Overview

Dataset statistics

Number of variables12
Number of observations65
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.3 KiB
Average record size in memory100.0 B

Variable types

Numeric2
Categorical5
Text5

Dataset

Description경기도 안산시 시내버스노선 정보로 연번,업체명,노선번호,기점,종점,정류소,운행대수,첫차시간,막차시간,배차간격,차고지명,데이터기준일자 등을 제공합니다.
Author경기도 안산시
URLhttps://www.data.go.kr/data/3035822/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
업체명 is highly overall correlated with 차고지명High correlation
차고지명 is highly overall correlated with 업체명High correlation
연번 has unique valuesUnique
노선번호 has unique valuesUnique

Reproduction

Analysis started2023-12-13 00:37:27.589558
Analysis finished2023-12-13 00:37:28.794655
Duration1.21 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct65
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean33
Minimum1
Maximum65
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size717.0 B
2023-12-13T09:37:28.847175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile4.2
Q117
median33
Q349
95-th percentile61.8
Maximum65
Range64
Interquartile range (IQR)32

Descriptive statistics

Standard deviation18.90767
Coefficient of variation (CV)0.57295971
Kurtosis-1.2
Mean33
Median Absolute Deviation (MAD)16
Skewness0
Sum2145
Variance357.5
MonotonicityStrictly increasing
2023-12-13T09:37:28.948665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.5%
50 1
 
1.5%
36 1
 
1.5%
37 1
 
1.5%
38 1
 
1.5%
39 1
 
1.5%
40 1
 
1.5%
41 1
 
1.5%
42 1
 
1.5%
43 1
 
1.5%
Other values (55) 55
84.6%
ValueCountFrequency (%)
1 1
1.5%
2 1
1.5%
3 1
1.5%
4 1
1.5%
5 1
1.5%
6 1
1.5%
7 1
1.5%
8 1
1.5%
9 1
1.5%
10 1
1.5%
ValueCountFrequency (%)
65 1
1.5%
64 1
1.5%
63 1
1.5%
62 1
1.5%
61 1
1.5%
60 1
1.5%
59 1
1.5%
58 1
1.5%
57 1
1.5%
56 1
1.5%

업체명
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)4.6%
Missing0
Missing (%)0.0%
Memory size652.0 B
경원여객
53 
써클라인
7 
태화상운
 
5

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row경원여객
2nd row경원여객
3rd row경원여객
4th row경원여객
5th row태화상운

Common Values

ValueCountFrequency (%)
경원여객 53
81.5%
써클라인 7
 
10.8%
태화상운 5
 
7.7%

Length

2023-12-13T09:37:29.057303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T09:37:29.133101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경원여객 53
81.5%
써클라인 7
 
10.8%
태화상운 5
 
7.7%

노선번호
Text

UNIQUE 

Distinct65
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size652.0 B
2023-12-13T09:37:29.335547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length5
Mean length3.7076923
Min length2

Characters and Unicode

Total characters241
Distinct characters16
Distinct categories4 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique65 ?
Unique (%)100.0%

Sample

1st row10번
2nd row10-1번
3rd row101번
4th row110번
5th row123번
ValueCountFrequency (%)
10번 1
 
1.5%
55번 1
 
1.5%
6번 1
 
1.5%
60a번 1
 
1.5%
60b번 1
 
1.5%
61번 1
 
1.5%
62번 1
 
1.5%
66번 1
 
1.5%
7번 1
 
1.5%
707번 1
 
1.5%
Other values (55) 55
84.6%
2023-12-13T09:37:29.648317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
번 65
27.0%
1 33
13.7%
0 33
13.7%
7 19
 
7.9%
3 16
 
6.6%
5 13
 
5.4%
2 12
 
5.0%
6 11
 
4.6%
- 10
 
4.1%
9 9
 
3.7%
Other values (6) 20
 
8.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 156
64.7%
Other Letter 65
27.0%
Dash Punctuation 10
 
