Overview

Dataset statistics

Number of variables10
Number of observations57
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.6 KiB
Average record size in memory82.3 B

Variable types

Categorical6
Text4

Dataset

Description경기도 시흥시 버스 현황입니다. (시흥시 버스현황에는 노선번호, 배차간격, 기점, 경유지, 종점 정보가 있습니다)
URLhttps://www.data.go.kr/data/3074141/fileData.do

Alerts

데이터기준일 has constant value ""Constant
구분 is highly overall correlated with 배차간격 and 2 other fieldsHigh correlation
배차간격 is highly overall correlated with 구분High correlation
기점첫차 is highly overall correlated with 구분High correlation
운수회사 is highly overall correlated with 구분High correlation
노선번호 has unique valuesUnique

Reproduction

Analysis started2023-12-12 12:25:30.731950
Analysis finished2023-12-12 12:25:31.842646
Duration1.11 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구분
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)7.0%
Missing0
Missing (%)0.0%
Memory size588.0 B
시내일반
34 
시내좌석
12 
마을버스
10 
<NA>
 
1

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique1 ?
Unique (%)1.8%

Sample

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

Common Values

ValueCountFrequency (%)
시내일반 34
59.6%
시내좌석 12
 
21.1%
마을버스 10
 
17.5%
<NA> 1
 
1.8%

Length

2023-12-12T21:25:31.926415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:25:32.071414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
시내일반 34
59.6%
시내좌석 12
 
21.1%
마을버스 10
 
17.5%
na 1
 
1.8%

노선번호
Text

UNIQUE 

Distinct57
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size588.0 B
2023-12-12T21:25:32.362311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4
Mean length3.1754386
Min length1

Characters and Unicode

Total characters181
Distinct characters19
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique57 ?
Unique (%)100.0%

Sample

1st row7
2nd row11-A
3rd row11-B
4th row11-C
5th row12
ValueCountFrequency (%)
7 1
 
1.8%
99-2 1
 
1.8%
530 1
 
1.8%
5602 1
 
1.8%
5604 1
 
1.8%
3200 1
 
1.8%
3300 1
 
1.8%
3400 1
 
1.8%
5200 1
 
1.8%
3201 1
 
1.8%
Other values (47) 47
82.5%
2023-12-12T21:25:32.863057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 28
15.5%
1 27
14.9%
0 26
14.4%
- 19
10.5%
2 17
9.4%
6 12
6.6%
5 12
6.6%
9 10
 
5.5%
7 6
 
3.3%
A 4
 
2.2%
Other values (9) 20
11.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 145
80.1%
Dash Punctuation 19
 
10.5%
Uppercase Letter 14
 
7.7%
Close Punctuation 1
 
0.6%
Other Letter 1
 
0.6%
Open Punctuation 1
 
0.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 28
19.3%
1 27
18.6%
0 26
17.9%
2 17
11.7%
6 12
8.3%
5 12
8.3%
9 10
 
6.9%
7 6
 
4.1%
4 4
 
2.8%
8 3
 
2.1%
Uppercase Letter
ValueCountFrequency (%)
A 4
28.6%
B 4
28.6%
P 3
21.4%
N 2
14.3%
C 1
 
7.1%
Dash Punctuation
ValueCountFrequency (%)
- 19
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Other Letter
ValueCountFrequency (%)
통 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 166
91.7%
Latin 14
 
7.7%
Hangul 1
 
0.6%

Most frequent character per script

Common
ValueCountFrequency (%)
3 28
16.9%
1 27
16.3%
0 26
15.7%
- 19
11.4%
2 17
10.2%
6 12
7.2%
5 12
7.2%
9 10
 
6.0%
7 6
 
3.6%
4 4
 
2.4%
Other values (3) 5
 
3.0%
Latin
ValueCountFrequency (%)
A 4
28.6%
B 4
28.6%
P 3
21.4%
N 2
14.3%
C 1
 
7.1%
Hangul
ValueCountFrequency (%)
통 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 180
99.4%
Hangul 1
 
0.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 28
15.6%
1 27
15.0%
0 26
14.4%
- 19
10.6%
2 17
9.4%
6 12
6.7%
5 12
6.7%
9 10
 
5.6%
7 6
 
3.3%
A 4
 
2.2%
Other values (8) 19
10.6%
Hangul
ValueCountFrequency (%)
통 1
100.0%

배차간격
Categorical

HIGH CORRELATION 

Distinct27
Distinct (%)47.4%
Missing0
Missing (%)0.0%
Memory size588.0 B
15~25
6 
15~30
4 
20~40
4 
6~10
4 
15~20
 
