Overview

Dataset statistics

Number of variables3
Number of observations100
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.6 KiB
Average record size in memory26.3 B

Variable types

Numeric1
Text2

Dataset

Description광주광역시 내 식당 증 외국어메뉴판 보급 업소에 대한 데이터입니다. 상호명, 소재지(도로명주소) 등의 항목의 내용을 제공합니다.
Author광주광역시
URLhttps://www.data.go.kr/data/3056868/fileData.do

Alerts

연번 has unique valuesUnique

Reproduction

Analysis started2024-04-06 08:13:55.404052
Analysis finished2024-04-06 08:13:57.747413
Duration2.34 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean50.5
Minimum1
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-04-06T17:13:57.912573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile5.95
Q125.75
median50.5
Q375.25
95-th percentile95.05
Maximum100
Range99
Interquartile range (IQR)49.5

Descriptive statistics

Standard deviation29.011492
Coefficient of variation (CV)0.57448499
Kurtosis-1.2
Mean50.5
Median Absolute Deviation (MAD)25
Skewness0
Sum5050
Variance841.66667
MonotonicityStrictly increasing
2024-04-06T17:13:58.337795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.0%
65 1
 
1.0%
75 1
 
1.0%
74 1
 
1.0%
73 1
 
1.0%
72 1
 
1.0%
71 1
 
1.0%
70 1
 
1.0%
69 1
 
1.0%
68 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
1 1
1.0%
2 1
1.0%
3 1
1.0%
4 1
1.0%
5 1
1.0%
6 1
1.0%
7 1
1.0%
8 1
1.0%
9 1
1.0%
10 1
1.0%
ValueCountFrequency (%)
100 1
1.0%
99 1
1.0%
98 1
1.0%
97 1
1.0%
96 1
1.0%
95 1
1.0%
94 1
1.0%
93 1
1.0%
92 1
1.0%
91 1
1.0%

상호명
Text

Distinct99
Distinct (%)99.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2024-04-06T17:13:58.946076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length9
Mean length5.07
Min length1

Characters and Unicode

Total characters507
Distinct characters212
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

Unique98 ?
Unique (%)98.0%

Sample

1st row광동진씨
2nd row재주당 본점
3rd row장터
4th row여자만
5th row화롯불
ValueCountFrequency (%)
고려조삼계탕 2
 
1.9%
청원모밀 2
 
1.9%
칠산바다 1
 
1.0%
하남낙지마당 1
 
1.0%
큰집나주곰탕 1
 
1.0%
쿠우쿠우광주하남점 1
 
1.0%
청정바다 1
 
1.0%
임가네일반음식점 1
 
1.0%
궁 1
 
1.0%
산골갈비탕 1
 
1.0%
Other values (91) 91
88.3%
2024-04-06T17:14:00.021845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
점 15
 
3.0%
우 12
 
2.4%
가 11
 
2.2%
탕 10
 
2.0%
한 8
 
1.6%
이 8
 
1.6%
대 8
 
1.6%
수 8
 
1.6%
원 7
 
1.4%
주 7
 
1.4%
Other values (202) 413
81.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 484
95.5%
Open Punctuation 5
 
1.0%
Close Punctuation 5
 
1.0%
Uppercase Letter 4
 
0.8%
Decimal Number 4
 
0.8%
Space Separator 3
 
0.6%
Other Punctuation 1
 
0.2%
Lowercase Letter 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
점 15
 
3.1%
우 12
 
2.5%
가 11
 
2.3%
탕 10
 
2.1%
한 8
 
1.7%
이 8
 
1.7%
대 8
 
1.7%
수 8
 
1.7%
원 7
 
1.4%
주 7
 
1.4%
Other values (191) 390
80.6%
Uppercase Letter
ValueCountFrequency (%)
L 2
50.0%
U 1
25.0%
F 1
25.0%
Decimal Number
ValueCountFrequency (%)
4 2
50.0%
3 1
25.0%
2 1
25.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%
Space Separator
ValueCountFrequency (%)
3
100.0%
Other Punctuation
ValueCountFrequency (%)
' 1
100.0%
Lowercase Letter
ValueCountFrequency (%)
s 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 483
95.3%
Common 18
 
3.6%
Latin 5
 
1.0%
Han 1
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
점 15
 
3.1%
우 12
 
2.5%
가 11
 
2.3%
탕 10
 
2.1%
한 8
 
1.7%
이 8
 
1.7%
대 8
 
1.7%
수 8
 
1.7%
원 7
 
1.4%
주 7
 
1.4%
Other values (190) 389
80.5%
Common
ValueCountFrequency (%)
( 5
27.8%
) 5
27.8%
3
16.7%
4 2
 
11.1%
' 1
 
5.6%
3 1
 
5.6%
2 1
 
5.6%
Latin
ValueCountFrequency (%)
L 2
40.0%
U 1
20.0%
F 1
20.0%
s 1
20.0%
Han
ValueCountFrequency (%)
愛 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 483
95.3%
ASCII 23
 
4.5%
CJK 1
 
0.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
점 15
 
3.1%
우 12
 
2.5%
가 11
 
2.3%
탕 10
 
2.1%
한 8
 
1.7%
이 8
 
1.7%
대 8
 
1.7%
수 8
 
1.7%
원 7
 
1.4%
주 7
 
1.4%
Other values (190) 389
80.5%
ASCII
ValueCountFrequency (%)
( 5
21.7%
) 5
21.7%
3
13.0%
L 2
 