4.1%
Uppercase Letter 10
 
4.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 33
21.2%
0 33
21.2%
7 19
12.2%
3 16
10.3%
5 13
 
8.3%
2 12
 
7.7%
6 11
 
7.1%
9 9
 
5.8%
8 7
 
4.5%
4 3
 
1.9%
Uppercase Letter
ValueCountFrequency (%)
A 4
40.0%
B 4
40.0%
C 1
 
10.0%
M 1
 
10.0%
Other Letter
ValueCountFrequency (%)
번 65
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 166
68.9%
Hangul 65
 
27.0%
Latin 10
 
4.1%

Most frequent character per script

Common
ValueCountFrequency (%)
1 33
19.9%
0 33
19.9%
7 19
11.4%
3 16
9.6%
5 13
 
7.8%
2 12
 
7.2%
6 11
 
6.6%
- 10
 
6.0%
9 9
 
5.4%
8 7
 
4.2%
Latin
ValueCountFrequency (%)
A 4
40.0%
B 4
40.0%
C 1
 
10.0%
M 1
 
10.0%
Hangul
ValueCountFrequency (%)
번 65
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 176
73.0%
Hangul 65
 
27.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
번 65
100.0%
ASCII
ValueCountFrequency (%)
1 33
18.8%
0 33
18.8%
7 19
10.8%
3 16
9.1%
5 13
 
7.4%
2 12
 
6.8%
6 11
 
6.2%
- 10
 
5.7%
9 9
 
5.1%
8 7
 
4.0%
Other values (5) 13
 
7.4%

기점
Text

Distinct39
Distinct (%)60.0%
Missing0
Missing (%)0.0%
Memory size652.0 B
2023-12-13T09:37:29.813966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length11
Mean length5.8461538
Min length3

Characters and Unicode

Total characters380
Distinct characters108
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique28 ?
Unique (%)43.1%

Sample

1st row중앙역1번출구
2nd row상록수역앞
3rd row경원여객
4th row선부동차고지
5th row세영리첼
ValueCountFrequency (%)
경원여객 9
 
13.8%
오이도차고지 4
 
6.2%
선부동차고지 4
 
6.2%
안산해솔초등학교 3
 
4.6%
경인합섬앞 3
 
4.6%
본오동종점 3
 
4.6%
신안산대학교 3
 
4.6%
중앙역2번출구 2
 
3.1%
본오아파트앞 2
 
3.1%
중앙역1번출구 2
 
3.1%
Other values (29) 30
46.2%
2023-12-13T09:37:30.069363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
경 13
 
3.4%
고 13
 
3.4%
차 12
 
3.2%
지 12
 
3.2%
오 12
 
3.2%
원 11
 
2.9%
역 11
 
2.9%
동 10
 
2.6%
객 10
 
2.6%
여 10
 
2.6%
Other values (98) 266
70.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 368
96.8%
Decimal Number 10
 
2.6%
Other Punctuation 2
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
경 13
 
3.5%
고 13
 
3.5%
차 12
 
3.3%
지 12
 
3.3%
오 12
 
3.3%
원 11
 
3.0%
역 11
 
3.0%
동 10
 
2.7%
객 10
 
2.7%
여 10
 
2.7%
Other values (93) 254
69.0%
Decimal Number
ValueCountFrequency (%)
1 4
40.0%
2 3
30.0%
3 2
20.0%
6 1
 
10.0%
Other Punctuation
ValueCountFrequency (%)
. 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 368
96.8%
Common 12
 
3.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
경 13
 
3.5%
고 13
 
3.5%
차 12
 
3.3%
지 12
 
3.3%
오 12
 
3.3%
원 11
 
3.0%
역 11
 
3.0%
동 10
 
2.7%
객 10
 
2.7%
여 10
 
2.7%
Other values (93) 254
69.0%
Common
ValueCountFrequency (%)
1 4
33.3%
2 3
25.0%
3 2
16.7%
. 2
16.7%
6 1
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 368
96.8%
ASCII 12
 