3
Other values (22)
36 

Length

Max length6
Median length5
Mean length4.7368421
Min length2

Unique

Unique12 ?
Unique (%)21.1%

Sample

1st row15~20
2nd row20~40
3rd row25~40
4th row25~35
5th row90~120

Common Values

ValueCountFrequency (%)
15~25 6
 
10.5%
15~30 4
 
7.0%
20~40 4
 
7.0%
6~10 4
 
7.0%
15~20 3
 
5.3%
25~35 3
 
5.3%
<NA> 3
 
5.3%
15~40 3
 
5.3%
60~90 3
 
5.3%
60~80 2
 
3.5%
Other values (17) 22
38.6%

Length

2023-12-12T21:25:33.033149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
15~25 6
 
10.5%
20~40 4
 
7.0%
6~10 4
 
7.0%
15~30 4
 
7.0%
15~20 3
 
5.3%
25~35 3
 
5.3%
na 3
 
5.3%
15~40 3
 
5.3%
60~90 3
 
5.3%
30~60 2
 
3.5%
Other values (17) 22
38.6%

기점첫차
Categorical

HIGH CORRELATION 

Distinct18
Distinct (%)31.6%
Missing0
Missing (%)0.0%
Memory size588.0 B
5:30
11 
6:00
9 
5:40
9 
5:00
6 
5:20
4 
Other values (13)
18 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique9 ?
Unique (%)15.8%

Sample

1st row6:10
2nd row5:45
3rd row8:40
4th row6:30
5th row4:30

Common Values

ValueCountFrequency (%)
5:30 11
19.3%
6:00 9
15.8%
5:40 9
15.8%
5:00 6
10.5%
5:20 4
 
7.0%
4:50 3
 
5.3%
5:45 2
 
3.5%
6:10 2
 
3.5%
6:30 2
 
3.5%
6:20 1
 
1.8%
Other values (8) 8
14.0%

Length

2023-12-12T21:25:33.179868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
5:30 11
19.3%
5:40 9
15.8%
6:00 9
15.8%
5:00 6
10.5%
5:20 4
 
7.0%
4:50 3
 
5.3%
5:45 2
 
3.5%
6:10 2
 
3.5%
6:30 2
 
3.5%
5:50 1
 
1.8%
Other values (8) 8
14.0%

종점 막차
Categorical

Distinct28
Distinct (%)49.1%
Missing0
Missing (%)0.0%
Memory size588.0 B
23:00
8 
22:00
5 
0:00
4 
23:20
 
3
23:50
 
3
Other values (23)
34 

Length

Max length5
Median length5
Mean length4.7894737
Min length4

Unique

Unique14 ?
Unique (%)24.6%

Sample

1st row23:05
2nd row23:00
3rd row17:00
4th row21:30
5th row23:40

Common Values

ValueCountFrequency (%)
23:00 8
 
14.0%
22:00 5
 
8.8%
0:00 4
 
7.0%
23:20 3
 
5.3%
23:50 3
 
5.3%
0:30 3
 
5.3%
22:50 3
 
5.3%
23:45 2
 
3.5%
23:55 2
 
3.5%
22:40 2
 
3.5%
Other values (18) 22
38.6%

Length

2023-12-12T21:25:33.326944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
23:00 8
 
14.0%
22:00 5
 
8.8%
0:00 4
 
7.0%
23:20 3
 
5.3%
23:50 3
 
5.3%
0:30 3
 
5.3%
22:50 3
 
5.3%
21:30 2
 
3.5%
23:05 2
 
3.5%
0:50 2
 
3.5%
Other values (18) 22
38.6%

기 점
Text

Distinct33
Distinct (%)57.9%
Missing0
Missing (%)0.0%
Memory size588.0 B
2023-12-12T21:25:33.551598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length5.2631579
Min length3

Characters and Unicode

Total characters300
Distinct characters95
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

Unique17 ?
Unique (%)29.8%

Sample

1st row푸르지오6차
2nd row생명공원
3rd row생명공원
4th row오이도역
5th row삼미시장
ValueCountFrequency (%)
시흥대야역 4
 
