Overview

Dataset statistics

Number of variables10
Number of observations71
Missing cells30
Missing cells (%)4.2%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.8 KiB
Average record size in memory83.9 B

Variable types

Categorical3
Text5
Numeric2

Dataset

Description경상남도 김해시 시내버스 운행 현황에 대한 데이터로 업체구분,노선번호,기점,종점,첫차,막차 등의 항목을 제공합니다
Author경상남도 김해시
URLhttps://www.data.go.kr/data/3063197/fileData.do

Alerts

운행대수 is highly overall correlated with 업체구분 and 1 other fieldsHigh correlation
운행거리(키로미터) is highly overall correlated with 업체구분High correlation
업체구분 is highly overall correlated with 운행대수 and 2 other fieldsHigh correlation
기점 is highly overall correlated with 업체구분High correlation
배차간격 is highly overall correlated with 운행대수High correlation
운행대수 has 12 (16.9%) missing valuesMissing
운행거리(키로미터) has 18 (25.4%) missing valuesMissing
노선번호 has unique valuesUnique

Reproduction

Analysis started2023-12-12 08:08:57.952590
Analysis finished2023-12-12 08:08:59.601051
Duration1.65 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

업체구분
Categorical

HIGH CORRELATION 

Distinct6
Distinct (%)8.5%
Missing0
Missing (%)0.0%
Memory size700.0 B
김해버스
32 
가야IBS
16 
동부교통
13 
부산버스
8 
태영고속
 
1

Length

Max length5
Median length4
Mean length4.2253521
Min length4

Unique

Unique2 ?
Unique (%)2.8%

Sample

1st row가야IBS
2nd row가야IBS
3rd row동부교통
4th row동부교통
5th row김해버스

Common Values

ValueCountFrequency (%)
김해버스 32
45.1%
가야IBS 16
22.5%
동부교통 13
18.3%
부산버스 8
 
11.3%
태영고속 1
 
1.4%
창원버스 1
 
1.4%

Length

2023-12-12T17:08:59.666297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T17:09:00.144112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
김해버스 32
45.1%
가야ibs 16
22.5%
동부교통 13
18.3%
부산버스 8
 
11.3%
태영고속 1
 
1.4%
창원버스 1
 
1.4%

노선번호
Text

UNIQUE 

Distinct71
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size700.0 B
2023-12-12T17:09:00.444058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length6
Mean length3.7323944
Min length2

Characters and Unicode

Total characters265
Distinct characters26
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

Unique71 ?
Unique (%)100.0%

Sample

1st row1번
2nd row1-1번
3rd row2번
4th row2-1번
5th row3번
ValueCountFrequency (%)
1번 1
 
1.4%
220번 1
 
1.4%
98번 1
 
1.4%
97-1번 1
 
1.4%
97번 1
 
1.4%
83번 1
 
1.4%
82번 1
 
1.4%
73번 1
 
1.4%
70번 1
 
1.4%
56번 1
 
1.4%
Other values (61) 61
85.9%
2023-12-12T17:09:01.041321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
번 71
26.8%
1 45
17.0%
2 26
 
9.8%
0 16
 
6.0%
- 14
 
5.3%
3 14
 
5.3%
5 12
 
4.5%
7 9
 
3.4%
4 9
 
3.4%
8 8
 
3.0%
Other values (16) 41
15.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 151
57.0%
Other Letter 94
35.5%
Dash Punctuation 14
 
5.3%
Uppercase Letter 4
 
1.5%
Open Punctuation 1
 
0.4%
Close Punctuation 1
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
번 71
75.5%
공 3
 
3.2%
형 3
 
3.2%
시 3
 
3.2%
도 3
 
3.2%
영 3
 
3.2%
동 3
 
3.2%
상 2
 
2.1%
대 1
 
1.1%
심 1
 
1.1%
Decimal Number
ValueCountFrequency (%)
1 45
29.8%
2 26
17.2%
0 16
 
10.6%
3 14
 
9.3%
5 12
 
7.9%
7 9
 
6.0%
4 9
 
6.0%
8 8
 
5.3%
6 6
 
4.0%
9 6
 
4.0%
Uppercase Letter
ValueCountFrequency (%)
A 3
75.0%
B 1
 
25.0%
Dash Punctuation
ValueCountFrequency (%)
- 14
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 167
63.0%
Hangul 94
35.5%
Latin 4
 
