Overview

Dataset statistics

Number of variables5
Number of observations164
Missing cells12
Missing cells (%)1.5%
Duplicate rows1
Duplicate rows (%)0.6%
Total size in memory6.5 KiB
Average record size in memory40.8 B

Variable types

Categorical1
Text3
DateTime1

Dataset

Description충청남도 공주시 결식아동 지정 급식소에 대한 데이터로 (읍면동, 가맹점명, 전화번호, 주소) 등의 항목을 제공합니다.
Author충청남도
URLhttps://alldam.chungnam.go.kr/index.chungnam?menuCd=DOM_000000201001001001&st=&cds=&orgCd=&apiType=&isOpen=Y&pageIndex=442&beforeMenuCd=DOM_000000201001001000&publicdatapk=3084483

Alerts

데이터기준일자 has constant value ""Constant
Dataset has 1 (0.6%) duplicate rowsDuplicates
전화번호 has 12 (7.3%) missing valuesMissing

Reproduction

Analysis started2024-01-09 22:38:38.886291
Analysis finished2024-01-09 22:38:39.458537
Duration0.57 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

읍면동
Categorical

Distinct17
Distinct (%)10.4%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
신관동
42 
웅진동
31 
중학동
15 
유구읍
10 
옥룡동
9 
Other values (12)
57 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
신관동 42
25.6%
웅진동 31
18.9%
중학동 15
 
9.1%
유구읍 10
 
6.1%
옥룡동 9
 
5.5%
의당면 8
 
4.9%
금학동 7
 
4.3%
반포면 7
 
4.3%
계룡면 6
 
3.7%
사곡면 5
 
3.0%
Other values (7) 24
14.6%

Length

2024-01-10T07:38:39.512955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
신관동 42
25.6%
웅진동 31
18.9%
중학동 15
 
9.1%
유구읍 10
 
6.1%
옥룡동 9
 
5.5%
의당면 8
 
4.9%
금학동 7
 
4.3%
반포면 7
 
4.3%
계룡면 6
 
3.7%
사곡면 5
 
3.0%
Other values (7) 24
14.6%

가맹점명
Text

Distinct156
Distinct (%)95.1%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
2024-01-10T07:38:39.719917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length12
Mean length7.4268293
Min length2

Characters and Unicode

Total characters1218
Distinct characters211
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

Unique148 ?
Unique (%)90.2%

Sample

1st row주식회사 계룡산오마트
2nd row백화마트
3rd row경천할인마트
4th row장순루
5th row계룡농협하나로마트
ValueCountFrequency (%)
공주마트 3
 
1.7%
주식회사 3
 
1.7%
충남슈퍼 2
 
1.1%
드림마트 2
 
1.1%
세븐일레븐공주여고점 2
 
1.1%
사곡농협하나로마트 2
 
1.1%
공주농협 2
 
1.1%
김밥천국 2
 
1.1%
주공할인마트 2
 
1.1%
소비자마트 2
 
1.1%
Other values (156) 157
87.7%
2024-01-10T07:38:40.051946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
점 70
 
5.7%
주 67
 
5.5%
공 60
 
4.9%
븐 47
 
3.9%
마 46
 
3.8%
트 38
 
3.1%
2 28
 
2.3%
G 27
 
2.2%
S 26
 
2.1%
5 26
 
2.1%
Other values (201) 783
64.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1069
87.8%
Uppercase Letter 63
 
5.2%
Decimal Number 56
 
4.6%
Space Separator 15
 
1.2%
Close Punctuation 7
 
0.6%
Open Punctuation 7
 
0.6%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
점 70
 
6.5%
주 67
 
6.3%
공 60
 
5.6%
븐 47
 
4.4%
마 46
 
4.3%
트 38
 
3.6%
세 25
 
2.3%
일 25
 
2.3%
농 23
 
2.2%
레 23
 
2.2%
Other values (189) 645
60.3%
Decimal Number
ValueCountFrequency (%)
2 28
50.0%
5 26
46.4%
4 1
 
1.8%
1 1
 
1.8%
Uppercase Letter
ValueCountFrequency (%)
G 27
42.9%
S 26
41.3%
U 5
 
7.9%
C 5
 
7.9%
Space Separator
ValueCountFrequency (%)
15
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7
100.0%
Open Punctuation
ValueCountFrequency (%)
( 7
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1069
87.8%
Common 86
 
7.1%
Latin 63
 
5.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
점 70
 
6.5%
주 67
 
6.3%
공 60
 
5.6%
븐 47
 
4.4%
마 46
 
4.3%
트 38
 
3.6%
세 25
 
2.3%
일 25
 
2.3%
농 23
 
2.2%
레 23
 
2.2%
Other values (189) 645
60.3%
Common
ValueCountFrequency (%)
2 28
32.6%
5 26
30.2%
15
17.4%
) 7
 
