Overview

Dataset statistics

Number of variables5
Number of observations178
Missing cells7
Missing cells (%)0.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory7.3 KiB
Average record size in memory41.7 B

Variable types

Numeric1
Categorical1
Text3

Dataset

Description전라남도 광양시에 설치된 집단급식소 신고현황에 대한 정보입니다.(식품위생법 제88조제1항) 업소명, 쇄지주소, 전화번호를 제공합니다.
Author전라남도 광양시
URLhttps://www.data.go.kr/data/15043289/fileData.do

Alerts

업종명 has constant value ""Constant
소재지전화 has 7 (3.9%) missing valuesMissing
연번 has unique valuesUnique
업소명 has unique valuesUnique

Reproduction

Analysis started2024-03-14 20:40:29.490045
Analysis finished2024-03-14 20:40:31.493691
Duration2 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct178
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean89.5
Minimum1
Maximum178
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.7 KiB
2024-03-15T05:40:32.022066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile9.85
Q145.25
median89.5
Q3133.75
95-th percentile169.15
Maximum178
Range177
Interquartile range (IQR)88.5

Descriptive statistics

Standard deviation51.528309
Coefficient of variation (CV)0.5757353
Kurtosis-1.2
Mean89.5
Median Absolute Deviation (MAD)44.5
Skewness0
Sum15931
Variance2655.1667
MonotonicityStrictly increasing
2024-03-15T05:40:32.845327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.6%
135 1
 
0.6%
115 1
 
0.6%
116 1
 
0.6%
117 1
 
0.6%
118 1
 
0.6%
119 1
 
0.6%
120 1
 
0.6%
121 1
 
0.6%
122 1
 
0.6%
Other values (168) 168
94.4%
ValueCountFrequency (%)
1 1
0.6%
2 1
0.6%
3 1
0.6%
4 1
0.6%
5 1
0.6%
6 1
0.6%
7 1
0.6%
8 1
0.6%
9 1
0.6%
10 1
0.6%
ValueCountFrequency (%)
178 1
0.6%
177 1
0.6%
176 1
0.6%
175 1
0.6%
174 1
0.6%
173 1
0.6%
172 1
0.6%
171 1
0.6%
170 1
0.6%
169 1
0.6%

업종명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
집단급식소
178 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
집단급식소 178
100.0%

Length

2024-03-15T05:40:33.385959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T05:40:33.735848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
집단급식소 178
100.0%

업소명
Text

UNIQUE 

Distinct178
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
2024-03-15T05:40:34.931911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length16
Mean length8.0224719
Min length4

Characters and Unicode

Total characters1428
Distinct characters245
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

Unique178 ?
Unique (%)100.0%

Sample

1st row오씨아이주식회사
2nd row조선내화 주식회사 광양공장
3rd row대한시멘트주식회사 제1공장
4th row태인초등학교
5th row(주)포스코아이씨티
ValueCountFrequency (%)
구내식당 5
 
2.4%
어린이집 5
 
2.4%
주식회사 5
 
2.4%
사)제철복지회 3
 
1.4%
광양시 3
 
1.4%
대한시멘트주식회사 2
 
1.0%
광양공장 2
 
1.0%
의료법인 2
 
1.0%
오씨아이주식회사 1
 
0.5%
느티나무요양원 1
 
0.5%
Other values (180) 180
86.1%
2024-03-15T05:40:36.263449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
이 71
 
5.0%
양 67
 
4.7%
광 65
 
4.6%
린 57
 
4.0%
집 55
 
3.9%
어 55
 
3.9%
교 53
 
3.7%
학 52
 
3.6%
등 37
 
2.6%
31
 
2.2%
Other values (235) 885
62.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1350
94.5%
Space Separator 31
 
2.2%
Close Punctuation 21
 
1.5%
Open Punctuation 20
 
1.4%
Uppercase Letter 4
 
0.3%
Decimal Number 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 71
 
5.3%
양 67
 
5.0%
광 65
 
4.8%
린 57
 
4.2%
집 55
 
4.1%
어 55
 
4.1%
교 53
 
3.9%
학 52
 
3.9%
등 37
 
2.7%
초 29
 
2.1%
Other values (226) 809
59.9%
Uppercase Letter
ValueCountFrequency (%)
Y 1
25.0%
A 1
25.0%
C 1
25.0%
M 1
25.0%
Decimal Number
ValueCountFrequency (%)
2 1
50.0%
1 1
50.0%
Space Separator
ValueCountFrequency (%)
31
100.0%
Close Punctuation
ValueCountFrequency (%)
) 21
100.0%
Open Punctuation
ValueCountFrequency (%)
( 20
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1350
94.5%
Common 74
 
5.2%
Latin 4
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 71
 
5.3%
양 67
 
5.0%
광 65
 
4.8%
린 57
 
4.2%
집 55
 
4.1%
어 55
 
4.1%
교 53
 
3.9%
학 52
 
3.9%
등 37
 
2.7%
초 29
 
2.1%
Other values (226) 809
59.9%
Common
ValueCountFrequency (%)
31
41.9%
) 21
28.4%
( 20
27.0%
2 1
 
