Overview

Dataset statistics

Number of variables14
Number of observations80
Missing cells127
Missing cells (%)11.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory9.0 KiB
Average record size in memory115.7 B

Variable types

Numeric2
Categorical2
Text5
DateTime3
Boolean2

Dataset

Description대전광역시 중구 착한가격업소(연번, 업종, 업소명, 주소, 연락처, 영업시작시각, 영업종료시각, 배달가능여부, 주차가능여부, 메뉴, 가격, 데이터 기준일자) 현황정보를 제공합니다.
Author대전광역시 중구
URLhttps://www.data.go.kr/data/15072855/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
업종 is highly overall correlated with 가격1High correlation
가격1 is highly overall correlated with 업종High correlation
연락처 has 7 (8.8%) missing valuesMissing
영업시작시간 has 1 (1.2%) missing valuesMissing
영업종료시간 has 1 (1.2%) missing valuesMissing
메뉴2 has 59 (73.8%) missing valuesMissing
가격2 has 59 (73.8%) missing valuesMissing
연번 has unique valuesUnique
업소명 has unique valuesUnique
주소(도로명새주소명기) has unique valuesUnique

Reproduction

Analysis started2023-12-12 10:04:02.865670
Analysis finished2023-12-12 10:04:05.161220
Duration2.3 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct80
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean40.5
Minimum1
Maximum80
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size852.0 B
2023-12-12T19:04:05.244969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile4.95
Q120.75
median40.5
Q360.25
95-th percentile76.05
Maximum80
Range79
Interquartile range (IQR)39.5

Descriptive statistics

Standard deviation23.2379
Coefficient of variation (CV)0.57377531
Kurtosis-1.2
Mean40.5
Median Absolute Deviation (MAD)20
Skewness0
Sum3240
Variance540
MonotonicityStrictly increasing
2023-12-12T19:04:05.434194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.2%
42 1
 
1.2%
60 1
 
1.2%
59 1
 
1.2%
58 1
 
1.2%
57 1
 
1.2%
56 1
 
1.2%
55 1
 
1.2%
54 1
 
1.2%
53 1
 
1.2%
Other values (70) 70
87.5%
ValueCountFrequency (%)
1 1
1.2%
2 1
1.2%
3 1
1.2%
4 1
1.2%
5 1
1.2%
6 1
1.2%
7 1
1.2%
8 1
1.2%
9 1
1.2%
10 1
1.2%
ValueCountFrequency (%)
80 1
1.2%
79 1
1.2%
78 1
1.2%
77 1
1.2%
76 1
1.2%
75 1
1.2%
74 1
1.2%
73 1
1.2%
72 1
1.2%
71 1
1.2%

업종
Categorical

HIGH CORRELATION 

Distinct10
Distinct (%)12.5%
Missing0
Missing (%)0.0%
Memory size772.0 B
한식
44 
이미용업
11 
중식
8 
기타외식
7 
한식
 
4
Other values (5)
6 

Length

Max length4
Median length2
Mean length2.5625
Min length2

Unique

Unique4 ?
Unique (%)5.0%

Sample

1st row기타외식
2nd row중식
3rd row한식
4th row한식
5th row한식

Common Values

ValueCountFrequency (%)
한식 44
55.0%
이미용업 11
 
13.8%
중식 8
 
10.0%
기타외식 7
 
8.8%
한식 4
 
5.0%
세탁업 2
 
2.5%
경양식 1
 
1.2%
카페 1
 
1.2%
세탁 1
 
1.2%
당구장업 1
 
1.2%

Length

2023-12-12T19:04:05.610988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:04:05.767445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
한식 48
60.0%
이미용업 11
 
13.8%
중식 8
 
10.0%
기타외식 7
 
8.8%
세탁업 2
 
2.5%
경양식 1
 
1.2%
카페 1
 
1.2%
세탁 1
 
1.2%
당구장업 1
 
1.2%

업소명
Text

UNIQUE 

Distinct80
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size772.0 B
2023-12-12T19:04:06.058848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length16
Median length12.5
Mean length5.675
Min length3

Characters and Unicode

Total characters454
Distinct characters199
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique80 ?
Unique (%)100.0%

Sample

1st row성심당
2nd row옛날전통짜장
3rd row24시대전해장국
4th row신삼정식당
5th row동원식당
ValueCountFrequency (%)
신도칼국수 2
 
