Overview

Dataset statistics

Number of variables12
Number of observations28
Missing cells42
Missing cells (%)12.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.8 KiB
Average record size in memory102.7 B

Variable types

Text3
Categorical6
Numeric1
DateTime2

Dataset

Description부산광역시 기장군 시내버스 운행 현황에 대한 데이터로 기장군을 경유하는 시내버스 노선,시간표 등의 항목을 제공합니다.
Author부산광역시 기장군
URLhttps://www.data.go.kr/data/15053837/fileData.do

Alerts

첫차 is highly overall correlated with 심야배차간격(분)High correlation
심야배차간격(분) is highly overall correlated with 배차간격(분) and 4 other fieldsHigh correlation
업체전화번호 is highly overall correlated with 기점 and 2 other fieldsHigh correlation
업체명 is highly overall correlated with 기점 and 2 other fieldsHigh correlation
배차간격(분) is highly overall correlated with 심야배차간격(분)High correlation
기점 is highly overall correlated with 업체명 and 1 other fieldsHigh correlation
막차 is highly overall correlated with 심야배차간격(분)High correlation
심야배차간격(분) is highly imbalanced (52.6%)Imbalance
심야첫차 has 21 (75.0%) missing valuesMissing
심야막차 has 21 (75.0%) missing valuesMissing
노선번호 has unique valuesUnique

Reproduction

Analysis started2023-12-12 10:11:31.496042
Analysis finished2023-12-12 10:11:32.814080
Duration1.32 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

노선번호
Text

UNIQUE 

Distinct28
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size356.0 B
2023-12-12T19:11:33.008864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length4.5
Mean length3.0357143
Min length2

Characters and Unicode

Total characters85
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

Unique28 ?
Unique (%)100.0%

Sample

1st row36
2nd row37
3rd row38
4th row39
5th row40
ValueCountFrequency (%)
36 1
 
3.6%
37 1
 
3.6%
1010 1
 
3.6%
1008 1
 
3.6%
1003 1
 
3.6%
1002 1
 
3.6%
1001 1
 
3.6%
302 1
 
3.6%
200 1
 
3.6%
188 1
 
3.6%
Other values (18) 18
64.3%
2023-12-12T19:11:33.454238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 25
29.4%
0 22
25.9%
8 11
12.9%
3 10
 
11.8%
7 4
 
4.7%
2 4
 
4.7%
6 2
 
2.4%
9 2
 
2.4%
4 2
 
2.4%
5 2
 
2.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 84
98.8%
Dash Punctuation 1
 
1.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 25
29.8%
0 22
26.2%
8 11
13.1%
3 10
 
11.9%
7 4
 
4.8%
2 4
 
4.8%
6 2
 
2.4%
9 2
 
2.4%
4 2
 
2.4%
5 2
 
2.4%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 85
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 25
29.4%
0 22
25.9%
8 11
12.9%
3 10
 
11.8%
7 4
 
4.7%
2 4
 
4.7%
6 2
 
2.4%
9 2
 
2.4%
4 2
 
2.4%
5 2
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 85
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 25
29.4%
0 22
25.9%
8 11
12.9%
3 10
 
11.8%
7 4
 
4.7%
2 4
 
4.7%
6 2
 
2.4%
9 2
 
2.4%
4 2
 
2.4%
5 2
 
2.4%

기점
Categorical

HIGH CORRELATION 

Distinct9
Distinct (%)32.1%
Missing0
Missing (%)0.0%
Memory size356.0 B
청강리
15 
정관
5 
기장
2 
금정차고지
 
1
사직동
 
1
Other values (4)
4 

Length

Max length7
Median length3
Mean length2.8571429
Min length2

Unique

Unique6 ?
Unique (%)21.4%

Sample

1st row청강리
2nd row금정차고지
3rd row청강리
4th row기장
5th row청강리

Common Values

ValueCountFrequency (%)
청강리 15
53.6%
정관 5
 
17.9%
기장 2
 
7.1%
금정차고지 1
 
3.6%
사직동 1
 
3.6%
반송 1
 
3.6%
용당공영차고지 1
 
3.6%
서창 1
 
3.6%
좌천 1
 
3.6%

Length

2023-12-12T19:11:33.637133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:11:33.790400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
청강리 15
53.6%
정관 5
 
