Overview

Dataset statistics

Number of variables8
Number of observations64
Missing cells42
Missing cells (%)8.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.1 KiB
Average record size in memory66.0 B

Variable types

Categorical4
Text4

Dataset

Description세종특별자치시 고속버스, 시외버스, 시내버스운행 정보 및 세부 버스 시간표 입니다.세종특별자치시 교통정보센터 홈페이지에서 버스 노선, 경유 정류장 및 실시간 버스 위치정보를 확인하실 수 있습니다.
Author세종특별자치시
URLhttps://www.data.go.kr/data/3077230/fileData.do

Alerts

등록기준일 has constant value ""Constant
구분 is highly overall correlated with 기점지High correlation
기점지 is highly overall correlated with 구분High correlation
경유지 has 3 (4.7%) missing valuesMissing
배차간격 has 39 (60.9%) missing valuesMissing
노선번호 has unique valuesUnique

Reproduction

Analysis started2024-03-14 10:07:45.023333
Analysis finished2024-03-14 10:07:46.493712
Duration1.47 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구분
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)7.8%
Missing0
Missing (%)0.0%
Memory size640.0 B
마을버스
34 
지선버스
14 
간선버스
8 
BRT
4 
광역버스
4 

Length

Max length4
Median length4
Mean length3.9375
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowBRT
2nd rowBRT
3rd rowBRT
4th rowBRT
5th row광역버스

Common Values

ValueCountFrequency (%)
마을버스 34
53.1%
지선버스 14
21.9%
간선버스 8
 
12.5%
BRT 4
 
6.2%
광역버스 4
 
6.2%

Length

2024-03-14T19:07:46.613540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T19:07:47.009765image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
마을버스 34
53.1%
지선버스 14
21.9%
간선버스 8
 
12.5%
brt 4
 
6.2%
광역버스 4
 
6.2%

노선번호
Text

UNIQUE 

Distinct64
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size640.0 B
2024-03-14T19:07:47.951074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length2
Mean length2.40625
Min length2

Characters and Unicode

Total characters154
Distinct characters11
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

Unique64 ?
Unique (%)100.0%

Sample

1st rowB0
2nd rowB2
3rd rowB4
4th rowB5
5th row1000
ValueCountFrequency (%)
b0 1
 
1.6%
b2 1
 
1.6%
71 1
 
1.6%
33 1
 
1.6%
34 1
 
1.6%
35 1
 
1.6%
54 1
 
1.6%
62 1
 
1.6%
63 1
 
1.6%
64 1
 
1.6%
Other values (54) 54
84.4%
2024-03-14T19:07:49.151376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 25
16.2%
0 22
14.3%
2 18
11.7%
6 17
11.0%
5 16
10.4%
3 16
10.4%
4 11
7.1%
9 10
 
6.5%
7 8
 
5.2%
8 7
 
4.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 150
97.4%
Uppercase Letter 4
 
2.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 25
16.7%
0 22
14.7%
2 18
12.0%
6 17
11.3%
5 16
10.7%
3 16
10.7%
4 11
7.3%
9 10
 
6.7%
7 8
 
5.3%
8 7
 
4.7%
Uppercase Letter
ValueCountFrequency (%)
B 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 150
97.4%
Latin 4
 
2.6%

Most frequent character per script

Common
ValueCountFrequency (%)
1 25
16.7%
0 22
14.7%
2 18
12.0%
6 17
11.3%
5 16
10.7%
3 16
10.7%
4 11
7.3%
9 10
 
6.7%
7 8
 
5.3%
8 7
 
4.7%
Latin
ValueCountFrequency (%)
B 4
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 154
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 25
16.2%
0 22
14.3%
2 18
11.7%
6 17
11.0%
5 16
10.4%
3 16
10.4%
4 11
7.1%
9 10
 
6.5%
7 8
 
5.2%
8 7
 
4.5%

기점지
Categorical

HIGH CORRELATION 

Distinct19
Distinct (%)29.7%
Missing0
Missing (%)0.0%
Memory size640.0 B
조치원터미널
24 
세종터미널
13 
전의역
5 
조치원역
3 
오송역
 
2
Other values (14)
17 

Length

Max length11
Median length9
Mean length5.53125
Min length3

Unique

Unique11 ?
Unique (%)17.2%

Sample

1st row세종고속시외버스터미널
2nd row오송역
3rd row오송역
4th row세종고속시외버스터미널
5th row조치원 신안2리

Common Values

ValueCountFrequency (%)
조치원터미널 24
37.5%
세종터미널 13
20.3%
전의역 5
 
7.8%
조치원역 3
 
4.7%
오송역 2
 
3.1%
장군면사무소 2
 
3.1%
세종고속시외버스터미널 2
 
3.1%
정부세종청사 2
 
3.1%
꽃동네대학교 1
 
1.6%
부강면 1
 
1.6%
Other values (9) 9
 
14.1%

Length

2024-03-14T19:07:49.403077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
조치원터미널 24
36.9%
세종터미널 13
20.0%
전의역 5
 
