Overview

Dataset statistics

Number of variables19
Number of observations30
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.8 KiB
Average record size in memory165.4 B

Variable types

DateTime2
Text1
Categorical10
Numeric6

Dataset

Description샘플 데이터
Author펌프킨
URLhttps://bigdata-region.kr/#/dataset/d3b891d2-9dbb-4e38-bb56-9fe06b777cc7

Alerts

비고 has constant value ""Constant
생산_일시 has constant value ""Constant
기점 is highly overall correlated with 노선_번호 and 12 other fieldsHigh correlation
시도_코드 is highly overall correlated with 노선_번호 and 12 other fieldsHigh correlation
종점 is highly overall correlated with 노선_번호 and 12 other fieldsHigh correlation
시군구_명 is highly overall correlated with 노선_번호 and 12 other fieldsHigh correlation
노선_ID is highly overall correlated with 노선_번호 and 12 other fieldsHigh correlation
시군구_코드 is highly overall correlated with 노선_번호 and 12 other fieldsHigh correlation
시도_명 is highly overall correlated with 노선_번호 and 12 other fieldsHigh correlation
노선_번호 is highly overall correlated with 정류장_수 and 8 other fieldsHigh correlation
정류장_수 is highly overall correlated with 노선_번호 and 7 other fieldsHigh correlation
노선_거리 is highly overall correlated with 최단_거리 and 10 other fieldsHigh correlation
최단_거리 is highly overall correlated with 노선_거리 and 10 other fieldsHigh correlation
SOC사용량 is highly overall correlated with 노선_거리 and 10 other fieldsHigh correlation
전력_사용량 is highly overall correlated with 노선_거리 and 10 other fieldsHigh correlation
굴곡도 is highly overall correlated with 노선_번호 and 11 other fieldsHigh correlation
버스번호 has unique valuesUnique

Reproduction

Analysis started2024-03-13 11:55:11.007556
Analysis finished2024-03-13 11:55:16.674488
Duration5.67 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

운행_시작_일시
Date

Distinct24
Distinct (%)80.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
Minimum2023-10-01 04:30:00
Maximum2023-10-01 05:49:00
2024-03-13T20:55:16.726231image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:55:16.833236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)

버스번호
Text

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
2024-03-13T20:55:17.161956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length64
Median length64
Mean length64
Min length64

Characters and Unicode

Total characters1920
Distinct characters16
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique30 ?
Unique (%)100.0%

Sample

1st rowfd0db1761c206a922d4d4fa4ef9ad333da285d6e00e40d7091da4292ee18d007
2nd row32b901ff71ec2ab55cfdad89b12ab245b2de8fa940642941f4fbc8901c94377e
3rd row3e8d763036e2ba9d7b907f6cb8ce45a3c2f9d5e4ac7cd1aa240ab945d6b5d82f
4th row2556f1f28ebb092f29b3ea59ff28f399e7825b19d648b87980ac399f858fe308
5th row583338fe7ef08c7542e9a0addd23160c4115a6fed7ed59c157488263c3968347
ValueCountFrequency (%)
fd0db1761c206a922d4d4fa4ef9ad333da285d6e00e40d7091da4292ee18d007 1
 
3.3%
32b901ff71ec2ab55cfdad89b12ab245b2de8fa940642941f4fbc8901c94377e 1
 
3.3%
45c0f4cded62e0f8886086c8bc672f82d5e35a3f3f5eab55b1640614a1b032d7 1
 
3.3%
cdfaaa825235f97f2a9747c8dccc1dffcc07ab5bc50b481dbfe9eaed522a512b 1
 
3.3%
3bf6556f8fe5486859c710c7c29a757b35adbdb9f6ddd2aef64286bd6994a860 1
 
3.3%
633e40f03eeea0d33394a1d1da02a88b838e669d1cb6b8cbd0fff29e1cbdedb1 1
 
3.3%
03a926f07945722a542d41b545e24bebf53907cef807251cbf07bce7694c39a3 1
 
3.3%
99624bb55170fe020ac8e9ddeec4c2debc4322f85fa02e3e2fcba72d27ce98f3 1
 
3.3%
04ebeb0d8551f252a52337657861a696e0e16c10baf99da273ee07900cba7457 1
 
3.3%
db80cca3f15e218f3e37113da11312c3100d3216029b9042f080a8f49d010078 1
 
3.3%
Other values (20) 20
66.7%
2024-03-13T20:55:17.621077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
f 145
 
