Overview

Dataset statistics

Number of variables5
Number of observations142
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.8 KiB
Average record size in memory41.9 B

Variable types

Numeric1
Text4

Dataset

Description광주광역시에서 지정한 모범음식점 현황에 대한 데이터로 업소명, 소재지, 전화번호, 주메뉴의 정보를 제공합니다.
Author광주광역시
URLhttps://www.data.go.kr/data/3077702/fileData.do

Alerts

연번 has unique valuesUnique
소재지(도로명) has unique valuesUnique
업소전화번호 has unique valuesUnique

Reproduction

Analysis started2023-12-12 05:28:21.000548
Analysis finished2023-12-12 05:28:21.765952
Duration0.77 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct142
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean71.5
Minimum1
Maximum142
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2023-12-12T14:28:21.878971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile8.05
Q136.25
median71.5
Q3106.75
95-th percentile134.95
Maximum142
Range141
Interquartile range (IQR)70.5

Descriptive statistics

Standard deviation41.135953
Coefficient of variation (CV)0.57532802
Kurtosis-1.2
Mean71.5
Median Absolute Deviation (MAD)35.5
Skewness0
Sum10153
Variance1692.1667
MonotonicityStrictly increasing
2023-12-12T14:28:22.088886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.7%
99 1
 
0.7%
93 1
 
0.7%
94 1
 
0.7%
95 1
 
0.7%
96 1
 
0.7%
97 1
 
0.7%
98 1
 
0.7%
100 1
 
0.7%
91 1
 
0.7%
Other values (132) 132
93.0%
ValueCountFrequency (%)
1 1
0.7%
2 1
0.7%
3 1
0.7%
4 1
0.7%
5 1
0.7%
6 1
0.7%
7 1
0.7%
8 1
0.7%
9 1
0.7%
10 1
0.7%
ValueCountFrequency (%)
142 1
0.7%
141 1
0.7%
140 1
0.7%
139 1
0.7%
138 1
0.7%
137 1
0.7%
136 1
0.7%
135 1
0.7%
134 1
0.7%
133 1
0.7%

업소명
Text

Distinct137
Distinct (%)96.5%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2023-12-12T14:28:22.397580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length13
Mean length5.5704225
Min length1

Characters and Unicode

Total characters791
Distinct characters243
Distinct categories5 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique134 ?
Unique (%)94.4%

Sample

1st row고려조삼계탕
2nd row고흥장어나라
3rd row관가
4th row광양숯불구이지산점
5th row구수숯불갈비
ValueCountFrequency (%)
신락원 4
 
2.7%
올능이능이버섯백숙 2
 
1.3%
등촌 2
 
1.3%
고려조삼계탕 2
 
1.3%
자미원 1
 
0.7%
무등골한우식육식당 1
 
0.7%
한국 1
 
0.7%
피가로(전남대점 1
 
0.7%
풍천애장어 1
 
0.7%
뼈다귀천국 1
 
0.7%
Other values (133) 133
89.3%
2023-12-12T14:28:22.866933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
한 18
 
2.3%
이 17
 
2.1%
원 16
 
2.0%
점 16
 
2.0%
우 15
 
1.9%
가 14
 
1.8%
식 13
 
1.6%
탕 12
 
1.5%
( 11
 
1.4%
장 11
 
1.4%
Other values (233) 648
81.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 761
96.2%
Open Punctuation 11
 
1.4%
Close Punctuation 11
 
1.4%
Space Separator 7
 
0.9%
Uppercase Letter 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
한 18
 
2.4%
이 17
 
2.2%
원 16
 
2.1%
점 16
 
2.1%
우 15
 
2.0%
가 14
 
1.8%
식 13
 
1.7%
탕 12
 
1.6%
장 11
 
1.4%
당 11
 
1.4%
Other values (229) 618
81.2%
Open Punctuation
ValueCountFrequency (%)
( 11
100.0%
Close Punctuation
ValueCountFrequency (%)
) 11
100.0%
Space Separator
ValueCountFrequency (%)
7
100.0%
Uppercase Letter
ValueCountFrequency (%)
X 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 759
96.0%
Common 29
 