17.9%
기장 2
 
7.1%
금정차고지 1
 
3.6%
사직동 1
 
3.6%
반송 1
 
3.6%
용당공영차고지 1
 
3.6%
서창 1
 
3.6%
좌천 1
 
3.6%

경유지
Text

Distinct18
Distinct (%)64.3%
Missing0
Missing (%)0.0%
Memory size356.0 B
2023-12-12T19:11:34.046695image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length7
Mean length3.8214286
Min length2

Characters and Unicode

Total characters107
Distinct characters45
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

Unique10 ?
Unique (%)35.7%

Sample

1st row반여동
2nd row정관
3rd row중앙공원관리사무소
4th row해운대
5th row수영교차로
ValueCountFrequency (%)
동래 3
10.3%
철마 3
10.3%
기장 3
10.3%
해운대 2
 
6.9%
수영교차로 2
 
6.9%
반여농산물시장 2
 
6.9%
부산역 2
 
6.9%
정관 2
 
6.9%
반여동 2
 
6.9%
장산역 1
 
3.4%
Other values (7) 7
24.1%
2023-12-12T19:11:34.373363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
산 7
 
6.5%
동 6
 
5.6%
장 6
 
5.6%
대 4
 
3.7%
여 4
 
3.7%
교 4
 
3.7%
반 4
 
3.7%
관 4
 
3.7%
마 3
 
2.8%
역 3
 
2.8%
Other values (35) 62
57.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 105
98.1%
Other Punctuation 1
 
0.9%
Space Separator 1
 
0.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 7
 
6.7%
동 6
 
5.7%
장 6
 
5.7%
대 4
 
3.8%
여 4
 
3.8%
교 4
 
3.8%
반 4
 
3.8%
관 4
 
3.8%
마 3
 
2.9%
역 3
 
2.9%
Other values (33) 60
57.1%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 105
98.1%
Common 2
 
1.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 7
 
6.7%
동 6
 
5.7%
장 6
 
5.7%
대 4
 
3.8%
여 4
 
3.8%
교 4
 
3.8%
반 4
 
3.8%
관 4
 
3.8%
마 3
 
2.9%
역 3
 
2.9%
Other values (33) 60
57.1%
Common
ValueCountFrequency (%)
, 1
50.0%
1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 105
98.1%
ASCII 2
 
1.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
산 7
 
6.7%
동 6
 
5.7%
장 6
 
5.7%
대 4
 
3.8%
여 4
 
3.8%
교 4
 
3.8%
반 4
 
3.8%
관 4
 
3.8%
마 3
 
2.9%
역 3
 
2.9%
Other values (33) 60
57.1%
ASCII
ValueCountFrequency (%)
, 1
50.0%
1
50.0%

종점
Text

Distinct24
Distinct (%)85.7%
Missing0
Missing (%)0.0%
Memory size356.0 B
2023-12-12T19:11:34.613445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length9
Mean length5.3214286
Min length2

Characters and Unicode

Total characters149
Distinct characters81
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

Unique20 ?
Unique (%)71.4%

Sample

1st row거제역
2nd row한빛3차아파트
3rd row중앙공원관리사무소
4th row용호동 남구국민체육센터
5th row구덕운동장
ValueCountFrequency (%)
반송 2
 
6.7%
한빛3차아파트 2
 
6.7%
부산대 2
 
6.7%
정관 2
 
6.7%
올림픽교차로환승센터 2
 
6.7%
대룡마을 1
 
3.3%
거제역 1
 
3.3%
장산역 1
 
3.3%
서면 1
 
3.3%
동래지하철역 1
 
3.3%
Other values (15) 15
50.0%
2023-12-12T19:11:34.917004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
역 6
 
4.0%
산 6
 
4.0%
대 5
 
3.4%
구 5
 
3.4%
센 5
 
3.4%
터 4
 
2.7%
장 4
 
2.7%
차 4
 
2.7%
부 4
 
2.7%
파 4
 
2.7%
Other values (71) 102
68.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 145
97.3%
Space Separator 2
 
1.3%
Decimal Number 2
 
1.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
역 6
 
4.1%
산 6
 
4.1%
대 5
 
3.4%
구 5
 
3.4%
센 5
 
3.4%
터 4
 
2.8%
장 4
 
2.8%
차 4
 
2.8%
부 4
 
2.8%
파 4
 
2.8%
Other values (69) 98
67.6%
Space Separator
ValueCountFrequency (%)
2
100.0%
Decimal Number
ValueCountFrequency (%)
3 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 145
97.3%
Common 4
 