1.5%

Most frequent character per script

Common
ValueCountFrequency (%)
1 45
26.9%
2 26
15.6%
0 16
 
9.6%
- 14
 
8.4%
3 14
 
8.4%
5 12
 
7.2%
7 9
 
5.4%
4 9
 
5.4%
8 8
 
4.8%
6 6
 
3.6%
Other values (3) 8
 
4.8%
Hangul
ValueCountFrequency (%)
번 71
75.5%
공 3
 
3.2%
형 3
 
3.2%
시 3
 
3.2%
도 3
 
3.2%
영 3
 
3.2%
동 3
 
3.2%
상 2
 
2.1%
대 1
 
1.1%
심 1
 
1.1%
Latin
ValueCountFrequency (%)
A 3
75.0%
B 1
 
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 171
64.5%
Hangul 94
35.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
번 71
75.5%
공 3
 
3.2%
형 3
 
3.2%
시 3
 
3.2%
도 3
 
3.2%
영 3
 
3.2%
동 3
 
3.2%
상 2
 
2.1%
대 1
 
1.1%
심 1
 
1.1%
ASCII
ValueCountFrequency (%)
1 45
26.3%
2 26
15.2%
0 16
 
9.4%
- 14
 
8.2%
3 14
 
8.2%
5 12
 
7.0%
7 9
 
5.3%
4 9
 
5.3%
8 8
 
4.7%
6 6
 
3.5%
Other values (5) 12
 
7.0%

기점
Categorical

HIGH CORRELATION 

Distinct30
Distinct (%)42.3%
Missing0
Missing (%)0.0%
Memory size700.0 B
외동차고지
18 
풍유동차고지
12 
삼계기점
4 
무계e편한
4 
구산동
 
3
Other values (25)
30 

Length

Max length9
Median length8
Mean length4.7746479
Min length2

Unique

Unique20 ?
Unique (%)28.2%

Sample

1st row삼계기점
2nd row삼계기점
3rd row외동차고지
4th row외동차고지
5th row풍유동차고지

Common Values

ValueCountFrequency (%)
외동차고지 18
25.4%
풍유동차고지 12
16.9%
삼계기점 4
 
5.6%
무계e편한 4
 
5.6%
구산동 3
 
4.2%
삼계 2
 
2.8%
구산동탑마트 2
 
2.8%
진영시외주차장 2
 
2.8%
선암 2
 
2.8%
롯데워터파크 2
 
2.8%
Other values (20) 20
28.2%

Length

2023-12-12T17:09:01.245329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
외동차고지 18
25.4%
풍유동차고지 12
16.9%
삼계기점 4
 
5.6%
무계e편한 4
 
5.6%
구산동 3
 
4.2%
진영시외주차장 2
 
2.8%
선암 2
 
2.8%
롯데워터파크 2
 
2.8%
구산동탑마트 2
 
2.8%
삼계 2
 
2.8%
Other values (20) 20
28.2%

종점
Text

Distinct54
Distinct (%)76.1%
Missing0
Missing (%)0.0%
Memory size700.0 B
2023-12-12T17:09:01.531501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length8
Mean length4.8450704
Min length2

Characters and Unicode

Total characters344
Distinct characters128
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique40 ?
Unique (%)56.3%

Sample

1st row경남은행
2nd row김해대학역
3rd row어방동
4th row어방동
5th row김해여객터미널(순환)
ValueCountFrequency (%)
창원대학교 4
 
5.6%
상동매리농협 3
 
4.2%
하단전철역 2
 
2.8%
덕천교차로 2
 
2.8%
옥천소류지 2
 
2.8%
구포시장종점 2
 
2.8%
대동1단지 2
 
2.8%
롯데워터파크 2
 
2.8%
서구청 2
 
2.8%
봉하마을 2
 
2.8%
Other values (44) 48
67.6%
2023-12-12T17:09:01.998692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
대 11
 
3.2%
교 11
 
3.2%
동 11
 
3.2%
시 10
 
2.9%
학 9
 
2.6%
터 8
 
2.3%
하 7
 
2.0%
장 7
 
2.0%
마 7
 
2.0%
구 7
 
2.0%
Other values (118) 256
74.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 337
98.0%
Decimal Number 4
 
