Overview

Dataset statistics

Number of variables6
Number of observations70
Missing cells85
Missing cells (%)20.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.4 KiB
Average record size in memory49.9 B

Variable types

Categorical2
Text4

Dataset

Description강원도 평창군의 음식물류폐기물 다량배출사업장 목록에 대한 데이터로 사업장 구분, 상호명, 주소, 면적 등의 항목에 대한 데이터를 제공합니다.
Author강원도 평창군
URLhttps://www.data.go.kr/data/15094126/fileData.do

Alerts

데이터기준일 has constant value ""Constant
면 적(제곱미터_실) has 20 (28.6%) missing valuesMissing
비 고 has 65 (92.9%) missing valuesMissing
상호명 has unique valuesUnique

Reproduction

Analysis started2023-12-12 14:45:12.674543
Analysis finished2023-12-12 14:45:13.320851
Duration0.65 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

사업장 구분
Categorical

Distinct6
Distinct (%)8.6%
Missing0
Missing (%)0.0%
Memory size692.0 B
일반음식점
37 
집단급식소
22 
호텔업
4 
유통센터
4 
휴게음식점
 
2

Length

Max length7
Median length5
Mean length4.8571429
Min length3

Unique

Unique1 ?
Unique (%)1.4%

Sample

1st row일반음식점
2nd row일반음식점
3rd row일반음식점
4th row일반음식점
5th row휴양콘도미니엄

Common Values

ValueCountFrequency (%)
일반음식점 37
52.9%
집단급식소 22
31.4%
호텔업 4
 
5.7%
유통센터 4
 
5.7%
휴게음식점 2
 
2.9%
휴양콘도미니엄 1
 
1.4%

Length

2023-12-12T23:45:13.642882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:45:13.777969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반음식점 37
52.9%
집단급식소 22
31.4%
호텔업 4
 
5.7%
유통센터 4
 
5.7%
휴게음식점 2
 
2.9%
휴양콘도미니엄 1
 
1.4%

상호명
Text

UNIQUE 

Distinct70
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size692.0 B
2023-12-12T23:45:13.989977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length16
Mean length7.6857143
Min length3

Characters and Unicode

Total characters538
Distinct characters209
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique70 ?
Unique (%)100.0%

Sample

1st row라프레리
2nd row라포레
3rd row하늘정원
4th row글로리홀(Glory Hall)
5th row아이원리조트휴양콘도미니엄
ValueCountFrequency (%)
농산물산지유통센터 2
 
2.5%
평창한우마을 2
 
2.5%
라프레리 1
 
1.3%
일송정 1
 
1.3%
그린밸리 1
 
1.3%
배나무집 1
 
1.3%
소금강 1
 
1.3%
table 1
 
1.3%
라떼브(la 1
 
1.3%
편배기 1
 
1.3%
Other values (67) 67
84.8%
2023-12-12T23:45:14.353576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
교 19
 
3.5%
학 18
 
3.3%
평 15
 
2.8%
등 14
 
2.6%
원 13
 
2.4%
대 12
 
2.2%
창 11
 
2.0%
) 11
 
2.0%
( 11
 
2.0%
관 10
 
1.9%
Other values (199) 404
75.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 471
87.5%
Uppercase Letter 14
 
2.6%
Lowercase Letter 13
 
2.4%
Close Punctuation 11
 
2.0%
Open Punctuation 11
 
2.0%
Space Separator 9
 
1.7%
Decimal Number 8
 
1.5%
Other Punctuation 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
교 19
 
4.0%
학 18
 
3.8%
평 15
 
3.2%
등 14
 
3.0%
원 13
 
2.8%
대 12
 
2.5%
창 11
 
2.3%
관 10
 
2.1%
한 9
 
1.9%
산 9
 
1.9%
Other values (171) 341
72.4%
Uppercase Letter
ValueCountFrequency (%)
C 2
14.3%
D 2
14.3%
H 2
14.3%
L 1
7.1%
E 1
7.1%
U 1
7.1%
N 1
7.1%
R 1
7.1%
A 1
7.1%
M 1
7.1%
Lowercase Letter
ValueCountFrequency (%)
l 4
30.8%
a 3
23.1%
t 1
 