3.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
경 13
 
3.5%
고 13
 
3.5%
차 12
 
3.3%
지 12
 
3.3%
오 12
 
3.3%
원 11
 
3.0%
역 11
 
3.0%
동 10
 
2.7%
객 10
 
2.7%
여 10
 
2.7%
Other values (93) 254
69.0%
ASCII
ValueCountFrequency (%)
1 4
33.3%
2 3
25.0%
3 2
16.7%
. 2
16.7%
6 1
 
8.3%

종점
Text

Distinct50
Distinct (%)76.9%
Missing0
Missing (%)0.0%
Memory size652.0 B
2023-12-13T09:37:30.263677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length7.2769231
Min length2

Characters and Unicode

Total characters473
Distinct characters138
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

Unique39 ?
Unique (%)60.0%

Sample

1st row새솔고
2nd row푸르지오6차후문
3rd row사리운동장
4th row수원역.노보텔수원
5th row탄도
ValueCountFrequency (%)
새솔고 3
 
4.6%
삼천리마을앞 3
 
4.6%
수원역.노보텔수원 3
 
4.6%
경원여객종점 3
 
4.6%
상록수역3번출구건너편 2
 
3.1%
안산역(도로변 2
 
3.1%
강남역우리은행 2
 
3.1%
중앙역2번출구 2
 
3.1%
중앙역1번출구 2
 
3.1%
안산갈대습지 2
 
3.1%
Other values (40) 41
63.1%
2023-12-13T09:37:30.561130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
역 23
 
4.9%
구 16
 
3.4%
번 15
 
3.2%
원 12
 
2.5%
출 12
 
2.5%
1 10
 
2.1%
지 10
 
2.1%
리 10
 
2.1%
수 10
 
2.1%
부 9
 
1.9%
Other values (128) 346
73.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 433
91.5%
Decimal Number 19
 
4.0%
Other Punctuation 8
 
1.7%
Close Punctuation 5
 
1.1%
Open Punctuation 5
 
1.1%
Uppercase Letter 3
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
역 23
 
5.3%
구 16
 
3.7%
번 15
 
3.5%
원 12
 
2.8%
출 12
 
2.8%
지 10
 
2.3%
리 10
 
2.3%
수 10
 
2.3%
부 9
 
2.1%
대 8
 
1.8%
Other values (118) 308
71.1%
Decimal Number
ValueCountFrequency (%)
1 10
52.6%
2 5
26.3%
3 3
 
15.8%
6 1
 
5.3%
Uppercase Letter
ValueCountFrequency (%)
K 1
33.3%
T 1
33.3%
X 1
33.3%
Other Punctuation
ValueCountFrequency (%)
. 8
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%
Open Punctuation
ValueCountFrequency (%)
( 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 433
91.5%
Common 37
 
7.8%
Latin 3
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
역 23
 
5.3%
구 16
 
3.7%
번 15
 
3.5%
원 12
 
2.8%
출 12
 
2.8%
지 10
 
2.3%
리 10
 
2.3%
수 10
 
2.3%
부 9
 
2.1%
대 8
 
1.8%
Other values (118) 308
71.1%
Common
ValueCountFrequency (%)
1 10
27.0%
. 8
21.6%
) 5
13.5%
( 5
13.5%
2 5
13.5%
3 3
 
8.1%
6 1
 
2.7%
Latin
ValueCountFrequency (%)
K 1
33.3%
T 1
33.3%
X 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 433
91.5%
ASCII 40
 
8.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
역 23
 
5.3%
구 16
 
3.7%
번 15
 
3.5%
원 12
 
2.8%
출 12
 
2.8%
지 10
 
2.3%
리 10
 
2.3%
수 10
 
2.3%
부 9
 
2.1%
대 8
 
1.8%
Other values (118) 308
71.1%
ASCII
ValueCountFrequency (%)
1 10
25.0%
. 8
20.0%
) 5
12.5%
( 5
12.5%
2 5
12.5%
3 3
 