1.2%
Close Punctuation 1
 
0.3%
Open Punctuation 1
 
0.3%
Lowercase Letter 1
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
대 11
 
3.3%
교 11
 
3.3%
동 11
 
3.3%
시 10
 
3.0%
학 9
 
2.7%
터 8
 
2.4%
하 7
 
2.1%
장 7
 
2.1%
마 7
 
2.1%
구 7
 
2.1%
Other values (112) 249
73.9%
Decimal Number
ValueCountFrequency (%)
1 2
50.0%
3 1
25.0%
4 1
25.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 337
98.0%
Common 6
 
1.7%
Latin 1
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
대 11
 
3.3%
교 11
 
3.3%
동 11
 
3.3%
시 10
 
3.0%
학 9
 
2.7%
터 8
 
2.4%
하 7
 
2.1%
장 7
 
2.1%
마 7
 
2.1%
구 7
 
2.1%
Other values (112) 249
73.9%
Common
ValueCountFrequency (%)
1 2
33.3%
3 1
16.7%
) 1
16.7%
( 1
16.7%
4 1
16.7%
Latin
ValueCountFrequency (%)
e 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 337
98.0%
ASCII 7
 
2.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
대 11
 
3.3%
교 11
 
3.3%
동 11
 
3.3%
시 10
 
3.0%
학 9
 
2.7%
터 8
 
2.4%
하 7
 
2.1%
장 7
 
2.1%
마 7
 
2.1%
구 7
 
2.1%
Other values (112) 249
73.9%
ASCII
ValueCountFrequency (%)
1 2
28.6%
3 1
14.3%
) 1
14.3%
( 1
14.3%
4 1
14.3%
e 1
14.3%

첫차
Text

Distinct55
Distinct (%)77.5%
Missing0
Missing (%)0.0%
Memory size700.0 B
2023-12-12T17:09:02.257853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length11
Mean length8.9014085
Min length3

Characters and Unicode

Total characters632
Distinct characters13
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

Unique47 ?
Unique (%)66.2%

Sample

1st row05:00/05:20
2nd row05:08/05:30
3rd row05:30/-
4th row05:40/-
5th row06:10/-
ValueCountFrequency (%)
05:00 4
 
5.6%
06:00/06:50 3
 
4.2%
06:00 3
 
4.2%
04:50 3
 
4.2%
05:50 3
 
4.2%
3
 
4.2%
05:30 3
 
4.2%
06:30 2
 
2.8%
05:00/05:20 1
 
1.4%
05:50/06:50 1
 
1.4%
Other values (45) 45
63.4%
2023-12-12T17:09:02.729138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 222
35.1%
: 105
16.6%
/ 71
 
11.2%
5 65
 
10.3%
6 39
 
6.2%
- 37
 
5.9%
3 22
 
3.5%
2 22
 
3.5%
7 15
 
2.4%
4 14
 
2.2%
Other values (3) 20
 
3.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 419
66.3%
Other Punctuation 176
27.8%
Dash Punctuation 37
 
5.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 222
53.0%
5 65
 
15.5%
6 39
 
9.3%
3 22
 
5.3%
2 22
 
5.3%
7 15
 
3.6%
4 14
 
3.3%
1 9
 
2.1%
8 7
 
1.7%
9 4
 
1.0%
Other Punctuation
ValueCountFrequency (%)
: 105
59.7%
/ 71
40.3%
Dash Punctuation
ValueCountFrequency (%)
- 37
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 632
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 222
35.1%
: 105
16.6%
/ 71
 
11.2%
5 65
 
10.3%
6 39
 
6.2%
- 37
 
5.9%
3 22
 
3.5%
2 22
 
3.5%
7 15
 
2.4%
4 14
 
2.2%
Other values (3) 20
 
3.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 632
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 222
35.1%
: 105
16.6%
/ 71
 
11.2%
5 65
 
10.3%
6 39
 
6.2%
- 37
 
5.9%
3 22
 
3.5%
2 22
 
3.5%
7 15
 
2.4%
4 14
 
2.2%
Other values (3) 20
 
3.2%

막차
Text

Distinct55
Distinct (%)77.5%
Missing0
Missing (%)0.0%
Memory size700.0 B
2023-12-12T17:09:03.060841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length11
Mean length8.915493
Min length3

Characters and Unicode

Total characters633
Distinct characters14
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

