Overview

Dataset statistics

Number of variables10
Number of observations44
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.7 KiB
Average record size in memory86.0 B

Variable types

Categorical4
Text3
Numeric2
DateTime1

Dataset

Description제주특별자치도내 읍면지역에서 운행하는 시내/외 버스 관련한 데이터로 노선명, 운행구간, 거리, 운행횟수, 배차간격, 운행업체 등 정보를 제공합니다.
Author제주특별자치도
URLhttps://www.data.go.kr/data/15051472/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
거리(km) is highly overall correlated with 운행대수 (평일)High correlation
1일운행횟수 (평일) is highly overall correlated with 운행대수 (평일) and 1 other fieldsHigh correlation
행정시 is highly overall correlated with 운행업체High correlation
운행대수 (평일) is highly overall correlated with 거리(km) and 2 other fieldsHigh correlation
운행업체 is highly overall correlated with 행정시High correlation
비고 is highly overall correlated with 1일운행횟수 (평일) and 1 other fieldsHigh correlation
노선명 has unique valuesUnique
운행구간 has unique valuesUnique

Reproduction

Analysis started2023-12-12 23:05:03.528700
Analysis finished2023-12-12 23:05:04.682198
Duration1.15 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

행정시
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)4.5%
Missing0
Missing (%)0.0%
Memory size484.0 B
제주시
25 
서귀포시
19 

Length

Max length4
Median length3
Mean length3.4318182
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
제주시 25
56.8%
서귀포시 19
43.2%

Length

2023-12-13T08:05:04.760864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:05:04.908355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
제주시 25
56.8%
서귀포시 19
43.2%

노선명
Text

UNIQUE 

Distinct44
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size484.0 B
2023-12-13T08:05:05.123095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length5
Mean length6.1136364
Min length3

Characters and Unicode

Total characters269
Distinct characters14
Distinct categories5 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique44 ?
Unique (%)100.0%

Sample

1st row701(-1.-2)
2nd row702(-1.-2)
3rd row703(-1.-2)
4th row704(-1.-3)
5th row704(-2.-3)
ValueCountFrequency (%)
701(-1.-2 1
 
2.3%
702(-1.-2 1
 
2.3%
732-2 1
 
2.3%
795 1
 
2.3%
721-2 1
 
2.3%
721-3 1
 
2.3%
722-1 1
 
2.3%
722-2 1
 
2.3%
731-1 1
 
2.3%
731-2 1
 
2.3%
Other values (34) 34
77.3%
2023-12-13T08:05:05.474927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 50
18.6%
7 47
17.5%
1 41
15.2%
2 38
14.1%
3 16
 
5.9%
4 13
 
4.8%
( 12
 
4.5%
. 12
 
4.5%
) 12
 
4.5%
8 7
 
2.6%
Other values (4) 21
7.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 183
68.0%
Dash Punctuation 50
 
18.6%
Open Punctuation 12
 
4.5%
Other Punctuation 12
 
4.5%
Close Punctuation 12
 
4.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
7 47
25.7%
1 41
22.4%
2 38
20.8%
3 16
 
8.7%
4 13
 
7.1%
8 7
 
3.8%
9 7
 
3.8%
0 6
 
3.3%
5 5
 
2.7%
6 3
 
1.6%
Dash Punctuation
ValueCountFrequency (%)
- 50
100.0%
Open Punctuation
ValueCountFrequency (%)
( 12
100.0%
Other Punctuation
ValueCountFrequency (%)
. 12
100.0%
Close Punctuation
ValueCountFrequency (%)
) 12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 269
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 50
18.6%
7 47
17.5%
1 41
15.2%
2 38
14.1%
3 16
 
5.9%
4 13
 
4.8%
( 12
 
4.5%
. 12
 
4.5%
) 12
 
4.5%
8 7
 
2.6%
Other values (4) 21
7.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 269
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 50
18.6%
7 47
17.5%
1 41
15.2%
2 38
14.1%
3 16
 
