Overview

Dataset statistics

Number of variables13
Number of observations21
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.4 KiB
Average record size in memory115.3 B

Variable types

Categorical5
Text2
Numeric5
DateTime1

Dataset

Description부산광역시영도구_시내버스노선현황_20220620
Author부산광역시 영도구
URLhttp://data.busan.go.kr/dataSet/detail.nm?contentId=10&publicdatapk=15053334

Alerts

업체명 is highly overall correlated with 소재지 and 2 other fieldsHigh correlation
대표번호 is highly overall correlated with 업체명 and 2 other fieldsHigh correlation
소재지 is highly overall correlated with 업체명 and 2 other fieldsHigh correlation
면허대수(예비포함) is highly overall correlated with 운행횟수 and 1 other fieldsHigh correlation
운행횟수 is highly overall correlated with 면허대수(예비포함) and 3 other fieldsHigh correlation
거리(킬로미터) is highly overall correlated with 운행횟수 and 3 other fieldsHigh correlation
배차간격 is highly overall correlated with 면허대수(예비포함) and 3 other fieldsHigh correlation
소요시간 is highly overall correlated with 운행횟수 and 3 other fieldsHigh correlation
운행구간_기점 is highly overall correlated with 거리(킬로미터) and 4 other fieldsHigh correlation

Reproduction

Analysis started2023-12-10 16:37:06.444179
Analysis finished2023-12-10 16:37:11.342525
Duration4.9 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업체명
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)23.8%
Missing0
Missing (%)0.0%
Memory size300.0 B
신한여객
9 
남부여객
6 
유한여객
4 
부일여객
1 
동진여객
1 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique2 ?
Unique (%)9.5%

Sample

1st row부일여객
2nd row신한여객
3rd row신한여객
4th row신한여객
5th row신한여객

Common Values

ValueCountFrequency (%)
신한여객 9
42.9%
남부여객 6
28.6%
유한여객 4
19.0%
부일여객 1
 
4.8%
동진여객 1
 
4.8%

Length

2023-12-11T01:37:11.424218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:37:11.576868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
신한여객 9
42.9%
남부여객 6
28.6%
유한여객 4
19.0%
부일여객 1
 
4.8%
동진여객 1
 
4.8%

소재지
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)23.8%
Missing0
Missing (%)0.0%
Memory size300.0 B
부산광역시 영도구 태종로 808(동삼동)
9 
부산광역시 영도구 와치로 113(청학동)
6 
부산광역시 영도구 청학서로 37(청학동)
4 
부산광역시 기장군 기장읍 기장대로 313
1 
부산광역시 사하구 다대로 722(다대동)
1 

Length

Max length22
Median length22
Mean length22
Min length22

Unique

Unique2 ?
Unique (%)9.5%

Sample

1st row부산광역시 기장군 기장읍 기장대로 313
2nd row부산광역시 영도구 태종로 808(동삼동)
3rd row부산광역시 영도구 태종로 808(동삼동)
4th row부산광역시 영도구 태종로 808(동삼동)
5th row부산광역시 영도구 태종로 808(동삼동)

Common Values

ValueCountFrequency (%)
부산광역시 영도구 태종로 808(동삼동) 9
42.9%
부산광역시 영도구 와치로 113(청학동) 6
28.6%
부산광역시 영도구 청학서로 37(청학동) 4
19.0%
부산광역시 기장군 기장읍 기장대로 313 1
 
4.8%
부산광역시 사하구 다대로 722(다대동) 1
 
4.8%

Length

2023-12-11T01:37:11.720977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:37:11.877447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
부산광역시 21
24.7%
영도구 19
22.4%
태종로 9
10.6%
808(동삼동 9
10.6%
와치로 6
 
7.1%
113(청학동 6
 
7.1%
청학서로 4
 
4.7%
37(청학동 4
 
4.7%
기장군 1
 
1.2%
기장읍 1
 
1.2%
Other values (5) 5
 
5.9%

대표번호
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)23.8%
Missing0
Missing (%)0.0%
Memory size300.0 B
051-405-0511
9 
051-415-5555
6 
051-415-6256
4 
051-703-5501
1 
051-261-2773
1 

Length

Max length12
Median length12
Mean length12
Min length12

Unique

Unique2 ?
Unique (%)9.5%

Sample

1st row051-703-5501
2nd row051-405-0511
3rd row051-405-0511
4th row051-405-0511
5th row051-405-0511