2.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
역 6
 
4.1%
산 6
 
4.1%
대 5
 
3.4%
구 5
 
3.4%
센 5
 
3.4%
터 4
 
2.8%
장 4
 
2.8%
차 4
 
2.8%
부 4
 
2.8%
파 4
 
2.8%
Other values (69) 98
67.6%
Common
ValueCountFrequency (%)
2
50.0%
3 2
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 145
97.3%
ASCII 4
 
2.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
역 6
 
4.1%
산 6
 
4.1%
대 5
 
3.4%
구 5
 
3.4%
센 5
 
3.4%
터 4
 
2.8%
장 4
 
2.8%
차 4
 
2.8%
부 4
 
2.8%
파 4
 
2.8%
Other values (69) 98
67.6%
ASCII
ValueCountFrequency (%)
2
50.0%
3 2
50.0%

첫차
Categorical

HIGH CORRELATION 

Distinct6
Distinct (%)21.4%
Missing0
Missing (%)0.0%
Memory size356.0 B
05:00
17 
04:40
3 
04:30
3 
04:50
3 
04:20
 
1

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique2 ?
Unique (%)7.1%

Sample

1st row05:00
2nd row05:00
3rd row04:40
4th row05:00
5th row04:40

Common Values

ValueCountFrequency (%)
05:00 17
60.7%
04:40 3
 
10.7%
04:30 3
 
10.7%
04:50 3
 
10.7%
04:20 1
 
3.6%
05:20 1
 
3.6%

Length

2023-12-12T19:11:35.032450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:11:35.159575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
05:00 17
60.7%
04:40 3
 
10.7%
04:30 3
 
10.7%
04:50 3
 
10.7%
04:20 1
 
3.6%
05:20 1
 
3.6%

막차
Categorical

HIGH CORRELATION 

Distinct10
Distinct (%)35.7%
Missing0
Missing (%)0.0%
Memory size356.0 B
22:00
9 
21:50
6 
22:05
2 
22:30
2 
22:10
2 
Other values (5)
7 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique3 ?
Unique (%)10.7%

Sample

1st row22:05
2nd row22:30
3rd row21:50
4th row22:05
5th row21:50

Common Values

ValueCountFrequency (%)
22:00 9
32.1%
21:50 6
21.4%
22:05 2
 
7.1%
22:30 2
 
7.1%
22:10 2
 
7.1%
22:25 2
 
7.1%
22:20 2
 
7.1%
22:15 1
 
3.6%
21:40 1
 
3.6%
21:00 1
 
3.6%

Length

2023-12-12T19:11:35.289268image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:11:35.421323image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
22:00 9
32.1%
21:50 6
21.4%
22:05 2
 
7.1%
22:30 2
 
7.1%
22:10 2
 
7.1%
22:25 2
 
7.1%
22:20 2
 
7.1%
22:15 1
 
3.6%
21:40 1
 
3.6%
21:00 1
 
3.6%

배차간격(분)
Real number (ℝ)

HIGH CORRELATION 

Distinct20
Distinct (%)71.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean22.107143
Minimum9
Maximum60
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size384.0 B
2023-12-12T19:11:35.548206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum9
5-th percentile10.35
Q111.75
median16.5
Q326.25
95-th percentile45
Maximum60
Range51
Interquartile range (IQR)14.5

Descriptive statistics

Standard deviation13.261862
Coefficient of variation (CV)0.59989037
Kurtosis1.1754571
Mean22.107143
Median Absolute Deviation (MAD)5.5
Skewness1.3318956
Sum619
Variance175.87698
MonotonicityNot monotonic
2023-12-12T19:11:35.689798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
11 5
17.9%
45 2
 
7.1%
15 2
 
7.1%
25 2
 
7.1%
14 2
 
7.1%
27 1
 
3.6%
17 1
 
3.6%
10 1
 
3.6%
30 1
 
3.6%
40 1
 
3.6%
Other values (10) 10
35.7%
ValueCountFrequency (%)
9 1
 
3.6%
10 1
 
3.6%
11 5
17.9%
12 1
 
3.6%
13 1
 
3.6%
14 2
 
7.1%
15 2
 
7.1%
16 1
 
3.6%
17 1
 
3.6%
19 1
 
3.6%
ValueCountFrequency (%)
60 1
3.6%
45 2
7.1%
42 1
3.6%
40 1
3.6%
30 1
3.6%
27 1
3.6%
26 1
3.6%
25 2
7.1%
24 1
3.6%
21 1
3.6%