6.9%
정왕역 4
 
6.9%
능곡공영차고지 4
 
6.9%
부천소방서 3
 
5.2%
포동차고지 3
 
5.2%
오이도역 2
 
3.4%
푸르지오6차 2
 
3.4%
신천중학교 2
 
3.4%
시화이마트 2
 
3.4%
오이도차고지 2
 
3.4%
Other values (24) 30
51.7%
2023-12-12T21:25:33.946094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
지 17
 
5.7%
차 16
 
5.3%
시 13
 
4.3%
고 13
 
4.3%
역 12
 
4.0%
공 10
 
3.3%
이 10
 
3.3%
흥 8
 
2.7%
능 8
 
2.7%
곡 8
 
2.7%
Other values (85) 185
61.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 285
95.0%
Uppercase Letter 5
 
1.7%
Decimal Number 4
 
1.3%
Close Punctuation 2
 
0.7%
Open Punctuation 2
 
0.7%
Space Separator 1
 
0.3%
Other Punctuation 1
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 17
 
6.0%
차 16
 
5.6%
시 13
 
4.6%
고 13
 
4.6%
역 12
 
4.2%
공 10
 
3.5%
이 10
 
3.5%
흥 8
 
2.8%
능 8
 
2.8%
곡 8
 
2.8%
Other values (74) 170
59.6%
Uppercase Letter
ValueCountFrequency (%)
M 1
20.0%
T 1
20.0%
V 1
20.0%
A 1
20.0%
E 1
20.0%
Decimal Number
ValueCountFrequency (%)
6 3
75.0%
7 1
 
25.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 285
95.0%
Common 10
 
3.3%
Latin 5
 
1.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 17
 
6.0%
차 16
 
5.6%
시 13
 
4.6%
고 13
 
4.6%
역 12
 
4.2%
공 10
 
3.5%
이 10
 
3.5%
흥 8
 
2.8%
능 8
 
2.8%
곡 8
 
2.8%
Other values (74) 170
59.6%
Common
ValueCountFrequency (%)
6 3
30.0%
) 2
20.0%
( 2
20.0%
1
 
10.0%
, 1
 
10.0%
7 1
 
10.0%
Latin
ValueCountFrequency (%)
M 1
20.0%
T 1
20.0%
V 1
20.0%
A 1
20.0%
E 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 285
95.0%
ASCII 15
 
5.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
지 17
 
6.0%
차 16
 
5.6%
시 13
 
4.6%
고 13
 
4.6%
역 12
 
4.2%
공 10
 
3.5%
이 10
 
3.5%
흥 8
 
2.8%
능 8
 
2.8%
곡 8
 
2.8%
Other values (74) 170
59.6%
ASCII
ValueCountFrequency (%)
6 3
20.0%
) 2
13.3%
( 2
13.3%
1
 
6.7%
M 1
 
6.7%
T 1
 
6.7%
V 1
 
6.7%
, 1
 
6.7%
7 1
 
6.7%
A 1
 
6.7%

경 유 지
Text

Distinct55
Distinct (%)96.5%
Missing0
Missing (%)0.0%
Memory size588.0 B
2023-12-12T21:25:34.223797image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length72
Median length44
Mean length33.807018
Min length7

Characters and Unicode

Total characters1927
Distinct characters220
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

Unique53 ?
Unique (%)93.0%

Sample

1st row정왕역환승센터
2nd row배곧고, 오이도역, 시화병원, 정왕역, 이마트, 시화산단
3rd row배곧고, 오이도역, 건영7차.신호새피앙, 이마트
4th row배곧고, 생명공원, 오이도해양단지
5th row신천역, 은행단지, 은계지구, 옥길지구, 역곡역, 부천역, 내동, 오정동
ValueCountFrequency (%)
은행단지 11
 
3.9%
삼미시장 8
 
2.9%
미산동 6
 
2.1%
이마트 6
 
2.1%
신천역 5
 
1.8%
오이도역 5
 
1.8%
대흥중 4
 
1.4%
은계지구 4
 
1.4%
사당역 4
 
1.4%
태광a 4
 
1.4%
Other values (157) 223
79.6%
2023-12-12T21:25:34.711997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
, 260
 
13.5%
223
 
11.6%
시 70
 
3.6%
역 68
 
3.5%
동 60
 
3.1%
지 48
 
2.5%
흥 32
 
1.7%
중 32
 
1.7%
구 28
 
1.5%
단 27
 
1.4%
Other values (210) 1079
56.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1373
71.3%
Other Punctuation 282
 