Unique47 ?
Unique (%)66.2%

Sample

1st row22:16/23:15
2nd row22:30/23:20
3rd row22:15/-
4th row22:30/-
5th row21:20/-
ValueCountFrequency (%)
22:30 4
 
5.6%
22:00 4
 
5.6%
3
 
4.2%
21:20 3
 
4.2%
22:40 3
 
4.2%
21:50 3
 
4.2%
22:35 2
 
2.8%
21:30 2
 
2.8%
21:50/23:30 1
 
1.4%
22:00/22:15 1
 
1.4%
Other values (45) 45
63.4%
2023-12-12T17:09:03.534099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 145
22.9%
0 125
19.7%
: 103
16.3%
/ 71
11.2%
1 59
9.3%
- 37
 
5.8%
5 34
 
5.4%
3 30
 
4.7%
4 14
 
2.2%
9 4
 
0.6%
Other values (4) 11
 
1.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 420
66.4%
Other Punctuation 176
27.8%
Dash Punctuation 37
 
5.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 145
34.5%
0 125
29.8%
1 59
14.0%
5 34
 
8.1%
3 30
 
7.1%
4 14
 
3.3%
9 4
 
1.0%
7 4
 
1.0%
8 3
 
0.7%
6 2
 
0.5%
Other Punctuation
ValueCountFrequency (%)
: 103
58.5%
/ 71
40.3%
; 2
 
1.1%
Dash Punctuation
ValueCountFrequency (%)
- 37
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 633
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 145
22.9%
0 125
19.7%
: 103
16.3%
/ 71
11.2%
1 59
9.3%
- 37
 
5.8%
5 34
 
5.4%
3 30
 
4.7%
4 14
 
2.2%
9 4
 
0.6%
Other values (4) 11
 
1.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 633
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 145
22.9%
0 125
19.7%
: 103
16.3%
/ 71
11.2%
1 59
9.3%
- 37
 
5.8%
5 34
 
5.4%
3 30
 
4.7%
4 14
 
2.2%
9 4
 
0.6%
Other values (4) 11
 
1.7%

배차간격
Categorical

HIGH CORRELATION 

Distinct26
Distinct (%)36.6%
Missing0
Missing (%)0.0%
Memory size700.0 B
고정배차
34 
-
10 
24~26분
 
2
25~30분
 
2
30분
 
2
Other values (21)
21 

Length

Max length8
Median length7
Mean length4.2253521
Min length1

Unique

Unique21 ?
Unique (%)29.6%

Sample

1st row10~18분
2nd row10분~15분
3rd row24~26분
4th row24~26분
5th row고정배차

Common Values

ValueCountFrequency (%)
고정배차 34
47.9%
- 10
 
14.1%
24~26분 2
 
2.8%
25~30분 2
 
2.8%
30분 2
 
2.8%
22분~26분 1
 
1.4%
10~13분 1
 
1.4%
20~23분 1
 
1.4%
30~40분 1
 
1.4%
25~35 1
 
1.4%
Other values (16) 16
22.5%

Length

2023-12-12T17:09:03.718079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
고정배차 34
47.9%
10
 
14.1%
24~26분 2
 
2.8%
25~30분 2
 
2.8%
30분 2
 
2.8%
14~16분 1
 
1.4%
10~18분 1
 
1.4%
60~65분 1
 
1.4%
5~7분 1
 
1.4%
13~15분 1
 
1.4%
Other values (16) 16
22.5%

운행대수
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct11
Distinct (%)18.6%
Missing12
Missing (%)16.9%
Infinite0
Infinite (%)0.0%
Mean3.779661
Minimum1
Maximum26
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size771.0 B
2023-12-12T17:09:03.857703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median2
Q35
95-th percentile10
Maximum26
Range25
Interquartile range (IQR)4

Descriptive statistics

Standard deviation4.1856396
Coefficient of variation (CV)1.1074114
Kurtosis12.794188
Mean3.779661
Median Absolute Deviation (MAD)1
Skewness2.9611361
Sum223
Variance17.519579
MonotonicityNot monotonic
2023-12-12T17:09:03.981157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
1 24
33.8%
2 9
 
