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
Categorical4
Text8
DateTime1

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 (58.2%)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 started2024-03-13 23:46:35.263251
Analysis finished2024-03-13 23:46:36.512802
Duration1.25 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
2024-03-14T08:46:36.584711image/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
2024-03-14T08:46:36.733522image/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

2024-03-14T08:46:36.854580image/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
2024-03-14T08:46:37.110715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length11
Mean length4.7738854
Min length2

Characters and Unicode

Total characters1499
Distinct characters314
Distinct categories6 ?
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 (313) 313
95.1%
2024-03-14T08:46:37.715421image/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%
실 26
 
1.7%
원 26
 
1.7%
가 25
 
1.7%
국 24
 
1.6%
관 23
 
1.5%
Other values (304) 1145
76.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1475
98.4%
Space Separator 14
 
0.9%
Decimal Number 6
 
0.4%
Control 2
 
0.1%
Close Punctuation 1
 
0.1%
Open 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%
실 26
 
1.8%
원 26
 
1.8%
가 25
 
1.7%
국 24
 
1.6%
관 23
 
1.6%
Other values (296) 1121
76.0%
Decimal Number
ValueCountFrequency (%)
2 2
33.3%
0 2
33.3%
1 1
16.7%
5 1
16.7%
Space Separator
ValueCountFrequency (%)
14
100.0%
Control
ValueCountFrequency (%)
2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1475
98.4%
Common 24
 
1.6%

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%
실 26
 
1.8%
원 26
 
1.8%
가 25
 
1.7%
국 24
 
1.6%
관 23
 
1.6%
Other values (296) 1121
76.0%
Common
ValueCountFrequency (%)
14
58.3%
2
 
8.3%
2 2
 
8.3%
0 2
 
8.3%
) 1
 
4.2%
1 1
 
4.2%
( 1
 
4.2%
5 1
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1475
98.4%
ASCII 24
 
1.6%

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%
실 26
 
1.8%
원 26
 
1.8%
가 25
 
1.7%
국 24
 
1.6%
관 23
 
1.6%
Other values (296) 1121
76.0%
ASCII
ValueCountFrequency (%)
14
58.3%
2
 
8.3%
2 2
 
8.3%
0 2
 
8.3%
) 1
 
4.2%
1 1
 
4.2%
( 1
 
4.2%
5 1
 
4.2%

대표자
Text

MISSING 

Distinct300
Distinct (%)97.4%
Missing6
Missing (%)1.9%
Memory size2.6 KiB
2024-03-14T08:46:37.999813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length3
Mean length3.0292208
Min length2

Characters and Unicode

Total characters933
Distinct characters149
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

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%
한준상 1
 
0.3%
허명숙 1
 
0.3%
최정희 1
 
0.3%
Other values (294) 294
94.2%
2024-03-14T08:46:38.374727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
김 69
 
7.4%
이 56
 
6.0%
순 43
 
4.6%
영 38
 
4.1%
자 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 (139) 564
60.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 927
99.4%
Space Separator 4
 
0.4%
Control 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 69
 
7.4%
이 56
 
6.0%
순 43
 
4.6%
영 38
 
4.1%
자 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 (%)
4
100.0%
Control
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 927
99.4%
Common 6
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 69
 
7.4%
이 56
 
6.0%
순 43
 
4.6%
영 38
 
4.1%
자 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 (%)
4
66.7%
2
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 927
99.4%
ASCII 6
 
0.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
김 69
 
7.4%
이 56
 
6.0%
순 43
 
4.6%
영 38
 
4.1%
자 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 (%)
4
66.7%
2
33.3%

업종
Categorical

IMBALANCE 

Distinct19
Distinct (%)6.1%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
한식
219 
이미용업
37 
중식
22 
분식
 
5
미용업
 
5
Other values (14)
26 

Length

Max length6
Median length2
Mean length2.343949
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 37
 