14.6%
Space Separator 223
 
11.6%
Uppercase Letter 26
 
1.3%
Decimal Number 15
 
0.8%
Open Punctuation 4
 
0.2%
Close Punctuation 4
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 70
 
5.1%
역 68
 
5.0%
동 60
 
4.4%
지 48
 
3.5%
흥 32
 
2.3%
중 32
 
2.3%
구 28
 
2.0%
단 27
 
2.0%
행 27
 
2.0%
고 26
 
1.9%
Other values (192) 955
69.6%
Uppercase Letter
ValueCountFrequency (%)
A 14
53.8%
V 3
 
11.5%
T 3
 
11.5%
M 3
 
11.5%
S 1
 
3.8%
C 1
 
3.8%
B 1
 
3.8%
Decimal Number
ValueCountFrequency (%)
4 5
33.3%
1 4
26.7%
2 3
20.0%
7 2
 
13.3%
3 1
 
6.7%
Other Punctuation
ValueCountFrequency (%)
, 260
92.2%
. 20
 
7.1%
@ 2
 
0.7%
Space Separator
ValueCountFrequency (%)
223
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1373
71.3%
Common 528
 
27.4%
Latin 26
 
1.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 70
 
5.1%
역 68
 
5.0%
동 60
 
4.4%
지 48
 
3.5%
흥 32
 
2.3%
중 32
 
2.3%
구 28
 
2.0%
단 27
 
2.0%
행 27
 
2.0%
고 26
 
1.9%
Other values (192) 955
69.6%
Common
ValueCountFrequency (%)
, 260
49.2%
223
42.2%
. 20
 
3.8%
4 5
 
0.9%
( 4
 
0.8%
) 4
 
0.8%
1 4
 
0.8%
2 3
 
0.6%
7 2
 
0.4%
@ 2
 
0.4%
Latin
ValueCountFrequency (%)
A 14
53.8%
V 3
 
11.5%
T 3
 
11.5%
M 3
 
11.5%
S 1
 
3.8%
C 1
 
3.8%
B 1
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1373
71.3%
ASCII 554
28.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
, 260
46.9%
223
40.3%
. 20
 
3.6%
A 14
 
2.5%
4 5
 
0.9%
( 4
 
0.7%
) 4
 
0.7%
1 4
 
0.7%
V 3
 
0.5%
T 3
 
0.5%
Other values (8) 14
 
2.5%
Hangul
ValueCountFrequency (%)
시 70
 
5.1%
역 68
 
5.0%
동 60
 
4.4%
지 48
 
3.5%
흥 32
 
2.3%
중 32
 
2.3%
구 28
 
2.0%
단 27
 
2.0%
행 27
 
2.0%
고 26
 
1.9%
Other values (192) 955
69.6%

종 점
Text

Distinct38
Distinct (%)66.7%
Missing0
Missing (%)0.0%
Memory size588.0 B
2023-12-12T21:25:34.965429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length5.3859649
Min length3

Characters and Unicode

Total characters307
Distinct characters120
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique26 ?
Unique (%)45.6%

Sample

1st row정왕역
2nd row시화MTV
3rd row센트럴병원
4th row오이도차고지
5th row김포공항국내선
ValueCountFrequency (%)
시흥대야역 5
 
8.6%
사당역 5
 
8.6%
시흥웨이브파크 3
 
5.2%
강남역 3
 
5.2%
판교제2테크노밸리 2
 
3.4%
정왕역 2
 
3.4%
신천중학교 2
 
3.4%
능곡지구 2
 
3.4%
포동차고지 2
 
3.4%
센트럴병원 2
 
3.4%
Other values (28) 30
51.7%
2023-12-12T21:25:35.335152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
역 24
 
7.8%
시 16
 
5.2%
흥 12
 
3.9%
지 12
 
3.9%
대 7
 
2.3%
이 7
 
2.3%
파 6
 
2.0%
구 6
 
2.0%
트 6
 
2.0%
아 6
 
2.0%
Other values (110) 205
66.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 294
95.8%
Uppercase Letter 5
 
1.6%
Decimal Number 4
 
1.3%
Other Punctuation 3
 
1.0%
Space Separator 1
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
역 24
 