5.9%
4 13
 
4.8%
( 12
 
4.5%
. 12
 
4.5%
) 12
 
4.5%
8 7
 
2.6%
Other values (4) 21
7.8%

운행구간
Text

UNIQUE 

Distinct44
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size484.0 B
2023-12-13T08:05:05.750921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length103
Median length60.5
Mean length53.545455
Min length26

Characters and Unicode

Total characters2356
Distinct characters226
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique44 ?
Unique (%)100.0%

Sample

1st row조천체육관-조천-함덕-함덕에덴빌리지-대흘2-와산-대흘교차로-남조로검문소-돌문화공원/돌문화공원-고평동-뒷산길-대흘1리-와흘-신안동-동수동-조천체육관
2nd row조천체육관-조천-함덕-대흘2-와산-대흘1-와흘-신안동-동수동-조천체육관(신흥리경유)
3rd row신촌-조천-함덕-함덕에덴빌리지-신사동-대흘2-봉소동-대흘초-양천하동-병디왓-조천-신촌
4th row조천체육관-억수동-낙선동-선흘-목선동-선인동-선흘2리-조천만세동산
5th row조천체육관-대흘2리-금산-와산-선인동-선흘2리-조천만세동산
ValueCountFrequency (%)
조천체육관-조천-함덕-함덕에덴빌리지-대흘2-와산-대흘교차로-남조로검문소-돌문화공원/돌문화공원-고평동-뒷산길-대흘1리-와흘-신안동-동수동-조천체육관 1
 
2.2%
성읍-가시리-토산1리-세화1리-허브동산-농기구수리센터-표선고-표선면사무소-제주민속촌 1
 
2.2%
애월-납읍-봉성리사무소-어음1리사무소-어음2리사무소 1
 
2.2%
표선생활체육관-표선리-향기마을-가시리-역지동-향기마을-허브동산-표선면사무소-표선고-예담요양원-표선생활체육관 1
 
2.2%
한라수목원-하귀가문동)-하귀해안도로-애월해안도로 1
 
2.2%
대천-수산2-수산1-고성-일출봉입구-성산고-성산읍사무소-신양리-섭지코지-고성리(구.한국물류 1
 
2.2%
성읍-수산2-수산1마을-성산읍사무소-신양리입구-섭지코지-동모루왓-제주은행-광치기해변-성산고-고성오일시장-고성리(구.한국물류 1
 
2.2%
성읍-신풍입구-신풍하동-농협신산지점-선인장마을-난산-온평초-신양리입구-성산읍사무소-고성오일시장-성산고-광치기해변-제주은행-고성리(구.한국물류 1
 
2.2%
성읍-일출랜드입구-삼달1-김영갑갤러리-삼달교차로-신산-난산-온평초-성산읍사무소-고성오일시장-성산고-광치기해변-고성리(구.한국물류 1
 
2.2%
성읍-삼달1-신풍-하천-표선고-표선리-제주민속촌 1
 
2.2%
Other values (36) 36
78.3%
2023-12-13T08:05:06.146764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 440
 
18.7%
리 104
 
4.4%
동 80
 
3.4%
산 50
 
2.1%
성 43
 
1.8%
수 43
 
1.8%
신 40
 
1.7%
사 38
 
1.6%
한 35
 
1.5%
고 32
 
1.4%
Other values (216) 1451
61.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1802
76.5%
Dash Punctuation 440
 
18.7%
Decimal Number 64
 
2.7%
Close Punctuation 21
 
0.9%
Open Punctuation 21
 
0.9%
Other Punctuation 6
 
0.3%
Space Separator 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
리 104
 
5.8%
동 80
 
4.4%
산 50
 
2.8%
성 43
 
2.4%
수 43
 
2.4%
신 40
 
2.2%
사 38
 
2.1%
한 35
 
1.9%
고 32
 
1.8%
소 31
 
1.7%
Other values (207) 1306
72.5%
Decimal Number
ValueCountFrequency (%)
1 28
43.8%
2 26
40.6%
3 10
 