2.4%
성심당 1
 
1.2%
뮬랑샵 1
 
1.2%
공주얼큰이칼국수 1
 
1.2%
문화남성컷트 1
 
1.2%
대박짬뽕케이쓰리푸드문화점 1
 
1.2%
엄니곰탕 1
 
1.2%
홈런김밥 1
 
1.2%
동춘원 1
 
1.2%
딸둘아들하나 1
 
1.2%
Other values (73) 73
86.9%
2023-12-12T19:04:06.448132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
국 16
 
3.5%
수 14
 
3.1%
당 12
 
2.6%
칼 10
 
2.2%
식 10
 
2.2%
이 10
 
2.2%
소 9
 
2.0%
어 8
 
1.8%
미 8
 
1.8%
장 8
 
1.8%
Other values (189) 349
76.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 431
94.9%
Uppercase Letter 9
 
2.0%
Decimal Number 5
 
1.1%
Space Separator 4
 
0.9%
Close Punctuation 2
 
0.4%
Open Punctuation 2
 
0.4%
Other Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
국 16
 
3.7%
수 14
 
3.2%
당 12
 
2.8%
칼 10
 
2.3%
식 10
 
2.3%
이 10
 
2.3%
소 9
 
2.1%
어 8
 
1.9%
미 8
 
1.9%
장 8
 
1.9%
Other values (173) 326
75.6%
Uppercase Letter
ValueCountFrequency (%)
R 2
22.2%
E 1
11.1%
A 1
11.1%
S 1
11.1%
M 1
11.1%
T 1
11.1%
F 1
11.1%
C 1
11.1%
Decimal Number
ValueCountFrequency (%)
2 2
40.0%
3 1
20.0%
1 1
20.0%
4 1
20.0%
Space Separator
ValueCountFrequency (%)
4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Other Punctuation
ValueCountFrequency (%)
& 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 431
94.9%
Common 14
 
3.1%
Latin 9
 
2.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
국 16
 
3.7%
수 14
 
3.2%
당 12
 
2.8%
칼 10
 
2.3%
식 10
 
2.3%
이 10
 
2.3%
소 9
 
2.1%
어 8
 
1.9%
미 8
 
1.9%
장 8
 
1.9%
Other values (173) 326
75.6%
Common
ValueCountFrequency (%)
4
28.6%
) 2
14.3%
2 2
14.3%
( 2
14.3%
& 1
 
7.1%
3 1
 
7.1%
1 1
 
7.1%
4 1
 
7.1%
Latin
ValueCountFrequency (%)
R 2
22.2%
E 1
11.1%
A 1
11.1%
S 1
11.1%
M 1
11.1%
T 1
11.1%
F 1
11.1%
C 1
11.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 431
94.9%
ASCII 23
 
5.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
국 16
 
3.7%
수 14
 
3.2%
당 12
 
2.8%
칼 10
 
2.3%
식 10
 
2.3%
이 10
 
2.3%
소 9
 
2.1%
어 8
 
1.9%
미 8
 
1.9%
장 8
 
1.9%
Other values (173) 326
75.6%
ASCII
ValueCountFrequency (%)
4
17.4%
) 2
 
8.7%
2 2
 
8.7%
R 2
 
8.7%
( 2
 
8.7%
E 1
 
4.3%
A 1
 
4.3%
S 1
 
4.3%
M 1
 
4.3%
& 1
 
4.3%
Other values (6) 6
26.1%

주소(도로명새주소명기)
Text

UNIQUE 

Distinct80
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size772.0 B
2023-12-12T19:04:06.730480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length40
Median length29
Mean length22.3
Min length16

Characters and Unicode

Total characters1784
Distinct characters86
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique80 ?
Unique (%)100.0%

Sample

1st row대전 중구 대종로480번길 15(은행동)
2nd row대전 중구 동서대로 1208-5(태평동)
3rd row대전 중구 우암로 12(선화동)
4th row대전 중구 중교로11-1(대흥동)
5th row대전 중구 중교로29-1(대흥동)
ValueCountFrequency (%)
대전 80
23.4%
중구 80
23.4%
1층 6
 
1.8%
1층(문화동 5
 
1.5%
충무로 5
 
1.5%
동서대로 4
 
1.2%
1층(선화동 3
 
0.9%
수침로55번길 3
 
0.9%
선화로 3
 
0.9%
1층(문창동 3
 
0.9%
Other values (140) 150
43.9%
2023-12-12T19:04:07.182433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
265
 
