Overview

Dataset statistics

Number of variables11
Number of observations142
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory12.7 KiB
Average record size in memory91.9 B

Variable types

Text3
Categorical7
DateTime1

Dataset

Description강원도 평창군의 현수막 지정 게시대 현황에 대한 데이터로 관리번호, 게시대명, 주소, 부착일, 부착금액, 규격, 면수, 용도, 관리기관, 전화번호 등의 항목에 대한 정보를 제공합니다.
Author강원도 평창군
URLhttps://www.data.go.kr/data/15066648/fileData.do

Alerts

부착일 has constant value ""Constant
부착금액 has constant value ""Constant
관리기관 has constant value ""Constant
전화번호 has constant value ""Constant
데이터기준일자 has constant value ""Constant
용도 is highly overall correlated with 규격(cm) and 1 other fieldsHigh correlation
면수 is highly overall correlated with 용도High correlation
규격(cm) is highly overall correlated with 용도High correlation
관리번호 has unique valuesUnique
게시대명 has unique valuesUnique

Reproduction

Analysis started2023-12-11 23:48:34.163647
Analysis finished2023-12-11 23:48:34.805471
Duration0.64 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

관리번호
Text

UNIQUE 

Distinct142
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2023-12-12T08:48:35.126729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length4
Mean length4
Min length4

Characters and Unicode

Total characters568
Distinct characters12
Distinct categories2 ?
Distinct scripts2 ?
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 rowA101
2nd rowA102
3rd rowA103
4th rowA104
5th rowA105
ValueCountFrequency (%)
a101 1
 
0.7%
b201 1
 
0.7%
b203 1
 
0.7%
b106 1
 
0.7%
b107 1
 
0.7%
b108 1
 
0.7%
b109 1
 
0.7%
b110 1
 
0.7%
b104 1
 
0.7%
b103 1
 
0.7%
Other values (132) 132
93.0%
2023-12-12T08:48:35.763722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 125
22.0%
A 86
15.1%
1 70
12.3%
B 56
9.9%
7 38
 
6.7%
4 33
 
5.8%
3 32
 
5.6%
5 32
 
5.6%
6 30
 
5.3%
2 30
 
5.3%
Other values (2) 36
 
6.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 426
75.0%
Uppercase Letter 142
 
25.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 125
29.3%
1 70
16.4%
7 38
 
8.9%
4 33
 
7.7%
3 32
 
7.5%
5 32
 
7.5%
6 30
 
7.0%
2 30
 
7.0%
8 26
 
6.1%
9 10
 
2.3%
Uppercase Letter
ValueCountFrequency (%)
A 86
60.6%
B 56
39.4%

Most occurring scripts

ValueCountFrequency (%)
Common 426
75.0%
Latin 142
 
25.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 125
29.3%
1 70
16.4%
7 38
 
8.9%
4 33
 
7.7%
3 32
 
7.5%
5 32
 
7.5%
6 30
 
7.0%
2 30
 
7.0%
8 26
 
6.1%
9 10
 
2.3%
Latin
ValueCountFrequency (%)
A 86
60.6%
B 56
39.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 568
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 125
22.0%
A 86
15.1%
1 70
12.3%
B 56
9.9%
7 38
 
6.7%
4 33
 
5.8%
3 32
 
5.6%
5 32
 
5.6%
6 30
 
5.3%
2 30
 
5.3%
Other values (2) 36
 
6.3%

게시대명
Text

UNIQUE 

Distinct142
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2023-12-12T08:48:36.065786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length17
Mean length11.570423
Min length4

Characters and Unicode

Total characters1643
Distinct characters196
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

Unique142 ?
Unique (%)100.0%

Sample

1st row평창교차로(좌)
2nd row평창교차로(우)
3rd row평창 1차아파트 앞
4th row기아자동차 맞은편(좌)
5th row기아자동차 맞은편(우)
ValueCountFrequency (%)
앞 16
 
5.3%
행정용 10
 
3.3%
입구 9
 
3.0%
앞(행정용 7
 
2.3%
맞은편 5
 
1.7%
진부 5
 
1.7%
옆(좌 4
 
1.3%
앞(우 4
 
1.3%
앞(좌 4
 
1.3%
옆(우 4
 
1.3%
Other values (172) 234
77.5%
2023-12-12T08:48:36.570754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
281
 
17.1%
( 90
 
5.5%
) 89
 
5.4%
정 46
 
2.8%
용 45
 
2.7%
행 41
 
2.5%
앞 37
 
2.3%
좌 36
 
2.2%
우 32
 
1.9%
사 29
 
1.8%
Other values (186) 917
55.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1147
69.8%
Space Separator 281
 