7.7%
e 1
 
7.7%
b 1
 
7.7%
y 1
 
7.7%
r 1
 
7.7%
o 1
 
7.7%
Decimal Number
ValueCountFrequency (%)
1 3
37.5%
5 2
25.0%
8 1
 
12.5%
7 1
 
12.5%
0 1
 
12.5%
Close Punctuation
ValueCountFrequency (%)
) 11
100.0%
Open Punctuation
ValueCountFrequency (%)
( 11
100.0%
Space Separator
ValueCountFrequency (%)
9
100.0%
Other Punctuation
ValueCountFrequency (%)
· 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 471
87.5%
Common 40
 
7.4%
Latin 27
 
5.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
교 19
 
4.0%
학 18
 
3.8%
평 15
 
3.2%
등 14
 
3.0%
원 13
 
2.8%
대 12
 
2.5%
창 11
 
2.3%
관 10
 
2.1%
한 9
 
1.9%
산 9
 
1.9%
Other values (171) 341
72.4%
Latin
ValueCountFrequency (%)
l 4
14.8%
a 3
 
11.1%
C 2
 
7.4%
D 2
 
7.4%
H 2
 
7.4%
L 1
 
3.7%
t 1
 
3.7%
e 1
 
3.7%
b 1
 
3.7%
E 1
 
3.7%
Other values (9) 9
33.3%
Common
ValueCountFrequency (%)
) 11
27.5%
( 11
27.5%
9
22.5%
1 3
 
7.5%
5 2
 
5.0%
8 1
 
2.5%
7 1
 
2.5%
0 1
 
2.5%
· 1
 
2.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 471
87.5%
ASCII 66
 
12.3%
None 1
 
0.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
교 19
 
4.0%
학 18
 
3.8%
평 15
 
3.2%
등 14
 
3.0%
원 13
 
2.8%
대 12
 
2.5%
창 11
 
2.3%
관 10
 
2.1%
한 9
 
1.9%
산 9
 
1.9%
Other values (171) 341
72.4%
ASCII
ValueCountFrequency (%)
) 11
16.7%
( 11
16.7%
9
13.6%
l 4
 
6.1%
a 3
 
4.5%
1 3
 
4.5%
C 2
 
3.0%
D 2
 
3.0%
H 2
 
3.0%
5 2
 
3.0%
Other values (17) 17
25.8%
None
ValueCountFrequency (%)
· 1
100.0%

주소
Text

Distinct66
Distinct (%)94.3%
Missing0
Missing (%)0.0%
Memory size692.0 B
2023-12-12T23:45:14.580510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length41
Median length35
Mean length23.171429
Min length18

Characters and Unicode

Total characters1622
Distinct characters124
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique64 ?
Unique (%)91.4%

Sample

1st row강원도 평창군 봉평면 태기로 228-95, 지하1층
2nd row강원도 평창군 봉평면 태기로 228-95, 지하1층
3rd row강원도 평창군 대관령면 오목길 107, 라마다호텔 1층
4th row강원도 평창군 대관령면 오목길 107, 라마다호텔&스위트평창 지하2층
5th row강원도 평창군 대관령면 솔봉로 471
ValueCountFrequency (%)
강원도 70
18.4%
평창군 70
18.4%
대관령면 20
 
5.3%
진부면 18
 
4.7%
봉평면 14
 
3.7%
태기로 8
 
2.1%
용평면 7
 
1.8%
진고개로 6
 
1.6%
경강로 6
 
1.6%
대화면 5
 
1.3%
Other values (122) 156
41.1%
2023-12-12T23:45:14.986811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
310
19.1%
평 100
 
6.2%
창 79
 
4.9%
강 78
 
4.8%
도 70
 
4.3%
군 70
 
4.3%
원 70
 
4.3%
1 67
 
4.1%
면 66
 
4.1%
2 47
 
2.9%
Other values (114) 665
41.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 993
61.2%
Space Separator 310
 
19.1%
Decimal Number 266
 
16.4%
Other Punctuation 22
 
1.4%
Dash Punctuation 21
 
1.3%
Close Punctuation 5
 
0.3%
Open Punctuation 5
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
평 100
 