14.9%
대 117
 
6.6%
1 109
 
6.1%
중 97
 
5.4%
동 87
 
4.9%
전 83
 
4.7%
) 81
 
4.5%
( 81
 
4.5%
구 80
 
4.5%
로 79
 
4.4%
Other values (76) 705
39.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 938
52.6%
Decimal Number 369
 
20.7%
Space Separator 265
 
14.9%
Close Punctuation 81
 
4.5%
Open Punctuation 81
 
4.5%
Other Punctuation 28
 
1.6%
Dash Punctuation 21
 
1.2%
Uppercase Letter 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
대 117
12.5%
중 97
 
10.3%
동 87
 
9.3%
전 83
 
8.8%
구 80
 
8.5%
로 79
 
8.4%
길 39
 
4.2%
번 38
 
4.1%
화 35
 
3.7%
문 30
 
3.2%
Other values (60) 253
27.0%
Decimal Number
ValueCountFrequency (%)
1 109
29.5%
2 51
13.8%
5 42
 
11.4%
0 36
 
9.8%
3 29
 
7.9%
6 26
 
7.0%
4 25
 
6.8%
7 22
 
6.0%
9 15
 
4.1%
8 14
 
3.8%
Space Separator
ValueCountFrequency (%)
265
100.0%
Close Punctuation
ValueCountFrequency (%)
) 81
100.0%
Open Punctuation
ValueCountFrequency (%)
( 81
100.0%
Other Punctuation
ValueCountFrequency (%)
, 28
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 21
100.0%
Uppercase Letter
ValueCountFrequency (%)
A 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 938
52.6%
Common 845
47.4%
Latin 1
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
대 117
12.5%
중 97
 
10.3%
동 87
 
9.3%
전 83
 
8.8%
구 80
 
8.5%
로 79
 
8.4%
길 39
 
4.2%
번 38
 
4.1%
화 35
 
3.7%
문 30
 
3.2%
Other values (60) 253
27.0%
Common
ValueCountFrequency (%)
265
31.4%
1 109
12.9%
) 81
 
9.6%
( 81
 
9.6%
2 51
 
6.0%
5 42
 
5.0%
0 36
 
4.3%
3 29
 
3.4%
, 28
 
3.3%
6 26
 
3.1%
Other values (5) 97
 
11.5%
Latin
ValueCountFrequency (%)
A 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 938
52.6%
ASCII 846
47.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
265
31.3%
1 109
12.9%
) 81
 
9.6%
( 81
 
9.6%
2 51
 
6.0%
5 42
 
5.0%
0 36
 
4.3%
3 29
 
3.4%
, 28
 
3.3%
6 26
 
3.1%
Other values (6) 98
 
11.6%
Hangul
ValueCountFrequency (%)
대 117
12.5%
중 97
 
10.3%
동 87
 
9.3%
전 83
 
8.8%
구 80
 
8.5%
로 79
 
8.4%
길 39
 
4.2%
번 38
 
4.1%
화 35
 
3.7%
문 30
 
3.2%
Other values (60) 253
27.0%

연락처
Text

MISSING 

Distinct73
Distinct (%)100.0%
Missing7
Missing (%)8.8%
Memory size772.0 B
2023-12-12T19:04:07.535515image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.027397
Min length12

Characters and Unicode

Total characters878
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

Unique73 ?
Unique (%)100.0%

Sample

1st row042-256-4114
2nd row042-532-4494
3rd row042-255-1066
4th row042-222-1533
5th row042-252-3620
ValueCountFrequency (%)
042-257-4732 1
 
1.4%
042-585-1566 1
 
1.4%
042-221-7304 1
 
1.4%
042-222-6366 1
 
1.4%
042-252-8532 1
 
1.4%
042-535-1541 1
 
1.4%
042-257-5478 1
 
1.4%
042-320-3335 1
 
1.4%
042-254-9404 1
 
1.4%
042-586-3573 1
 
1.4%
Other values (63) 63
86.3%
2023-12-12T19:04:08.014576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 182
20.7%
- 146
16.6%
0 108
12.3%
5 105
12.0%
4 103
11.7%
3 50
 