1.4%
1 1
 
1.4%
Latin
ValueCountFrequency (%)
Y 1
25.0%
A 1
25.0%
C 1
25.0%
M 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1350
94.5%
ASCII 78
 
5.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
이 71
 
5.3%
양 67
 
5.0%
광 65
 
4.8%
린 57
 
4.2%
집 55
 
4.1%
어 55
 
4.1%
교 53
 
3.9%
학 52
 
3.9%
등 37
 
2.7%
초 29
 
2.1%
Other values (226) 809
59.9%
ASCII
ValueCountFrequency (%)
31
39.7%
) 21
26.9%
( 20
25.6%
2 1
 
1.3%
Y 1
 
1.3%
A 1
 
1.3%
C 1
 
1.3%
M 1
 
1.3%
1 1
 
1.3%

도로명주소
Text

Distinct175
Distinct (%)98.3%
Missing0
Missing (%)0.0%
Memory size1.5 KiB
2024-03-15T05:40:37.602465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length49
Median length40
Mean length27.280899
Min length18

Characters and Unicode

Total characters4856
Distinct characters203
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

Unique173 ?
Unique (%)97.2%

Sample

1st row전라남도 광양시 산업로 109 (태인동)
2nd row전라남도 광양시 산업로 55 (태인동)
3rd row전라남도 광양시 태인3길 33, 1층중 1층 일부층 (태인동)
4th row전라남도 광양시 태인길 95 (태인동, 태인초등학교)
5th row전라남도 광양시 태인4길 20 (태인동)
ValueCountFrequency (%)
전라남도 178
 
16.5%
광양시 178
 
16.5%
광양읍 55
 
5.1%
1층 30
 
2.8%
중동 28
 
2.6%
일부 27
 
2.5%
금호동 19
 
1.8%
태인동 14
 
1.3%
마동 14
 
1.3%
2층중 14
 
1.3%
Other values (337) 520
48.3%
2024-03-15T05:40:39.310978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
899
18.5%
광 263
 
5.4%
양 244
 
5.0%
1 184
 
3.8%
도 184
 
3.8%
남 183
 
3.8%
시 181
 
3.7%
전 180
 
3.7%
라 179
 
3.7%
( 146
 
3.0%
Other values (193) 2213
45.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2879
59.3%
Space Separator 899
 
18.5%
Decimal Number 669
 
13.8%
Open Punctuation 146
 
3.0%
Close Punctuation 146
 
3.0%
Other Punctuation 73
 
1.5%
Dash Punctuation 38
 
0.8%
Uppercase Letter 6
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
광 263
 
9.1%
양 244
 
8.5%
도 184
 
6.4%
남 183
 
6.4%
시 181
 
6.3%
전 180
 
6.3%
라 179
 
6.2%
층 142
 
4.9%
동 124
 
4.3%
중 119
 
4.1%
Other values (173) 1080
37.5%
Decimal Number
ValueCountFrequency (%)
1 184
27.5%
2 104
15.5%
3 64
 
9.6%
5 59
 
8.8%
6 59
 
8.8%
4 55
 
8.2%
0 44
 
6.6%
7 37
 
5.5%
9 36
 
5.4%
8 27
 
4.0%
Uppercase Letter
ValueCountFrequency (%)
O 2
33.3%
B 1
16.7%
P 1
16.7%
S 1
16.7%
C 1
16.7%
Space Separator
ValueCountFrequency (%)
899
100.0%
Open Punctuation
ValueCountFrequency (%)
( 146
100.0%
Close Punctuation
ValueCountFrequency (%)
) 146
100.0%
Other Punctuation
ValueCountFrequency (%)
, 73
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 38
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2879
59.3%
Common 1971
40.6%
Latin 6
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
광 263
 
9.1%
양 244
 
8.5%
도 184
 
6.4%
남 183
 
6.4%
시 181
 
6.3%
전 180
 
6.3%
라 179
 
6.2%
층 142
 
4.9%
동 124
 
4.3%
중 119
 
4.1%
Other values (173) 1080
37.5%
Common
ValueCountFrequency (%)
899
45.6%
1 184
 
9.3%
( 146
 
7.4%
) 146
 
7.4%
2 104
 
5.3%
, 73
 
3.7%
3 64
 
3.2%
5 59
 
3.0%
6 59
 
3.0%
4 55
 
2.8%
Other values (5) 182
 
9.2%
Latin
ValueCountFrequency (%)
O 2
33.3%
B 1
16.7%
P 1
16.7%
S 1
16.7%
C 1
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2879
59.3%
ASCII 1977
40.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
899
45.5%
1 184
 