7.6%
3 137
 
7.1%
0 135
 
7.0%
4 128
 
6.7%
2 126
 
6.6%
d 122
 
6.4%
5 122
 
6.4%
8 120
 
6.2%
e 117
 
6.1%
9 116
 
6.0%
Other values (6) 652
34.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1195
62.2%
Lowercase Letter 725
37.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 137
11.5%
0 135
11.3%
4 128
10.7%
2 126
10.5%
5 122
10.2%
8 120
10.0%
9 116
9.7%
6 110
9.2%
1 105
8.8%
7 96
8.0%
Lowercase Letter
ValueCountFrequency (%)
f 145
20.0%
d 122
16.8%
e 117
16.1%
a 115
15.9%
b 113
15.6%
c 113
15.6%

Most occurring scripts

ValueCountFrequency (%)
Common 1195
62.2%
Latin 725
37.8%

Most frequent character per script

Common
ValueCountFrequency (%)
3 137
11.5%
0 135
11.3%
4 128
10.7%
2 126
10.5%
5 122
10.2%
8 120
10.0%
9 116
9.7%
6 110
9.2%
1 105
8.8%
7 96
8.0%
Latin
ValueCountFrequency (%)
f 145
20.0%
d 122
16.8%
e 117
16.1%
a 115
15.9%
b 113
15.6%
c 113
15.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1920
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
f 145
 
7.6%
3 137
 
7.1%
0 135
 
7.0%
4 128
 
6.7%
2 126
 
6.6%
d 122
 
6.4%
5 122
 
6.4%
8 120
 
6.2%
e 117
 
6.1%
9 116
 
6.0%
Other values (6) 652
34.0%

노선_ID
Categorical

HIGH CORRELATION 

Distinct11
Distinct (%)36.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
SOB100100286
8 
SOB100100346
6 
BSB5200107000
3 
CWB379001050
3 
CWB379000270
3 
Other values (6)
7 

Length

Max length13
Median length12
Mean length12.133333
Min length12

Unique

Unique5 ?
Unique (%)16.7%

Sample

1st rowSOB100100286
2nd rowSOB100100286
3rd rowSOB100100346
4th rowSOB100100286
5th rowSOB100100286

Common Values

ValueCountFrequency (%)
SOB100100286 8
26.7%
SOB100100346 6
20.0%
BSB5200107000 3
 
10.0%
CWB379001050 3
 
10.0%
CWB379000270 3
 
10.0%
SOB100100273 2
 
6.7%
CWB379001080 1
 
3.3%
BSB5200188000 1
 
3.3%
CWB379007070 1
 
3.3%
CWB379001220 1
 
3.3%

Length

2024-03-13T20:55:17.778079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
sob100100286 8
26.7%
sob100100346 6
20.0%
bsb5200107000 3
 
10.0%
cwb379001050 3
 
10.0%
cwb379000270 3
 
10.0%
sob100100273 2
 
6.7%
cwb379001080 1
 
3.3%
bsb5200188000 1
 
3.3%
cwb379007070 1
 
3.3%
cwb379001220 1
 
3.3%

노선_번호
Real number (ℝ)

HIGH CORRELATION 

Distinct11
Distinct (%)36.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3490.2667
Minimum27
Maximum7612
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2024-03-13T20:55:17.883412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum27
5-th percentile27
Q1107
median5616
Q35712
95-th percentile7612
Maximum7612
Range7585
Interquartile range (IQR)5605