5.7%
8 48
 
5.5%
6 38
 
4.3%
1 35
 
4.0%
7 34
 
3.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 732
83.4%
Dash Punctuation 146
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 182
24.9%
0 108
14.8%
5 105
14.3%
4 103
14.1%
3 50
 
6.8%
8 48
 
6.6%
6 38
 
5.2%
1 35
 
4.8%
7 34
 
4.6%
9 29
 
4.0%
Dash Punctuation
ValueCountFrequency (%)
- 146
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 878
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 182
20.7%
- 146
16.6%
0 108
12.3%
5 105
12.0%
4 103
11.7%
3 50
 
5.7%
8 48
 
5.5%
6 38
 
4.3%
1 35
 
4.0%
7 34
 
3.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 878
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 182
20.7%
- 146
16.6%
0 108
12.3%
5 105
12.0%
4 103
11.7%
3 50
 
5.7%
8 48
 
5.5%
6 38
 
4.3%
1 35
 
4.0%
7 34
 
3.9%

영업시작시간
Date

MISSING 

Distinct17
Distinct (%)21.5%
Missing1
Missing (%)1.2%
Memory size772.0 B
Minimum2023-12-12 06:00:00
Maximum2023-12-12 17:00:00
2023-12-12T19:04:08.184536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:04:08.371352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)

영업종료시간
Date

MISSING 

Distinct16
Distinct (%)20.3%
Missing1
Missing (%)1.2%
Memory size772.0 B
Minimum2023-12-12 00:00:00
Maximum2023-12-12 23:00:00
2023-12-12T19:04:08.534692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:04:08.647493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)

배달가능여부
Boolean

Distinct2
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size212.0 B
False
54 
True
26 
ValueCountFrequency (%)
False 54
67.5%
True 26
32.5%
2023-12-12T19:04:08.760966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

주차가능여부
Boolean

Distinct2
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size212.0 B
False
53 
True
27 
ValueCountFrequency (%)
False 53
66.2%
True 27
33.8%
2023-12-12T19:04:08.879491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

메뉴1
Text

Distinct46
Distinct (%)57.5%
Missing0
Missing (%)0.0%
Memory size772.0 B
2023-12-12T19:04:09.091282image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length4.0625
Min length2

Characters and Unicode

Total characters325
Distinct characters104
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique33 ?
Unique (%)41.2%

Sample

1st row튀김소보로
2nd row자장면
3rd row해장국
4th row동태찌개
5th row황태탕
ValueCountFrequency (%)
자장면 10
 
12.2%
컷트 6
 
7.3%
칼국수 5
 
6.1%
백반 4
 
4.9%
아메리카노 3
 
3.7%
커피 3
 
3.7%
삼겹살 3
 
3.7%
컷트(남 3
 
3.7%
냉면 2
 
2.4%
잔치국수 2
 
2.4%
Other values (38) 41
50.0%
2023-12-12T19:04:09.455058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
국 18
 
5.5%
장 16
 
4.9%
수 13
 
4.0%
면 12
 
3.7%
( 11
 
3.4%
컷 11
 
3.4%
트 11
 
3.4%
) 11
 
3.4%
자 10
 
3.1%
칼 10
 
3.1%
Other values (94) 202
62.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 289
88.9%
Open Punctuation 11
 
3.4%
Close Punctuation 11
 
3.4%
Lowercase Letter 7
 
2.2%
Space Separator 5
 
1.5%
Other Punctuation 2
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
국 18
 
6.2%
장 16
 
5.5%
수 13
 
4.5%
면 12
 
4.2%
컷 11
 
3.8%
트 11
 
3.8%
자 10
 
3.5%
칼 10
 
3.5%
반 6
 
2.1%
백 6
 
2.1%
Other values (84) 176
60.9%
Lowercase Letter
ValueCountFrequency (%)
t 2
28.6%
a 1
14.3%
k 1
14.3%
e 1
14.3%
o 1
14.3%
u 1
14.3%
Open Punctuation
ValueCountFrequency (%)
( 11
100.0%
Close Punctuation
ValueCountFrequency (%)
) 11
100.0%
Space Separator
ValueCountFrequency (%)
5
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 289
88.9%
Common 29
 