Common Values

ValueCountFrequency (%)
051-405-0511 9
42.9%
051-415-5555 6
28.6%
051-415-6256 4
19.0%
051-703-5501 1
 
4.8%
051-261-2773 1
 
4.8%

Length

2023-12-11T01:37:12.057146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:37:12.202829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
051-405-0511 9
42.9%
051-415-5555 6
28.6%
051-415-6256 4
19.0%
051-703-5501 1
 
4.8%
051-261-2773 1
 
4.8%

버스노선
Text

Distinct20
Distinct (%)95.2%
Missing0
Missing (%)0.0%
Memory size300.0 B
2023-12-11T01:37:12.428963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length2.3809524
Min length1

Characters and Unicode

Total characters50
Distinct characters10
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique19 ?
Unique (%)90.5%

Sample

1st row1011
2nd row1006
3rd row8
4th row30
5th row66
ValueCountFrequency (%)
190 2
 
9.5%
1011 1
 
4.8%
85 1
 
4.8%
508 1
 
4.8%
71 1
 
4.8%
70 1
 
4.8%
9 1
 
4.8%
7 1
 
4.8%
6 1
 
4.8%
88ㅡ1 1
 
4.8%
Other values (10) 10
47.6%
2023-12-11T01:37:12.848160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 15
30.0%
0 9
18.0%
8 9
18.0%
6 5
 
10.0%
9 3
 
6.0%
7 3
 
6.0%
3 2
 
4.0%
5 2
 
4.0%
2 1
 
2.0%
ㅡ 1
 
2.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 49
98.0%
Other Letter 1
 
2.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 15
30.6%
0 9
18.4%
8 9
18.4%
6 5
 
10.2%
9 3
 
6.1%
7 3
 
6.1%
3 2
 
4.1%
5 2
 
4.1%
2 1
 
2.0%
Other Letter
ValueCountFrequency (%)
ㅡ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 49
98.0%
Hangul 1
 
2.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 15
30.6%
0 9
18.4%
8 9
18.4%
6 5
 
10.2%
9 3
 
6.1%
7 3
 
6.1%
3 2
 
4.1%
5 2
 
4.1%
2 1
 
2.0%
Hangul
ValueCountFrequency (%)
ㅡ 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 49
98.0%
Compat Jamo 1
 
2.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 15
30.6%
0 9
18.4%
8 9
18.4%
6 5
 
10.2%
9 3
 
6.1%
7 3
 
6.1%
3 2
 
4.1%
5 2
 
4.1%
2 1
 
2.0%
Compat Jamo
ValueCountFrequency (%)
ㅡ 1
100.0%

면허대수(예비포함)
Real number (ℝ)

HIGH CORRELATION 

Distinct14
Distinct (%)66.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean13.285714
Minimum4
Maximum28
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size321.0 B
2023-12-11T01:37:12.997211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum4
5-th percentile6
Q19
median11
Q318
95-th percentile22
Maximum28
Range24
Interquartile range (IQR)9

Descriptive statistics

Standard deviation6.1167218
Coefficient of variation (CV)0.46039842
Kurtosis-0.0035992587
Mean13.285714
Median Absolute Deviation (MAD)3
Skewness0.7360578
Sum279
Variance37.414286
MonotonicityNot monotonic
2023-12-11T01:37:13.136717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
8 3
14.3%
10 3
14.3%
19 2
9.5%
18 2
9.5%
11 2
9.5%
14 1
 
4.8%
6 1
 
4.8%
22 1
 
4.8%
9 1
 
4.8%
28 1
 
4.8%
Other values (4) 4
19.0%
ValueCountFrequency (%)
4 1
 
4.8%
6 1
 
4.8%
8 3
14.3%
9 1
 
4.8%
10 3
14.3%
11 2
9.5%
12 1
 
4.8%
13 1
 
4.8%
14 1
 
4.8%
18 2
9.5%
ValueCountFrequency (%)
28 1
 
4.8%
22 1
 
4.8%
21 1
 
4.8%
19 2
9.5%
18 2
9.5%
14 1
 
4.8%
13 1
 
4.8%
12 1
 
4.8%
11 2
9.5%
10 3
14.3%

운행횟수
Real number (ℝ)

HIGH CORRELATION 

Distinct17
Distinct (%)81.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean99.238095
Minimum45
Maximum180
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size321.0 B
2023-12-11T01:37:13.285214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum45
5-th percentile48
Q164
median90
Q3142
95-th percentile174
Maximum180
Range135
Interquartile range (IQR)78