12.7%
10 5
 
7.0%
5 5
 
7.0%
4 5
 
7.0%
3 3
 
4.2%
6 3
 
4.2%
7 2
 
2.8%
11 1
 
1.4%
8 1
 
1.4%
(Missing) 12
16.9%
ValueCountFrequency (%)
1 24
33.8%
2 9
 
12.7%
3 3
 
4.2%
4 5
 
7.0%
5 5
 
7.0%
6 3
 
4.2%
7 2
 
2.8%
8 1
 
1.4%
10 5
 
7.0%
11 1
 
1.4%
ValueCountFrequency (%)
26 1
 
1.4%
11 1
 
1.4%
10 5
7.0%
8 1
 
1.4%
7 2
 
2.8%
6 3
 
4.2%
5 5
7.0%
4 5
7.0%
3 3
 
4.2%
2 9
12.7%

운행거리(키로미터)
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct45
Distinct (%)84.9%
Missing18
Missing (%)25.4%
Infinite0
Infinite (%)0.0%
Mean43.669811
Minimum12.4
Maximum91.1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size771.0 B
2023-12-12T17:09:04.159632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum12.4
5-th percentile19.4
Q127
median35.9
Q355.2
95-th percentile89.9
Maximum91.1
Range78.7
Interquartile range (IQR)28.2

Descriptive statistics

Standard deviation21.513221
Coefficient of variation (CV)0.49263371
Kurtosis-0.14213195
Mean43.669811
Median Absolute Deviation (MAD)13.4
Skewness0.81874055
Sum2314.5
Variance462.81869
MonotonicityNot monotonic
2023-12-12T17:09:04.315532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=45)
ValueCountFrequency (%)
89.3 2
 
2.8%
64.0 2
 
2.8%
91.1 2
 
2.8%
50.0 2
 
2.8%
22.5 2
 
2.8%
26.0 2
 
2.8%
62.0 2
 
2.8%
53.5 2
 
2.8%
25.7 1
 
1.4%
61.0 1
 
1.4%
Other values (35) 35
49.3%
(Missing) 18
25.4%
ValueCountFrequency (%)
12.4 1
1.4%
14.2 1
1.4%
15.5 1
1.4%
22.0 1
1.4%
22.5 2
2.8%
22.6 1
1.4%
23.7 1
1.4%
23.8 1
1.4%
25.2 1
1.4%
25.7 1
1.4%
ValueCountFrequency (%)
91.1 2
2.8%
90.8 1
1.4%
89.3 2
2.8%
75.0 1
1.4%
67.4 1
1.4%
64.0 2
2.8%
62.0 2
2.8%
61.0 1
1.4%
60.0 1
1.4%
55.2 1
1.4%

경유지
Text

Distinct69
Distinct (%)97.2%
Missing0
Missing (%)0.0%
Memory size700.0 B
2023-12-12T17:09:04.656929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length61
Median length40
Mean length27.577465
Min length6

Characters and Unicode

Total characters1958
Distinct characters229
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

Unique68 ?
Unique (%)95.8%

Sample

1st row가야대-푸르지오2차-가락로-복음병원-인제대-한일여고
2nd row북부동사무소-푸르지오2차가락로-한일여고-안동4
3rd row가야고-금강병원-시청-안동6-인제대
4th row가야고-세무서-시청-안동공단입구-인제대
5th row골든루트-마찰-흥동3-동아그린-가락로-교육청
ValueCountFrequency (%)
가락로-분성로-일동한신a-주촌농협-후포-외덕-장유초-장유농협 3
 
4.0%
북부동사무소-연지공원-내동4-장유농협-중앙하이츠 1
 
1.3%
반대노선 1
 
1.3%
98번동일)창원구간만 1
 
1.3%
갑오마을-대청계곡-신안마을-남산터미널 1
 
1.3%
지내동-인제대-활천고개--장유초-대청초-관동중 1
 
1.3%
덕산-월촌-안막3구 1
 
1.3%
교육청-호계로-선암-안막 1
 
1.3%
김해보건소-중부경찰서-신안-신정-안막-원지-괴정-지나 1
 
1.3%
김해tr-중부서-호계로-삼계역-나전공단-매리 1
 
1.3%
Other values (63) 63
84.0%
2023-12-12T17:09:05.212446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 363
 
18.5%
동 55
 
2.8%
장 38
 
1.9%
역 34
 
1.7%
대 33
 
1.7%
로 32
 
1.6%
구 32
 
1.6%
중 32
 
1.6%
부 29
 
1.5%
유 29
 
1.5%
Other values (219) 1281
65.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1512
77.2%
Dash Punctuation 363
 