8.9%
Latin 7
 
2.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
국 18
 
6.2%
장 16
 
5.5%
수 13
 
4.5%
면 12
 
4.2%
컷 11
 
3.8%
트 11
 
3.8%
자 10
 
3.5%
칼 10
 
3.5%
반 6
 
2.1%
백 6
 
2.1%
Other values (84) 176
60.9%
Latin
ValueCountFrequency (%)
t 2
28.6%
a 1
14.3%
k 1
14.3%
e 1
14.3%
o 1
14.3%
u 1
14.3%
Common
ValueCountFrequency (%)
( 11
37.9%
) 11
37.9%
5
17.2%
, 2
 
6.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 289
88.9%
ASCII 36
 
11.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
국 18
 
6.2%
장 16
 
5.5%
수 13
 
4.5%
면 12
 
4.2%
컷 11
 
3.8%
트 11
 
3.8%
자 10
 
3.5%
칼 10
 
3.5%
반 6
 
2.1%
백 6
 
2.1%
Other values (84) 176
60.9%
ASCII
ValueCountFrequency (%)
( 11
30.6%
) 11
30.6%
5
13.9%
, 2
 
5.6%
t 2
 
5.6%
a 1
 
2.8%
k 1
 
2.8%
e 1
 
2.8%
o 1
 
2.8%
u 1
 
2.8%

가격1
Categorical

HIGH CORRELATION 

Distinct22
Distinct (%)27.5%
Missing0
Missing (%)0.0%
Memory size772.0 B
6000
21 
5000
11 
8000
7 
2000
6 
10000
6 
Other values (17)
29 

Length

Max length15
Median length4
Mean length4.25
Min length4

Unique

Unique11 ?
Unique (%)13.8%

Sample

1st row1600
2nd row4000
3rd row5000
4th row8000
5th row8000

Common Values

ValueCountFrequency (%)
6000 21
26.2%
5000 11
13.8%
8000 7
 
8.8%
2000 6
 
7.5%
10000 6
 
7.5%
7000 4
 
5.0%
4000 4
 
5.0%
4500 3
 
3.8%
9000 3
 
3.8%
6500 2
 
2.5%
Other values (12) 13
16.2%

Length

2023-12-12T19:04:09.595996image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
6000 21
25.9%
5000 11
13.6%
8000 7
 
8.6%
2000 6
 
7.4%
10000 6
 
7.4%
7000 4
 
4.9%
4000 4
 
4.9%
4500 3
 
3.7%
9000 3
 
3.7%
6500 2
 
2.5%
Other values (13) 14
17.3%

메뉴2
Text

MISSING 

Distinct19
Distinct (%)90.5%
Missing59
Missing (%)73.8%
Memory size772.0 B
2023-12-12T19:04:09.742728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length6
Mean length4.1428571
Min length2

Characters and Unicode

Total characters87
Distinct characters54
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

Unique18 ?
Unique (%)85.7%

Sample

1st row뼈해장국
2nd row불쌈국수
3rd row돈가스
4th row짬뽕
5th row제육덮밥
ValueCountFrequency (%)
짬뽕 3
 
14.3%
닭볶음탕(한마리 1
 
4.8%
냉면 1
 
4.8%
불고기백반 1
 
4.8%
아이스커피 1
 
4.8%
커피(매장 1
 
4.8%
비빔국수 1
 
4.8%
멸치국수 1
 
4.8%
콩국수 1
 
4.8%
커트+염색 1
 
4.8%
Other values (9) 9
42.9%
2023-12-12T19:04:10.040451image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
국 7
 
8.0%
수 6
 
6.9%
짬 3
 
3.4%
뽕 3
 
3.4%
커 3
 
3.4%
한 3
 
3.4%
탕 2
 
2.3%
) 2
 
2.3%
피 2
 
2.3%
( 2
 
2.3%
Other values (44) 54
62.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 81
93.1%
Close Punctuation 2
 
2.3%
Open Punctuation 2
 
2.3%
Other Punctuation 1
 
1.1%
Math Symbol 1
 
1.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
국 7
 
8.6%
수 6
 
7.4%
짬 3
 
3.7%
뽕 3
 
3.7%
커 3
 
3.7%
한 3
 
3.7%
탕 2
 
2.5%
피 2
 
2.5%
장 2
 
2.5%
이 2
 
2.5%
Other values (40) 48
59.3%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 1
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 81
93.1%
Common 6
 