Descriptive statistics

Standard deviation3253.608
Coefficient of variation (CV)0.93219468
Kurtosis-1.9243631
Mean3490.2667
Median Absolute Deviation (MAD)1996
Skewness0.0020402129
Sum104708
Variance10585965
MonotonicityNot monotonic
2024-03-13T20:55:18.006566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
5712 8
26.7%
7612 6
20.0%
107 3
 
10.0%
105 3
 
10.0%
27 3
 
10.0%
5616 2
 
6.7%
108 1
 
3.3%
188 1
 
3.3%
707 1
 
3.3%
122 1
 
3.3%
ValueCountFrequency (%)
27 3
 
10.0%
105 3
 
10.0%
107 3
 
10.0%
108 1
 
3.3%
122 1
 
3.3%
188 1
 
3.3%
266 1
 
3.3%
707 1
 
3.3%
5616 2
 
6.7%
5712 8
26.7%
ValueCountFrequency (%)
7612 6
20.0%
5712 8
26.7%
5616 2
 
6.7%
707 1
 
3.3%
266 1
 
3.3%
188 1
 
3.3%
122 1
 
3.3%
108 1
 
3.3%
107 3
 
10.0%
105 3
 
10.0%

기점
Categorical

HIGH CORRELATION 

Distinct8
Distinct (%)26.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
가산동기점(가상)
10 
홍연2교(기점가상)
6 
정관
4 
월영아파트종점
4 
가포고등학교
3 
Other values (3)
3 

Length

Max length10
Median length9
Mean length7.6
Min length2

Unique

Unique3 ?
Unique (%)10.0%

Sample

1st row가산동기점(가상)
2nd row가산동기점(가상)
3rd row홍연2교(기점가상)
4th row가산동기점(가상)
5th row가산동기점(가상)

Common Values

ValueCountFrequency (%)
가산동기점(가상) 10
33.3%
홍연2교(기점가상) 6
20.0%
정관 4
 
13.3%
월영아파트종점 4
 
13.3%
가포고등학교 3
 
10.0%
월영마린애시앙APT 1
 
3.3%
대방동종점 1
 
3.3%
성주사역 환승센터 1
 
3.3%

Length

2024-03-13T20:55:18.157843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T20:55:18.285526image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
가산동기점(가상 10
32.3%
홍연2교(기점가상 6
19.4%
정관 4
 
12.9%
월영아파트종점 4
 
12.9%
가포고등학교 3
 
9.7%
월영마린애시앙apt 1
 
3.2%
대방동종점 1
 
3.2%
성주사역 1
 
3.2%
환승센터 1
 
3.2%

종점
Categorical

HIGH CORRELATION 

Distinct8
Distinct (%)26.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
가산동종점(가상)
10 
홍연2교현대교통종점
6 
대방동종점
4 
센텀시티역
3 
북면종점
3 
Other values (3)
4 

Length

Max length10
Median length9
Mean length7.3666667
Min length3

Unique

Unique2 ?
Unique (%)6.7%

Sample

1st row가산동종점(가상)
2nd row가산동종점(가상)
3rd row홍연2교현대교통종점
4th row가산동종점(가상)
5th row가산동종점(가상)

Common Values

ValueCountFrequency (%)
가산동종점(가상) 10
33.3%
홍연2교현대교통종점 6
20.0%
대방동종점 4
 
13.3%
센텀시티역 3
 
10.0%
북면종점 3
 
10.0%
월영아파트종점 2
 
6.7%
안평역 1
 
3.3%
해운중학교종점 1
 
3.3%

Length

2024-03-13T20:55:18.458592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T20:55:18.583247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
가산동종점(가상 10
33.3%
홍연2교현대교통종점 6
20.0%
대방동종점 4
 
13.3%
센텀시티역 3
 
10.0%
북면종점 3
 
10.0%
월영아파트종점 2
 
6.7%
안평역 1
 
3.3%
해운중학교종점 1
 
3.3%

시도_코드
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)10.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
11
16 
48
10 
26
4 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row11
2nd row11
3rd row11
4th row11
5th row11