15.6%
Other Punctuation
ValueCountFrequency (%)
. 4
66.7%
/ 2
33.3%
Dash Punctuation
ValueCountFrequency (%)
- 440
100.0%
Close Punctuation
ValueCountFrequency (%)
) 21
100.0%
Open Punctuation
ValueCountFrequency (%)
( 21
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1802
76.5%
Common 554
 
23.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
리 104
 
5.8%
동 80
 
4.4%
산 50
 
2.8%
성 43
 
2.4%
수 43
 
2.4%
신 40
 
2.2%
사 38
 
2.1%
한 35
 
1.9%
고 32
 
1.8%
소 31
 
1.7%
Other values (207) 1306
72.5%
Common
ValueCountFrequency (%)
- 440
79.4%
1 28
 
5.1%
2 26
 
4.7%
) 21
 
3.8%
( 21
 
3.8%
3 10
 
1.8%
. 4
 
0.7%
2
 
0.4%
/ 2
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1802
76.5%
ASCII 554
 
23.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 440
79.4%
1 28
 
5.1%
2 26
 
4.7%
) 21
 
3.8%
( 21
 
3.8%
3 10
 
1.8%
. 4
 
0.7%
2
 
0.4%
/ 2
 
0.4%
Hangul
ValueCountFrequency (%)
리 104
 
5.8%
동 80
 
4.4%
산 50
 
2.8%
성 43
 
2.4%
수 43
 
2.4%
신 40
 
2.2%
사 38
 
2.1%
한 35
 
1.9%
고 32
 
1.8%
소 31
 
1.7%
Other values (207) 1306
72.5%

거리(km)
Real number (ℝ)

HIGH CORRELATION 

Distinct41
Distinct (%)93.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean26.193182
Minimum13.4
Maximum52.8
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size528.0 B
2023-12-13T08:05:06.257979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum13.4
5-th percentile16.175
Q120.075
median25.35
Q329.65
95-th percentile39.495
Maximum52.8
Range39.4
Interquartile range (IQR)9.575

Descriptive statistics

Standard deviation8.15331
Coefficient of variation (CV)0.31127604
Kurtosis1.7209808
Mean26.193182
Median Absolute Deviation (MAD)4.8
Skewness1.0257705
Sum1152.5
Variance66.476464
MonotonicityNot monotonic
2023-12-13T08:05:06.380674image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%)
24.0 2
 
4.5%
29.6 2
 
4.5%
26.2 2
 
4.5%
39.9 1
 
2.3%
31.7 1
 
2.3%
21.2 1
 
2.3%
32.2 1
 
2.3%
24.3 1
 
2.3%
13.5 1
 
2.3%
13.4 1
 
2.3%
Other values (31) 31
70.5%
ValueCountFrequency (%)
13.4 1
2.3%
13.5 1
2.3%
16.1 1
2.3%
16.6 1
2.3%
16.9 1
2.3%
17.4 1
2.3%
17.6 1
2.3%
18.7 1
2.3%
19.2 1
2.3%
19.5 1
2.3%
ValueCountFrequency (%)
52.8 1
2.3%
45.6 1
2.3%
39.9 1
2.3%
37.2 1
2.3%
35.0 1
2.3%
34.7 1
2.3%
34.1 1
2.3%
33.9 1
2.3%
32.2 1
2.3%
31.7 1
2.3%

1일운행횟수 (평일)
Real number (ℝ)

HIGH CORRELATION 

Distinct17
Distinct (%)38.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean17.75
Minimum8
Maximum48
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size528.0 B
2023-12-13T08:05:06.481179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum8
5-th percentile9.15
Q111
median18
Q321.25
95-th percentile29.4
Maximum48
Range40
Interquartile range (IQR)10.25

Descriptive statistics

Standard deviation7.5640674
Coefficient of variation (CV)0.42614464
Kurtosis4.5177007
Mean17.75
Median Absolute Deviation (MAD)6
Skewness1.4989562
Sum781
Variance57.215116
MonotonicityNot monotonic
2023-12-13T08:05:06.575199image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
20 6
13.6%
10 5
11.4%
11 5
11.4%
24 4
 
