Overview

Dataset statistics

Number of variables8
Number of observations1103
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory75.5 KiB
Average record size in memory70.1 B

Variable types

Numeric2
DateTime1
Categorical5

Dataset

Description광역버스정보시스템(MPBIS)의 목포시 버스시간표에 대하여 노선식별자, 순번, 출발시간, 평일운행여부, 토요일운행여부, 공휴일운행여부, 방학운행여부를 제공하고 있습니다.
Author전라남도 목포시
URLhttps://www.data.go.kr/data/15066989/fileData.do

Alerts

공휴일운행여부 is highly overall correlated with 토요일운행여부 and 2 other fieldsHigh correlation
방학운행여부 is highly overall correlated with 토요일운행여부 and 2 other fieldsHigh correlation
평일운행여부 is highly overall correlated with 비고High correlation
비고 is highly overall correlated with 노선식별자 and 4 other fieldsHigh correlation
토요일운행여부 is highly overall correlated with 공휴일운행여부 and 2 other fieldsHigh correlation
노선식별자 is highly overall correlated with 비고High correlation
비고 is highly imbalanced (83.2%)Imbalance

Reproduction

Analysis started2023-12-12 22:29:25.991637
Analysis finished2023-12-12 22:29:26.792024
Duration0.8 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

노선식별자
Real number (ℝ)

HIGH CORRELATION 

Distinct33
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.2400004 × 108
Minimum3.24 × 108
Maximum3.2400022 × 108
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size9.8 KiB
2023-12-13T07:29:26.847011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.24 × 108
5-th percentile3.24 × 108
Q13.2400001 × 108
median3.2400002 × 108
Q33.2400004 × 108
95-th percentile3.2400012 × 108
Maximum3.2400022 × 108
Range215
Interquartile range (IQR)30

Descriptive statistics

Standard deviation46.739352
Coefficient of variation (CV)1.4425724 × 10-7
Kurtosis1.1725778
Mean3.2400004 × 108
Median Absolute Deviation (MAD)15
Skewness1.4727148
Sum3.5737204 × 1011
Variance2184.567
MonotonicityIncreasing
2023-12-13T07:29:26.947510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
324000005 105
 
9.5%
324000010 78
 
7.1%
324000027 77
 
7.0%
324000023 75
 
6.8%
324000011 70
 
6.3%
324000007 69
 
6.3%
324000001 67
 
6.1%
324000024 38
 
3.4%
324000008 36
 
3.3%
324000105 35
 
3.2%
Other values (23) 453
41.1%
ValueCountFrequency (%)
324000001 67
6.1%
324000002 33
 
3.0%
324000005 105
9.5%
324000006 30
 
2.7%
324000007 69
6.3%
324000008 36
 
3.3%
324000010 78
7.1%
324000011 70
6.3%
324000013 26
 
2.4%
324000015 32
 
2.9%
ValueCountFrequency (%)
324000216 12
1.1%
324000131 17
1.5%
324000125 20
1.8%
324000124 20
1.8%
324000123 28
2.5%
324000118 17
1.5%
324000117 28
2.5%
324000116 24
2.2%
324000110 24
2.2%
324000107 21
1.9%

순번
Real number (ℝ)

Distinct105
Distinct (%)9.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean26.675431
Minimum1
Maximum105
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size9.8 KiB
2023-12-13T07:29:27.055270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q19
median20
Q338
95-th percentile70
Maximum105
Range104
Interquartile range (IQR)29

Descriptive statistics

Standard deviation22.342325
Coefficient of variation (CV)0.83756193
Kurtosis0.53121741
Mean26.675431
Median Absolute Deviation (MAD)13
Skewness1.0933446
Sum29423
Variance499.1795
MonotonicityNot monotonic
2023-12-13T07:29:27.168871image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 32
 
2.9%
4 32
 
2.9%
2 32
 
2.9%
3 32
 
2.9%
5 31
 
2.8%
6 31
 
2.8%
7 31
 
2.8%
8 31
 
2.8%
9 29
 
2.6%
10 29
 
2.6%
Other values (95) 793
71.9%
ValueCountFrequency (%)
1 32
2.9%
2 32
2.9%
3 32
2.9%
4 32
2.9%
5 31
2.8%
6 31
2.8%
7 31
2.8%
8 31
2.8%
9 29
2.6%
10 29
2.6%
ValueCountFrequency (%)
105 1
0.1%
104 1
0.1%
103 1
0.1%
102 1
0.1%
101 1
0.1%
100 1
0.1%
99 1
0.1%
98 1
0.1%
97 1
0.1%
96 1
0.1%