8.1%
( 7
 
8.1%
4 1
 
1.2%
, 1
 
1.2%
1 1
 
1.2%
Latin
ValueCountFrequency (%)
G 27
42.9%
S 26
41.3%
U 5
 
7.9%
C 5
 
7.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1069
87.8%
ASCII 149
 
12.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
점 70
 
6.5%
주 67
 
6.3%
공 60
 
5.6%
븐 47
 
4.4%
마 46
 
4.3%
트 38
 
3.6%
세 25
 
2.3%
일 25
 
2.3%
농 23
 
2.2%
레 23
 
2.2%
Other values (189) 645
60.3%
ASCII
ValueCountFrequency (%)
2 28
18.8%
G 27
18.1%
S 26
17.4%
5 26
17.4%
15
10.1%
) 7
 
4.7%
( 7
 
4.7%
U 5
 
3.4%
C 5
 
3.4%
4 1
 
0.7%
Other values (2) 2
 
1.3%

전화번호
Text

MISSING 

Distinct145
Distinct (%)95.4%
Missing12
Missing (%)7.3%
Memory size1.4 KiB
2024-01-10T07:38:40.292820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters1824
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

Unique138 ?
Unique (%)90.8%

Sample

1st row041-853-6677
2nd row041-857-8465
3rd row041-853-7663
4th row041-857-3498
5th row041-857-5035
ValueCountFrequency (%)
041-857-9999 2
 
1.3%
041-854-7741 2
 
1.3%
041-881-9511 2
 
1.3%
041-855-6413 2
 
1.3%
041-856-1017 2
 
1.3%
041-841-0624 2
 
1.3%
041-857-6885 2
 
1.3%
041-857-0037 1
 
0.7%
041-856-4097 1
 
0.7%
041-857-0011 1
 
0.7%
Other values (135) 135
88.8%
2024-01-10T07:38:40.680251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 304
16.7%
0 256
14.0%
4 232
12.7%
1 232
12.7%
8 228
12.5%
5 203
11.1%
6 84
 
4.6%
3 78
 
4.3%
2 73
 
4.0%
7 71
 
3.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1520
83.3%
Dash Punctuation 304
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 256
16.8%
4 232
15.3%
1 232
15.3%
8 228
15.0%
5 203
13.4%
6 84
 
5.5%
3 78
 
5.1%
2 73
 
4.8%
7 71
 
4.7%
9 63
 
4.1%
Dash Punctuation
ValueCountFrequency (%)
- 304
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1824
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 304
16.7%
0 256
14.0%
4 232
12.7%
1 232
12.7%
8 228
12.5%
5 203
11.1%
6 84
 
4.6%
3 78
 
4.3%
2 73
 
4.0%
7 71
 
3.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1824
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 304
16.7%
0 256
14.0%
4 232
12.7%
1 232
12.7%
8 228
12.5%
5 203
11.1%
6 84
 
4.6%
3 78
 
4.3%
2 73
 
4.0%
7 71
 
3.9%

주소
Text

Distinct161
Distinct (%)98.2%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
2024-01-10T07:38:40.906891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length43
Median length36
Mean length23.29878
Min length16

Characters and Unicode

Total characters3821
Distinct characters169
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

Unique158 ?
Unique (%)96.3%

Sample

1st row충청남도 공주시 계룡면 갑사로 5
2nd row충청남도 공주시 계룡면 영규대사로 478(월암리54-1)
3rd row충청남도 공주시 계룡면 신원사로 117
4th row충청남도 공주시 계룡면 월암리 23-5
5th row충청남도 공주시 계룡면 월암리 241
ValueCountFrequency (%)
공주시 161
19.9%
충청남도 129
 
15.9%
충남 32
 
4.0%
신관동 30
 
3.7%
산성동 15
 
1.9%
중동 14
 
1.7%
의당면 9
 
1.1%
웅진로 7
 
0.9%
유구읍 7
 
0.9%
반포면 7
 
0.9%
Other values (305) 399
49.3%
2024-01-10T07:38:41.240705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
646
 
16.9%
1 182
 
4.8%
공 169
 
4.4%
주 169
 
4.4%
남 166
 
4.3%
시 164
 
4.3%
충 161
 
4.2%
청 132
 
3.5%
도 131
 
3.4%
동 129
 
3.4%
Other values (159) 1772
46.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2205
57.7%
Decimal Number 729
 
19.1%
Space Separator 646
 
16.9%
Dash Punctuation 94
 
2.5%
Open Punctuation 68
 
1.8%
Close Punctuation 68
 
1.8%
Other Punctuation 11
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
공 169
 
7.7%
주 169
 
7.7%
남 166
 
7.5%
시 164
 
7.4%
충 161
 
7.3%
청 132
 
6.0%
도 131
 
5.9%
동 129
 
5.9%
신 59
 
2.7%
로 49
 
2.2%
Other values (143) 876
39.7%
Decimal Number
ValueCountFrequency (%)
1 182
25.0%
2 122
16.7%
3 69
 