18.5%
Decimal Number 35
 
1.8%
Uppercase Letter 13
 
0.7%
Lowercase Letter 13
 
0.7%
Open Punctuation 8
 
0.4%
Close Punctuation 8
 
0.4%
Space Separator 4
 
0.2%
Other Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 55
 
3.6%
장 38
 
2.5%
역 34
 
2.2%
대 33
 
2.2%
로 32
 
2.1%
구 32
 
2.1%
중 32
 
2.1%
부 29
 
1.9%
유 29
 
1.9%
서 29
 
1.9%
Other values (196) 1169
77.3%
Decimal Number
ValueCountFrequency (%)
4 10
28.6%
2 7
20.0%
3 6
17.1%
6 5
14.3%
1 3
 
8.6%
8 1
 
2.9%
5 1
 
2.9%
9 1
 
2.9%
0 1
 
2.9%
Uppercase Letter
ValueCountFrequency (%)
T 8
61.5%
R 2
 
15.4%
U 1
 
7.7%
N 1
 
7.7%
I 1
 
7.7%
Lowercase Letter
ValueCountFrequency (%)
r 7
53.8%
a 4
30.8%
c 1
 
7.7%
i 1
 
7.7%
Dash Punctuation
ValueCountFrequency (%)
- 363
100.0%
Open Punctuation
ValueCountFrequency (%)
( 8
100.0%
Close Punctuation
ValueCountFrequency (%)
) 8
100.0%
Space Separator
ValueCountFrequency (%)
4
100.0%
Other Punctuation
ValueCountFrequency (%)
@ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1512
77.2%
Common 420
 
21.5%
Latin 26
 
1.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 55
 
3.6%
장 38
 
2.5%
역 34
 
2.2%
대 33
 
2.2%
로 32
 
2.1%
구 32
 
2.1%
중 32
 
2.1%
부 29
 
1.9%
유 29
 
1.9%
서 29
 
1.9%
Other values (196) 1169
77.3%
Common
ValueCountFrequency (%)
- 363
86.4%
4 10
 
2.4%
( 8
 
1.9%
) 8
 
1.9%
2 7
 
1.7%
3 6
 
1.4%
6 5
 
1.2%
4
 
1.0%
1 3
 
0.7%
@ 2
 
0.5%
Other values (4) 4
 
1.0%
Latin
ValueCountFrequency (%)
T 8
30.8%
r 7
26.9%
a 4
15.4%
R 2
 
7.7%
U 1
 
3.8%
N 1
 
3.8%
I 1
 
3.8%
c 1
 
3.8%
i 1
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1512
77.2%
ASCII 446
 
22.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 363
81.4%
4 10
 
2.2%
T 8
 
1.8%
( 8
 
1.8%
) 8
 
1.8%
r 7
 
1.6%
2 7
 
1.6%
3 6
 
1.3%
6 5
 
1.1%
a 4
 
0.9%
Other values (13) 20
 
4.5%
Hangul
ValueCountFrequency (%)
동 55
 
3.6%
장 38
 
2.5%
역 34
 
2.2%
대 33
 
2.2%
로 32
 
2.1%
구 32
 
2.1%
중 32
 
2.1%
부 29
 
1.9%
유 29
 
1.9%
서 29
 
1.9%
Other values (196) 1169
77.3%

Interactions

2023-12-12T17:08:59.076595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:08:58.904074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:08:59.168382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T17:08:58.988642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T17:09:05.336396image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업체구분노선번호기점종점첫차막차배차간격운행대수운행거리(키로미터)경유지
업체구분1.0001.0000.9740.9810.5700.0000.7920.7110.7791.000
노선번호1.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
기점0.9741.0001.0000.9340.9530.9680.0000.7370.7791.000
종점0.9811.0000.9341.0000.7990.7280.9750.9600.9570.995
첫차0.5701.0000.9530.7991.0000.9950.0000.8910.7900.995
막차0.0001.0000.9680.7280.9951.0000.0000.0000.8000.995
배차간격0.7921.0000.0000.9750.0000.0001.0000.9670.7780.957
운행대수0.7111.0000.7370.9600.8910.0000.9671.0000.4081.000
운행거리(키로미터)0.7791.0000.7790.9570.7900.8000.7780.4081.0001.000
경유지1.0001.0001.0000.9950.9950.9950.9571.0001.0001.000
2023-12-12T17:09:05.502884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
배차간격업체구분기점
배차간격1.0000.4180.000
업체구분0.4181.0000.629
기점0.0000.6291.000
2023-12-12T17:09:05.610188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
운행대수운행거리(키로미터)업체구분기점배차간격
운행대수1.0000.1500.5880.4970.739
운행거리(키로미터)0.1501.0000.5690.3810.365
업체구분0.5880.5691.0000.6290.418
기점0.4970.3810.6291.0000.000
배차간격0.7390.3650.4180.0001.000

