Overview

Dataset statistics

Number of variables3
Number of observations102
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.5 KiB
Average record size in memory25.3 B

Variable types

Text3

Dataset

Description대전광역시 버스전용차로 위반 위치별 단속현황입니다. 단속장소, 전체건수, 단속원금 등의 데이터가 파일에 있습니다.
Author대전광역시
URLhttps://www.data.go.kr/data/15062791/fileData.do

Alerts

단속장소 has unique valuesUnique

Reproduction

Analysis started2023-12-12 00:02:30.808613
Analysis finished2023-12-12 00:02:31.226917
Duration0.42 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

단속장소
Text

UNIQUE 

Distinct102
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size948.0 B
2023-12-12T09:02:31.369320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length18
Mean length15.352941
Min length10

Characters and Unicode

Total characters1566
Distinct characters122
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique102 ?
Unique (%)100.0%

Sample

1st row"LH대전에너지사업단(가수원방향)"
2nd row"LH대전에너지사업단(유성방향)"
3rd row"가수원네거리->가수원교 방향"
4th row"가수원네거리->가수원교방향"
5th row"가수원네거리->건양대병원네거리방향"
ValueCountFrequency (%)
방향 16
 
12.4%
건너편 4
 
3.1%
대전일보사 2
 
1.6%
월평동 2
 
1.6%
삼성네거리->농수산오거리 2
 
1.6%
외삼네거리->시경계 1
 
0.8%
유성네거리~용계동 1
 
0.8%
유성네거리->용계동 1
 
0.8%
유성네거리->서대전네거리 1
 
0.8%
유성네거리->만년교방향 1
 
0.8%
Other values (98) 98
76.0%
2023-12-12T09:02:31.756281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
" 204
 
13.0%
리 140
 
8.9%
거 133
 
8.5%
네 113
 
7.2%
- 81
 
5.2%
> 81
 
5.2%
대 54
 
3.4%
향 47
 
3.0%
방 45
 
2.9%
전 32
 
2.0%
Other values (112) 636
40.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1132
72.3%
Other Punctuation 204
 
13.0%
Math Symbol 88
 
5.6%
Dash Punctuation 81
 
5.2%
Space Separator 27
 
1.7%
Uppercase Letter 12
 
0.8%
Decimal Number 10
 
0.6%
Open Punctuation 6
 
0.4%
Close Punctuation 6
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 140
 
12.4%
거 133
 
11.7%
네 113
 
10.0%
대 54
 
4.8%
향 47
 
4.2%
방 45
 
4.0%
전 32
 
2.8%
교 27
 
2.4%
동 23
 
2.0%
성 18
 
1.6%
Other values (95) 500
44.2%
Uppercase Letter
ValueCountFrequency (%)
H 2
16.7%
L 2
16.7%
I 2
16.7%
G 2
16.7%
T 2
16.7%
C 2
16.7%
Math Symbol
ValueCountFrequency (%)
> 81
92.0%
~ 4
 
4.5%
→ 3
 
3.4%
Decimal Number
ValueCountFrequency (%)
2 4
40.0%
4 4
40.0%
5 2
20.0%
Other Punctuation
ValueCountFrequency (%)
" 204
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 81
100.0%
Space Separator
ValueCountFrequency (%)
27
100.0%
Open Punctuation
ValueCountFrequency (%)
( 6
100.0%
Close Punctuation
ValueCountFrequency (%)
) 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1132
72.3%
Common 422
 
26.9%
Latin 12
 
0.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 140
 
12.4%
거 133
 
11.7%
네 113
 
10.0%
대 54
 
4.8%
향 47
 
4.2%
방 45
 
4.0%
전 32
 
2.8%
교 27
 
2.4%
동 23
 
2.0%
성 18
 
1.6%
Other values (95) 500
44.2%
Common
ValueCountFrequency (%)
" 204
48.3%
- 81
 
19.2%
> 81
 
19.2%
27
 
6.4%
( 6
 
1.4%
) 6
 
1.4%
~ 4
 
0.9%
2 4
 
0.9%
4 4
 
0.9%
→ 3
 
0.7%
Latin
ValueCountFrequency (%)
H 2
16.7%
L 2
16.7%
I 2
16.7%
G 2
16.7%
T 2
16.7%
C 2
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1132
72.3%
ASCII 431
 
27.5%
Arrows 3
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
" 204
47.3%
- 81
 
18.8%
> 81
 
18.8%
27
 
6.3%
( 6
 
1.4%
) 6
 
1.4%
~ 4
 
0.9%
2 4
 
0.9%
4 4
 
0.9%
5 2
 
0.5%
Other values (6) 12
 
2.8%
Hangul
ValueCountFrequency (%)
리 140
 
12.4%
거 133
 
11.7%
네 113
 
10.0%
대 54
 
4.8%
향 47
 
4.2%
방 45
 
4.0%
전 32
 
2.8%
교 27
 
2.4%
동 23
 
2.0%
성 18
 
1.6%
Other values (95) 500
44.2%
Arrows
ValueCountFrequency (%)
→ 3
100.0%

전체건수
Text

Distinct80
Distinct (%)78.4%
Missing0
Missing (%)0.0%
Memory size948.0 B
2023-12-12T09:02:32.024914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length3
Mean length2.4019608
Min length1