Common Values

ValueCountFrequency (%)
11 16
53.3%
48 10
33.3%
26 4
 
13.3%

Length

2024-03-13T20:55:18.712621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T20:55:18.802552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
11 16
53.3%
48 10
33.3%
26 4
 
13.3%

시군구_코드
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)13.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
545
10 
120
10 
410
6 
710
4 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row545
2nd row545
3rd row410
4th row545
5th row545

Common Values

ValueCountFrequency (%)
545 10
33.3%
120 10
33.3%
410 6
20.0%
710 4
 
13.3%

Length

2024-03-13T20:55:18.928838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T20:55:19.043805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
545 10
33.3%
120 10
33.3%
410 6
20.0%
710 4
 
13.3%

시도_명
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)10.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
서울특별시
16 
경상남도
10 
부산광역시
4 

Length

Max length5
Median length5
Mean length4.6666667
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
서울특별시 16
53.3%
경상남도 10
33.3%
부산광역시 4
 
13.3%

Length

2024-03-13T20:55:19.176461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T20:55:19.656083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
서울특별시 16
53.3%
경상남도 10
33.3%
부산광역시 4
 
13.3%

시군구_명
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)13.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
금천구
10 
창원시
10 
서대문구
6 
기장군
4 

Length

Max length4
Median length3
Mean length3.2
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row금천구
2nd row금천구
3rd row서대문구
4th row금천구
5th row금천구

Common Values

ValueCountFrequency (%)
금천구 10
33.3%
창원시 10
33.3%
서대문구 6
20.0%
기장군 4
 
13.3%

Length

2024-03-13T20:55:19.798360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T20:55:19.942120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
금천구 10
33.3%
창원시 10
33.3%
서대문구 6
20.0%
기장군 4
 
13.3%

정류장_수
Real number (ℝ)

HIGH CORRELATION 

Distinct10
Distinct (%)33.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean101.43333
Minimum47
Maximum159
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2024-03-13T20:55:20.058586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum47
5-th percentile47
Q190
median94.5
Q3132.5
95-th percentile158
Maximum159
Range112
Interquartile range (IQR)42.5

Descriptive statistics

Standard deviation38.907214
Coefficient of variation (CV)0.38357424
Kurtosis-1.0669442
Mean101.43333
Median Absolute Deviation (MAD)31
Skewness0.045301917
Sum3043
Variance1513.7713
MonotonicityNot monotonic
2024-03-13T20:55:20.186742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
90 8
26.7%
47 6
20.0%
108 3
 
10.0%
113 3
 
10.0%
152 3
 
10.0%
158 3
 
10.0%
159 1
 
3.3%
99 1
 
3.3%
139 1
 
3.3%
51 1
 
3.3%
ValueCountFrequency (%)
47 6
20.0%
51 1
 
3.3%
90 8
26.7%
99 1
 
3.3%
108 3
 
10.0%
113 3
 
10.0%
139 1
 
3.3%
152 3
 
10.0%
158 3
 
10.0%
159 1
 
3.3%
ValueCountFrequency (%)
159 1
 
3.3%
158 3
 
10.0%
152 3
 
10.0%
139 1
 
3.3%
113 3
 
10.0%
108 3
 
10.0%
99 1
 
3.3%
90 8
26.7%
51 1
 
3.3%
47 6
20.0%

노선_거리
Real number (ℝ)

HIGH CORRELATION 

Distinct10
Distinct (%)33.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean47.033333
Minimum11
Maximum75
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2024-03-13T20:55:20.294585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum11
5-th percentile11
Q136
median50
Q371.75
95-th percentile75
Maximum75
Range64
Interquartile range (IQR)35.75

Descriptive statistics

Standard deviation23.364405
Coefficient of variation (CV)0.49676268
Kurtosis-1.0543873
Mean47.033333
Median Absolute Deviation (MAD)19.5
Skewness-0.38388618
Sum1411
Variance545.8954
MonotonicityNot monotonic
2024-03-13T20:55:20.399637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
75 8
26.7%
11 6
20.0%
44 4
13.3%
52 3
 
