Overview

Dataset statistics

Number of variables6
Number of observations105
Missing cells0
Missing cells (%)0.0%
Duplicate rows4
Duplicate rows (%)3.8%
Total size in memory5.3 KiB
Average record size in memory51.3 B

Variable types

Categorical5
Text1

Dataset

Description보령시에 설치되어 있는 현수막 지정 게시대의 정보(설치 읍면동, 위치, 현수막 규격, 상업용 게시면수, 행정용 게시면수)를 제공하는 파일데이터 입니다. (제공부서: 도시과 041-930-3881)
Author충청남도
URLhttps://alldam.chungnam.go.kr/index.chungnam?menuCd=DOM_000000201001001001&st=&cds=&orgCd=&apiType=&isOpen=Y&pageIndex=419&beforeMenuCd=DOM_000000201001001000&publicdatapk=15031394

Alerts

데이터기준일자 has constant value ""Constant
Dataset has 4 (3.8%) duplicate rowsDuplicates
규격(m) is highly overall correlated with 읍면동 and 1 other fieldsHigh correlation
게시면수(상업용) is highly overall correlated with 규격(m) and 1 other fieldsHigh correlation
게시면수(행정용) is highly overall correlated with 읍면동 and 1 other fieldsHigh correlation
읍면동 is highly overall correlated with 규격(m) and 1 other fieldsHigh correlation
규격(m) is highly imbalanced (76.7%)Imbalance

Reproduction

Analysis started2024-01-09 22:49:03.311980
Analysis finished2024-01-09 22:49:03.700899
Duration0.39 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

읍면동
Categorical

HIGH CORRELATION 

Distinct17
Distinct (%)16.2%
Missing0
Missing (%)0.0%
Memory size972.0 B
대천4동
34 
대천3동
8 
남포면
8 
오천면
7 
웅천읍
7 
Other values (12)
41 

Length

Max length5
Median length4
Mean length3.552381
Min length3

Unique

Unique1 ?
Unique (%)1.0%

Sample

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

Common Values

ValueCountFrequency (%)
대천4동 34
32.4%
대천3동 8
 
7.6%
남포면 8
 
7.6%
오천면 7
 
6.7%
웅천읍 7
 
6.7%
대천5동 7
 
6.7%
주교면 5
 
4.8%
성주면 5
 
4.8%
천북면 4
 
3.8%
대천2동 4
 
3.8%
Other values (7) 16
15.2%

Length

2024-01-10T07:49:03.760888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
대천4동 34
32.4%
대천3동 8
 
7.6%
남포면 8
 
7.6%
오천면 7
 
6.7%
웅천읍 7
 
6.7%
대천5동 7
 
6.7%
주교면 5
 
4.8%
성주면 5
 
4.8%
천북면 4
 
3.8%
대천2동 4
 
3.8%
Other values (6) 16
15.2%

위치
Text

Distinct83
Distinct (%)79.0%
Missing0
Missing (%)0.0%
Memory size972.0 B
2024-01-10T07:49:04.002467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length13
Mean length9.9904762
Min length5

Characters and Unicode

Total characters1049
Distinct characters142
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

Unique79 ?
Unique (%)75.2%

Sample

1st row남포저수지 앞
2nd row남포중학교 입구
3rd row남포보건소 앞
4th row남포파출소 앞
5th row남포면사무소 앞
ValueCountFrequency (%)
앞 26
 
11.0%
신설사거리~수청사거리 20
 
8.5%
삼거리 9
 
3.8%
입구 8
 
3.4%
주차장 6
 
2.5%
2 6
 
2.5%
1 6
 
2.5%
앞(1 5
 
2.1%
앞(2 5
 
2.1%
대천 5
 
2.1%
Other values (100) 140
59.3%
2024-01-10T07:49:04.348522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
140
 