9.3%
( 146
 
7.4%
) 146
 
7.4%
2 104
 
5.3%
, 73
 
3.7%
3 64
 
3.2%
5 59
 
3.0%
6 59
 
3.0%
4 55
 
2.8%
Other values (10) 188
 
9.5%
Hangul
ValueCountFrequency (%)
광 263
 
9.1%
양 244
 
8.5%
도 184
 
6.4%
남 183
 
6.4%
시 181
 
6.3%
전 180
 
6.3%
라 179
 
6.2%
층 142
 
4.9%
동 124
 
4.3%
중 119
 
4.1%
Other values (173) 1080
37.5%

소재지전화
Text

MISSING 

Distinct170
Distinct (%)99.4%
Missing7
Missing (%)3.9%
Memory size1.5 KiB
2024-03-15T05:40:40.323705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.023392
Min length12

Characters and Unicode

Total characters2056
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

Unique169 ?
Unique (%)98.8%

Sample

1st row061-798-6097
2nd row061-798-8114
3rd row061-798-8510
4th row061-792-5077
5th row061-798-2021
ValueCountFrequency (%)
061-792-0777 2
 
1.2%
433 1
 
0.6%
061-793-9335 1
 
0.6%
061-798-6097 1
 
0.6%
061-763-0088 1
 
0.6%
061-792-0501 1
 
0.6%
061-763-7621 1
 
0.6%
061-792-3841 1
 
0.6%
061-762-6710 1
 
0.6%
070-4009 1
 
0.6%
Other values (162) 162
93.6%
2024-03-15T05:40:41.480958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 342
16.6%
0 329
16.0%
1 299
14.5%
6 280
13.6%
7 254
12.4%
9 155
7.5%
2 121
 
5.9%
8 84
 
4.1%
3 80
 
3.9%
4 59
 
2.9%
Other values (2) 53
 
2.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1712
83.3%
Dash Punctuation 342
 
16.6%
Space Separator 2
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 329
19.2%
1 299
17.5%
6 280
16.4%
7 254
14.8%
9 155
9.1%
2 121
 
7.1%
8 84
 
4.9%
3 80
 
4.7%
4 59
 
3.4%
5 51
 
3.0%
Dash Punctuation
ValueCountFrequency (%)
- 342
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2056
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 342
16.6%
0 329
16.0%
1 299
14.5%
6 280
13.6%
7 254
12.4%
9 155
7.5%
2 121
 
5.9%
8 84
 
4.1%
3 80
 
3.9%
4 59
 
2.9%
Other values (2) 53
 
2.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2056
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 342
16.6%
0 329
16.0%
1 299
14.5%
6 280
13.6%
7 254
12.4%
9 155
7.5%
2 121
 
5.9%
8 84
 
4.1%
3 80
 
3.9%
4 59
 
2.9%
Other values (2) 53
 
2.6%

Interactions

2024-03-15T05:40:30.153685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Missing values

2024-03-15T05:40:30.752557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-15T05:40:31.280932image/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

연번업종명업소명도로명주소소재지전화
01집단급식소오씨아이주식회사전라남도 광양시 산업로 109 (태인동)061-798-6097
12집단급식소조선내화 주식회사 광양공장전라남도 광양시 산업로 55 (태인동)061-798-8114
23집단급식소대한시멘트주식회사 제1공장전라남도 광양시 태인3길 33, 1층중 1층 일부층 (태인동)061-798-8510
34집단급식소태인초등학교전라남도 광양시 태인길 95 (태인동, 태인초등학교)061-792-5077
45집단급식소(주)포스코아이씨티전라남도 광양시 태인4길 20 (태인동)061-798-2021
56집단급식소옥룡초등학교전라남도 광양시 옥룡면 신재로 607061-762-8909
67집단급식소광양마로초등학교전라남도 광양시 광양읍 와룡길 60 (4층중1층일부)061-762-1702
78집단급식소다압초등학교전라남도 광양시 다압면 항동3길 10 (다압초등학교)061-772-4087
89집단급식소(사)제철복지회전라남도 광양시 희망1길 69 (금호동)061-799-3152
910집단급식소(사)제철복지회 백운산수련관전라남도 광양시 옥룡면 약수제단길 154 ((4층중 2층 일부))061-790-0650
연번업종명업소명도로명주소소재지전화
168169집단급식소다솜어린이집전라남도 광양시 중마용소길 30-5, 2층중 1층 일부 (중동)061-793-4229
169170집단급식소탑요양병원전라남도 광양시 광양읍 대림오성로 63, 4층중 2층 일부061-913-8000
170171집단급식소사)제철복지회 율촌전라남도 광양시 광양읍 율촌산단8로 45, 3층중 1층 일부061-790-1575
171172집단급식소광양햇살학교전라남도 광양시 옥룡면 옥동길 14, 3층중 1층 일부061-798-6413
172173집단급식소광양푸르지오더퍼스트어린이집전라남도 광양시 성황수동로 22 (성황동, 광양푸르지오더퍼스트)<NA>
173174집단급식소월드마린센터 구내식당전라남도 광양시 항만대로 465, 월드마린센터 지하1층 일부 (황길동)061-797-4341
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