9.1%
18 3
 
6.8%
21 3
 
6.8%
30 2
 
4.5%
22 2
 
4.5%
17 2
 
4.5%
12 2
 
4.5%
Other values (7) 10
22.7%
ValueCountFrequency (%)
8 1
 
2.3%
9 2
 
4.5%
10 5
11.4%
11 5
11.4%
12 2
 
4.5%
13 2
 
4.5%
16 2
 
4.5%
17 2
 
4.5%
18 3
6.8%
20 6
13.6%
ValueCountFrequency (%)
48 1
 
2.3%
30 2
 
4.5%
26 1
 
2.3%
24 4
9.1%
23 1
 
2.3%
22 2
 
4.5%
21 3
6.8%
20 6
13.6%
18 3
6.8%
17 2
 
4.5%

배차간격(분) (평일)
Text

Distinct43
Distinct (%)97.7%
Missing0
Missing (%)0.0%
Memory size484.0 B
2023-12-13T08:05:06.746101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.2272727
Min length5

Characters and Unicode

Total characters274
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique42 ?
Unique (%)95.5%

Sample

1st row89~155
2nd row55~120
3rd row65~140
4th row60~123
5th row57~120
ValueCountFrequency (%)
50~135 2
 
4.5%
89~155 1
 
2.3%
76~142 1
 
2.3%
120~180 1
 
2.3%
105~155 1
 
2.3%
50~129 1
 
2.3%
56~150 1
 
2.3%
69~146 1
 
2.3%
64~145 1
 
2.3%
80~170 1
 
2.3%
Other values (33) 33
75.0%
2023-12-13T08:05:07.103334image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 56
20.4%
5 44
16.1%
~ 43
15.7%
0 38
13.9%
2 29
10.6%
3 17
 
6.2%
6 13
 
4.7%
4 11
 
4.0%
7 10
 
3.6%
9 8
 
2.9%
Other values (2) 5
 
1.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 230
83.9%
Math Symbol 43
 
15.7%
Dash Punctuation 1
 
0.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 56
24.3%
5 44
19.1%
0 38
16.5%
2 29
12.6%
3 17
 
7.4%
6 13
 
5.7%
4 11
 
4.8%
7 10
 
4.3%
9 8
 
3.5%
8 4
 
1.7%
Math Symbol
ValueCountFrequency (%)
~ 43
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 274
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 56
20.4%
5 44
16.1%
~ 43
15.7%
0 38
13.9%
2 29
10.6%
3 17
 
6.2%
6 13
 
4.7%
4 11
 
4.0%
7 10
 
3.6%
9 8
 
2.9%
Other values (2) 5
 
1.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 274
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 56
20.4%
5 44
16.1%
~ 43
15.7%
0 38
13.9%
2 29
10.6%
3 17
 
6.2%
6 13
 
4.7%
4 11
 
4.0%
7 10
 
3.6%
9 8
 
2.9%
Other values (2) 5
 
1.8%

운행대수 (평일)
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)9.1%
Missing0
Missing (%)0.0%
Memory size484.0 B
2
23 
1
18 
3
 
2
4
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)2.3%

Sample

1st row2
2nd row2
3rd row2
4th row2
5th row2

Common Values

ValueCountFrequency (%)
2 23
52.3%
1 18
40.9%
3 2
 
4.5%
4 1
 
2.3%

Length

2023-12-13T08:05:07.250380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:05:07.341187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 23
52.3%
1 18
40.9%
3 2
 
4.5%
4 1
 
2.3%

운행업체
Categorical

HIGH CORRELATION 

Distinct6
Distinct (%)13.6%
Missing0
Missing (%)0.0%
Memory size484.0 B
제주공영
18 
서귀공영
11 
수요응답형
7 
제주공영(소형)
4 
서귀공영(소형)
3 