8.7%
4 2
 
8.7%
U 1
 
4.3%
F 1
 
4.3%
' 1
 
4.3%
3 1
 
4.3%
s 1
 
4.3%
CJK
ValueCountFrequency (%)
愛 1
100.0%

소재지
Text

Distinct98
Distinct (%)98.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2024-04-06T17:14:00.716657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length21.5
Mean length13.64
Min length9

Characters and Unicode

Total characters1364
Distinct characters95
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

Unique97 ?
Unique (%)97.0%

Sample

1st row동구 서석동 10-28
2nd row동구 동명동 143-33
3rd row동구 서석동 468-9
4th row동구 서석동 469-4
5th row동구 서석동 470-32
ValueCountFrequency (%)
광산구 32
 
10.1%
서구 29
 
9.2%
남구 19
 
6.0%
동구 17
 
5.4%
1층 7
 
2.2%
서석동 6
 
1.9%
지산동 6
 
1.9%
금화로 5
 
1.6%
노대동 5
 
1.6%
광산로29번길 4
 
1.3%
Other values (154) 186
58.9%
2024-04-06T17:14:01.744290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
218
 
16.0%
구 101
 
7.4%
1 74
 
5.4%
2 65
 
4.8%
동 64
 
4.7%
로 55
 
4.0%
- 49
 
3.6%
산 47
 
3.4%
3 42
 
3.1%
0 41
 
3.0%
Other values (85) 608
44.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 670
49.1%
Decimal Number 400
29.3%
Space Separator 218
 
16.0%
Dash Punctuation 49
 
3.6%
Other Punctuation 11
 
0.8%
Close Punctuation 8
 
0.6%
Open Punctuation 8
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 101
15.1%
동 64
 
9.6%
로 55
 
8.2%
산 47
 
7.0%
광 39
 
5.8%
길 35
 
5.2%
서 35
 
5.2%
번 33
 
4.9%
남 19
 
2.8%
층 14
 
2.1%
Other values (70) 228
34.0%
Decimal Number
ValueCountFrequency (%)
1 74
18.5%
2 65
16.2%
3 42
10.5%
0 41
10.2%
6 38
9.5%
5 36
9.0%
4 33
8.2%
7 26
 
6.5%
8 24
 
6.0%
9 21
 
5.2%
Space Separator
ValueCountFrequency (%)
218
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 49
100.0%
Other Punctuation
ValueCountFrequency (%)
, 11
100.0%
Close Punctuation
ValueCountFrequency (%)
) 8
100.0%
Open Punctuation
ValueCountFrequency (%)
( 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 694
50.9%
Hangul 670
49.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 101
15.1%
동 64
 
9.6%
로 55
 
8.2%
산 47
 
7.0%
광 39
 
5.8%
길 35
 
5.2%
서 35
 
5.2%
번 33
 
4.9%
남 19
 
2.8%
층 14
 
2.1%
Other values (70) 228
34.0%
Common
ValueCountFrequency (%)
218
31.4%
1 74
 
10.7%
2 65
 
9.4%
- 49
 
7.1%
3 42
 
6.1%
0 41
 
5.9%
6 38
 
5.5%
5 36
 
5.2%
4 33
 
4.8%
7 26
 
3.7%
Other values (5) 72
 
10.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 694
50.9%
Hangul 670
49.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
218
31.4%
1 74
 
10.7%
2 65
 
9.4%
- 49
 
7.1%
3 42
 
6.1%
0 41
 
5.9%
6 38
 
5.5%
5 36
 
5.2%
4 33
 
4.8%
7 26
 
3.7%
Other values (5) 72
 
10.4%
Hangul
ValueCountFrequency (%)
구 101
15.1%
동 64
 
9.6%
로 55
 
8.2%
산 47
 
7.0%
광 39
 
5.8%
길 35
 
5.2%
서 35
 
5.2%
번 33
 
4.9%
남 19
 
2.8%
층 14
 
2.1%
Other values (70) 228
34.0%

Interactions

2024-04-06T17:13:57.266134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-06T17:14:02.017300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번상호명소재지
연번1.0000.9401.000
상호명0.9401.0000.997
소재지1.0000.9971.000

Missing values

2024-04-06T17:13:57.546928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-06T17:13:57.691799image/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

연번상호명소재지
01광동진씨동구 서석동 10-28
12재주당 본점동구 동명동 143-33
23장터동구 서석동 468-9
34여자만동구 서석동 469-4
45화롯불동구 서석동 470-32
56서석식당동구 서석동 97-43
67향루동구 서석동 470-10
78교촌치킨동구 지산동 500
89마쏘라까망베르동구 지산동 500
910밥's동구 지산동 500
연번상호명소재지
9091보향미광산구 첨단중앙로124번길41, 1층
9192상무초밥첨단점광산구 첨단중앙로106번길 37, 가동 1층
9293신락원광산구 풍영로200번길9
9394해궁광산구 풍영로229번길 53
9495(유)황솔촌수완점광산구 장신로19번안길23
9596(주)웰빙마을수완점광산구 임방울대로 261 (2층)
9697달봉이회수산광산구 첨단중앙로152번길 31-16
9798구수한식당광산구 광산로 67번길 7
9899밥FULL호남대점광산구 선운로 2
99100숙성된감자탕광산구 장신로 266번길 8