3.7%
Han 2
 
0.3%
Latin 1
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
한 18
 
2.4%
이 17
 
2.2%
원 16
 
2.1%
점 16
 
2.1%
우 15
 
2.0%
가 14
 
1.8%
식 13
 
1.7%
탕 12
 
1.6%
장 11
 
1.4%
당 11
 
1.4%
Other values (227) 616
81.2%
Common
ValueCountFrequency (%)
( 11
37.9%
) 11
37.9%
7
24.1%
Han
ValueCountFrequency (%)
富 1
50.0%
園 1
50.0%
Latin
ValueCountFrequency (%)
X 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 759
96.0%
ASCII 30
 
3.8%
CJK 2
 
0.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
한 18
 
2.4%
이 17
 
2.2%
원 16
 
2.1%
점 16
 
2.1%
우 15
 
2.0%
가 14
 
1.8%
식 13
 
1.7%
탕 12
 
1.6%
장 11
 
1.4%
당 11
 
1.4%
Other values (227) 616
81.2%
ASCII
ValueCountFrequency (%)
( 11
36.7%
) 11
36.7%
7
23.3%
X 1
 
3.3%
CJK
ValueCountFrequency (%)
富 1
50.0%
園 1
50.0%

소재지(도로명)
Text

UNIQUE 

Distinct142
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2023-12-12T14:28:23.326601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length47
Median length35
Mean length28.119718
Min length21

Characters and Unicode

Total characters3993
Distinct characters166
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique142 ?
Unique (%)100.0%

Sample

1st row광주광역시 동구 금남로 231 (금남로2가,(점포21개))
2nd row광주광역시 동구 필문대로191번길 5-10 (산수동)
3rd row광주광역시 동구 의재로96번길 18 (소태동)
4th row광주광역시 동구 필문대로 229 (지산동)
5th row광주광역시 동구 필문대로191번길 15-10 (산수동,(1층))
ValueCountFrequency (%)
광주광역시 142
 
18.9%
북구 56
 
7.4%
광산구 30
 
4.0%
동구 27
 
3.6%
1층 26
 
3.5%
서구 21
 
2.8%
용봉동 10
 
1.3%
2층 8
 
1.1%
남구 8
 
1.1%
일곡동 5
 
0.7%
Other values (334) 420
55.8%
2023-12-12T14:28:24.018192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
611
 
15.3%
광 320
 
8.0%
) 189
 
4.7%
( 189
 
4.7%
1 189
 
4.7%
동 171
 
4.3%
로 147
 
3.7%
구 147
 
3.7%
주 144
 
3.6%
시 143
 
3.6%
Other values (156) 1743
43.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2214
55.4%
Decimal Number 647
 
16.2%
Space Separator 611
 
15.3%
Close Punctuation 189
 
4.7%
Open Punctuation 189
 
4.7%
Other Punctuation 107
 
2.7%
Dash Punctuation 34
 
0.9%
Uppercase Letter 1
 
< 0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
광 320
14.5%
동 171
 
7.7%
로 147
 
6.6%
구 147
 
6.6%
주 144
 
6.5%
시 143
 
6.5%
역 142
 
6.4%
층 88
 
4.0%
길 62
 
2.8%
북 61
 
2.8%
Other values (138) 789
35.6%
Decimal Number
ValueCountFrequency (%)
1 189
29.2%
2 112
17.3%
3 59
 