11.8%
중식 22
 
7.0%
분식 5
 
1.6%
미용업 5
 
1.6%
세탁업 5
 
1.6%
목욕업 4
 
1.3%
이미 용업 3
 
1.0%
미용 2
 
0.6%
기타양식 2
 
0.6%
Other values (9) 10
 
3.2%

Length

2024-03-14T08:46:38.597779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
한식 219
69.1%
이미용업 37
 
11.7%
중식 22
 
6.9%
분식 5
 
1.6%
미용업 5
 
1.6%
세탁업 5
 
1.6%
목욕업 4
 
1.3%
이미 3
 
0.9%
용업 3
 
0.9%
숙박업 2
 
0.6%
Other values (10) 12
 
3.8%

도로명주소
Text

Distinct309
Distinct (%)98.4%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
2024-03-14T08:46:38.867730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length19
Mean length10.694268
Min length5

Characters and Unicode

Total characters3358
Distinct characters201
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks3 ?
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 row완산구 동문1길 103
2nd row덕진구 쪽구름로 19
3rd row완산구 공북로71
4th row완산구 거마평로 122
5th row완산구 기린대로 222
ValueCountFrequency (%)
완산구 36
 
4.3%
무주읍 17
 
2.0%
고창읍 14
 
1.7%
중앙로 12
 
1.4%
봉동읍 10
 
1.2%
16 9
 
1.1%
장수읍 8
 
0.9%
진안읍 7
 
0.8%
장계면 7
 
0.8%
덕진구 6
 
0.7%
Other values (525) 721
85.1%
2024-03-14T08:46:39.245638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
509
 
15.2%
1 220
 
6.6%
로 203
 
6.0%
길 123
 
3.7%
2 115
 
3.4%
3 101
 
3.0%
4 92
 
2.7%
면 87
 
2.6%
읍 75
 
2.2%
- 75
 
2.2%
Other values (191) 1758
52.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1794
53.4%
Decimal Number 891
26.5%
Space Separator 522
 
15.5%
Dash Punctuation 75
 
2.2%
Close Punctuation 25
 
0.7%
Open Punctuation 25
 
0.7%
Control 21
 
0.6%
Other Punctuation 5
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 203
 
11.3%
길 123
 
6.9%
면 87
 
4.8%
읍 75
 
4.2%
동 73
 
4.1%
산 70
 
3.9%
구 52
 
2.9%
장 47
 
2.6%
무 44
 
2.5%
완 39
 
2.2%
Other values (173) 981
54.7%
Decimal Number
ValueCountFrequency (%)
1 220
24.7%
2 115
12.9%
3 101
11.3%
4 92
10.3%
6 67
 
7.5%
9 65
 
7.3%
7 64
 
7.2%
8 61
 
6.8%
5 61
 
6.8%
0 45
 
5.1%
Space Separator
ValueCountFrequency (%)
509
97.5%
  13
 
2.5%
Other Punctuation
ValueCountFrequency (%)
, 3
60.0%
* 2
40.0%
Dash Punctuation
ValueCountFrequency (%)
- 75
100.0%
Close Punctuation
ValueCountFrequency (%)
) 25
100.0%
Open Punctuation
ValueCountFrequency (%)
( 25
100.0%
Control
ValueCountFrequency (%)
21
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1794
53.4%
Common 1564
46.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 203
 
11.3%
길 123
 
6.9%
면 87
 
4.8%
읍 75
 
4.2%
동 73
 
4.1%
산 70
 
3.9%
구 52
 
2.9%
장 47
 
2.6%
무 44
 
2.5%
완 39
 
2.2%
Other values (173) 981
54.7%
Common
ValueCountFrequency (%)
509
32.5%
1 220
14.1%
2 115
 
7.4%
3 101
 
6.5%
4 92
 
5.9%
- 75
 
4.8%
6 67
 
4.3%
9 65
 
4.2%
7 64
 
4.1%
8 61
 
3.9%
Other values (8) 195
 
12.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1794
53.4%
ASCII 1551
46.2%
None 13
 