7.5%
K 1
 
2.5%
T 1
 
2.5%
X 1
 
2.5%
6 1
 
2.5%

정류소
Text

Distinct64
Distinct (%)98.5%
Missing0
Missing (%)0.0%
Memory size652.0 B
2023-12-13T09:37:30.703888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length95
Median length55
Mean length42.261538
Min length4

Characters and Unicode

Total characters2747
Distinct characters258
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique63 ?
Unique (%)96.9%

Sample

1st row중앙역-안산문화광장-호수공원-푸르지오6,7,9차A-경기테크노파크-송산그린시티
2nd row상록수역-푸른마을A-성안고-한양대입구-게스트하우스-경기테크노파크-푸르지오6,7,9차A
3rd row반월공단차고지-안산역-초지역-선부동-와동-중앙동-상록수역-본오동
4th row수원역-농촌진흥청-상록수역-예술인A-자유센타-와동-선부동
5th row푸르지오6.7차 중앙역, 안산역, 시흥관광호텔, 시화이마트, 오이도역, 서울대시흥캠퍼스, 방아머리, 탄도
ValueCountFrequency (%)
황제아파트 2
 
1.8%
서해아파트 2
 
1.8%
양촌마을 2
 
1.8%
반월역 2
 
1.8%
방아머리 2
 
1.8%
반월농협 2
 
1.8%
인정아파트 2
 
1.8%
메추리섬입구-대남초-남동보건소-대부출장소-부흥리-대부종고-종현동-두우현-당전-영전-대동초-대부출장소-남동보건소-대남초-메추리섬입구 1
 
0.9%
차량등록사업소-초지역-그린빌14단지-고잔고-중앙역-선경a-다농-강서고-동명a 1
 
0.9%
시외버스터미널-선경a-부곡고-점섬체육관-일동행정복지센터-상록수역-신안코아-사동행정복지센터-고잔고 1
 
0.9%
Other values (96) 96
85.0%
2023-12-13T09:37:30.948819image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 417
 
15.2%
동 115
 
4.2%
역 107
 
3.9%
시 61
 
2.2%
안 59
 
2.1%
, 58
 
2.1%
고 57
 
2.1%
지 57
 
2.1%
산 54
 
2.0%
48
 
1.7%
Other values (248) 1714
62.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2102
76.5%
Dash Punctuation 417
 
15.2%
Other Punctuation 64
 
2.3%
Uppercase Letter 50
 
1.8%
Space Separator 48
 
1.7%
Decimal Number 44
 
1.6%
Open Punctuation 8
 
0.3%
Close Punctuation 8
 
0.3%
Lowercase Letter 6
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 115
 
5.5%
역 107
 
5.1%
시 61
 
2.9%
안 59
 
2.8%
고 57
 
2.7%
지 57
 
2.7%
산 54
 
2.6%
부 40
 
1.9%
단 37
 
1.8%
상 35
 
1.7%
Other values (222) 1480
70.4%
Decimal Number
ValueCountFrequency (%)
1 16
36.4%
6 7
15.9%
7 5
 
11.4%
4 5
 
11.4%
2 5
 
11.4%
3 2
 
4.5%
9 2
 
4.5%
0 1
 
2.3%
5 1
 
2.3%
Uppercase Letter
ValueCountFrequency (%)
A 38
76.0%
E 6
 
12.0%
S 2
 
4.0%
C 1
 
2.0%
I 1
 
2.0%
G 1
 
2.0%
D 1
 
2.0%
Other Punctuation
ValueCountFrequency (%)
, 58
90.6%
. 5
 
7.8%
: 1
 
1.6%
Lowercase Letter
ValueCountFrequency (%)
v 2
33.3%
t 2
33.3%
m 2
33.3%
Dash Punctuation
ValueCountFrequency (%)
- 417
100.0%
Space Separator
ValueCountFrequency (%)
48
100.0%
Open Punctuation
ValueCountFrequency (%)
( 8
100.0%
Close Punctuation
ValueCountFrequency (%)
) 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2102
76.5%
Common 589
 