8.2%
시 16
 
5.4%
흥 12
 
4.1%
지 12
 
4.1%
대 7
 
2.4%
이 7
 
2.4%
파 6
 
2.0%
구 6
 
2.0%
트 6
 
2.0%
아 6
 
2.0%
Other values (100) 192
65.3%
Uppercase Letter
ValueCountFrequency (%)
M 1
20.0%
T 1
20.0%
V 1
20.0%
A 1
20.0%
S 1
20.0%
Decimal Number
ValueCountFrequency (%)
2 2
50.0%
1 1
25.0%
4 1
25.0%
Other Punctuation
ValueCountFrequency (%)
. 3
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 294
95.8%
Common 8
 
2.6%
Latin 5
 
1.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
역 24
 
8.2%
시 16
 
5.4%
흥 12
 
4.1%
지 12
 
4.1%
대 7
 
2.4%
이 7
 
2.4%
파 6
 
2.0%
구 6
 
2.0%
트 6
 
2.0%
아 6
 
2.0%
Other values (100) 192
65.3%
Common
ValueCountFrequency (%)
. 3
37.5%
2 2
25.0%
1
 
12.5%
1 1
 
12.5%
4 1
 
12.5%
Latin
ValueCountFrequency (%)
M 1
20.0%
T 1
20.0%
V 1
20.0%
A 1
20.0%
S 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 294
95.8%
ASCII 13
 
4.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
역 24
 
8.2%
시 16
 
5.4%
흥 12
 
4.1%
지 12
 
4.1%
대 7
 
2.4%
이 7
 
2.4%
파 6
 
2.0%
구 6
 
2.0%
트 6
 
2.0%
아 6
 
2.0%
Other values (100) 192
65.3%
ASCII
ValueCountFrequency (%)
. 3
23.1%
2 2
15.4%
1
 
7.7%
1 1
 
7.7%
4 1
 
7.7%
M 1
 
7.7%
T 1
 
7.7%
V 1
 
7.7%
A 1
 
7.7%
S 1
 
7.7%

운수회사
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)8.8%
Missing0
Missing (%)0.0%
Memory size588.0 B
시흥교통
43 
녹색교통
8 
코모빌리티협동조합
 
3
경원여객자동차
 
2
녹색교통, 시흥교통
 
1

Length

Max length10
Median length4
Mean length4.4736842
Min length4

Unique

Unique1 ?
Unique (%)1.8%

Sample

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

Common Values

ValueCountFrequency (%)
시흥교통 43
75.4%
녹색교통 8
 
14.0%
코모빌리티협동조합 3
 
5.3%
경원여객자동차 2
 
3.5%
녹색교통, 시흥교통 1
 
1.8%

Length

2023-12-12T21:25:35.484960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:25:35.627650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
시흥교통 44
75.9%
녹색교통 9
 
15.5%
코모빌리티협동조합 3
 
5.2%
경원여객자동차 2
 
3.4%

데이터기준일
Categorical

CONSTANT 

Distinct1
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Memory size588.0 B
2023-08-04
57 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-08-04
2nd row2023-08-04
3rd row2023-08-04
4th row2023-08-04
5th row2023-08-04

Common Values

ValueCountFrequency (%)
2023-08-04 57
100.0%

Length

2023-12-12T21:25:35.759115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:25:35.861926image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-08-04 57
100.0%

Correlations

2023-12-12T21:25:35.944012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분노선번호배차간격기점첫차종점 막차기 점경 유 지종 점운수회사
구분1.0001.0000.9290.8560.7240.9631.0000.9820.729
노선번호1.0001.0001.0001.0001.0001.0001.0001.0001.000
배차간격0.9291.0001.0000.8450.8760.8801.0000.9170.766
기점첫차0.8561.0000.8451.0000.8660.0000.9720.7770.768
종점 막차0.7241.0000.8760.8661.0000.7490.9910.1230.737
기 점0.9631.0000.8800.0000.7491.0001.0000.9650.971
경 유 지1.0001.0001.0000.9720.9911.0001.0001.0001.000
종 점0.9821.0000.9170.7770.1230.9651.0001.0000.924
운수회사0.7291.0000.7660.7680.7370.9711.0000.9241.000
2023-12-12T21:25:36.077657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
배차간격종점 막차구분기점첫차운수회사
배차간격1.0000.3960.5930.3630.380
종점 막차0.3961.0000.3580.3680.337
구분0.5930.3581.0000.5110.708
기점첫차0.3630.3680.5111.0000.452
운수회사0.3800.3370.7080.4521.000
2023-12-12T21:25:36.183572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분배차간격기점첫차종점 막차운수회사
구분1.0000.5930.5110.3580.708
배차간격0.5931.0000.3630.3960.380
기점첫차0.5110.3631.0000.3680.452
종점 막차0.3580.3960.3681.0000.337
운수회사0.7080.3800.4520.3371.000