0.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
509
32.8%
1 220
14.2%
2 115
 
7.4%
3 101
 
6.5%
4 92
 
5.9%
- 75
 
4.8%
6 67
 
4.3%
9 65
 
4.2%
7 64
 
4.1%
8 61
 
3.9%
Other values (7) 182
 
11.7%
Hangul
ValueCountFrequency (%)
로 203
 
11.3%
길 123
 
6.9%
면 87
 
4.8%
읍 75
 
4.2%
동 73
 
4.1%
산 70
 
3.9%
구 52
 
2.9%
장 47
 
2.6%
무 44
 
2.5%
완 39
 
2.2%
Other values (173) 981
54.7%
None
ValueCountFrequency (%)
  13
100.0%

전화번호
Text

MISSING 

Distinct306
Distinct (%)100.0%
Missing8
Missing (%)2.5%
Memory size2.6 KiB
2024-03-14T08:46:39.497136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length8
Mean length9.7156863
Min length8

Characters and Unicode

Total characters2973
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

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%
2024-03-14T08:46:39.889441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 438
14.7%
3 431
14.5%
6 363
12.2%
2 322
10.8%
5 302
10.2%
0 289
9.7%
4 225
7.6%
8 197
6.6%
1 168
 
5.7%
7 128
 
4.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2535
85.3%
Dash Punctuation 438
 
14.7%

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%

Most occurring scripts

ValueCountFrequency (%)
Common 2973
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 438
14.7%
3 431
14.5%
6 363
12.2%
2 322
10.8%
5 302
10.2%
0 289
9.7%
4 225
7.6%
8 197
6.6%
1 168
 
5.7%
7 128
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2973
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 438
14.7%
3 431
14.5%
6 363
12.2%
2 322
10.8%
5 302
10.2%
0 289
9.7%
4 225
7.6%
8 197
6.6%
1 168
 
5.7%
7 128
 
4.3%

품목1
Text

Distinct141
Distinct (%)44.9%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
2024-03-14T08:46:40.154876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length12
Mean length4.0031847
Min length1

Characters and Unicode

Total characters1257
Distinct characters173
Distinct categories9 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique96 ?
Unique (%)30.6%

Sample

1st row갈비탕
2nd row양복
3rd row짜장면
4th row백반
5th row비빔밥
ValueCountFrequency (%)
백반 33
 
9.9%
커트 22
 
6.6%
김치찌개 17
 
5.1%
삼겹살 12
 
3.6%
삼겹살(200g 9
 
2.7%
짜장면 8
 
2.4%
200g 7
 
2.1%
자장면 7
 
2.1%
국수 7
 
2.1%
컷트 6
 
1.8%
Other values (132) 206
61.7%
2024-03-14T08:46:40.522159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
국 53
 
4.2%
반 47
 
3.7%
0 46
 
3.7%
백 45
 
3.6%
밥 40
 
3.2%
장 37
 
2.9%
트 34
 
2.7%
개 33
 
2.6%
찌 32
 
2.5%
삼 30
 
2.4%
Other values (163) 860
68.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1067
84.9%
Decimal Number 76
 
6.0%
Close Punctuation 30
 
2.4%
Open Punctuation 29
 
2.3%
Lowercase Letter 24
 
1.9%
Control 12
 
1.0%
Space Separator 11
 
0.9%
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%
5 2
 
2.6%
1 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%
Control
ValueCountFrequency (%)
12
100.0%
Space Separator
ValueCountFrequency (%)
11
100.0%
Other Punctuation
ValueCountFrequency (%)
, 6
100.0%
Math Symbol
ValueCountFrequency (%)
+ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1066
84.8%
Common 166
 
13.2%
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
27.7%
) 30
18.1%
( 29
17.5%
2 22
13.3%
12
 