7.7%
조치원역 3
 
4.6%
오송역 2
 
3.1%
장군면사무소 2
 
3.1%
세종고속시외버스터미널 2
 
3.1%
정부세종청사 2
 
3.1%
장기중학교 1
 
1.5%
은하수공원 1
 
1.5%
Other values (10) 10
15.4%

경유지
Text

MISSING 

Distinct48
Distinct (%)78.7%
Missing3
Missing (%)4.7%
Memory size640.0 B
2024-03-14T19:07:50.182601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length9
Mean length5.0983607
Min length3

Characters and Unicode

Total characters311
Distinct characters105
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

Unique43 ?
Unique (%)70.5%

Sample

1st row정부세종청사
2nd row정부세종청사
3rd row세종시청
4th row고운동+아름동
5th row고운뜰공원
ValueCountFrequency (%)
정부세종청사 8
 
13.1%
다정동커뮤니티센터 3
 
4.9%
명학산업단지 3
 
4.9%
베어트리파크 2
 
3.3%
황용리 2
 
3.3%
석교리 1
 
1.6%
송곡1리 1
 
1.6%
심중리 1
 
1.6%
연서면 1
 
1.6%
봉암리 1
 
1.6%
Other values (38) 38
62.3%
2024-03-14T19:07:51.397771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
리 27
 
8.7%
정 15
 
4.8%
세 13
 
4.2%
종 13
 
4.2%
부 10
 
3.2%
단 9
 
2.9%
사 9
 
2.9%
청 9
 
2.9%
지 8
 
2.6%
동 8
 
2.6%
Other values (95) 190
61.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 302
97.1%
Decimal Number 6
 
1.9%
Math Symbol 3
 
1.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 27
 
8.9%
정 15
 
5.0%
세 13
 
4.3%
종 13
 
4.3%
부 10
 
3.3%
단 9
 
3.0%
사 9
 
3.0%
청 9
 
3.0%
지 8
 
2.6%
동 8
 
2.6%
Other values (92) 181
59.9%
Decimal Number
ValueCountFrequency (%)
2 3
50.0%
1 3
50.0%
Math Symbol
ValueCountFrequency (%)
+ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 302
97.1%
Common 9
 
2.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 27
 
8.9%
정 15
 
5.0%
세 13
 
4.3%
종 13
 
4.3%
부 10
 
3.3%
단 9
 
3.0%
사 9
 
3.0%
청 9
 
3.0%
지 8
 
2.6%
동 8
 
2.6%
Other values (92) 181
59.9%
Common
ValueCountFrequency (%)
2 3
33.3%
+ 3
33.3%
1 3
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 302
97.1%
ASCII 9
 
2.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
리 27
 
8.9%
정 15
 
5.0%
세 13
 
4.3%
종 13
 
4.3%
부 10
 
3.3%
단 9
 
3.0%
사 9
 
3.0%
청 9
 
3.0%
지 8
 
2.6%
동 8
 
2.6%
Other values (92) 181
59.9%
ASCII
ValueCountFrequency (%)
2 3
33.3%
+ 3
33.3%
1 3
33.3%

종점지
Text

Distinct42
Distinct (%)65.6%
Missing0
Missing (%)0.0%
Memory size640.0 B
2024-03-14T19:07:52.228204image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length9
Mean length4.8125
Min length3

Characters and Unicode

Total characters308
Distinct characters95
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique31 ?
Unique (%)48.4%

Sample

1st row세종고속시외버스터미널
2nd row반석역
3rd row반석역
4th row세종고속시외버스터미널
5th row반석역
ValueCountFrequency (%)
조치원터미널 6
 
9.2%
반석역 5
 
7.7%
부강면 4
 
6.2%
세종터미널 4
 
6.2%
송정리 2
 
3.1%
세종고속시외버스터미널 2
 
3.1%
전의역 2
 
3.1%
송성3리 2
 
3.1%
장군면사무소 2
 
3.1%
정부세종청사 2
 
3.1%
Other values (33) 34
52.3%
2024-03-14T19:07:53.517134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
리 17
 
5.5%
터 12
 
3.9%
미 12
 
3.9%
널 12
 
3.9%
원 11
 
3.6%
종 10
 
3.2%
세 9
 
2.9%
역 9
 
2.9%
강 8
 
2.6%
면 7
 
2.3%
Other values (85) 201
65.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 293
95.1%
Decimal Number 10
 
3.2%
Math Symbol 2
 
0.6%
Open Punctuation 1
 
0.3%
Space Separator 1
 
0.3%
Close Punctuation 1
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 17
 