21.4%
Latin 56
 
2.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 115
 
5.5%
역 107
 
5.1%
시 61
 
2.9%
안 59
 
2.8%
고 57
 
2.7%
지 57
 
2.7%
산 54
 
2.6%
부 40
 
1.9%
단 37
 
1.8%
상 35
 
1.7%
Other values (222) 1480
70.4%
Common
ValueCountFrequency (%)
- 417
70.8%
, 58
 
9.8%
48
 
8.1%
1 16
 
2.7%
( 8
 
1.4%
) 8
 
1.4%
6 7
 
1.2%
7 5
 
0.8%
4 5
 
0.8%
2 5
 
0.8%
Other values (6) 12
 
2.0%
Latin
ValueCountFrequency (%)
A 38
67.9%
E 6
 
10.7%
v 2
 
3.6%
t 2
 
3.6%
m 2
 
3.6%
S 2
 
3.6%
C 1
 
1.8%
I 1
 
1.8%
G 1
 
1.8%
D 1
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2102
76.5%
ASCII 645
 
23.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 417
64.7%
, 58
 
9.0%
48
 
7.4%
A 38
 
5.9%
1 16
 
2.5%
( 8
 
1.2%
) 8
 
1.2%
6 7
 
1.1%
E 6
 
0.9%
7 5
 
0.8%
Other values (16) 34
 
5.3%
Hangul
ValueCountFrequency (%)
동 115
 
5.5%
역 107
 
5.1%
시 61
 
2.9%
안 59
 
2.8%
고 57
 
2.7%
지 57
 
2.7%
산 54
 
2.6%
부 40
 
1.9%
단 37
 
1.8%
상 35
 
1.7%
Other values (222) 1480
70.4%

운행대수
Real number (ℝ)

Distinct23
Distinct (%)35.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean7.8
Minimum1
Maximum32
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size717.0 B
2023-12-13T09:37:31.044621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q12
median5
Q312
95-th percentile25.4
Maximum32
Range31
Interquartile range (IQR)10

Descriptive statistics

Standard deviation7.7099773
Coefficient of variation (CV)0.98845863
Kurtosis1.4066529
Mean7.8
Median Absolute Deviation (MAD)3
Skewness1.4480881
Sum507
Variance59.44375
MonotonicityNot monotonic
2023-12-13T09:37:31.146657image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
2 11
16.9%
3 10
15.4%
1 8
12.3%
5 5
 
7.7%
6 5
 
7.7%
13 3
 
4.6%
9 3
 
4.6%
4 2
 
3.1%
12 2
 
3.1%
26 2
 
3.1%
Other values (13) 14
21.5%
ValueCountFrequency (%)
1 8
12.3%
2 11
16.9%
3 10
15.4%
4 2
 
3.1%
5 5
7.7%
6 5
7.7%
7 1
 
1.5%
8 1
 
1.5%
9 3
 
4.6%
10 1
 
1.5%
ValueCountFrequency (%)
32 1
1.5%
29 1
1.5%
26 2
3.1%
23 1
1.5%
21 1
1.5%
20 1
1.5%
18 1
1.5%
17 1
1.5%
16 2
3.1%
14 1
1.5%

첫차시간
Categorical

Distinct22
Distinct (%)33.8%
Missing0
Missing (%)0.0%
Memory size652.0 B
05:30
11 
05:40
8 
05:20
7 
04:50
6 
05:00
4 
Other values (17)
29 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique11 ?
Unique (%)16.9%

Sample

1st row06:10
2nd row06:00
3rd row05:10
4th row05:30
5th row04:50

Common Values

ValueCountFrequency (%)
05:30 11
16.9%
05:40 8
12.3%
05:20 7
10.8%
04:50 6
9.2%
05:00 4
 