10.0%
56 3
 
10.0%
36 2
 
6.7%
62 1
 
3.3%
47 1
 
3.3%
48 1
 
3.3%
16 1
 
3.3%
ValueCountFrequency (%)
11 6
20.0%
16 1
 
3.3%
36 2
 
6.7%
44 4
13.3%
47 1
 
3.3%
48 1
 
3.3%
52 3
 
10.0%
56 3
 
10.0%
62 1
 
3.3%
75 8
26.7%
ValueCountFrequency (%)
75 8
26.7%
62 1
 
3.3%
56 3
 
10.0%
52 3
 
10.0%
48 1
 
3.3%
47 1
 
3.3%
44 4
13.3%
36 2
 
6.7%
16 1
 
3.3%
11 6
20.0%

최단_거리
Real number (ℝ)

HIGH CORRELATION 

Distinct9
Distinct (%)30.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean26.7
Minimum6
Maximum42
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2024-03-13T20:55:20.503935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum6
5-th percentile6
Q119
median30
Q339.5
95-th percentile42
Maximum42
Range36
Interquartile range (IQR)20.5

Descriptive statistics

Standard deviation13.009678
Coefficient of variation (CV)0.48725386
Kurtosis-1.0016396
Mean26.7
Median Absolute Deviation (MAD)11.5
Skewness-0.44801086
Sum801
Variance169.25172
MonotonicityNot monotonic
2024-03-13T20:55:20.603009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
42 8
26.7%
6 6
20.0%
25 4
13.3%
32 4
13.3%
31 3
 
10.0%
19 2
 
6.7%
27 1
 
3.3%
29 1
 
3.3%
14 1
 
3.3%
ValueCountFrequency (%)
6 6
20.0%
14 1
 
3.3%
19 2
 
6.7%
25 4
13.3%
27 1
 
3.3%
29 1
 
3.3%
31 3
 
10.0%
32 4
13.3%
42 8
26.7%
ValueCountFrequency (%)
42 8
26.7%
32 4
13.3%
31 3
 
10.0%
29 1
 
3.3%
27 1
 
3.3%
25 4
13.3%
19 2
 
6.7%
14 1
 
3.3%
6 6
20.0%

굴곡도
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)13.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
2
18 
3
10 
5
 
1
1
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique2 ?
Unique (%)6.7%

Sample

1st row3
2nd row3
3rd row2
4th row3
5th row3

Common Values

ValueCountFrequency (%)
2 18
60.0%
3 10
33.3%
5 1
 
3.3%
1 1
 
3.3%

Length

2024-03-13T20:55:20.730376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T20:55:20.837175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 18
60.0%
3 10
33.3%
5 1
 
3.3%
1 1
 
3.3%

운행_종료_일시
Date

Distinct28
Distinct (%)93.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
Minimum2023-10-01 06:05:00
Maximum2023-10-01 23:59:00
2024-03-13T20:55:20.938455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:55:21.048522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=28)

SOC사용량
Real number (ℝ)

HIGH CORRELATION 

Distinct14
Distinct (%)46.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean29.666667
Minimum7
Maximum47
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2024-03-13T20:55:21.175877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum7
5-th percentile7
Q123.25
median31.5
Q344.25
95-th percentile47
Maximum47
Range40
Interquartile range (IQR)21

Descriptive statistics

Standard deviation14.302962
Coefficient of variation (CV)0.4821223
Kurtosis-1.0099016
Mean29.666667
Median Absolute Deviation (MAD)11.5
Skewness-0.42241394
Sum890
Variance204.57471
MonotonicityNot monotonic
2024-03-13T20:55:21.296587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
47 5
16.7%
7 4
13.3%
46 3
10.0%
28 3
10.0%
35 3
10.0%
8 2
 