Length

Max length9
Median length4
Mean length4.9090909
Min length4

Unique

Unique1 ?
Unique (%)2.3%

Sample

1st row제주공영(소형)
2nd row제주공영
3rd row수요응답형
4th row제주공영
5th row제주공영

Common Values

ValueCountFrequency (%)
제주공영 18
40.9%
서귀공영 11
25.0%
수요응답형 7
 
15.9%
제주공영(소형) 4
 
9.1%
서귀공영(소형) 3
 
6.8%
서귀공영(소형1) 1
 
2.3%

Length

2023-12-13T08:05:07.484415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:05:07.609436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
제주공영 18
40.9%
서귀공영 11
25.0%
수요응답형 7
 
15.9%
제주공영(소형 4
 
9.1%
서귀공영(소형 3
 
6.8%
서귀공영(소형1 1
 
2.3%

비고
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)4.5%
Missing0
Missing (%)0.0%
Memory size484.0 B
없음
38 
휴일감차
6 

Length

Max length4
Median length2
Mean length2.2727273
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
없음 38
86.4%
휴일감차 6
 
13.6%

Length

2023-12-13T08:05:07.737415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T08:05:07.837808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
없음 38
86.4%
휴일감차 6
 
13.6%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)2.3%
Missing0
Missing (%)0.0%
Memory size484.0 B
Minimum2022-12-31 00:00:00
Maximum2022-12-31 00:00:00
2023-12-13T08:05:07.952284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:08.047934image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-13T08:05:04.214187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:04.023613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:04.326437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T08:05:04.111518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T08:05:08.136447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
행정시노선명운행구간거리(km)1일운행횟수 (평일)배차간격(분) (평일)운행대수 (평일)운행업체비고
행정시1.0001.0001.0000.4180.0000.0000.2350.9890.321
노선명1.0001.0001.0001.0001.0001.0001.0001.0001.000
운행구간1.0001.0001.0001.0001.0001.0001.0001.0001.000
거리(km)0.4181.0001.0001.0000.3930.9550.7250.3150.270
1일운행횟수 (평일)0.0001.0001.0000.3931.0001.0000.8010.4200.558
배차간격(분) (평일)0.0001.0001.0000.9551.0001.0001.0000.0000.000
운행대수 (평일)0.2351.0001.0000.7250.8011.0001.0000.4630.770
운행업체0.9891.0001.0000.3150.4200.0000.4631.0000.575
비고0.3211.0001.0000.2700.5580.0000.7700.5751.000
2023-12-13T08:05:08.251928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
운행업체비고운행대수 (평일)행정시
운행업체1.0000.3940.3030.862
비고0.3941.0000.5470.207
운행대수 (평일)0.3030.5471.0000.147
행정시0.8620.2070.1471.000
2023-12-13T08:05:08.360901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
거리(km)1일운행횟수 (평일)행정시운행대수 (평일)운행업체비고
거리(km)1.0000.0700.3780.5230.1400.238
1일운행횟수 (평일)0.0701.0000.0000.8580.2920.535
행정시0.3780.0001.0000.1470.8620.207
운행대수 (평일)0.5230.8580.1471.0000.3030.547
운행업체0.1400.2920.8620.3031.0000.394
비고0.2380.5350.2070.5470.3941.000

Missing values

2023-12-13T08:05:04.481766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T08:05:04.628140image/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