Missing values

2023-12-12T17:08:59.294317image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T17:08:59.435638image/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.
2023-12-12T17:08:59.551032image/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

업체구분노선번호기점종점첫차막차배차간격운행대수운행거리(키로미터)경유지
0가야IBS1번삼계기점경남은행05:00/05:2022:16/23:1510~18분1030.2가야대-푸르지오2차-가락로-복음병원-인제대-한일여고
1가야IBS1-1번삼계기점김해대학역05:08/05:3022:30/23:2010분~15분1015.5북부동사무소-푸르지오2차가락로-한일여고-안동4
2동부교통2번외동차고지어방동05:30/-22:15/-24~26분527.6가야고-금강병원-시청-안동6-인제대
3동부교통2-1번외동차고지어방동05:40/-22:30/-24~26분527.0가야고-세무서-시청-안동공단입구-인제대
4김해버스3번풍유동차고지김해여객터미널(순환)06:10/-21:20/-고정배차230.4골든루트-마찰-흥동3-동아그린-가락로-교육청
5가야IBS3-1번외동차고지율하시티프라디움05:00/-22:40/-25~30분537.2김해보건소-분성로-호계로-중부서-흥동3통-칠산초-롯데아울렛-율하주공-율하초(율하초-중앙하이츠-관동초)
6동부교통4번풍유동차고지가락07:20/06:0522:00/20:50고정배차135.0보건소-교육청-호계로-초선대-불암동
7가야IBS5-1번풍유동차고지감분마을05:00/-21:30/-고정배차535.9외동축협-주민센터-내동사-구산백조-이진캐스빌-분성고
8김해버스6번외동차고지화목4통06:00/06:4021:50/22:30고정배차126.0동아그린-보건소-교육청-호계로-중부경찰서-강동
9동부교통7번외동차고지어방종점04:50/-22:35/-10~13분1028.0무접-외동4-교육청-가락로-동김해ic-지내동
업체구분노선번호기점종점첫차막차배차간격운행대수운행거리(키로미터)경유지
61김해버스도시형3번어병진영시외버스터미널09:00/09:4216:35/17:17-1<NA>소업마을-신기마을-진영역-윗양지-제일고
62부산버스123번구산동탑마트서구청04:30/-21:50/-10~13<NA><NA>구산동-중앙지구대-김해대학역-평강역-강서구청-동아대입구-부산대학병원
63부산버스124번구산육거리서면-/--/--<NA><NA>구산동-중앙지구대-김해대학역-평강역-강서구청-당감시장-서면역
64부산버스125번선암다리구포시장06:00/-21:20/-30분<NA><NA>불암역-원지마을-대저역-구포역
65부산버스127번구산동탑마트덕천교차로04:50/-22:40/-13~15분<NA><NA>탑마트-무접-평강역-구포시장
66부산버스128-1번구산동신라대학교04:40/-21:50/-5~7분2654.0구산동-인제대학교-신어중학교-구포역-신라대학교
67부산버스221번장유온천하단전철역06:00/-20:00/--<NA><NA>장유온천-한림풀에버-수가마을-렛츠런파크입구-하단역
68부산버스1004번구산동국제여객터미널04:50/-21:40/-11~13분<NA><NA>구산동-금강병원-불암역-화인아파트-서면역-부산항국제여객터미널
69부산버스1004(심야)번구산동서구청22:00/-23:40/-30분<NA><NA>구산동-금강병원-불암역-북부면허시험장-사상우체국-범일역-남포동
70창원버스170번창원대학교장유고등학교-/--/--<NA><NA>장유고등학교-남산중학교-까치아파트-창원대학교