6.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
국 7
 
8.6%
수 6
 
7.4%
짬 3
 
3.7%
뽕 3
 
3.7%
커 3
 
3.7%
한 3
 
3.7%
탕 2
 
2.5%
피 2
 
2.5%
장 2
 
2.5%
이 2
 
2.5%
Other values (40) 48
59.3%
Common
ValueCountFrequency (%)
) 2
33.3%
( 2
33.3%
/ 1
16.7%
+ 1
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 81
93.1%
ASCII 6
 
6.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
국 7
 
8.6%
수 6
 
7.4%
짬 3
 
3.7%
뽕 3
 
3.7%
커 3
 
3.7%
한 3
 
3.7%
탕 2
 
2.5%
피 2
 
2.5%
장 2
 
2.5%
이 2
 
2.5%
Other values (40) 48
59.3%
ASCII
ValueCountFrequency (%)
) 2
33.3%
( 2
33.3%
/ 1
16.7%
+ 1
16.7%

가격2
Real number (ℝ)

MISSING 

Distinct12
Distinct (%)57.1%
Missing59
Missing (%)73.8%
Infinite0
Infinite (%)0.0%
Mean8280.9524
Minimum2000
Maximum25000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size852.0 B
2023-12-12T19:04:10.140497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2000
5-th percentile2500
Q16000
median6000
Q38000
95-th percentile25000
Maximum25000
Range23000
Interquartile range (IQR)2000

Descriptive statistics

Standard deviation6194.5637
Coefficient of variation (CV)0.74804967
Kurtosis3.913283
Mean8280.9524
Median Absolute Deviation (MAD)1100
Skewness2.08529
Sum173900
Variance38372619
MonotonicityNot monotonic
2023-12-12T19:04:10.231271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
6000 8
 
10.0%
10000 2
 
2.5%
25000 2
 
2.5%
7500 1
 
1.2%
8000 1
 
1.2%
15000 1
 
1.2%
5000 1
 
1.2%
4000 1
 
1.2%
7000 1
 
1.2%
4900 1
 
1.2%
Other values (2) 2
 
2.5%
(Missing) 59
73.8%
ValueCountFrequency (%)
2000 1
 
1.2%
2500 1
 
1.2%
4000 1
 
1.2%
4900 1
 
1.2%
5000 1
 
1.2%
6000 8
10.0%
7000 1
 
1.2%
7500 1
 
1.2%
8000 1
 
1.2%
10000 2
 
2.5%
ValueCountFrequency (%)
25000 2
 
2.5%
15000 1
 
1.2%
10000 2
 
2.5%
8000 1
 
1.2%
7500 1
 
1.2%
7000 1
 
1.2%
6000 8
10.0%
5000 1
 
1.2%
4900 1
 
1.2%
4000 1
 
1.2%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size772.0 B
Minimum2022-11-10 00:00:00
Maximum2022-11-10 00:00:00
2023-12-12T19:04:10.311208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:04:10.405700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-12T19:04:04.011865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:04:03.751825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:04:04.112098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:04:03.899922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T19:04:10.479550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번업종업소명주소(도로명새주소명기)연락처영업시작시간영업종료시간배달가능여부주차가능여부메뉴1가격1메뉴2가격2
연번1.0000.5731.0001.0001.0000.0000.3510.0000.2320.5840.3000.6890.384
업종0.5731.0001.0001.0001.0000.7710.8270.2960.2160.9700.8881.0000.530
업소명1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
주소(도로명새주소명기)1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
연락처1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
영업시작시간0.0000.7711.0001.0001.0001.0000.8400.0070.0000.9250.8340.9750.000
영업종료시간0.3510.8271.0001.0001.0000.8401.0000.4150.3870.8670.8440.5000.712
배달가능여부0.0000.2961.0001.0001.0000.0070.4151.0000.0000.4280.2970.0000.000
주차가능여부0.2320.2161.0001.0001.0000.0000.3870.0001.0000.0000.0000.3430.000
메뉴10.5840.9701.0001.0001.0000.9250.8670.4280.0001.0000.9181.0000.711
가격10.3000.8881.0001.0001.0000.8340.8440.2970.0000.9181.0000.0000.520
메뉴20.6891.0001.0001.0001.0000.9750.5000.0000.3431.0000.0001.0000.976
가격20.3840.5301.0001.0001.0000.0000.7120.0000.0000.7110.5200.9761.000
2023-12-12T19:04:10.631964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
주차가능여부업종가격1배달가능여부
주차가능여부1.0000.1520.0000.000
업종0.1521.0000.5400.212
가격10.0000.5401.0000.195
배달가능여부0.0000.2120.1951.000
2023-12-12T19:04:10.725558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번가격2업종배달가능여부주차가능여부가격1
연번1.000-0.4080.2040.0000.1640.086
가격2-0.4081.0000.4250.0000.0000.200
업종0.2040.4251.0000.2120.1520.540
배달가능여부0.0000.0000.2121.0000.0000.195
주차가능여부0.1640.0000.1520.0001.0000.000
가격10.0860.2000.5400.1950.0001.000