9.1%
0 49
 
7.6%
4 48
 
7.4%
6 48
 
7.4%
5 48
 
7.4%
7 43
 
6.6%
9 27
 
4.2%
8 24
 
3.7%
Other Punctuation
ValueCountFrequency (%)
, 105
98.1%
. 2
 
1.9%
Space Separator
ValueCountFrequency (%)
611
100.0%
Close Punctuation
ValueCountFrequency (%)
) 189
100.0%
Open Punctuation
ValueCountFrequency (%)
( 189
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 34
100.0%
Uppercase Letter
ValueCountFrequency (%)
B 1
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2214
55.4%
Common 1778
44.5%
Latin 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
광 320
14.5%
동 171
 
7.7%
로 147
 
6.6%
구 147
 
6.6%
주 144
 
6.5%
시 143
 
6.5%
역 142
 
6.4%
층 88
 
4.0%
길 62
 
2.8%
북 61
 
2.8%
Other values (138) 789
35.6%
Common
ValueCountFrequency (%)
611
34.4%
) 189
 
10.6%
( 189
 
10.6%
1 189
 
10.6%
2 112
 
6.3%
, 105
 
5.9%
3 59
 
3.3%
0 49
 
2.8%
4 48
 
2.7%
6 48
 
2.7%
Other values (7) 179
 
10.1%
Latin
ValueCountFrequency (%)
B 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2214
55.4%
ASCII 1779
44.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
611
34.3%
) 189
 
10.6%
( 189
 
10.6%
1 189
 
10.6%
2 112
 
6.3%
, 105
 
5.9%
3 59
 
3.3%
0 49
 
2.8%
4 48
 
2.7%
6 48
 
2.7%
Other values (8) 180
 
10.1%
Hangul
ValueCountFrequency (%)
광 320
14.5%
동 171
 
7.7%
로 147
 
6.6%
구 147
 
6.6%
주 144
 
6.5%
시 143
 
6.5%
역 142
 
6.4%
층 88
 
4.0%
길 62
 
2.8%
북 61
 
2.8%
Other values (138) 789
35.6%

업소전화번호
Text

UNIQUE 

Distinct142
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2023-12-12T14:28:24.339030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters1704
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

Unique142 ?
Unique (%)100.0%

Sample

1st row062-224-2525
2nd row062-223-9609
3rd row062-228-0027
4th row062-226-8080
5th row062-225-4296
ValueCountFrequency (%)
062-224-2525 1
 
0.7%
062-515-9012 1
 
0.7%
062-525-1107 1
 
0.7%
062-573-6040 1
 
0.7%
062-575-8885 1
 
0.7%
062-266-0385 1
 
0.7%
062-574-8220 1
 
0.7%
062-262-7237 1
 
0.7%
062-512-3302 1
 
0.7%
062-528-3335 1
 
0.7%
Other values (132) 132
93.0%
2023-12-12T14:28:24.809027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 305
17.9%
- 284
16.7%
0 228
13.4%
6 224
13.1%
5 130
7.6%
3 105
 
6.2%
7 95
 
5.6%
9 95
 
5.6%
8 83
 
4.9%
1 83
 
4.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1420
83.3%
Dash Punctuation 284
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 305
21.5%
0 228
16.1%
6 224
15.8%
5 130
9.2%
3 105
 
7.4%
7 95
 
6.7%
9 95
 
6.7%
8 83
 
5.8%
1 83
 
5.8%
4 72
 
5.1%
Dash Punctuation
ValueCountFrequency (%)
- 284
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1704
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 305
17.9%
- 284
16.7%
0 228
13.4%
6 224
13.1%
5 130
7.6%
3 105
 
6.2%
7 95
 
5.6%
9 95
 
5.6%
8 83
 
4.9%
1 83
 
4.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1704
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 305
17.9%
- 284
16.7%
0 228
13.4%
6 224
13.1%
5 130
7.6%
3 105
 
6.2%
7 95
 
5.6%
9 95
 
5.6%
8 83
 
4.9%
1 83
 
4.9%

주된음식종류
Text

Distinct97
Distinct (%)68.3%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2023-12-12T14:28:25.108533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length4.6830986
Min length2