7.2%
11
 
6.6%
, 6
 
3.6%
3 3
 
1.8%
5 2
 
1.2%
1 2
 
1.2%
Other values (2) 3
 
1.8%
Latin
ValueCountFrequency (%)
g 24
100.0%
Han
ValueCountFrequency (%)
大 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1066
84.8%
ASCII 190
 
15.1%
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
24.2%
) 30
15.8%
( 29
15.3%
g 24
12.6%
2 22
11.6%
12
 
6.3%
11
 
5.8%
, 6
 
3.2%
3 3
 
1.6%
5 2
 
1.1%
Other values (3) 5
 
2.6%
CJK
ValueCountFrequency (%)
大 1
100.0%

품목2
Text

MISSING 

Distinct116
Distinct (%)49.6%
Missing80
Missing (%)25.5%
Memory size2.6 KiB
2024-03-14T08:46:40.829363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length12
Mean length3.9059829
Min length2

Characters and Unicode

Total characters914
Distinct characters173
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

Unique84 ?
Unique (%)35.9%

Sample

1st row비빔냉면
2nd row바지
3rd row짬뽕
4th row콩나물국밥
5th row김치찌개
ValueCountFrequency (%)
파마 18
 
7.3%
짬뽕 14
 
5.7%
김치찌개 11
 
4.5%
된장찌개 8
 
3.3%
청국장 7
 
2.9%
삼겹살 7
 
2.9%
국수 6
 
2.4%
갈비탕 6
 
2.4%
삼겹살(200g 6
 
2.4%
팥칼국수 5
 
2.0%
Other values (108) 157
64.1%
2024-03-14T08:46:41.198143image/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%
개 25
 
2.7%
) 23
 
2.5%
( 23
 
2.5%
장 23
 
2.5%
수 22
 
2.4%
찌 22
 
2.4%
Other values (163) 646
70.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 790
86.4%
Decimal Number 46
 
5.0%
Close Punctuation 23
 
2.5%
Open Punctuation 23
 
2.5%
Lowercase Letter 14
 
1.5%
Space Separator 8
 
0.9%
Control 8
 
0.9%
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%
마 18
 
2.3%
파 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%
3 1
 
2.2%
6 1
 
2.2%
4 1
 
2.2%
Close Punctuation
ValueCountFrequency (%)
) 23
100.0%
Open Punctuation
ValueCountFrequency (%)
( 23
100.0%
Lowercase Letter
ValueCountFrequency (%)
g 14
100.0%
Space Separator
ValueCountFrequency (%)
8
100.0%
Control
ValueCountFrequency (%)
8
100.0%
Math Symbol
ValueCountFrequency (%)
+ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 789
86.3%
Common 110
 
12.0%
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%
마 18
 
2.3%
파 18
 
2.3%
Other values (149) 535
67.8%
Common
ValueCountFrequency (%)
0 26
23.6%
) 23
20.9%
( 23
20.9%
2 13
11.8%
8
 
7.3%
8
 
7.3%
1 2
 
1.8%
5 2
 
1.8%
+ 2
 
1.8%
3 1
 
0.9%
Other values (2) 2
 
1.8%
Latin
ValueCountFrequency (%)
g 14
100.0%
Han
ValueCountFrequency (%)
大 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 789
86.3%
ASCII 124
 
13.6%
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%
마 18
 
2.3%
파 18
 
2.3%
Other values (149) 535
67.8%
ASCII
ValueCountFrequency (%)
0 26
21.0%
) 23
18.5%
( 23
18.5%
g 14
11.3%
2 13
10.5%
8
 
6.5%
8
 
6.5%
1 2
 
1.6%
5 2
 
1.6%
+ 2
 
1.6%
Other values (3) 3
 
2.4%
CJK
ValueCountFrequency (%)
大 1
100.0%

품목3
Text

MISSING 

Distinct78
Distinct (%)66.1%
Missing196
Missing (%)62.4%
Memory size2.6 KiB
2024-03-14T08:46:41.424700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length3.8813559
Min length2