5.8%
터 12
 
4.1%
미 12
 
4.1%
널 12
 
4.1%
원 11
 
3.8%
종 10
 
3.4%
세 9
 
3.1%
역 9
 
3.1%
강 8
 
2.7%
면 7
 
2.4%
Other values (76) 186
63.5%
Decimal Number
ValueCountFrequency (%)
2 4
40.0%
1 2
20.0%
3 2
20.0%
8 1
 
10.0%
9 1
 
10.0%
Math Symbol
ValueCountFrequency (%)
+ 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 293
95.1%
Common 15
 
4.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 17
 
5.8%
터 12
 
4.1%
미 12
 
4.1%
널 12
 
4.1%
원 11
 
3.8%
종 10
 
3.4%
세 9
 
3.1%
역 9
 
3.1%
강 8
 
2.7%
면 7
 
2.4%
Other values (76) 186
63.5%
Common
ValueCountFrequency (%)
2 4
26.7%
1 2
13.3%
+ 2
13.3%
3 2
13.3%
( 1
 
6.7%
1
 
6.7%
8 1
 
6.7%
9 1
 
6.7%
) 1
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 293
95.1%
ASCII 15
 
4.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
리 17
 
5.8%
터 12
 
4.1%
미 12
 
4.1%
널 12
 
4.1%
원 11
 
3.8%
종 10
 
3.4%
세 9
 
3.1%
역 9
 
3.1%
강 8
 
2.7%
면 7
 
2.4%
Other values (76) 186
63.5%
ASCII
ValueCountFrequency (%)
2 4
26.7%
1 2
13.3%
+ 2
13.3%
3 2
13.3%
( 1
 
6.7%
1
 
6.7%
8 1
 
6.7%
9 1
 
6.7%
) 1
 
6.7%

배차간격
Text

MISSING 

Distinct14
Distinct (%)56.0%
Missing39
Missing (%)60.9%
Memory size640.0 B
2024-03-14T19:07:54.217459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length6
Mean length6.92
Min length1

Characters and Unicode

Total characters173
Distinct characters20
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

Unique8 ?
Unique (%)32.0%

Sample

1st row8~12분
2nd row6~10분
3rd row20~30분
4th row15~20분
5th row평일 15분+주말 및 공휴일 20분
ValueCountFrequency (%)
30분 6
14.0%
평일 5
11.6%
및 5
11.6%
공휴일 5
11.6%
10~15분 3
 
7.0%
20분 3
 
7.0%
10분+주말 2
 
4.7%
15분 2
 
4.7%
60분 2
 
4.7%
15분+주말 2
 
4.7%
Other values (8) 8
18.6%
2024-03-14T19:07:55.328645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
분 28
16.2%
22
12.7%
0 21
12.1%
1 18
10.4%
5 10
 
5.8%
일 10
 
5.8%
3 8
 
4.6%
~ 8
 
4.6%
2 7
 
4.0%
및 5
 
2.9%
Other values (10) 36
20.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 70
40.5%
Other Letter 68
39.3%
Space Separator 22
 
12.7%
Math Symbol 13
 
7.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 21
30.0%
1 18
25.7%
5 10
14.3%
3 8
 
11.4%
2 7
 
10.0%
6 3
 
4.3%
8 1
 
1.4%
7 1
 
1.4%
4 1
 
1.4%
Other Letter
ValueCountFrequency (%)
분 28
41.2%
일 10
 
14.7%
및 5
 
7.4%
휴 5
 
7.4%
공 5
 
7.4%
주 5
 
7.4%
말 5
 
7.4%
평 5
 
7.4%
Math Symbol
ValueCountFrequency (%)
~ 8
61.5%
+ 5
38.5%
Space Separator
ValueCountFrequency (%)
22
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 105
60.7%
Hangul 68
39.3%

Most frequent character per script

Common
ValueCountFrequency (%)
22
21.0%
0 21
20.0%
1 18
17.1%
5 10
9.5%
3 8
 
7.6%
~ 8
 
7.6%
2 7
 
6.7%
+ 5
 
4.8%
6 3
 
2.9%
8 1
 
1.0%
Other values (2) 2
 
1.9%
Hangul
ValueCountFrequency (%)
분 28
41.2%
일 10
 
14.7%
및 5
 
7.4%
휴 5
 
7.4%
공 5
 
7.4%
주 5
 
7.4%
말 5
 
7.4%
평 5
 
7.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 105
60.7%
Hangul 68
39.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
분 28
41.2%
일 10
 