13.3%
리 76
 
7.2%
거 57
 
5.4%
사 56
 
5.3%
앞 37
 
3.5%
) 33
 
3.1%
( 33
 
3.1%
신 27
 
2.6%
수 27
 
2.6%
청 24
 
2.3%
Other values (132) 539
51.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 780
74.4%
Space Separator 140
 
13.3%
Decimal Number 39
 
3.7%
Close Punctuation 33
 
3.1%
Open Punctuation 33
 
3.1%
Math Symbol 20
 
1.9%
Uppercase Letter 3
 
0.3%
Dash Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 76
 
9.7%
거 57
 
7.3%
사 56
 
7.2%
앞 37
 
4.7%
신 27
 
3.5%
수 27
 
3.5%
청 24
 
3.1%
주 22
 
2.8%
설 22
 
2.8%
천 19
 
2.4%
Other values (117) 413
52.9%
Decimal Number
ValueCountFrequency (%)
1 17
43.6%
2 15
38.5%
3 3
 
7.7%
7 1
 
2.6%
8 1
 
2.6%
4 1
 
2.6%
5 1
 
2.6%
Uppercase Letter
ValueCountFrequency (%)
G 1
33.3%
P 1
33.3%
L 1
33.3%
Space Separator
ValueCountFrequency (%)
140
100.0%
Close Punctuation
ValueCountFrequency (%)
) 33
100.0%
Open Punctuation
ValueCountFrequency (%)
( 33
100.0%
Math Symbol
ValueCountFrequency (%)
~ 20
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 780
74.4%
Common 266
 
25.4%
Latin 3
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 76
 
9.7%
거 57
 
7.3%
사 56
 
7.2%
앞 37
 
4.7%
신 27
 
3.5%
수 27
 
3.5%
청 24
 
3.1%
주 22
 
2.8%
설 22
 
2.8%
천 19
 
2.4%
Other values (117) 413
52.9%
Common
ValueCountFrequency (%)
140
52.6%
) 33
 
12.4%
( 33
 
12.4%
~ 20
 
7.5%
1 17
 
6.4%
2 15
 
5.6%
3 3
 
1.1%
7 1
 
0.4%
8 1
 
0.4%
- 1
 
0.4%
Other values (2) 2
 
0.8%
Latin
ValueCountFrequency (%)
G 1
33.3%
P 1
33.3%
L 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 780
74.4%
ASCII 269
 
25.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
140
52.0%
) 33
 
12.3%
( 33
 
12.3%
~ 20
 
7.4%
1 17
 
6.3%
2 15
 
5.6%
3 3
 
1.1%
G 1
 
0.4%
P 1
 
0.4%
7 1
 
0.4%
Other values (5) 5
 
1.9%
Hangul
ValueCountFrequency (%)
리 76
 
9.7%
거 57
 
7.3%
사 56
 
7.2%
앞 37
 
4.7%
신 27
 
3.5%
수 27
 
3.5%
청 24
 
3.1%
주 22
 
2.8%
설 22
 
2.8%
천 19
 
2.4%
Other values (117) 413
52.9%

규격(m)
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size972.0 B
5.6 x 0.7
101 
2.4×1.7
 
4

Length

Max length9
Median length9
Mean length8.9238095
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row5.6 x 0.7
2nd row5.6 x 0.7
3rd row5.6 x 0.7
4th row5.6 x 0.7
5th row5.6 x 0.7

Common Values

ValueCountFrequency (%)
5.6 x 0.7 101
96.2%
2.4×1.7 4
 
3.8%

Length

2024-01-10T07:49:04.464491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T07:49:04.549922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
5.6 101
32.9%
x 101
32.9%
0.7 101
32.9%
2.4×1.7 4
 
1.3%

게시면수(상업용)
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Memory size972.0 B
5
53 
6
26 
0
22 
2
 
4

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 53
50.5%
6 26
24.8%
0 22
21.0%
2 4
 
3.8%

Length

2024-01-10T07:49:04.628995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T07:49:04.707188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
5 53
50.5%
6 26
24.8%
0 22
21.0%
2 4
 