Characters and Unicode

Total characters458
Distinct characters126
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

Unique58 ?
Unique (%)49.2%

Sample

1st row돼지불고기
2nd row티셔츠
3rd row간짜장
4th row시래기감자탕
5th row새알팥죽
ValueCountFrequency (%)
김치찌개 8
 
6.5%
염색 7
 
5.6%
된장찌개 6
 
4.8%
간짜장 4
 
3.2%
청국장 4
 
3.2%
우동 4
 
3.2%
드라이 3
 
2.4%
200g 3
 
2.4%
삼겹살 3
 
2.4%
백반 3
 
2.4%
Other values (68) 79
63.7%
2024-03-14T08:46:41.762950image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
장 22
 
4.8%
개 19
 
4.1%
국 18
 
3.9%
찌 17
 
3.7%
밥 16
 
3.5%
탕 13
 
2.8%
우 12
 
2.6%
치 11
 
2.4%
김 10
 
2.2%
비 10
 
2.2%
Other values (116) 310
67.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 418
91.3%
Decimal Number 13
 
2.8%
Open Punctuation 7
 
1.5%
Close Punctuation 7
 
1.5%
Space Separator 5
 
1.1%
Control 4
 
0.9%
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%
김 10
 
2.4%
비 10
 
2.4%
Other values (108) 270
64.6%
Decimal Number
ValueCountFrequency (%)
0 8
61.5%
2 4
30.8%
6 1
 
7.7%
Open Punctuation
ValueCountFrequency (%)
( 7
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7
100.0%
Space Separator
ValueCountFrequency (%)
5
100.0%
Control
ValueCountFrequency (%)
4
100.0%
Lowercase Letter
ValueCountFrequency (%)
g 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 416
90.8%
Common 36
 
7.9%
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%
김 10
 
2.4%
비 10
 
2.4%
Other values (106) 268
64.4%
Common
ValueCountFrequency (%)
0 8
22.2%
( 7
19.4%
) 7
19.4%
5
13.9%
4
11.1%
2 4
11.1%
6 1
 
2.8%
Han
ValueCountFrequency (%)
大 1
50.0%
小 1
50.0%
Latin
ValueCountFrequency (%)
g 4
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 416
90.8%
ASCII 40
 
8.7%
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%
김 10
 
2.4%
비 10
 
2.4%
Other values (106) 268
64.4%
ASCII
ValueCountFrequency (%)
0 8
20.0%
( 7
17.5%
) 7
17.5%
5
12.5%
4
10.0%
g 4
10.0%
2 4
10.0%
6 1
 
2.5%
CJK
ValueCountFrequency (%)
大 1
50.0%
小 1
50.0%

영업시간
Text

MISSING 

Distinct82
Distinct (%)32.4%
Missing61
Missing (%)19.4%
Memory size2.6 KiB
2024-03-14T08:46:41.997526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length11
Mean length11
Min length3

Characters and Unicode

Total characters2783
Distinct characters19
Distinct categories6 ?
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%
2024-03-14T08:46:42.353551image/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 (9) 32
 
1.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2021
72.6%
Other Punctuation 503
 
18.1%
Math Symbol 253
 
9.1%
Other Letter 3
 
0.1%
Space Separator 2
 
0.1%
Control 1
 
< 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 (%)
2
100.0%
Control
ValueCountFrequency (%)
1
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 (6) 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 (5) 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

2024-03-14T08:46:42.465642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T08:46:42.548131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공개 314
100.0%

작성일
Date

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size2.6 KiB
Minimum2017-01-01 00:00:00
Maximum2017-01-01 00:00:00
2024-03-14T08:46:42.610649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T08:46:42.679493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

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

2024-03-14T08:46:42.768081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T08:46:42.856006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1년 314
100.0%