Characters and Unicode

Total characters665
Distinct characters138
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

Unique76 ?
Unique (%)53.5%

Sample

1st row삼계탕
2nd row장어구이
3rd row통오리구이
4th row숯불구이
5th row숯불갈비
ValueCountFrequency (%)
한정식 8
 
4.7%
돼지갈비 7
 
4.1%
꽃등심 6
 
3.5%
삼겹살 5
 
2.9%
샤브샤브 4
 
2.3%
삼계탕 4
 
2.3%
짜장면 4
 
2.3%
등심 4
 
2.3%
소고기 4
 
2.3%
생고기 3
 
1.7%
Other values (94) 123
71.5%
2023-12-12T14:28:25.567351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
, 35
 
5.3%
30
 
4.5%
비 28
 
4.2%
탕 27
 
4.1%
식 23
 
3.5%
갈 21
 
3.2%
정 17
 
2.6%
한 15
 
2.3%
회 15
 
2.3%
고 14
 
2.1%
Other values (128) 440
66.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 596
89.6%
Other Punctuation 35
 
5.3%
Space Separator 30
 
4.5%
Open Punctuation 2
 
0.3%
Close Punctuation 2
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
비 28
 
4.7%
탕 27
 
4.5%
식 23
 
3.9%
갈 21
 
3.5%
정 17
 
2.9%
한 15
 
2.5%
회 15
 
2.5%
고 14
 
2.3%
기 14
 
2.3%
지 12
 
2.0%
Other values (124) 410
68.8%
Other Punctuation
ValueCountFrequency (%)
, 35
100.0%
Space Separator
ValueCountFrequency (%)
30
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 596
89.6%
Common 69
 
10.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
비 28
 
4.7%
탕 27
 
4.5%
식 23
 
3.9%
갈 21
 
3.5%
정 17
 
2.9%
한 15
 
2.5%
회 15
 
2.5%
고 14
 
2.3%
기 14
 
2.3%
지 12
 
2.0%
Other values (124) 410
68.8%
Common
ValueCountFrequency (%)
, 35
50.7%
30
43.5%
( 2
 
2.9%
) 2
 
2.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 596
89.6%
ASCII 69
 
10.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
, 35
50.7%
30
43.5%
( 2
 
2.9%
) 2
 
2.9%
Hangul
ValueCountFrequency (%)
비 28
 
4.7%
탕 27
 
4.5%
식 23
 
3.9%
갈 21
 
3.5%
정 17
 
2.9%
한 15
 
2.5%
회 15
 
2.5%
고 14
 
2.3%
기 14
 
2.3%
지 12
 
2.0%
Other values (124) 410
68.8%

Interactions

2023-12-12T14:28:21.386654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T14:28:25.685751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번주된음식종류
연번1.0000.448
주된음식종류0.4481.000

Missing values

2023-12-12T14:28:21.525786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T14:28:21.714307image/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

연번업소명소재지(도로명)업소전화번호주된음식종류
01고려조삼계탕광주광역시 동구 금남로 231 (금남로2가,(점포21개))062-224-2525삼계탕
12고흥장어나라광주광역시 동구 필문대로191번길 5-10 (산수동)062-223-9609장어구이
23관가광주광역시 동구 의재로96번길 18 (소태동)062-228-0027통오리구이
34광양숯불구이지산점광주광역시 동구 필문대로 229 (지산동)062-226-8080숯불구이
45구수숯불갈비광주광역시 동구 필문대로191번길 15-10 (산수동,(1층))062-225-4296숯불갈비
56동명가원식당광주광역시 동구 필문대로 230 (동명동,(1층))062-232-8877꽃등심
67동원게장백반광주광역시 동구 지호로 128 (지산동,(1층))062-223-7200게장백반
78동해바다광주광역시 동구 충장로46번길 6-1 (충장로5가)062-224-4844회정식
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