6.2%
06:00 4
 
6.2%
05:50 4
 
6.2%
06:10 3
 
4.6%
05:10 3
 
4.6%
07:00 2
 
3.1%
Other values (12) 13
20.0%

Length

2023-12-13T09:37:31.264311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
05:30 11
16.9%
05:40 8
12.3%
05:20 7
10.8%
04:50 6
9.2%
05:00 4
 
6.2%
06:00 4
 
6.2%
05:50 4
 
6.2%
06:10 3
 
4.6%
05:10 3
 
4.6%
07:00 2
 
3.1%
Other values (12) 13
20.0%

막차시간
Categorical

Distinct27
Distinct (%)41.5%
Missing0
Missing (%)0.0%
Memory size652.0 B
23:00
13 
22:40
6 
22:30
6 
22:50
5 
22:00
5 
Other values (22)
30 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique16 ?
Unique (%)24.6%

Sample

1st row23:40
2nd row22:50
3rd row23:00
4th row22:55
5th row22:00

Common Values

ValueCountFrequency (%)
23:00 13
20.0%
22:40 6
 
9.2%
22:30 6
 
9.2%
22:50 5
 
7.7%
22:00 5
 
7.7%
23:10 3
 
4.6%
23:20 3
 
4.6%
19:30 2
 
3.1%
21:50 2
 
3.1%
21:40 2
 
3.1%
Other values (17) 18
27.7%

Length

2023-12-13T09:37:31.366102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
23:00 13
20.0%
22:30 6
 
9.2%
22:40 6
 
9.2%
22:50 5
 
7.7%
22:00 5
 
7.7%
23:10 3
 
4.6%
23:20 3
 
4.6%
20:30 2
 
3.1%
21:40 2
 
3.1%
21:50 2
 
3.1%
Other values (17) 18
27.7%

배차간격
Text

Distinct34
Distinct (%)52.3%
Missing0
Missing (%)0.0%
Memory size652.0 B
2023-12-13T09:37:31.490954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length4.9230769
Min length2

Characters and Unicode

Total characters320
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

Unique23 ?
Unique (%)35.4%

Sample

1st row8~15
2nd row25~50
3rd row20~30
4th row10~20
5th row20~40
ValueCountFrequency (%)
20~40 10
 
15.4%
10~20 7
 
10.8%
15~25 5
 
7.7%
40~60 3
 
4.6%
20~30 3
 
4.6%
10~15 3
 
4.6%
30~60 3
 
4.6%
5~10 2
 
3.1%
40 2
 
3.1%
8~15 2
 
3.1%
Other values (24) 25
38.5%
2023-12-13T09:37:31.742107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 97
30.3%
~ 62
19.4%
2 38
 
11.9%
1 38
 
11.9%
5 31
 
9.7%
4 20
 
6.2%
3 12
 
3.8%
8 9
 
2.8%
6 8
 
2.5%
9 3
 
0.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 258
80.6%
Math Symbol 62
 
19.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 97
37.6%
2 38
 
14.7%
1 38
 
14.7%
5 31
 
12.0%
4 20
 
7.8%
3 12
 
4.7%
8 9
 
3.5%
6 8
 
3.1%
9 3
 
1.2%
7 2
 
0.8%
Math Symbol
ValueCountFrequency (%)
~ 62
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 320
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 97
30.3%
~ 62
19.4%
2 38
 
11.9%
1 38
 
11.9%
5 31
 
9.7%
4 20
 
6.2%
3 12
 
3.8%
8 9
 
2.8%
6 8
 
2.5%
9 3
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 320
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 97
30.3%
~ 62
19.4%
2 38
 
11.9%
1 38
 
11.9%
5 31
 
9.7%
4 20
 
6.2%
3 12
 
3.8%
8 9
 
2.8%
6 8
 
2.5%
9 3
 
0.9%

차고지명
Categorical

HIGH CORRELATION 

Distinct13
Distinct (%)20.0%
Missing0
Missing (%)0.0%
Memory size652.0 B
성곡동
22 
원시동
11 
본오동
11 
오이도
5 
선부동
3 
Other values (8)
13 