Interactions

2024-03-14T08:46:35.973329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-14T08:46:42.943506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번시군명업종품목3영업시간
순번1.0000.9460.3720.8560.752
시군명0.9461.0000.5720.9060.855
업종0.3720.5721.0000.9720.916
품목30.8560.9060.9721.0000.780
영업시간0.7520.8550.9160.7801.000
2024-03-14T08:46:43.063365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군명업종
시군명1.0000.226
업종0.2261.000
2024-03-14T08:46:43.139138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번시군명업종
순번1.0000.7780.145
시군명0.7781.0000.226
업종0.1450.2261.000

Missing values

2024-03-14T08:46:36.078532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T08:46:36.304950image/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.
2024-03-14T08:46:36.454051image/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
01전주시이래면옥최정희한식완산구 동문1길 103288-6644갈비탕비빔냉면돼지불고기11:00~21:00공개2017-01-011년
12전주시제일크리너스샵권기호세탁업덕진구 쪽구름로 19211-2177양복바지티셔츠09:00~20:30공개2017-01-011년
23전주시중본이쟁반짜장김종복중식완산구 공북로71271-2223짜장면짬뽕간짜장10:30~20:30공개2017-01-011년
34전주시만나별미김혜숙분식완산구 거마평로 122224-9529백반콩나물국밥<NA>09:00~21:00공개2017-01-011년
45전주시기린로가정식백반강정자한식완산구 기린대로 222285-1005비빔밥김치찌개<NA>11:30~18:30공개2017-01-011년
56전주시청라회관경진희한식완산구 노송여울2길 10286-3044시래기국밥삼겹살 (600g)시래기감자탕10:00~21:00공개2017-01-011년
67전주시옛살비이주형한식완산구 노송여울2길 14-3232-1406손칼국수팥칼국수새알팥죽09:30~21:30공개2017-01-011년
78전주시맛자랑 팥고향집김성환한식완산구 서학로 32-4231-0993순대국밥머리국밥돼지국밥09:00~21:00공개2017-01-011년
89전주시한가득순대국밥이창희한식완산구 풍남문2길 53232-4560커트파마<NA>09:30~21:30공개2017-01-011년
910전주시명보헤어김인자이미용업완산구 풍남문2길 22282-1643김치찌개된장찌개청국장10:00~17:00공개2017-01-011년
순번시군명업소명대표자업종도로명주소전화번호품목1품목2품목3영업시간공개여부작성일갱신주기
304305부안군송이미용실유은자이미용업백산 용계 산매길 557584-7060커트퍼머염색08:30~17:00공개2017-01-011년
305306부안군다미락허영희일식부안읍 수정길 7063-583-8407유부초밥김초밥참치초밥11:00~21:00공개2017-01-011년
306307부안군고향식당안순자한식동진면 동진로 129063-584-6683팥죽찬치국수새알죽11:00~15:00공개2017-01-011년
307308부안군장터구이김성수한식부안읍 봉동길 17063-581-9222점심,저녁뷔페삼겹살닭백숙11:00~21:00공개2017-01-011년
308309부안군소문난 해장국임회용한식부안읍 동중2길 15063-581-3045선지해장국콩나물국밥우거지갈비탕06:30~21:00공개2017-01-011년
309310부안군아트카페김동기카페부안읍 수정길 28063-583-9830아메리카노쌍화차스무디09:00~24:00공개2017-01-011년
310311부안군성심이용원김금철이미용업백산면 시기길 8-1063-582-2505이발면도드라이07:00~19:00공개2017-01-011년
311312부안군정진미용실정진숙이미용업백산면 시기길 3-1063-582-4633커트파마염색08:00~19:00공개2017-01-011년
312313부안군이백가든백재진한식백산면 임현로 21063-581-9990순두부찌개김치전골한우불고기전골10:00~19:00공개2017-01-011년
313314부안군동원반점유옥분중식하서면 신지길 30-2063-584-7908짜장면짬뽕간짜장10:00~20:00공개2017-01-011년