Descriptive statistics

Standard deviation46.52516
Coefficient of variation (CV)0.46882359
Kurtosis-1.2523221
Mean99.238095
Median Absolute Deviation (MAD)36
Skewness0.49548553
Sum2084
Variance2164.5905
MonotonicityNot monotonic
2023-12-11T01:37:13.461856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
48 3
14.3%
64 3
14.3%
150 1
 
4.8%
103 1
 
4.8%
110 1
 
4.8%
90 1
 
4.8%
70 1
 
4.8%
80 1
 
4.8%
165 1
 
4.8%
94 1
 
4.8%
Other values (7) 7
33.3%
ValueCountFrequency (%)
45 1
 
4.8%
48 3
14.3%
57 1
 
4.8%
64 3
14.3%
70 1
 
4.8%
80 1
 
4.8%
90 1
 
4.8%
94 1
 
4.8%
103 1
 
4.8%
110 1
 
4.8%
ValueCountFrequency (%)
180 1
4.8%
174 1
4.8%
165 1
4.8%
162 1
4.8%
150 1
4.8%
142 1
4.8%
126 1
4.8%
110 1
4.8%
103 1
4.8%
94 1
4.8%

거리(킬로미터)
Real number (ℝ)

HIGH CORRELATION 

Distinct19
Distinct (%)90.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean39.247619
Minimum17.2
Maximum97
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size321.0 B
2023-12-11T01:37:13.643441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum17.2
5-th percentile24.6
Q130.7
median37.1
Q343.5
95-th percentile56
Maximum97
Range79.8
Interquartile range (IQR)12.8

Descriptive statistics

Standard deviation15.829265
Coefficient of variation (CV)0.40331783
Kurtosis8.9161614
Mean39.247619
Median Absolute Deviation (MAD)6.4
Skewness2.4865968
Sum824.2
Variance250.56562
MonotonicityNot monotonic
2023-12-11T01:37:13.817009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
30.7 2
 
9.5%
44.3 2
 
9.5%
97.0 1
 
4.8%
42.6 1
 
4.8%
25.6 1
 
4.8%
31.2 1
 
4.8%
33.7 1
 
4.8%
34.6 1
 
4.8%
37.1 1
 
4.8%
17.2 1
 
4.8%
Other values (9) 9
42.9%
ValueCountFrequency (%)
17.2 1
4.8%
24.6 1
4.8%
25.6 1
4.8%
29.4 1
4.8%
30.7 2
9.5%
31.2 1
4.8%
33.7 1
4.8%
34.6 1
4.8%
35.4 1
4.8%
37.1 1
4.8%
ValueCountFrequency (%)
97.0 1
4.8%
56.0 1
4.8%
45.0 1
4.8%
44.3 2
9.5%
43.5 1
4.8%
42.7 1
4.8%
42.6 1
4.8%
40.6 1
4.8%
38.0 1
4.8%
37.1 1
4.8%

배차간격
Real number (ℝ)

HIGH CORRELATION 

Distinct10
Distinct (%)47.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean12.809524
Minimum5
Maximum25
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size321.0 B
2023-12-11T01:37:13.988693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5
5-th percentile6
Q17
median12
Q315
95-th percentile25
Maximum25
Range20
Interquartile range (IQR)8

Descriptive statistics

Standard deviation6.0549075
Coefficient of variation (CV)0.47268795
Kurtosis-0.39245134
Mean12.809524
Median Absolute Deviation (MAD)5
Skewness0.65452554
Sum269
Variance36.661905
MonotonicityNot monotonic
2023-12-11T01:37:14.153416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
15 4
19.0%
7 3
14.3%
12 3
14.3%
25 2
9.5%
6 2
9.5%
20 2
9.5%
10 2
9.5%
8 1
 
4.8%
17 1
 
4.8%
5 1
 
4.8%
ValueCountFrequency (%)
5 1
 
4.8%
6 2
9.5%
7 3
14.3%
8 1
 
4.8%
10 2
9.5%
12 3
14.3%
15 4
19.0%
17 1
 
4.8%
20 2
9.5%
25 2
9.5%
ValueCountFrequency (%)
25 2
9.5%
20 2
9.5%
17 1
 
4.8%
15 4
19.0%
12 3
14.3%
10 2
9.5%
8 1
 
4.8%
7 3
14.3%
6 2
9.5%
5 1
 
4.8%

운행구간_기점
Categorical

HIGH CORRELATION 

Distinct7
Distinct (%)33.3%
Missing0
Missing (%)0.0%
Memory size300.0 B
청학동
8 
태종대
7 
해양대학교
2 
청강리
1 
영도중리
1 
Other values (2)
2 