행정시노선명운행구간거리(km)1일운행횟수 (평일)배차간격(분) (평일)운행대수 (평일)운행업체비고데이터기준일자
0제주시701(-1.-2)조천체육관-조천-함덕-함덕에덴빌리지-대흘2-와산-대흘교차로-남조로검문소-돌문화공원/돌문화공원-고평동-뒷산길-대흘1리-와흘-신안동-동수동-조천체육관39.91689~1552제주공영(소형)없음2022-12-31
1제주시702(-1.-2)조천체육관-조천-함덕-대흘2-와산-대흘1-와흘-신안동-동수동-조천체육관(신흥리경유)24.92055~1202제주공영없음2022-12-31
2제주시703(-1.-2)신촌-조천-함덕-함덕에덴빌리지-신사동-대흘2-봉소동-대흘초-양천하동-병디왓-조천-신촌25.81865~1402수요응답형없음2022-12-31
3제주시704(-1.-3)조천체육관-억수동-낙선동-선흘-목선동-선인동-선흘2리-조천만세동산37.21160~1232제주공영없음2022-12-31
4제주시704(-2.-3)조천체육관-대흘2리-금산-와산-선인동-선흘2리-조천만세동산34.11157~1202제주공영없음2022-12-31
5제주시704-4조천체육관-북촌리해동-열방대학-선흘-동백동산-어대악-하덕천-상덕천-송당24.011128~2101제주공영없음2022-12-31
6제주시711-1김녕-만장굴-덕천-상덕천-송당-비자림-평대-세화-해녀박물관29.22316~1272제주공영없음2022-12-31
7제주시711-2김녕-만장굴-벌탬목-한라용사촌-용암해수단지-평대-세화-해녀박물관-별방진-종달항29.82155~1452제주공영없음2022-12-31
8제주시771-1고산성당-신창-한원리-조수1리-저지리-명리동-오설록-신화역사공원-동광육거리34.79155~2351제주공영(소형)없음2022-12-31
9제주시771-2고산성당-조수2-산양-월광동-청수리-명리동-오설록-신화역사공원-동광육거리35.013100~2001제주공영(소형)없음2022-12-31
행정시노선명운행구간거리(km)1일운행횟수 (평일)배차간격(분) (평일)운행대수 (평일)운행업체비고데이터기준일자
34서귀포시741(-1.-2)남원읍사무소-태흥3-신흥교차로-토산초-토산1-온천동-신흥2-신흥1-신흥교차로-태흥3-남원읍사무소22.53025~1373서귀공영(소형1)휴일감차2022-12-31
35서귀포시742(-1.-2)남원읍사무소-태흥3-신흥교차로-동모루-의귀초교-한남리-서의동-남원2리복지회관-남원중-남원읍사무소23.92255~1432서귀공영없음2022-12-31
36서귀포시743남원체육관-남원환승정류장(남원읍사무소)-수은동-대성동-상위미-신례리-위미리-대성동-의귀환승정류장(위귀초등학교)-대성동-위미리-상위미-대성동-수은동-남원환승정류장(남원읍사무소)-남원체육관52.88120~2001수요응답형없음2022-12-31
37서귀포시744신흥2리사무소-동모루-수망가름-불미터-의귀초등학교-송령이골-한남리(한남교)-대성동오거리-상위미-신례리-공업단지입구-토평사거리-측골-서귀포오일시장19.21047-1022수요응답형없음2022-12-31
38서귀포시751-1모슬포남항-대정초-보성-신평-구억-영어교육도시-서광서-덕수도련동-덕수초등학교-안덕농협-문화마을-안덕면사무소29.62157~1502서귀공영휴일감차2022-12-31
39서귀포시751-2모슬포남항-대정초-보성-신평-구억-영어교육도시-서광서-서광동-안덕면사무소-화순-안덕농협-대평29.62059~1502서귀공영휴일감차2022-12-31
40서귀포시752(-1.-2)모슬포남항-인성리-동광육거리-동광단지-광평-상천-동백동산-상창-창천-감산-화순-송악펜션단지-산이수동-상모-모슬포우체국-모슬포남항(덕수2리교차로교번경유)45.62625~1504서귀공영없음2022-12-31
41서귀포시761-1고산-신도2-신도1-무릉1-인향동-신평-보성-대정읍사무소-모슬포남항22.911135~2101수요응답형없음2022-12-31
42서귀포시761-2고산-신도2-신도1-무릉1-좌기동-인향동-동일2-농공단지-일과1리-대정읍사무소-모슬포남항22.62450~1352서귀공영(소형)휴일감차2022-12-31
43서귀포시761-3모슬포남항-보성리-신평리-인향동-산양리-수룡동-청수리-저지리-현대미술관-저지리-청수리-수룡동-산양리-인향동-신평리-보성리-모슬포남항23.610123~2131수요응답형없음2022-12-31