심야첫차
Date

MISSING 

Distinct6
Distinct (%)85.7%
Missing21
Missing (%)75.0%
Memory size356.0 B
Minimum2023-12-12 22:20:00
Maximum2023-12-12 23:00:00
2023-12-12T19:11:35.803167image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:11:35.907590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)

심야막차
Date

MISSING 

Distinct5
Distinct (%)71.4%
Missing21
Missing (%)75.0%
Memory size356.0 B
Minimum2023-12-12 22:45:00
Maximum2023-12-12 23:45:00
2023-12-12T19:11:36.034860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T19:11:36.194918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=5)

심야배차간격(분)
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct4
Distinct (%)14.3%
Missing0
Missing (%)0.0%
Memory size356.0 B
<NA>
23 
40
 
2
20
 
2
15
 
1

Length

Max length4
Median length4
Mean length3.6428571
Min length2

Unique

Unique1 ?
Unique (%)3.6%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 23
82.1%
40 2
 
7.1%
20 2
 
7.1%
15 1
 
3.6%

Length

2023-12-12T19:11:36.332642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:11:36.451079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 23
82.1%
40 2
 
7.1%
20 2
 
7.1%
15 1
 
3.6%

업체명
Categorical

HIGH CORRELATION 

Distinct9
Distinct (%)32.1%
Missing0
Missing (%)0.0%
Memory size356.0 B
부일여객
5 
부산여객
5 
세진여객
5 
삼신교통
4 
해동여객
3 
Other values (4)
6 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique2 ?
Unique (%)7.1%

Sample

1st row일광여객
2nd row삼신교통
3rd row부일여객
4th row부산여객
5th row부일여객

Common Values

ValueCountFrequency (%)
부일여객 5
17.9%
부산여객 5
17.9%
세진여객 5
17.9%
삼신교통 4
14.3%
해동여객 3
10.7%
일광여객 2
 
7.1%
세익여객 2
 
7.1%
학성여객 1
 
3.6%
대진버스 1
 
3.6%

Length

2023-12-12T19:11:36.587348image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:11:36.714161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
부일여객 5
17.9%
부산여객 5
17.9%
세진여객 5
17.9%
삼신교통 4
14.3%
해동여객 3
10.7%
일광여객 2
 
7.1%
세익여객 2
 
7.1%
학성여객 1
 
3.6%
대진버스 1
 
3.6%

업체전화번호
Categorical

HIGH CORRELATION 

Distinct8
Distinct (%)28.6%
Missing0
Missing (%)0.0%
Memory size356.0 B
051-703-5501
5 
051-702-7711
5 
051-518-5331
5 
051-746-0071
4 
051-508-0049
4 
Other values (3)
5 

Length

Max length12
Median length12
Mean length12
Min length12

Unique

Unique2 ?
Unique (%)7.1%

Sample

1st row051-746-0071
2nd row051-508-0049
3rd row051-703-5501
4th row051-702-7711
5th row051-703-5501

Common Values

ValueCountFrequency (%)
051-703-5501 5
17.9%
051-702-7711 5
17.9%
051-518-5331 5
17.9%
051-746-0071 4
14.3%
051-508-0049 4
14.3%
051-702-7725 3
10.7%
051-503-0501 1
 
3.6%
051-722-7621 1
 
3.6%

Length

2023-12-12T19:11:36.858017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T19:11:36.987017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
051-703-5501 5
17.9%
051-702-7711 5
17.9%
051-518-5331 5
17.9%
051-746-0071 4
14.3%
051-508-0049 4
14.3%
051-702-7725 3
10.7%
051-503-0501 1
 