Length

Max length5
Median length3
Mean length3.2857143
Min length3

Unique

Unique4 ?
Unique (%)19.0%

Sample

1st row청강리
2nd row태종대
3rd row태종대
4th row태종대
5th row태종대

Common Values

ValueCountFrequency (%)
청학동 8
38.1%
태종대 7
33.3%
해양대학교 2
 
9.5%
청강리 1
 
4.8%
영도중리 1
 
4.8%
영도주공 1
 
4.8%
다대포 1
 
4.8%

Length

2023-12-11T01:37:14.332899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:37:14.482044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
청학동 8
38.1%
태종대 7
33.3%
해양대학교 2
 
9.5%
청강리 1
 
4.8%
영도중리 1
 
4.8%
영도주공 1
 
4.8%
다대포 1
 
4.8%

운행구간_종점
Text

Distinct17
Distinct (%)81.0%
Missing0
Missing (%)0.0%
Memory size300.0 B
2023-12-11T01:37:14.661851image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length7
Mean length5.1428571
Min length2

Characters and Unicode

Total characters108
Distinct characters52
Distinct categories3 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique13 ?
Unique (%)61.9%

Sample

1st row경제자유구역청
2nd row동해선신해운대역
3rd row서부터미널
4th row송도
5th row당감주공
ValueCountFrequency (%)
서부터미널 2
 
9.5%
수산가공선진화단지 2
 
9.5%
당감주공 2
 
9.5%
남부민동 2
 
9.5%
감천사거리 1
 
4.8%
경제자유구역청 1
 
4.8%
부산역 1
 
4.8%
중앙공원,민주공원 1
 
4.8%
중앙공원입구 1
 
4.8%
괴정 1
 
4.8%
Other values (7) 7
33.3%
2023-12-11T01:37:15.030804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
공 7
 
6.5%
부 5
 
4.6%
동 4
 
3.7%
선 4
 
3.7%
거 3
 
2.8%
감 3
 
2.8%
신 3
 
2.8%
화 3
 
2.8%
사 3
 
2.8%
주 3
 
2.8%
Other values (42) 70
64.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 104
96.3%
Uppercase Letter 3
 
2.8%
Other Punctuation 1
 
0.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
공 7
 
6.7%
부 5
 
4.8%
동 4
 
3.8%
선 4
 
3.8%
거 3
 
2.9%
감 3
 
2.9%
신 3
 
2.9%
화 3
 
2.9%
사 3
 
2.9%
주 3
 
2.9%
Other values (38) 66
63.5%
Uppercase Letter
ValueCountFrequency (%)
T 1
33.3%
P 1
33.3%
A 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 104
96.3%
Latin 3
 
2.8%
Common 1
 
0.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
공 7
 
6.7%
부 5
 
4.8%
동 4
 
3.8%
선 4
 
3.8%
거 3
 
2.9%
감 3
 
2.9%
신 3
 
2.9%
화 3
 
2.9%
사 3
 
2.9%
주 3
 
2.9%
Other values (38) 66
63.5%
Latin
ValueCountFrequency (%)
T 1
33.3%
P 1
33.3%
A 1
33.3%
Common
ValueCountFrequency (%)
, 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 104
96.3%
ASCII 4
 
3.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
공 7
 
6.7%
부 5
 
4.8%
동 4
 
3.8%
선 4
 
3.8%
거 3
 
2.9%
감 3
 
2.9%
신 3
 
2.9%
화 3
 
2.9%
사 3
 
2.9%
주 3
 
2.9%
Other values (38) 66
63.5%
ASCII
ValueCountFrequency (%)
, 1
25.0%
T 1
25.0%
P 1
25.0%
A 1
25.0%

운행시간_첫차
Categorical

Distinct7
Distinct (%)33.3%
Missing0
Missing (%)0.0%
Memory size300.0 B
05:00
7 
04:55
5 
04:50
3 
04:48
2 
04:45
2 
Other values (2)
2 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique2 ?
Unique (%)9.5%

Sample

1st row05:00
2nd row05:00
3rd row04:48
4th row04:48
5th row04:56

Common Values

ValueCountFrequency (%)
05:00 7
33.3%
04:55 5
23.8%
04:50 3
14.3%
04:48 2
 
9.5%
04:45 2
 
9.5%
04:56 1
 
4.8%
04:46 1
 
4.8%

Length

2023-12-11T01:37:15.172099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:37:15.294008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
05:00 7
33.3%
04:55 5
23.8%
04:50 3
14.3%
04:48 2
 