Missing values

2023-12-12T19:04:04.609873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T19:04:04.907264image/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.
2023-12-12T19:04:05.071737image/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

연번업종업소명주소(도로명새주소명기)연락처영업시작시간영업종료시간배달가능여부주차가능여부메뉴1가격1메뉴2가격2데이터기준일자
01기타외식성심당대전 중구 대종로480번길 15(은행동)042-256-411408:0022:00YY튀김소보로1600<NA><NA>2022-11-10
12중식옛날전통짜장대전 중구 동서대로 1208-5(태평동)042-532-449410:0021:00YY자장면4000<NA><NA>2022-11-10
23한식24시대전해장국대전 중구 우암로 12(선화동)042-255-106607:3022:00YN해장국5000<NA><NA>2022-11-10
34한식신삼정식당대전 중구 중교로11-1(대흥동)042-222-153310:0022:00NN동태찌개8000<NA><NA>2022-11-10
45한식동원식당대전 중구 중교로29-1(대흥동)042-252-362010:0022:00NN황태탕8000<NA><NA>2022-11-10
56한식청양칼국수대전 중구 대종로505번길31(선화동)042-255-563010:0022:00YN바지락칼국수6000<NA><NA>2022-11-10
67한식선화콩나물밥식당대전 중구 선화로119번길33(선화동)042-252-530510:4015:00NN콩나물밥5500<NA><NA>2022-11-10
78한식123식당대전 중구 선화로 119번길29(선화동)042-256-073511:3020:00YN백반5000<NA><NA>2022-11-10
89한식영빈관식당대전 중구 대종로 83(옥계동)042-286-878810:3020:30YN자장면5000<NA><NA>2022-11-10
910경양식아저씨돈까스대전 중구 중앙로 164길 22-7(은행동)042-221-659511:0021:30NN돈까스6500<NA><NA>2022-11-10
연번업종업소명주소(도로명새주소명기)연락처영업시작시간영업종료시간배달가능여부주차가능여부메뉴1가격1메뉴2가격2데이터기준일자
7071한식국수집대전 중구 동서대로 1208-7, 1층(태평동)042-535-527711:0021:00YY잔치국수2900비빔국수49002022-11-10
7172기타외식카페드홍대전 중구 보문로335번길 14-2(선화동, 1층)<NA>08:3019:30NY커피(take out)2000커피(매장)25002022-11-10
7273세탁업문화세탁소대전 중구 보문로337번길 22(선화동)042-221-090408:3019:00NN세탁료(양복상하)6000<NA><NA>2022-11-10
7374이미용업미미모헤어대전 중구 대종로587번길 43, 1층(선화동)042-485-542310:0018:00NY컷트10000<NA><NA>2022-11-10
7475기타외식커피드림대전 중구 동서대로 1304번길 56, 1층 101호(오류동)070-7526-813107:3018:30NY커피1500아이스커피20002022-11-10
7576중식라이라이대전 중구 대전천서로249-1, 1층(문창동)042-282-998511:0021:00NY자장면3000짬뽕60002022-11-10
7677이미용업렛미인머리하는날대전 중구 보문로20번길 34, 1층(문창동)<NA>09:0018:00NN컷트8000<NA><NA>2022-11-10
7778기타외식소담커피대전 중구 선화로22번길 25, 상가동 101호(용두동, 미르마을아파트)<NA>09:0022:00YN커피2000<NA><NA>2022-11-10
7879한식용두골대전 중구 동서대로1322번길 19-9(용두동)042-226-764512:0020:00NY된장찌개백반6000불고기백반60002022-11-10
7980한식대전 칼국수대전 중구 선화로 110, 1층(선화동)042-224-050111:3021:00NY김치칼국수6000얼큰이/순한칼국수60002022-11-10