17.1%
Open Punctuation 90
 
5.5%
Close Punctuation 89
 
5.4%
Uppercase Letter 20
 
1.2%
Dash Punctuation 7
 
0.4%
Other Punctuation 6
 
0.4%
Decimal Number 3
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
정 46
 
4.0%
용 45
 
3.9%
행 41
 
3.6%
앞 37
 
3.2%
좌 36
 
3.1%
우 32
 
2.8%
사 29
 
2.5%
교 29
 
2.5%
리 29
 
2.5%
대 28
 
2.4%
Other values (171) 795
69.3%
Uppercase Letter
ValueCountFrequency (%)
C 8
40.0%
I 5
25.0%
S 2
 
10.0%
U 2
 
10.0%
A 1
 
5.0%
G 1
 
5.0%
J 1
 
5.0%
Other Punctuation
ValueCountFrequency (%)
, 5
83.3%
/ 1
 
16.7%
Decimal Number
ValueCountFrequency (%)
4 2
66.7%
1 1
33.3%
Space Separator
ValueCountFrequency (%)
281
100.0%
Open Punctuation
ValueCountFrequency (%)
( 90
100.0%
Close Punctuation
ValueCountFrequency (%)
) 89
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1147
69.8%
Common 476
29.0%
Latin 20
 
1.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
정 46
 
4.0%
용 45
 
3.9%
행 41
 
3.6%
앞 37
 
3.2%
좌 36
 
3.1%
우 32
 
2.8%
사 29
 
2.5%
교 29
 
2.5%
리 29
 
2.5%
대 28
 
2.4%
Other values (171) 795
69.3%
Common
ValueCountFrequency (%)
281
59.0%
( 90
 
18.9%
) 89
 
18.7%
- 7
 
1.5%
, 5
 
1.1%
4 2
 
0.4%
/ 1
 
0.2%
1 1
 
0.2%
Latin
ValueCountFrequency (%)
C 8
40.0%
I 5
25.0%
S 2
 
10.0%
U 2
 
10.0%
A 1
 
5.0%
G 1
 
5.0%
J 1
 
5.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1147
69.8%
ASCII 496
30.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
281
56.7%
( 90
 
18.1%
) 89
 
17.9%
C 8
 
1.6%
- 7
 
1.4%
I 5
 
1.0%
, 5
 
1.0%
4 2
 
0.4%
S 2
 
0.4%
U 2
 
0.4%
Other values (5) 5
 
1.0%
Hangul
ValueCountFrequency (%)
정 46
 
4.0%
용 45
 
3.9%
행 41
 
3.6%
앞 37
 
3.2%
좌 36
 
3.1%
우 32
 
2.8%
사 29
 
2.5%
교 29
 
2.5%
리 29
 
2.5%
대 28
 
2.4%
Other values (171) 795
69.3%

주소
Text

Distinct108
Distinct (%)76.1%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2023-12-12T08:48:36.997650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length23
Mean length21.21831
Min length16

Characters and Unicode

Total characters3013
Distinct characters72
Distinct categories4 ?
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 row강원도 평창군 평창읍 후평리 770-7
2nd row강원도 평창군 평창읍 후평리 770-7
3rd row강원도 평창군 평창읍 하리 186-1
4th row강원도 평창군 평창읍 하리 269-1
5th row강원도 평창군 평창읍 하리 269-1
ValueCountFrequency (%)
강원도 142
19.8%
평창군 142
19.8%
진부면 26
 
3.6%
평창읍 23
 
3.2%
봉평면 19
 
2.6%
대화면 18
 
2.5%
하진부리 18
 
2.5%
용평면 17
 
2.4%
대관령면 16
 
2.2%
횡계리 15
 
2.1%
Other values (142) 282
39.3%
2023-12-12T08:48:37.590214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
576
19.1%
평 211
 
7.0%
창 180
 
6.0%
원 145
 
4.8%
1 143
 
4.7%
강 142
 
4.7%
도 142
 
4.7%
군 142
 
4.7%
리 139
 
4.6%
면 124
 
4.1%
Other values (62) 1069
35.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1747
58.0%
Decimal Number 581
 
19.3%
Space Separator 576
 
19.1%
Dash Punctuation 109
 
3.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
평 211
12.1%
창 180
10.3%
원 145
 