6.7%
29 2
 
6.7%
33 2
 
6.7%
24 1
 
3.3%
39 1
 
3.3%
Other values (4) 4
13.3%
ValueCountFrequency (%)
7 4
13.3%
8 2
6.7%
11 1
 
3.3%
23 1
 
3.3%
24 1
 
3.3%
28 3
10.0%
29 2
6.7%
31 1
 
3.3%
32 1
 
3.3%
33 2
6.7%
ValueCountFrequency (%)
47 5
16.7%
46 3
10.0%
39 1
 
3.3%
35 3
10.0%
33 2
 
6.7%
32 1
 
3.3%
31 1
 
3.3%
29 2
 
6.7%
28 3
10.0%
24 1
 
3.3%

전력_사용량
Real number (ℝ)

HIGH CORRELATION 

Distinct14
Distinct (%)46.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean103.13333
Minimum23
Maximum165
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2024-03-13T20:55:21.462122image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum23
5-th percentile23
Q179
median110
Q3157.25
95-th percentile165
Maximum165
Range142
Interquartile range (IQR)78.25

Descriptive statistics

Standard deviation51.643161
Coefficient of variation (CV)0.5007417
Kurtosis-1.0527278
Mean103.13333
Median Absolute Deviation (MAD)42.5
Skewness-0.40061445
Sum3094
Variance2667.0161
MonotonicityNot monotonic
2024-03-13T20:55:21.605040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
23 5
16.7%
164 4
13.3%
165 4
13.3%
96 3
10.0%
114 3
10.0%
79 2
 
6.7%
124 2
 
6.7%
98 1
 
3.3%
137 1
 
3.3%
125 1
 
3.3%
Other values (4) 4
13.3%
ValueCountFrequency (%)
23 5
16.7%
24 1
 
3.3%
35 1
 
3.3%
79 2
 
6.7%
96 3
10.0%
98 1
 
3.3%
102 1
 
3.3%
106 1
 
3.3%
114 3
10.0%
124 2
 
6.7%
ValueCountFrequency (%)
165 4
13.3%
164 4
13.3%
137 1
 
3.3%
125 1
 
3.3%
124 2
6.7%
114 3
10.0%
106 1
 
3.3%
102 1
 
3.3%
98 1
 
3.3%
96 3
10.0%

비고
Categorical

CONSTANT 

Distinct1
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
2024-01-12 전기버스 노선 굴곡도 대비 에너지 사용량
30 

Length

Max length33
Median length33
Mean length33
Min length33

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2024-01-12 전기버스 노선 굴곡도 대비 에너지 사용량
2nd row2024-01-12 전기버스 노선 굴곡도 대비 에너지 사용량
3rd row2024-01-12 전기버스 노선 굴곡도 대비 에너지 사용량
4th row2024-01-12 전기버스 노선 굴곡도 대비 에너지 사용량
5th row2024-01-12 전기버스 노선 굴곡도 대비 에너지 사용량

Common Values

ValueCountFrequency (%)
2024-01-12 전기버스 노선 굴곡도 대비 에너지 사용량 30
100.0%

Length

2024-03-13T20:55:21.731278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T20:55:21.841190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2024-01-12 30
14.3%
전기버스 30
14.3%
노선 30
14.3%
굴곡도 30
14.3%
대비 30
14.3%
에너지 30
14.3%
사용량 30
14.3%

생산_일시
Categorical

CONSTANT 

Distinct1
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
2024-01-12 14:41:15
30 

Length

Max length19
Median length19
Mean length19
Min length19

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2024-01-12 14:41:15
2nd row2024-01-12 14:41:15
3rd row2024-01-12 14:41:15
4th row2024-01-12 14:41:15
5th row2024-01-12 14:41:15

Common Values

ValueCountFrequency (%)
2024-01-12 14:41:15 30
100.0%

Length

2024-03-13T20:55:21.958513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T20:55:22.060215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2024-01-12 30
50.0%
14:41:15 30
50.0%