3.8%

게시면수(행정용)
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size972.0 B
0
83 
1
22 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row0
5th row0

Common Values

ValueCountFrequency (%)
0 83
79.0%
1 22
 
21.0%

Length

2024-01-10T07:49:04.796492image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T07:49:04.871386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 83
79.0%
1 22
 
21.0%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size972.0 B
2022-09-05
105 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2022-09-05
2nd row2022-09-05
3rd row2022-09-05
4th row2022-09-05
5th row2022-09-05

Common Values

ValueCountFrequency (%)
2022-09-05 105
100.0%

Length

2024-01-10T07:49:04.953771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-01-10T07:49:05.026752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022-09-05 105
100.0%

Correlations

2024-01-10T07:49:05.075805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
읍면동위치규격(m)게시면수(상업용)게시면수(행정용)
읍면동1.0001.0000.6610.7240.640
위치1.0001.0001.0001.0001.000
규격(m)0.6611.0001.0001.0000.000
게시면수(상업용)0.7241.0001.0001.0001.000
게시면수(행정용)0.6401.0000.0001.0001.000
2024-01-10T07:49:05.407806image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
읍면동규격(m)게시면수(상업용)게시면수(행정용)
읍면동1.0000.5570.4640.538
규격(m)0.5571.0000.9900.000
게시면수(상업용)0.4640.9901.0000.990
게시면수(행정용)0.5380.0000.9901.000
2024-01-10T07:49:05.485242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
읍면동규격(m)게시면수(상업용)게시면수(행정용)
읍면동1.0000.5570.4640.538
규격(m)0.5571.0000.9900.000
게시면수(상업용)0.4640.9901.0000.990
게시면수(행정용)0.5380.0000.9901.000

Missing values

2024-01-10T07:49:03.583110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-10T07:49:03.665574image/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

읍면동위치규격(m)게시면수(상업용)게시면수(행정용)데이터기준일자
0남포면남포저수지 앞5.6 x 0.7502022-09-05
1남포면남포중학교 입구5.6 x 0.7502022-09-05
2남포면남포보건소 앞5.6 x 0.7502022-09-05
3남포면남포파출소 앞5.6 x 0.7502022-09-05
4남포면남포면사무소 앞5.6 x 0.7502022-09-05
5남포면욕장 흑포 삼거리 (1)5.6 x 0.7602022-09-05
6남포면욕장 흑포 삼거리 (2)5.6 x 0.7602022-09-05
7남포면죽도 입구 앞2.4×1.7202022-09-05
8대천1동대천 체육관 앞(2)5.6 x 0.7602022-09-05
9대천1동대천노인복지관 앞5.6 x 0.7502022-09-05
읍면동위치규격(m)게시면수(상업용)게시면수(행정용)데이터기준일자
95대천4동신설사거리~수청사거리5.6 x 0.7012022-09-05
96대천4동신설사거리~수청사거리5.6 x 0.7012022-09-05
97대천4동신설사거리~수청사거리5.6 x 0.7012022-09-05
98대천4동신설사거리~수청사거리5.6 x 0.7012022-09-05
99대천4동신설사거리~수청사거리5.6 x 0.7012022-09-05
100대천4동신설사거리~수청사거리5.6 x 0.7012022-09-05
101대천4동신설사거리~수청사거리5.6 x 0.7012022-09-05
102대천4동신설사거리~수청사거리5.6 x 0.7012022-09-05
103대천4동신설사거리~수청사거리5.6 x 0.7012022-09-05
104대천4동신설사거리~수청사거리5.6 x 0.7012022-09-05

Duplicate rows

Most frequently occurring

읍면동위치규격(m)게시면수(상업용)게시면수(행정용)데이터기준일자# duplicates
1대천4동신설사거리~수청사거리5.6 x 0.7012022-09-0520
0대천3동한내로터리5.6 x 0.7012022-09-052
2오천면원산사거리5.6 x 0.7502022-09-052
3오천면원의사거리5.6 x 0.7502022-09-052