 502
99.8%
; 1
 
0.2%
Math Symbol
ValueCountFrequency (%)
~ 249
98.4%
∼ 4
 
1.6%
Space Separator
ValueCountFrequency (%)
3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2780
99.9%
Hangul 3
 
0.1%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1184
42.6%
: 502
18.1%
1 353
 
12.7%
2 274
 
9.9%
~ 249
 
9.0%
9 69
 
2.5%
3 56
 
2.0%
8 31
 
1.1%
7 20
 
0.7%
4 13
 
0.5%
Other values (5) 29
 
1.0%
Hangul
ValueCountFrequency (%)
불 1
33.3%
가 1
33.3%
능 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2776
99.7%
Math Operators 4
 
0.1%
Hangul 3
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1184
42.7%
: 502
18.1%
1 353
 
12.7%
2 274
 
9.9%
~ 249
 
9.0%
9 69
 
2.5%
3 56
 
2.0%
8 31
 
1.1%
7 20
 
0.7%
4 13
 
0.5%
Other values (4) 25
 
0.9%
Math Operators
ValueCountFrequency (%)
∼ 4
100.0%
Hangul
ValueCountFrequency (%)
불 1
33.3%
가 1
33.3%
능 1
33.3%

공개여부
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
공개
314 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
공개 314
100.0%

Length

2024-03-14T09:54:52.550868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T09:54:52.625131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공개 314
100.0%

작성일
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
17-Jan
314 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row17-Jan
2nd row17-Jan
3rd row17-Jan
4th row17-Jan
5th row17-Jan

Common Values

ValueCountFrequency (%)
17-Jan 314
100.0%

Length

2024-03-14T09:54:52.710377image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T09:54:52.781745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
17-jan 314
100.0%

갱신주기
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
1년
314 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1년
2nd row1년
3rd row1년
4th row1년
5th row1년

Common Values

ValueCountFrequency (%)
1년 314
100.0%

Length

2024-03-14T09:54:52.875968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T09:54:52.953427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1년 314
100.0%

Interactions

2024-03-14T09:54:46.618995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-14T09:54:53.009305image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번시군명업종품목3영업시간
순번1.0000.9460.3090.8520.752
시군명0.9461.0000.5360.9080.855
업종0.3090.5361.0000.9710.911
품목30.8520.9080.9711.0000.868
영업시간0.7520.8550.9110.8681.000
2024-03-14T09:54:53.090647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군명업종
시군명1.0000.208
업종0.2081.000
2024-03-14T09:54:53.164684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번시군명업종
순번1.0000.7780.121
시군명0.7781.0000.208
업종0.1210.2081.000

Missing values

2024-03-14T09:54:46.731822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T09:54:46.875236image/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.
2024-03-14T09:54:46.981839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

순번시군명업소명대표자업종도로명주소전화번호품목1품목2품목3영업시간공개여부작성일갱신주기
01전주시이래면옥최정희한식전주시 완산구 동문길 103288-6644갈비탕비빔냉면돼지불고기11:00~21:00공개17-Jan1년
12전주시제일크리너스샵권기호세탁업전주시 덕진구 쪽구름로 19211-2177양복바지티셔츠09:00~20:30공개17-Jan1년
23전주시중본이쟁반짜장김종복중식전주시 완산구 공북로71271-2223짜장면짬뽕간짜장10:30~20:30공개17-Jan1년
34전주시만나별미김혜숙분식전주시 완산구 거마평로 122224-9529백반콩나물국밥<NA>09:00~21:00공개17-Jan1년
45전주시기린로가정식백반강정자한식전주시 완산구 기린대로 222285-1005비빔밥김치찌개<NA>11:30~18:30공개17-Jan1년
56전주시청라회관경진희한식전주시 완산구 노송여울2길 10286-3044시래기국밥삼겹살(600g)시래기감자탕10:00~21:00공개17-Jan1년
67전주시옛살비이주형한식전주시 완산구 노송여울2길 14-3232-1406손칼국수팥칼국수새알팥죽09:30~21:30공개17-Jan1년
78전주시맛자랑 팥고향집김성환한식전주시 완산구 서학로 32-4231-0993순대국밥머리국밥돼지국밥09:00~21:00공개17-Jan1년
89전주시한가득순대국밥이창희한식전주시 완산구 풍남문2길 53232-4560커트파마<NA>09:30~21:30공개17-Jan1년
910전주시명보헤어김인자이미용업전주시 완산구 풍남문2길 22282-1643김치찌개된장찌개청국장10:00~17:00공개17-Jan1년
순번시군명업소명대표자업종도로명주소전화번호품목1품목2품목3영업시간공개여부작성일갱신주기
304305부안군송이미용실유은자이미용업전라북도 부안군 백산면 용계리 281584-7060커트퍼머염색08:30~17:00공개17-Jan1년
305306부안군다미락허영희일식부안군 부안읍 수정길 7063-583-8407유부초밥김초밥참치초밥11:00~21:00공개17-Jan1년
306307부안군고향식당안순자한식부안군 동진면 동진로 129063-584-6683팥죽찬치국수새알죽11:00~15:00공개17-Jan1년
307308부안군장터구이김성수한식부안군 부안읍 봉동길 17063-581-9222점심,저녁뷔페삼겹살닭백숙11:00~21:00공개17-Jan1년
308309부안군소문난 해장국임회용한식부안군 부안읍 동중2길 15063-581-3045선지해장국콩나물국밥우거지갈비탕06:30~21:00공개17-Jan1년
309310부안군아트카페김동기카페부안군 부안읍 수정길 28063-583-9830아메리카노쌍화차스무디09:00~24:00공개17-Jan1년
310311부안군성심이용원김금철이미용업부안군 백산면 시기길 8-1063-582-2505이발면도드라이07:00~19:00공개17-Jan1년
311312부안군정진미용실정진숙이미용업부안군 백산면 시기길 3-1063-582-4633커트파마염색08:00~19:00공개17-Jan1년
312313부안군이백가든백재진한식부안군 백산면 임현로 21063-581-9990순두부찌개김치전골한우불고기전골10:00~19:00공개17-Jan1년
313314부안군동원반점유옥분중식부안군 하서면 하서길 30-2063-584-7908짜장면짬뽕간짜장10:00~20:00공개17-Jan1년