14.7%
및 5
 
7.4%
휴 5
 
7.4%
공 5
 
7.4%
주 5
 
7.4%
말 5
 
7.4%
평 5
 
7.4%
ASCII
ValueCountFrequency (%)
22
21.0%
0 21
20.0%
1 18
17.1%
5 10
9.5%
3 8
 
7.6%
~ 8
 
7.6%
2 7
 
6.7%
+ 5
 
4.8%
6 3
 
2.9%
8 1
 
1.0%
Other values (2) 2
 
1.9%

운행횟수
Categorical

Distinct14
Distinct (%)21.9%
Missing0
Missing (%)0.0%
Memory size640.0 B
<NA>
27 
8회
9 
10회
6 
1회
4 
9회
3 
Other values (9)
15 

Length

Max length4
Median length3
Mean length2.984375
Min length2

Unique

Unique5 ?
Unique (%)7.8%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 27
42.2%
8회 9
 
14.1%
10회 6
 
9.4%
1회 4
 
6.2%
9회 3
 
4.7%
6회 3
 
4.7%
7회 3
 
4.7%
3회 2
 
3.1%
4회 2
 
3.1%
12회 1
 
1.6%
Other values (4) 4
 
6.2%

Length

2024-03-14T19:07:55.764228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 27
42.2%
8회 9
 
14.1%
10회 6
 
9.4%
1회 4
 
6.2%
9회 3
 
4.7%
6회 3
 
4.7%
7회 3
 
4.7%
3회 2
 
3.1%
4회 2
 
3.1%
12회 1
 
1.6%
Other values (4) 4
 
6.2%

등록기준일
Categorical

CONSTANT 

Distinct1
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Memory size640.0 B
2024-01-05
64 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2024-01-05
2nd row2024-01-05
3rd row2024-01-05
4th row2024-01-05
5th row2024-01-05

Common Values

ValueCountFrequency (%)
2024-01-05 64
100.0%

Length

2024-03-14T19:07:56.167109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T19:07:56.476389image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2024-01-05 64
100.0%

Correlations

2024-03-14T19:07:56.663375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분노선번호기점지경유지종점지배차간격운행횟수
구분1.0001.0000.9480.0000.8500.9300.000
노선번호1.0001.0001.0001.0001.0001.0001.000
기점지0.9481.0001.0000.0000.9520.7760.746
경유지0.0001.0000.0001.0000.9350.3910.000
종점지0.8501.0000.9520.9351.0000.7610.000
배차간격0.9301.0000.7760.3910.7611.000NaN
운행횟수0.0001.0000.7460.0000.000NaN1.000
2024-03-14T19:07:56.951067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분기점지운행횟수
구분1.0000.7230.000
기점지0.7231.0000.449
운행횟수0.0000.4491.000
2024-03-14T19:07:57.191300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분기점지운행횟수
구분1.0000.7230.000
기점지0.7231.0000.449
운행횟수0.0000.4491.000

Missing values

2024-03-14T19:07:45.665868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T19:07:46.079415image/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.
2024-03-14T19:07:46.401159image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

구분노선번호기점지경유지종점지배차간격운행횟수등록기준일
0BRTB0세종고속시외버스터미널정부세종청사세종고속시외버스터미널8~12분<NA>2024-01-05
1BRTB2오송역정부세종청사반석역6~10분<NA>2024-01-05
2BRTB4오송역세종시청반석역20~30분<NA>2024-01-05
3BRTB5세종고속시외버스터미널고운동+아름동세종고속시외버스터미널15~20분<NA>2024-01-05
4광역버스1000조치원 신안2리고운뜰공원반석역평일 15분+주말 및 공휴일 20분<NA>2024-01-05
5광역버스1001집현동국책연구단지+현대아울렛대전시청평일 13분+주말 및 공휴일 17분<NA>2024-01-05
6광역버스1004장기중학교다정동커뮤니티센터반석역평일 15분+주말 및 공휴일 20분<NA>2024-01-05
7광역버스1005은하수공원다정동커뮤니티센터반석역15~25분<NA>2024-01-05
8지선버스11조치원터미널신안리조치원터미널30분<NA>2024-01-05
9지선버스12조치원터미널번암리조치원터미널30분<NA>2024-01-05
구분노선번호기점지경유지종점지배차간격운행횟수등록기준일
54마을버스82전의역세종미래산업단지다방1리<NA>10회2024-01-05
55마을버스83전의역세종첨단산업단지전의역<NA>10회2024-01-05
56마을버스84전의역전의산업단지전의역<NA>10회2024-01-05
57마을버스85전의역소정리고등1리<NA>7회2024-01-05
58마을버스86조치원터미널다방1리재동아파트<NA>4회2024-01-05
59마을버스91조치원터미널심중리봉대리<NA>8회2024-01-05
60마을버스92조치원터미널석곡리청람리<NA>8회2024-01-05
61마을버스93조치원터미널송곡1리송정리<NA>13회2024-01-05
62마을버스94조치원터미널송곡2리송정리<NA>6회2024-01-05
63마을버스95조치원터미널베어트리파크송성3리<NA>4회2024-01-05