9.5%
04:45 2
 
9.5%
04:56 1
 
4.8%
04:46 1
 
4.8%

운행시간_막차
Date

Distinct17
Distinct (%)81.0%
Missing0
Missing (%)0.0%
Memory size300.0 B
Minimum2023-12-11 21:00:00
Maximum2023-12-11 23:16:00
2023-12-11T01:37:15.420737image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:37:15.557381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)

소요시간
Real number (ℝ)

HIGH CORRELATION 

Distinct18
Distinct (%)85.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean131.85714
Minimum62
Maximum215
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size321.0 B
2023-12-11T01:37:15.690831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum62
5-th percentile85
Q1106
median131
Q3152
95-th percentile175
Maximum215
Range153
Interquartile range (IQR)46

Descriptive statistics

Standard deviation35.327448
Coefficient of variation (CV)0.26792214
Kurtosis0.32969245
Mean131.85714
Median Absolute Deviation (MAD)25
Skewness0.23488519
Sum2769
Variance1248.0286
MonotonicityNot monotonic
2023-12-11T01:37:15.790399image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=18)
ValueCountFrequency (%)
152 2
 
9.5%
120 2
 
9.5%
166 2
 
9.5%
215 1
 
4.8%
135 1
 
4.8%
158 1
 
4.8%
90 1
 
4.8%
103 1
 
4.8%
119 1
 
4.8%
115 1
 
4.8%
Other values (8) 8
38.1%
ValueCountFrequency (%)
62 1
4.8%
85 1
4.8%
90 1
4.8%
103 1
4.8%
104 1
4.8%
106 1
4.8%
115 1
4.8%
119 1
4.8%
120 2
9.5%
131 1
4.8%
ValueCountFrequency (%)
215 1
4.8%
175 1
4.8%
166 2
9.5%
158 1
4.8%
152 2
9.5%
151 1
4.8%
144 1
4.8%
135 1
4.8%
131 1
4.8%
120 2
9.5%

Interactions

2023-12-11T01:37:10.277048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:37:07.257920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:37:07.915446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:37:08.599429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:37:09.253449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:37:10.410959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:37:07.370890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:37:08.052625image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:37:08.705084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:37:09.401271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:37:10.534046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:37:07.501637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:37:08.169410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:37:08.835155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:37:09.544344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:37:10.667396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:37:07.629341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:37:08.310351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:37:08.977328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:37:09.670713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:37:10.804385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:37:07.771716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:37:08.446584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:37:09.126584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:37:09.804558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T01:37:15.884636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업체명소재지대표번호버스노선면허대수(예비포함)운행횟수거리(킬로미터)배차간격운행구간_기점운행구간_종점운행시간_첫차운행시간_막차소요시간
업체명1.0001.0001.0000.9500.6710.0000.6400.4110.9010.9650.0000.0000.683
소재지1.0001.0001.0000.9500.6710.0000.6400.4110.9010.9650.0000.0000.683
대표번호1.0001.0001.0000.9500.6710.0000.6400.4110.9010.9650.0000.0000.683
버스노선0.9500.9500.9501.0000.9111.0001.0001.0001.0001.0001.0001.0001.000
면허대수(예비포함)0.6710.6710.6710.9111.0000.0000.7550.2960.6930.8880.0000.7730.500
운행횟수0.0000.0000.0001.0000.0001.0000.3380.8790.5170.9000.0000.9220.563
거리(킬로미터)0.6400.6400.6401.0000.7550.3381.0000.7850.7320.9040.0001.0000.966
배차간격0.4110.4110.4111.0000.2960.8790.7851.0000.5370.9480.4820.7830.723
운행구간_기점0.9010.9010.9011.0000.6930.5170.7320.5371.0001.0000.0000.5090.812
운행구간_종점0.9650.9650.9651.0000.8880.9000.9040.9481.0001.0000.0000.9510.948
운행시간_첫차0.0000.0000.0001.0000.0000.0000.0000.4820.0000.0001.0000.7750.000
운행시간_막차0.0000.0000.0001.0000.7730.9221.0000.7830.5090.9510.7751.0000.893
소요시간0.6830.6830.6831.0000.5000.5630.9660.7230.8120.9480.0000.8931.000
2023-12-11T01:37:16.013599image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업체명대표번호소재지운행시간_첫차운행구간_기점
업체명1.0001.0001.0000.0000.789
대표번호1.0001.0001.0000.0000.789
소재지1.0001.0001.0000.0000.789
운행시간_첫차0.0000.0000.0001.0000.000
운행구간_기점0.7890.7890.7890.0001.000
2023-12-11T01:37:16.108341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
면허대수(예비포함)운행횟수거리(킬로미터)배차간격소요시간업체명소재지대표번호운행구간_기점운행시간_첫차
면허대수(예비포함)1.0000.755-0.286-0.726-0.1110.3830.3830.3830.4010.000
운행횟수0.7551.000-0.704-0.991-0.5490.0000.0000.0000.2340.000
거리(킬로미터)-0.286-0.7041.0000.6880.9400.4720.4720.4720.5170.000
배차간격-0.726-0.9910.6881.0000.5420.1830.1830.1830.1670.242
소요시간-0.111-0.5490.9400.5421.0000.3950.3950.3950.5510.000
업체명0.3830.0000.4720.1830.3951.0001.0001.0000.7890.000
소재지0.3830.0000.4720.1830.3951.0001.0001.0000.7890.000
대표번호0.3830.0000.4720.1830.3951.0001.0001.0000.7890.000
운행구간_기점0.4010.2340.5170.1670.5510.7890.7890.7891.0000.000
운행시간_첫차0.0000.0000.0000.2420.0000.0000.0000.0000.0001.000