8.3%
강 142
 
8.1%
도 142
 
8.1%
군 142
 
8.1%
리 139
 
8.0%
면 124
 
7.1%
부 56
 
3.2%
진 49
 
2.8%
Other values (50) 417
23.9%
Decimal Number
ValueCountFrequency (%)
1 143
24.6%
3 66
11.4%
2 63
10.8%
7 62
10.7%
6 60
10.3%
4 45
 
7.7%
9 40
 
6.9%
0 38
 
6.5%
5 33
 
5.7%
8 31
 
5.3%
Space Separator
ValueCountFrequency (%)
576
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 109
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1747
58.0%
Common 1266
42.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
평 211
12.1%
창 180
10.3%
원 145
 
8.3%
강 142
 
8.1%
도 142
 
8.1%
군 142
 
8.1%
리 139
 
8.0%
면 124
 
7.1%
부 56
 
3.2%
진 49
 
2.8%
Other values (50) 417
23.9%
Common
ValueCountFrequency (%)
576
45.5%
1 143
 
11.3%
- 109
 
8.6%
3 66
 
5.2%
2 63
 
5.0%
7 62
 
4.9%
6 60
 
4.7%
4 45
 
3.6%
9 40
 
3.2%
0 38
 
3.0%
Other values (2) 64
 
5.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1747
58.0%
ASCII 1266
42.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
576
45.5%
1 143
 
11.3%
- 109
 
8.6%
3 66
 
5.2%
2 63
 
5.0%
7 62
 
4.9%
6 60
 
4.7%
4 45
 
3.6%
9 40
 
3.2%
0 38
 
3.0%
Other values (2) 64
 
5.1%
Hangul
ValueCountFrequency (%)
평 211
12.1%
창 180
10.3%
원 145
 
8.3%
강 142
 
8.1%
도 142
 
8.1%
군 142
 
8.1%
리 139
 
8.0%
면 124
 
7.1%
부 56
 
3.2%
진 49
 
2.8%
Other values (50) 417
23.9%

부착일
Categorical

CONSTANT 

Distinct1
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
10
142 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row10
2nd row10
3rd row10
4th row10
5th row10

Common Values

ValueCountFrequency (%)
10 142
100.0%

Length

2023-12-12T08:48:37.736826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:48:37.858790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
10 142
100.0%

부착금액
Categorical

CONSTANT 

Distinct1
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
13000
142 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row13000
2nd row13000
3rd row13000
4th row13000
5th row13000

Common Values

ValueCountFrequency (%)
13000 142
100.0%

Length

2023-12-12T08:48:37.975079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:48:38.078336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
13000 142
100.0%

규격(cm)
Categorical

HIGH CORRELATION 

Distinct11
Distinct (%)7.7%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
600x70
71 
610x70
31 
620x70
22 
500x70
9 
510x70
 
3
Other values (6)
 
6

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique6 ?
Unique (%)4.2%

Sample

1st row600x70
2nd row600x70
3rd row620x70
4th row600x70
5th row600x70

Common Values

ValueCountFrequency (%)
600x70 71
50.0%
610x70 31
21.8%
620x70 22
 
15.5%
500x70 9
 
6.3%
510x70 3
 
2.1%
585x70 1
 
0.7%
515x70 1
 
0.7%
570x70 1
 
0.7%
520x70 1
 
0.7%
450x70 1
 
0.7%

Length

2023-12-12T08:48:38.212019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
600x70 71
50.0%
610x70 31
21.8%
620x70 22
 
15.5%
500x70 9
 
6.3%
510x70 3
 
2.1%
585x70 1
 
0.7%
515x70 1
 
0.7%
570x70 1
 
0.7%
520x70 1
 
0.7%
450x70 1
 
0.7%

면수
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)3.5%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
5
79 
2
25 
1
20 
4
12 
3
 
6

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row5
2nd row5
3rd row5
4th row5
5th row5

Common Values

ValueCountFrequency (%)
5 79
55.6%
2 25
 
17.6%
1 20
 
14.1%
4 12
 
8.5%
3 6
 
4.2%

Length

2023-12-12T08:48:38.359213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:48:38.466113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
5 79
55.6%
2 25
 
17.6%
1 20
 
14.1%
4 12
 
8.5%
3 6
 
4.2%

용도
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
상업용
86 
행정용
56 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
상업용 86
60.6%
행정용 56
39.4%

Length

2023-12-12T08:48:38.598208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:48:38.727867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
상업용 86
60.6%
행정용 56
39.4%

관리기관
Categorical

CONSTANT 

Distinct1
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
평창군청
142 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
평창군청 142
100.0%