출발시간
Date

Distinct401
Distinct (%)36.4%
Missing0
Missing (%)0.0%
Memory size8.7 KiB
Minimum2023-12-13 05:00:00
Maximum2023-12-13 23:00:00
2023-12-13T07:29:27.282397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:29:27.444741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

평일운행여부
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size8.7 KiB
1
972 
0
131 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 972
88.1%
0 131
 
11.9%

Length

2023-12-13T07:29:27.551332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:29:27.629417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 972
88.1%
0 131
 
11.9%

토요일운행여부
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size8.7 KiB
1
935 
0
168 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 935
84.8%
0 168
 
15.2%

Length

2023-12-13T07:29:27.710637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:29:27.799620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 935
84.8%
0 168
 
15.2%

공휴일운행여부
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size8.7 KiB
1
935 
0
168 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 935
84.8%
0 168
 
15.2%

Length

2023-12-13T07:29:27.879093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:29:27.956424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 935
84.8%
0 168
 
15.2%

방학운행여부
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size8.7 KiB
1
788 
0
315 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 788
71.4%
0 315
 
28.6%

Length

2023-12-13T07:29:28.036381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:29:28.116413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 788
71.4%
0 315
 
28.6%

비고
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct5
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size8.7 KiB
<NA>
1047 
석현동→북항(900)
 
17
석현동→하당(900A)
 
17
(동문→한라A→용당)
 
11
(용당→한라A→남문)
 
11

Length

Max length12
Median length4
Mean length4.3708069
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 1047
94.9%
석현동→북항(900) 17
 
1.5%
석현동→하당(900A) 17
 
1.5%
(동문→한라A→용당) 11
 
1.0%
(용당→한라A→남문) 11
 
1.0%

Length

2023-12-13T07:29:28.209237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T07:29:28.302192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 1047
94.9%
석현동→북항(900 17
 
1.5%
석현동→하당(900a 17
 
1.5%
동문→한라a→용당 11
 
1.0%
용당→한라a→남문 11
 
1.0%

Interactions

2023-12-13T07:29:26.496408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:29:26.358166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:29:26.565283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T07:29:26.424951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T07:29:28.388355image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
노선식별자순번평일운행여부토요일운행여부공휴일운행여부방학운행여부비고
노선식별자1.0000.3190.3690.4210.4210.3601.000
순번0.3191.0000.3270.3950.3950.3160.529
평일운행여부0.3690.3271.0000.2320.2320.349NaN
토요일운행여부0.4210.3950.2321.0001.0000.866NaN
공휴일운행여부0.4210.3950.2321.0001.0000.866NaN
방학운행여부0.3600.3160.3490.8660.8661.000NaN
비고1.0000.529NaNNaNNaNNaN1.000
2023-12-13T07:29:28.505507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
공휴일운행여부방학운행여부평일운행여부비고토요일운행여부
공휴일운행여부1.0000.6670.1491.0000.996
방학운행여부0.6671.0000.2271.0000.667
평일운행여부0.1490.2271.0001.0000.149
비고1.0001.0001.0001.0001.000
토요일운행여부0.9960.6670.1491.0001.000
2023-12-13T07:29:28.985336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
노선식별자순번평일운행여부토요일운행여부공휴일운행여부방학운행여부비고
노선식별자1.000-0.4050.2330.2660.2660.2460.991
순번-0.4051.0000.2500.3030.3030.2410.352
평일운행여부0.2330.2501.0000.1490.1490.2271.000
토요일운행여부0.2660.3030.1491.0000.9960.6671.000
공휴일운행여부0.2660.3030.1490.9961.0000.6671.000
방학운행여부0.2460.2410.2270.6670.6671.0001.000
비고0.9910.3521.0001.0001.0001.0001.000

Missing values

2023-12-13T07:29:26.656430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T07:29:26.753859image/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

노선식별자순번출발시간평일운행여부토요일운행여부공휴일운행여부방학운행여부비고
0324000001106:001111<NA>
1324000001206:151111<NA>
2324000001306:301111<NA>
3324000001406:451111<NA>
4324000001507:001111<NA>
5324000001607:151111<NA>
6324000001707:301111<NA>
7324000001807:451111<NA>
8324000001908:001111<NA>
93240000011008:151111<NA>
노선식별자순번출발시간평일운행여부토요일운행여부공휴일운행여부방학운행여부비고
1093324000216309:501110<NA>
1094324000216410:201110<NA>
1095324000216512:501110<NA>
1096324000216613:201110<NA>
1097324000216715:501110<NA>
1098324000216816:201110<NA>
1099324000216918:501110<NA>
11003240002161019:201110<NA>
11013240002161120:301110<NA>
11023240002161222:101111<NA>