Missing values

2023-12-12T21:25:31.575685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T21:25:31.769182image/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

구분노선번호배차간격기점첫차종점 막차기 점경 유 지종 점운수회사데이터기준일
0시내일반715~206:1023:05푸르지오6차정왕역환승센터정왕역시흥교통2023-08-04
1시내일반11-A20~405:4523:00생명공원배곧고, 오이도역, 시화병원, 정왕역, 이마트, 시화산단시화MTV시흥교통2023-08-04
2시내일반11-B25~408:4017:00생명공원배곧고, 오이도역, 건영7차.신호새피앙, 이마트센트럴병원시흥교통2023-08-04
3시내일반11-C25~356:3021:30오이도역배곧고, 생명공원, 오이도해양단지오이도차고지시흥교통2023-08-04
4시내일반1290~1204:3023:40삼미시장신천역, 은행단지, 은계지구, 옥길지구, 역곡역, 부천역, 내동, 오정동김포공항국내선시흥교통2023-08-04
5시내일반1320~355:3523:05포동차고지신현역, 미산동, 소래중고, 신천역, 연합병원, 롯데마트은행단지시흥교통2023-08-04
6시내일반16(통)15~255:5023:20은계지구남단은계지구, 소래중고교, 신천역, 삼미시장, 신천동, 운연동인천대공원역시흥교통2023-08-04
7시내일반20-115~255:3023:50정왕역시화공단, 안산역, 동명, 월피동부곡중시흥교통2023-08-04
8시내일반2130~405:3023:00오이도시화공단, 안산역, 동명, 상록수역안산태영A시흥교통2023-08-04
9시내일반2320~305:0023:00월 곶오이도역, 시화공고, 안산역, 안산시청, 농수산시장, 일동, 상록수역, 본오동본오동차고지시흥교통2023-08-04
구분노선번호배차간격기점첫차종점 막차기 점경 유 지종 점운수회사데이터기준일
47마을버스N1-A6~104:500:30시흥대야역은행단지, 은행동주민센터, 뉴월드A, 삼미시장, 태광A, 대흥중시흥대야역녹색교통2023-08-04
48마을버스1-B6~106:0022:00시흥대야역대흥중, 태광A, 삼미시장, 뉴월드A, 은행동주민센터, 은행단지시흥대야역녹색교통2023-08-04
49<NA>N1-B6~104:500:30시흥대야역대흥중, 태광A, 삼미시장, 뉴월드A, 은행동주민센터, 은행단지시흥대야역녹색교통2023-08-04
50마을버스3-A15~306:0023:00신천중학교신천고등학교.삼미시장.소래중고등학교입구.은행동행정복지센터.은행고.시흥대야역.신천역신천중학교녹색교통2023-08-04
51마을버스3-B15~306:0023:00신천중학교신천역.시흥대야역.은행고.은행동행정복지센터.소래중고등학교입구.삼미시장.신천고등학교신천중학교녹색교통2023-08-04
52마을버스515~206:0022:40갯골생태공원장곡고, 장곡중, 장현지구, 시흥능곡역, 시흥시청역, 시흥고, 연꽃테마파크성원.동아아파트녹색교통, 시흥교통2023-08-04
53마을버스615~206:0022:00하늘휴게소입구목감중심상업지구, 산현초, 목감한신더휴.호반2차, 목감중심상업지구남측, 목감7단지, 목감고, 조남초.조남중, 남왕마을, 목감사거리논곡동.산호아파트녹색교통2023-08-04
54마을버스06-01406:0022:00하늘휴게소입구목감중심상업지구, 목감중흥S클래스, 운흥초, 목감고, 조남초.조남중, 목감지하차도입구, 목감네이처하임시흥시공공직장어린이집녹색교통2023-08-04
55마을버스810~205:150:00능곡공영차고지능곡초, 시흥능곡역, 장현4단지, 장현리슈빌.풍경채에듀, 루벤시아2차, 시흥시청후문시흥시청역시흥교통2023-08-04
56마을버스08-01605:2023:10능곡공영차고지우남퍼스트빌, 능곡어울림센터.능곡중, 노인종합복지관, 시흥능곡역, 한여울초, 시흥시청역트리플포레시흥시청역시흥교통2023-08-04