Missing values

2023-12-11T01:37:11.000461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T01:37:11.243593image/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

업체명소재지대표번호버스노선면허대수(예비포함)운행횟수거리(킬로미터)배차간격운행구간_기점운행구간_종점운행시간_첫차운행시간_막차소요시간
0부일여객부산광역시 기장군 기장읍 기장대로 313051-703-55011011144897.025청강리경제자유구역청05:0021:00215
1신한여객부산광역시 영도구 태종로 808(동삼동)051-405-0511100664545.025태종대동해선신해운대역05:0022:00144
2신한여객부산광역시 영도구 태종로 808(동삼동)051-405-051182214238.07태종대서부터미널04:4822:13131
3신한여객부산광역시 영도구 태종로 808(동삼동)051-405-0511301918024.66태종대송도04:4823:1085
4신한여객부산광역시 영도구 태종로 808(동삼동)051-405-05116684843.520태종대당감주공04:5622:05151
5신한여객부산광역시 영도구 태종로 808(동삼동)051-405-05118894842.720태종대당감주공04:4622:00152
6신한여객부산광역시 영도구 태종로 808(동삼동)051-405-05111011812635.48태종대대연사거리04:4522:25120
7신한여객부산광역시 영도구 태종로 808(동삼동)051-405-05111132816240.67영도중리신평04:4522:19152
8신한여객부산광역시 영도구 태종로 808(동삼동)051-405-0511186125756.017태종대서부터미널04:5521:40175
9신한여객부산광역시 영도구 태종로 808(동삼동)051-405-051119046444.315해양대학교남부민동04:5521:50166
업체명소재지대표번호버스노선면허대수(예비포함)운행횟수거리(킬로미터)배차간격운행구간_기점운행구간_종점운행시간_첫차운행시간_막차소요시간
11유한여객부산광역시 영도구 청학서로 37(청학동)051-415-625685139430.712청학동전포사거리04:5022:50120
12유한여객부산광역시 영도구 청학서로 37(청학동)051-415-625688ㅡ11115017.27영도주공부산역05:0023:1062
13유한여객부산광역시 영도구 청학서로 37(청학동)051-415-625619086444.315해양대학교남부민동04:5521:50166
14남부여객부산광역시 영도구 와치로 113(청학동)051-415-555561816537.16청학동괴정04:5022:45135
15남부여객부산광역시 영도구 와치로 113(청학동)051-415-55557108030.712청학동수산가공선진화단지05:0022:37104
16남부여객부산광역시 영도구 와치로 113(청학동)051-415-5555986434.615청학동감천사거리04:5022:35115
17남부여객부산광역시 영도구 와치로 113(청학동)051-415-555570107033.715청학동중앙공원입구05:0022:20119
18남부여객부산광역시 영도구 와치로 113(청학동)051-415-555571109031.212청학동수산가공선진화단지04:5522:43103
19남부여객부산광역시 영도구 와치로 113(청학동)051-415-55555081111025.610청학동중앙공원,민주공원05:0023:1690
20동진여객부산광역시 사하구 다대로 722(다대동)051-261-2773111910342.610다대포영선동05:0022:00158