Length

Max length8
Median length3
Mean length3.7076923
Min length2

Unique

Unique4 ?
Unique (%)6.2%

Sample

1st row성곡동
2nd row원시동
3rd row성곡동
4th row선부동
5th row원시동, 대부도

Common Values

ValueCountFrequency (%)
성곡동 22
33.8%
원시동 11
16.9%
본오동 11
16.9%
오이도 5
 
7.7%
선부동 3
 
4.6%
원시동(대부도) 3
 
4.6%
정왕동, 원시동 2
 
3.1%
안양 2
 
3.1%
오이도, 본오동 2
 
3.1%
원시동, 대부도 1
 
1.5%
Other values (3) 3
 
4.6%

Length

2023-12-13T09:37:31.845647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
성곡동 22
30.6%
원시동 15
20.8%
본오동 14
19.4%
오이도 8
 
11.1%
선부동 3
 
4.2%
원시동(대부도 3
 
4.2%
안양 3
 
4.2%
정왕동 2
 
2.8%
대부도 1
 
1.4%
부천 1
 
1.4%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size652.0 B
2023-10-27
65 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-10-27
2nd row2023-10-27
3rd row2023-10-27
4th row2023-10-27
5th row2023-10-27

Common Values

ValueCountFrequency (%)
2023-10-27 65
100.0%

Length

2023-12-13T09:37:31.937956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T09:37:32.009683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-10-27 65
100.0%

Interactions

2023-12-13T09:37:28.429632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:37:28.309438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:37:28.503009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T09:37:28.369713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T09:37:32.063633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번업체명노선번호기점종점정류소운행대수첫차시간막차시간배차간격차고지명
연번1.0000.4541.0000.7900.9391.0000.0000.5170.5310.0000.558
업체명0.4541.0001.0000.9960.9721.0000.3260.6720.7560.1200.795
노선번호1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
기점0.7900.9961.0001.0000.9800.9200.0000.0000.8710.8580.955
종점0.9390.9721.0000.9801.0000.9940.9250.9250.8360.9750.891
정류소1.0001.0001.0000.9200.9941.0001.0000.9890.9620.9951.000
운행대수0.0000.3261.0000.0000.9251.0001.0000.6490.0000.0000.764
첫차시간0.5170.6721.0000.0000.9250.9890.6491.0000.8530.7980.000
막차시간0.5310.7561.0000.8710.8360.9620.0000.8531.0000.9110.000
배차간격0.0000.1201.0000.8580.9750.9950.0000.7980.9111.0000.000
차고지명0.5580.7951.0000.9550.8911.0000.7640.0000.0000.0001.000
2023-12-13T09:37:32.156061image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
막차시간차고지명첫차시간업체명
막차시간1.0000.0000.3640.379
차고지명0.0001.0000.0000.594
첫차시간0.3640.0001.0000.378
업체명0.3790.5940.3781.000
2023-12-13T09:37:32.225852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번운행대수업체명첫차시간막차시간차고지명
연번1.000-0.1330.2860.1790.1650.256
운행대수-0.1331.0000.1890.2590.0000.434
업체명0.2860.1891.0000.3780.3790.594
첫차시간0.1790.2590.3781.0000.3640.000
막차시간0.1650.0000.3790.3641.0000.000
차고지명0.2560.4340.5940.0000.0001.000

Missing values

2023-12-13T09:37:28.611940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T09:37:28.745780image/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