Interactions

2024-03-13T20:55:15.684297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:55:11.917874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:55:12.842285image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:55:13.443373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:55:14.055055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:55:14.986979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:55:15.788781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:55:12.002823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:55:12.957553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:55:13.529730image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:55:14.196344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:55:15.122727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:55:15.882923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:55:12.097144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:55:13.043735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:55:13.641886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:55:14.346699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:55:15.237684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:55:15.968149image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:55:12.199602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:55:13.142758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:55:13.757918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:55:14.522275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:55:15.335781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:55:16.060365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:55:12.298419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:55:13.262772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:55:13.851887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:55:14.675911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:55:15.430832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:55:16.165963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:55:12.397574image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:55:13.354351image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:55:13.951923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:55:14.843829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:55:15.558251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-13T20:55:22.143979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
운행_시작_일시버스번호노선_ID노선_번호기점종점시도_코드시군구_코드시도_명시군구_명정류장_수노선_거리최단_거리굴곡도운행_종료_일시SOC사용량전력_사용량
운행_시작_일시1.0001.0000.0000.9600.2970.5920.0000.6040.0000.6040.9350.8220.0000.0000.9920.6530.847
버스번호1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
노선_ID0.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0000.0001.0001.000
노선_번호0.9601.0001.0001.0001.0001.0000.9321.0000.9321.0000.9870.9971.0000.6591.0001.0000.921
기점0.2971.0001.0001.0001.0000.9911.0001.0001.0001.0000.9480.8870.8750.8740.9170.8270.878
종점0.5921.0001.0001.0000.9911.0001.0001.0001.0001.0000.9210.9000.8990.9920.0000.9080.927
시도_코드0.0001.0001.0000.9321.0001.0001.0001.0001.0001.0000.9110.9230.8040.5131.0000.8710.809
시군구_코드0.6041.0001.0001.0001.0001.0001.0001.0001.0001.0000.8710.8910.8930.9051.0000.9280.883
시도_명0.0001.0001.0000.9321.0001.0001.0001.0001.0001.0000.9110.9230.8040.5131.0000.8710.809
시군구_명0.6041.0001.0001.0001.0001.0001.0001.0001.0001.0000.8710.8910.8930.9051.0000.9280.883
정류장_수0.9351.0001.0000.9870.9480.9210.9110.8710.9110.8711.0000.9700.8700.6090.9460.8580.861
노선_거리0.8221.0001.0000.9970.8870.9000.9230.8910.9230.8910.9701.0000.9500.7320.3770.9241.000
최단_거리0.0001.0001.0001.0000.8750.8990.8040.8930.8040.8930.8700.9501.0000.8770.0000.9970.990
굴곡도0.0001.0001.0000.6590.8740.9920.5130.9050.5130.9050.6090.7320.8771.0000.0001.0000.859
운행_종료_일시0.9921.0000.0001.0000.9170.0001.0001.0001.0001.0000.9460.3770.0000.0001.0000.0000.666
SOC사용량0.6531.0001.0001.0000.8270.9080.8710.9280.8710.9280.8580.9240.9971.0000.0001.0000.992
전력_사용량0.8471.0001.0000.9210.8780.9270.8090.8830.8090.8830.8611.0000.9900.8590.6660.9921.000
2024-03-13T20:55:22.318257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
굴곡도기점시도_코드종점시군구_명노선_ID시군구_코드시도_명
굴곡도1.0000.5070.5010.8060.5940.8550.5940.501
기점0.5071.0000.9030.8400.9200.9290.9200.903
시도_코드0.5010.9031.0000.9030.9810.8390.9811.000
종점0.8060.8400.9031.0000.9200.9290.9200.903
시군구_명0.5940.9200.9810.9201.0000.8551.0000.981
노선_ID0.8550.9290.8390.9290.8551.0000.8550.839
시군구_코드0.5940.9200.9810.9201.0000.8551.0000.981
시도_명0.5010.9031.0000.9030.9810.8390.9811.000
2024-03-13T20:55:22.443110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
노선_번호정류장_수노선_거리최단_거리SOC사용량전력_사용량노선_ID기점종점시도_코드시군구_코드시도_명시군구_명굴곡도
노선_번호1.000-0.908-0.247-0.240-0.244-0.2430.8390.9030.9030.6800.9810.6800.9810.672
정류장_수-0.9081.0000.3470.3320.3470.3460.8900.8340.7810.6020.7120.6020.7120.416
노선_거리-0.2470.3471.0000.9850.9890.9900.8900.7160.7400.6250.7380.6250.7380.541
최단_거리-0.2400.3320.9851.0000.9740.9750.9090.6920.7380.6970.7940.6970.7940.768
SOC사용량-0.2440.3470.9890.9741.0000.9760.7850.5510.6720.7040.7770.7040.7770.740
전력_사용량-0.2430.3460.9900.9750.9761.0000.9090.6980.7970.7040.7770.7040.7770.740
노선_ID0.8390.8900.8900.9090.7850.9091.0000.9290.9290.8390.8550.8390.8550.855
기점0.9030.8340.7160.6920.5510.6980.9291.0000.8400.9030.9200.9030.9200.507
종점0.9030.7810.7400.7380.6720.7970.9290.8401.0000.9030.9200.9030.9200.806
시도_코드0.6800.6020.6250.6970.7040.7040.8390.9030.9031.0000.9811.0000.9810.501
시군구_코드0.9810.7120.7380.7940.7770.7770.8550.9200.9200.9811.0000.9811.0000.594
시도_명0.6800.6020.6250.6970.7040.7040.8390.9030.9031.0000.9811.0000.9810.501
시군구_명0.9810.7120.7380.7940.7770.7770.8550.9200.9200.9811.0000.9811.0000.594
굴곡도0.6720.4160.5410.7680.7400.7400.8550.5070.8060.5010.5940.5010.5941.000