3.6%
051-722-7621 1
 
3.6%

Interactions

2023-12-12T19:11:32.164254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T19:11:37.381723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
노선번호기점경유지종점첫차막차배차간격(분)심야첫차심야막차심야배차간격(분)업체명업체전화번호
노선번호1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
기점1.0001.0000.5330.9400.6470.0000.5230.4840.6660.5980.9370.876
경유지1.0000.5331.0000.8510.0000.5480.0000.8970.7670.2610.6530.477
종점1.0000.9400.8511.0000.9930.3180.0001.0001.0001.0000.9060.937
첫차1.0000.6470.0000.9931.0000.0000.0001.0000.4181.0000.0000.000
막차1.0000.0000.5480.3180.0001.0000.0000.0001.0000.8980.2100.000
배차간격(분)1.0000.5230.0000.0000.0000.0001.0000.0000.323NaN0.0000.451
심야첫차1.0000.4840.8971.0001.0000.0000.0001.0000.7671.0000.7190.719
심야막차1.0000.6660.7671.0000.4181.0000.3230.7671.0001.0000.9360.936
심야배차간격(분)1.0000.5980.2611.0001.0000.898NaN1.0001.0001.0001.0001.000
업체명1.0000.9370.6530.9060.0000.2100.0000.7190.9361.0001.0001.000
업체전화번호1.0000.8760.4770.9370.0000.0000.4510.7190.9361.0001.0001.000
2023-12-12T19:11:37.524453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
첫차심야배차간격(분)기점막차업체전화번호업체명
첫차1.0001.0000.3450.0000.0000.000
심야배차간격(분)1.0001.0000.0000.5001.0001.000
기점0.3450.0001.0000.0000.6580.588
막차0.0000.5000.0001.0000.0000.000
업체전화번호0.0001.0000.6580.0001.0000.975
업체명0.0001.0000.5880.0000.9751.000
2023-12-12T19:11:37.643101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
배차간격(분)기점첫차막차심야배차간격(분)업체명업체전화번호
배차간격(분)1.0000.2570.0000.0001.0000.0000.122
기점0.2571.0000.3450.0000.0000.5880.658
첫차0.0000.3451.0000.0001.0000.0000.000
막차0.0000.0000.0001.0000.5000.0000.000
심야배차간격(분)1.0000.0001.0000.5001.0001.0001.000
업체명0.0000.5880.0000.0001.0001.0000.975
업체전화번호0.1220.6580.0000.0001.0000.9751.000

Missing values

2023-12-12T19:11:32.372082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T19:11:32.605809image/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.
2023-12-12T19:11:32.745439image/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

노선번호기점경유지종점첫차막차배차간격(분)심야첫차심야막차심야배차간격(분)업체명업체전화번호
036청강리반여동거제역05:0022:0519<NA><NA><NA>일광여객051-746-0071
137금정차고지정관한빛3차아파트05:0022:3021<NA><NA><NA>삼신교통051-508-0049
238청강리중앙공원관리사무소중앙공원관리사무소04:4021:5024<NA><NA><NA>부일여객051-703-5501
339기장해운대용호동 남구국민체육센터05:0022:0511<NA><NA><NA>부산여객051-702-7711
440청강리수영교차로구덕운동장04:4021:5011<NA><NA><NA>부일여객051-703-5501
563청강리수영교차로부산진구청04:3022:109<NA><NA><NA>일광여객051-746-0071
673정관철마반송05:0022:0060<NA><NA><NA>세진여객051-518-5331
7100청강리동래장전역04:5021:5015<NA><NA><NA>해동여객051-702-7725
8100-1청강리동래부산대05:0022:1012<NA><NA><NA>해동여객051-702-7725
9105사직동반여농산물시장정관05:0022:0015<NA><NA><NA>학성여객051-503-0501
노선번호기점경유지종점첫차막차배차간격(분)심야첫차심야막차심야배차간격(분)업체명업체전화번호
18187반송기장대룡마을05:0022:0040<NA><NA><NA>대진버스051-722-7621
19188정관기장반송04:3022:0030<NA><NA><NA>세진여객051-518-5331
20200청강리동래북구청04:4021:5011<NA><NA><NA>세익여객051-746-0071
21302용당공영차고지월평교차로좌천역05:0022:3045<NA><NA><NA>삼신교통051-508-0049
221001청강리부산역하단04:3022:001022:2023:0020부일여객051-703-5501
231002서창무산대학교해운대문화복합센터04:5022:001722:3023:00<NA>삼신교통051-508-0049
241003기장부산역부산대학병원04:2022:201122:4023:4515부산여객051-702-7711
251008좌천정관동래지하철역05:2022:001423:0023:0020삼신교통051-508-0049
261010정관반여농산물시장서면04:5021:401122:3023:1040세진여객051-518-5331
271011청강리영도경제자유구역청05:0021:0025<NA><NA><NA>부일여객051-703-5501