9.5%
5 56
 
7.7%
0 56
 
7.7%
4 56
 
7.7%
6 54
 
7.4%
7 51
 
7.0%
9 49
 
6.7%
8 34
 
4.7%
Other Punctuation
ValueCountFrequency (%)
, 9
81.8%
. 2
 
18.2%
Space Separator
ValueCountFrequency (%)
646
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 94
100.0%
Open Punctuation
ValueCountFrequency (%)
( 68
100.0%
Close Punctuation
ValueCountFrequency (%)
) 68
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2205
57.7%
Common 1616
42.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
공 169
 
7.7%
주 169
 
7.7%
남 166
 
7.5%
시 164
 
7.4%
충 161
 
7.3%
청 132
 
6.0%
도 131
 
5.9%
동 129
 
5.9%
신 59
 
2.7%
로 49
 
2.2%
Other values (143) 876
39.7%
Common
ValueCountFrequency (%)
646
40.0%
1 182
 
11.3%
2 122
 
7.5%
- 94
 
5.8%
3 69
 
4.3%
( 68
 
4.2%
) 68
 
4.2%
5 56
 
3.5%
0 56
 
3.5%
4 56
 
3.5%
Other values (6) 199
 
12.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2205
57.7%
ASCII 1616
42.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
646
40.0%
1 182
 
11.3%
2 122
 
7.5%
- 94
 
5.8%
3 69
 
4.3%
( 68
 
4.2%
) 68
 
4.2%
5 56
 
3.5%
0 56
 
3.5%
4 56
 
3.5%
Other values (6) 199
 
12.3%
Hangul
ValueCountFrequency (%)
공 169
 
7.7%
주 169
 
7.7%
남 166
 
7.5%
시 164
 
7.4%
충 161
 
7.3%
청 132
 
6.0%
도 131
 
5.9%
동 129
 
5.9%
신 59
 
2.7%
로 49
 
2.2%
Other values (143) 876
39.7%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size1.4 KiB
Minimum2017-05-12 00:00:00
Maximum2017-05-12 00:00:00
2024-01-10T07:38:41.349912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-01-10T07:38:41.449678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Missing values

2024-01-10T07:38:39.348820image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-10T07:38:39.422867image/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

읍면동가맹점명전화번호주소데이터기준일자
0계룡면주식회사 계룡산오마트041-853-6677충청남도 공주시 계룡면 갑사로 52017-05-12
1계룡면백화마트041-857-8465충청남도 공주시 계룡면 영규대사로 478(월암리54-1)2017-05-12
2계룡면경천할인마트041-853-7663충청남도 공주시 계룡면 신원사로 1172017-05-12
3계룡면장순루041-857-3498충청남도 공주시 계룡면 월암리 23-52017-05-12
4계룡면계룡농협하나로마트041-857-5035충청남도 공주시 계룡면 월암리 2412017-05-12
5계룡면계룡슈퍼041-857-4930충청남도 공주시 계룡면 월암리 5082017-05-12
6금학동세븐일레븐공주여고점<NA>충청남도 공주시 금학동249-122017-05-12
7금학동세븐일레븐공주여고점041-855-7110충청남도 공주시 금학동 249-122017-05-12
8금학동GS25공주새뜸점041-881-4545충남 공주시 신금1길100 102호103호 (금흥동 259 새뜸현대4차아파트)2017-05-12
9금학동GS25공주교대점02-0000-0000충남 공주시 제민천2길16 (금학동 270-31)2017-05-12
읍면동가맹점명전화번호주소데이터기준일자
154중학동빨간컵041-853-2223충청남도 공주시 웅진로 143-1 (중동)2017-05-12
155중학동공주원041-852-3104충청남도 공주시 봉산길 23 (중동)2017-05-12
156중학동피자마루 공주 중동점041-858-1082충청남도 공주시 웅진로 153-1 (중동)2017-05-12
157중학동드림마트041-858-4688충청남도 공주시 오거리길 6 (봉황동)2017-05-12
158중학동김밥마을041-855-3556충청남도 공주시 금성동 19762017-05-12
159중학동연안상회041-855-5988충청남도 공주시 웅진로 155 (중동)2017-05-12
160중학동삐리리 대반점041-853-9777충청남도 공주시 반죽동 327-12017-05-12
161탄천면세븐일레븐탄천휴게소점041-854-3521충청남도 공주시 탄천면 장선리 151-6 탄천휴게소2017-05-12
162탄천면충남슈퍼041-733-4205충청남도 공주시 탄천면 619-72017-05-12
163탄천면탄천농협하나로마트041-853-5153충청남도 공주시 탄천면 삼각리 50572017-05-12

Duplicate rows

Most frequently occurring

읍면동가맹점명전화번호주소데이터기준일자# duplicates
0이인면대복식당041-857-6885충청남도 공주시 이인면 검바위로 2182017-05-122