10.1%
창 79
 
8.0%
강 78
 
7.9%
도 70
 
7.0%
군 70
 
7.0%
원 70
 
7.0%
면 66
 
6.6%
로 45
 
4.5%
대 39
 
3.9%
진 28
 
2.8%
Other values (97) 348
35.0%
Decimal Number
ValueCountFrequency (%)
1 67
25.2%
2 47
17.7%
3 27
10.2%
5 25
 
9.4%
0 19
 
7.1%
8 18
 
6.8%
9 18
 
6.8%
6 16
 
6.0%
7 15
 
5.6%
4 14
 
5.3%
Other Punctuation
ValueCountFrequency (%)
, 18
81.8%
· 3
 
13.6%
& 1
 
4.5%
Space Separator
ValueCountFrequency (%)
310
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 21
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 993
61.2%
Common 629
38.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
평 100
 
10.1%
창 79
 
8.0%
강 78
 
7.9%
도 70
 
7.0%
군 70
 
7.0%
원 70
 
7.0%
면 66
 
6.6%
로 45
 
4.5%
대 39
 
3.9%
진 28
 
2.8%
Other values (97) 348
35.0%
Common
ValueCountFrequency (%)
310
49.3%
1 67
 
10.7%
2 47
 
7.5%
3 27
 
4.3%
5 25
 
4.0%
- 21
 
3.3%
0 19
 
3.0%
8 18
 
2.9%
9 18
 
2.9%
, 18
 
2.9%
Other values (7) 59
 
9.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 993
61.2%
ASCII 626
38.6%
None 3
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
310
49.5%
1 67
 
10.7%
2 47
 
7.5%
3 27
 
4.3%
5 25
 
4.0%
- 21
 
3.4%
0 19
 
3.0%
8 18
 
2.9%
9 18
 
2.9%
, 18
 
2.9%
Other values (6) 56
 
8.9%
Hangul
ValueCountFrequency (%)
평 100
 
10.1%
창 79
 
8.0%
강 78
 
7.9%
도 70
 
7.0%
군 70
 
7.0%
원 70
 
7.0%
면 66
 
6.6%
로 45
 
4.5%
대 39
 
3.9%
진 28
 
2.8%
Other values (97) 348
35.0%
None
ValueCountFrequency (%)
· 3
100.0%

면 적(제곱미터_실)
Text

MISSING 

Distinct47
Distinct (%)94.0%
Missing20
Missing (%)28.6%
Memory size692.0 B
2023-12-12T23:45:15.206094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length3.12
Min length3

Characters and Unicode

Total characters156
Distinct characters11
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique44 ?
Unique (%)88.0%

Sample

1st row783
2nd row615
3rd row576
4th row1017
5th row200실
ValueCountFrequency (%)
279 2
 
4.0%
252 2
 
4.0%
255 2
 
4.0%
426 1
 
2.0%
302 1
 
2.0%
122 1
 
2.0%
783 1
 
2.0%
263 1
 
2.0%
522 1
 
2.0%
353 1
 
2.0%
Other values (37) 37
74.0%
2023-12-12T23:45:15.579880image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 35
22.4%
5 23
14.7%
1 16
10.3%
6 15
9.6%
3 15
9.6%
4 11
 
7.1%
7 10
 
6.4%
0 10
 
6.4%
9 8
 
5.1%
8 8
 
5.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 151
96.8%
Other Letter 5
 
3.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 35
23.2%
5 23
15.2%
1 16
10.6%
6 15
9.9%
3 15
9.9%
4 11
 
7.3%
7 10
 
6.6%
0 10
 
6.6%
9 8
 
5.3%
8 8
 
5.3%
Other Letter
ValueCountFrequency (%)
실 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 151
96.8%
Hangul 5
 
3.2%

Most frequent character per script

Common
ValueCountFrequency (%)
2 35
23.2%
5 23
15.2%
1 16
10.6%
6 15
9.9%
3 15
9.9%
4 11
 
7.3%
7 10
 
6.6%
0 10
 
6.6%
9 8
 
5.3%
8 8
 
5.3%
Hangul
ValueCountFrequency (%)
실 5
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 151
96.8%
Hangul 5
 
3.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 35
23.2%
5 23
15.2%
1 16
10.6%
6 15
9.9%
3 15
9.9%
4 11
 