Characters and Unicode

Total characters245
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

Unique68 ?
Unique (%)66.7%

Sample

1st row3
2nd row248
3rd row42
4th row714
5th row1,668
ValueCountFrequency (%)
1 8
 
7.8%
3 5
 
4.9%
2 3
 
2.9%
10 2
 
2.0%
78 2
 
2.0%
9 2
 
2.0%
61 2
 
2.0%
6 2
 
2.0%
14 2
 
2.0%
42 2
 
2.0%
Other values (70) 72
70.6%
2023-12-12T09:02:32.423851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 46
18.8%
4 32
13.1%
2 31
12.7%
6 26
10.6%
3 25
10.2%
9 19
7.8%
0 17
 
6.9%
5 16
 
6.5%
8 14
 
5.7%
7 11
 
4.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 237
96.7%
Other Punctuation 8
 
3.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 46
19.4%
4 32
13.5%
2 31
13.1%
6 26
11.0%
3 25
10.5%
9 19
8.0%
0 17
 
7.2%
5 16
 
6.8%
8 14
 
5.9%
7 11
 
4.6%
Other Punctuation
ValueCountFrequency (%)
, 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 245
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 46
18.8%
4 32
13.1%
2 31
12.7%
6 26
10.6%
3 25
10.2%
9 19
7.8%
0 17
 
6.9%
5 16
 
6.5%
8 14
 
5.7%
7 11
 
4.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 245
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 46
18.8%
4 32
13.1%
2 31
12.7%
6 26
10.6%
3 25
10.2%
9 19
7.8%
0 17
 
6.9%
5 16
 
6.5%
8 14
 
5.7%
7 11
 
4.5%

단속원금
Text

Distinct87
Distinct (%)85.3%
Missing0
Missing (%)0.0%
Memory size948.0 B
2023-12-12T09:02:32.718672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length10
Mean length8.7156863
Min length6

Characters and Unicode

Total characters889
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

Unique82 ?
Unique (%)80.4%

Sample

1st row150,000
2nd row12,375,000
3rd row2,100,000
4th row35,990,000
5th row83,480,000
ValueCountFrequency (%)
50,000 8
 
7.8%
150,000 5
 
4.9%
100,000 3
 
2.9%
300,000 2
 
2.0%
3,910,000 2
 
2.0%
3,050,000 1
 
1.0%
15,460,000 1
 
1.0%
2,110,000 1
 
1.0%
1,820,000 1
 
1.0%
460,000 1
 
1.0%
Other values (77) 77
75.5%
2023-12-12T09:02:33.191003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 404
45.4%
, 174
19.6%
5 73
 
8.2%
1 61
 
6.9%
2 37
 
4.2%
3 29
 
3.3%
4 28
 
3.1%
9 26
 
2.9%
7 23
 
2.6%
6 19
 
2.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 715
80.4%
Other Punctuation 174
 
19.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 404
56.5%
5 73
 
10.2%
1 61
 
8.5%
2 37
 
5.2%
3 29
 
4.1%
4 28
 
3.9%
9 26
 
3.6%
7 23
 
3.2%
6 19
 
2.7%
8 15
 
2.1%
Other Punctuation
ValueCountFrequency (%)
, 174
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 889
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 404
45.4%
, 174
19.6%
5 73
 
8.2%
1 61
 
6.9%
2 37
 
4.2%
3 29
 
3.3%
4 28
 
3.1%
9 26
 
2.9%
7 23
 
2.6%
6 19
 
2.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 889
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 404
45.4%
, 174
19.6%
5 73
 
8.2%
1 61
 
6.9%
2 37
 
4.2%
3 29
 
3.3%
4 28
 
3.1%
9 26
 
2.9%
7 23
 
2.6%
6 19
 
2.1%

Correlations

2023-12-12T09:02:33.296849image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
전체건수단속원금
전체건수1.0001.000
단속원금1.0001.000

Missing values

2023-12-12T09:02:31.066617image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T09:02:31.176016image/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

단속장소전체건수단속원금
0"LH대전에너지사업단(가수원방향)"3150,000
1"LH대전에너지사업단(유성방향)"24812,375,000
2"가수원네거리->가수원교 방향"422,100,000
3"가수원네거리->가수원교방향"71435,990,000
4"가수원네거리->건양대병원네거리방향"1,66883,480,000
5"가수원네거리->도마네거리"39119,585,000
6"가수원네거리->만년교"1004,975,000
7"가장동 래미안아파트2단지 건너편"150,000
8"가장동래미안아파트2단지건너편"66933,525,000
9"갈마네거리->경성큰마을네거리"19925,000
단속장소전체건수단속원금
92"태평오거리->대전TG네거리"1346,725,000
93"한남오거리->삼성네거리"6300,000
94"한남오거리~농수산오거리"150,000
95"향우네거리->구농도원네거리 방향"401,990,000
96"향우네거리->구농도원네거리방향"1085,415,000
97"향우네거리->변동네거리 방향"653,280,000
98"향우네거리->변동네거리방향"1005,040,000
99"호반베르디움2차(가수원방향)"783,910,000
100"호반베르디움2차(유성방향)"24312,150,000
101"효동네거리->대전역네거리"472,360,000