연번업체명노선번호기점종점정류소운행대수첫차시간막차시간배차간격차고지명데이터기준일자
01경원여객10번중앙역1번출구새솔고중앙역-안산문화광장-호수공원-푸르지오6,7,9차A-경기테크노파크-송산그린시티706:1023:408~15성곡동2023-10-27
12경원여객10-1번상록수역앞푸르지오6차후문상록수역-푸른마을A-성안고-한양대입구-게스트하우스-경기테크노파크-푸르지오6,7,9차A206:0022:5025~50원시동2023-10-27
23경원여객101번경원여객사리운동장반월공단차고지-안산역-초지역-선부동-와동-중앙동-상록수역-본오동1405:1023:0020~30성곡동2023-10-27
34경원여객110번선부동차고지수원역.노보텔수원수원역-농촌진흥청-상록수역-예술인A-자유센타-와동-선부동1105:3022:5510~20선부동2023-10-27
45태화상운123번세영리첼탄도푸르지오6.7차 중앙역, 안산역, 시흥관광호텔, 시화이마트, 오이도역, 서울대시흥캠퍼스, 방아머리, 탄도1304:5022:0020~40원시동, 대부도2023-10-27
56써클라인125번홈플러스본오1동행정복지센터유천A-안산역-안산시청-한대앞-일동-상록수역2305:0022:3010~15정왕동, 원시동2023-10-27
67경원여객13번새솔고원시역1번출구세영리첼-이지더원-대방노블랜드-에코팜타운-경인합섬앞106:2022:4030~40성곡동2023-10-27
78경원여객16번상록수역3번출구건너편새솔고본오주공A-사리역-정비단지-그랑시티자이305:4022:3020~40원시동2023-10-27
89경원여객2번경원여객안산역(도로변)환경사업소-로지스밸리-S파워-진로발효-우성염직-시우역-초지역405:4022:2520~30성곡동2023-10-27
910경원여객20번경원여객시흥시청후문.종합일자리센터반월공단-안산역-신길고-도일시장-능곡지구205:3022:0040~50성곡동2023-10-27
연번업체명노선번호기점종점정류소운행대수첫차시간막차시간배차간격차고지명데이터기준일자
5556써클라인80A번안산해솔초등학교안산갈대습지호수공원-중앙역-한대앞역-일동행정복지센터-상록수역-신안A-사리역-정비단지605:4023:2010~20본오동2023-10-27
5657써클라인80B번안산해솔초등학교안산갈대습지정비단지-사리역-신안A-상록수역-일동행정복지센터-한대앞역-중앙역-호수공원605:4023:2010~20본오동2023-10-27
5758경원여객80C번본오아파트앞상록수역3번출구건너편그랑시티자이-사동대우6차A-호수공원-안산문화광장-중앙역-한대앞역-상록수역305:3022:3530~50성곡동2023-10-27
5859경원여객9번선부동차고지중앙역1번출구선부동차고지-선부3동-와동-올림픽기념관-자유센터-안산시청-중앙동-중앙역306:0021:4020~40선부동2023-10-27
5960경원여객9-1번선부동차고지중앙역1번출구관산중-선부고-땟골-선부2동행정복지센터-라프리모-단원구청-안산시청305:4021:4025~35성곡동2023-10-27
6061경원여객90번삼천리마을앞상록수역3번출구건너편반월역-반월농협-팔곡마을주공A-도금단지-각골공원-사리역-태영A205:4021:2030~60본오동2023-10-27
6162경원여객98번오이도차고지수변공원휴게소사동대우6,7차A-신도시중심상가-와동-선부동-안산역-반월공단-시화공단806:0022:0020~40오이도2023-10-27
6263경원여객99번오이도차고지삼천리마을앞반월동-본오동-상록수-중앙역-안산시청-안산역-시화E마트-오이도차고지1205:2023:0015~20오이도, 본오동2023-10-27
6364경원여객99-1번본오동종점새솔고본오동차고지-상록수역-부곡동-월피동-중앙역-예술인A-고대병원-신도시중심상가-E마트-사동대우6,7차-송산그린시티1705:0523:0015~25본오동, 원시동2023-10-27
6465경원여객M6410번사리울중학교강남역서초현대타워앞11.12단지, 청능로사거리, 주공10.11단지, 소래포구입구, 월곶 풍림아파트, 정왕IC, 고속도로, 선바위역, 우면산터널, 서초역, 교대역, 양재역, 시민의숲양재꽃시장1305:5023:308~15오이도2023-10-27