Length

2023-12-12T08:48:38.851869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:48:38.957958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
평창군청 142
100.0%

전화번호
Categorical

CONSTANT 

Distinct1
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
033-330-2410
142 

Length

Max length12
Median length12
Mean length12
Min length12

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row033-330-2410
2nd row033-330-2410
3rd row033-330-2410
4th row033-330-2410
5th row033-330-2410

Common Values

ValueCountFrequency (%)
033-330-2410 142
100.0%

Length

2023-12-12T08:48:39.052980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T08:48:39.138913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
033-330-2410 142
100.0%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
Minimum2022-09-29 00:00:00
Maximum2022-09-29 00:00:00
2023-12-12T08:48:39.211721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T08:48:39.353145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Correlations

2023-12-12T08:48:39.426349image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
규격(cm)면수용도
규격(cm)1.0000.5790.748
면수0.5791.0000.816
용도0.7480.8161.000
2023-12-12T08:48:39.513504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
용도면수규격(cm)
용도1.0000.9330.710
면수0.9331.0000.357
규격(cm)0.7100.3571.000
2023-12-12T08:48:39.600587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
규격(cm)면수용도
규격(cm)1.0000.3570.710
면수0.3571.0000.933
용도0.7100.9331.000

Missing values

2023-12-12T08:48:34.565860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T08:48:34.736928image/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

관리번호게시대명주소부착일부착금액규격(cm)면수용도관리기관전화번호데이터기준일자
0A101평창교차로(좌)강원도 평창군 평창읍 후평리 770-71013000600x705상업용평창군청033-330-24102022-09-29
1A102평창교차로(우)강원도 평창군 평창읍 후평리 770-71013000600x705상업용평창군청033-330-24102022-09-29
2A103평창 1차아파트 앞강원도 평창군 평창읍 하리 186-11013000620x705상업용평창군청033-330-24102022-09-29
3A104기아자동차 맞은편(좌)강원도 평창군 평창읍 하리 269-11013000600x705상업용평창군청033-330-24102022-09-29
4A105기아자동차 맞은편(우)강원도 평창군 평창읍 하리 269-11013000600x705상업용평창군청033-330-24102022-09-29
5A106마지삼거리강원도 평창군 평창읍 마지리 343-21013000600x705상업용평창군청033-330-24102022-09-29
6A107평창장례식장 앞강원도 평창군 평창읍 종부리 508-1791013000600x705상업용평창군청033-330-24102022-09-29
7A108문화예술회관 입구강원도 평창군 평창읍 종부리 497-71013000600x705상업용평창군청033-330-24102022-09-29
8A109시외버스터미널 맞은편강원도 평창군 평창읍 하리 4381013000600x704상업용평창군청033-330-24102022-09-29
9A110지구대 맞은편(좌)강원도 평창군 평창읍 천변리 11-21013000600x705상업용평창군청033-330-24102022-09-29
관리번호게시대명주소부착일부착금액규격(cm)면수용도관리기관전화번호데이터기준일자
132B706하진부교차로 (좌)행정용강원도 평창군 진부면 하진부리 312-71013000610x701행정용평창군청033-330-24102022-09-29
133B707하진부교차로 (우)행정용강원도 평창군 진부면 하진부리 312-71013000610x701행정용평창군청033-330-24102022-09-29
134B708진부체육공원입구강원도 평창군 진부면 하진부리 1289-801013000600x702행정용평창군청033-330-24102022-09-29
135B709진부 종합운동장 안(좌)강원도 평창군 진부면 하진부리 1289-711013000600x702행정용평창군청033-330-24102022-09-29
136B710진부 종합운동장 안(우)강원도 평창군 진부면 하진부리 1289-711013000600x702행정용평창군청033-330-24102022-09-29
137B711진부 장례식장 입구강원도 평창군 진부면 하진부리 3401013000600x702행정용평창군청033-330-24102022-09-29
138B801대관령보건지소 앞(행정용)강원도 평창군 대관령면 횡계리 335-311013000620x702행정용평창군청033-330-24102022-09-29
139B802횡계교 부근(행정용)강원도 평창군 대관령면 횡계리 314-51013000620x702행정용평창군청033-330-24102022-09-29
140B803횡계로타리강원도 평창군 대관령면 횡계리 332-81013000610x702행정용평창군청033-330-24102022-09-29
141B804가금류연구소 앞강원도 평창군 대관령면 횡계리 6711013000610x701행정용평창군청033-330-24102022-09-29