7.3%
7 10
 
6.6%
0 10
 
6.6%
9 8
 
5.3%
8 8
 
5.3%
Hangul
ValueCountFrequency (%)
실 5
100.0%

비 고
Text

MISSING 

Distinct3
Distinct (%)60.0%
Missing65
Missing (%)92.9%
Memory size692.0 B
2023-12-12T23:45:15.763958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length6
Mean length5.6
Min length5

Characters and Unicode

Total characters28
Distinct characters13
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)20.0%

Sample

1st row더화이트호텔
2nd row더화이트호텔
3rd row라마다호텔
4th row라마다호텔
5th row아이원리조트
ValueCountFrequency (%)
더화이트호텔 2
40.0%
라마다호텔 2
40.0%
아이원리조트 1
20.0%
2023-12-12T23:45:16.086432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
호 4
14.3%
텔 4
14.3%
이 3
10.7%
트 3
10.7%
더 2
7.1%
화 2
7.1%
라 2
7.1%
마 2
7.1%
다 2
7.1%
아 1
 
3.6%
Other values (3) 3
10.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 28
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
호 4
14.3%
텔 4
14.3%
이 3
10.7%
트 3
10.7%
더 2
7.1%
화 2
7.1%
라 2
7.1%
마 2
7.1%
다 2
7.1%
아 1
 
3.6%
Other values (3) 3
10.7%

Most occurring scripts

ValueCountFrequency (%)
Hangul 28
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
호 4
14.3%
텔 4
14.3%
이 3
10.7%
트 3
10.7%
더 2
7.1%
화 2
7.1%
라 2
7.1%
마 2
7.1%
다 2
7.1%
아 1
 
3.6%
Other values (3) 3
10.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 28
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
호 4
14.3%
텔 4
14.3%
이 3
10.7%
트 3
10.7%
더 2
7.1%
화 2
7.1%
라 2
7.1%
마 2
7.1%
다 2
7.1%
아 1
 
3.6%
Other values (3) 3
10.7%

데이터기준일
Categorical

CONSTANT 

Distinct1
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size692.0 B
2022-09-26
70 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2022-09-26
2nd row2022-09-26
3rd row2022-09-26
4th row2022-09-26
5th row2022-09-26

Common Values

ValueCountFrequency (%)
2022-09-26 70
100.0%

Length

2023-12-12T23:45:16.244527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T23:45:16.374444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022-09-26 70
100.0%

Correlations

2023-12-12T23:45:16.442680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
사업장 구분상호명주소면 적(제곱미터_실)비 고
사업장 구분1.0001.0000.9141.0001.000
상호명1.0001.0001.0001.0001.000
주소0.9141.0001.0000.9321.000
면 적(제곱미터_실)1.0001.0000.9321.0001.000
비 고1.0001.0001.0001.0001.000

Missing values

2023-12-12T23:45:13.085115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T23:45:13.187148image/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.
2023-12-12T23:45:13.277148image/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

사업장 구분상호명주소면 적(제곱미터_실)비 고데이터기준일
0일반음식점라프레리강원도 평창군 봉평면 태기로 228-95, 지하1층783더화이트호텔2022-09-26
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2일반음식점하늘정원강원도 평창군 대관령면 오목길 107, 라마다호텔 1층576라마다호텔2022-09-26
3일반음식점글로리홀(Glory Hall)강원도 평창군 대관령면 오목길 107, 라마다호텔&스위트평창 지하2층1017라마다호텔2022-09-26
4휴양콘도미니엄아이원리조트휴양콘도미니엄강원도 평창군 대관령면 솔봉로 471200실아이원리조트2022-09-26
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7일반음식점대관령한우타운강원도 평창군 대관령면 올림픽로 381099<NA>2022-09-26
8일반음식점고려궁강원도 평창군 대관령면 올림픽로 1169, 1동350<NA>2022-09-26
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62일반음식점장원(카페)강원도 평창군 진부면 오대산로 80-36, 1,2층255<NA>2022-09-26
63휴게음식점세븐헌드레드(7HUNDRED)강원도 평창군 대관령면 강변길 93466<NA>2022-09-26
64휴게음식점산850강원도 평창군 대관령면 오목길 111, 대관령순수양떼목장 제1동426<NA>2022-09-26
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68호텔업서림관광개발(유)강원도 평창군 진부면 청송로 10935실<NA>2022-09-26
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