Missing values

2024-03-13T20:55:16.321420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-13T20:55:16.582762image/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

운행_시작_일시버스번호노선_ID노선_번호기점종점시도_코드시군구_코드시도_명시군구_명정류장_수노선_거리최단_거리굴곡도운행_종료_일시SOC사용량전력_사용량비고생산_일시
02023-10-01 04:30:00fd0db1761c206a922d4d4fa4ef9ad333da285d6e00e40d7091da4292ee18d007SOB1001002865712가산동기점(가상)가산동종점(가상)11545서울특별시금천구90754232023-10-01 07:18:00471642024-01-12 전기버스 노선 굴곡도 대비 에너지 사용량2024-01-12 14:41:15
12023-10-01 04:38:0032b901ff71ec2ab55cfdad89b12ab245b2de8fa940642941f4fbc8901c94377eSOB1001002865712가산동기점(가상)가산동종점(가상)11545서울특별시금천구90754232023-10-01 07:26:00461652024-01-12 전기버스 노선 굴곡도 대비 에너지 사용량2024-01-12 14:41:15
22023-10-01 04:47:003e8d763036e2ba9d7b907f6cb8ce45a3c2f9d5e4ac7cd1aa240ab945d6b5d82fSOB1001003467612홍연2교(기점가상)홍연2교현대교통종점11410서울특별시서대문구4711622023-10-01 06:05:008232024-01-12 전기버스 노선 굴곡도 대비 에너지 사용량2024-01-12 14:41:15
32023-10-01 04:49:002556f1f28ebb092f29b3ea59ff28f399e7825b19d648b87980ac399f858fe308SOB1001002865712가산동기점(가상)가산동종점(가상)11545서울특별시금천구90754232023-10-01 07:35:00471652024-01-12 전기버스 노선 굴곡도 대비 에너지 사용량2024-01-12 14:41:15
42023-10-01 04:58:00583338fe7ef08c7542e9a0addd23160c4115a6fed7ed59c157488263c3968347SOB1001002865712가산동기점(가상)가산동종점(가상)11545서울특별시금천구90754232023-10-01 07:45:00471652024-01-12 전기버스 노선 굴곡도 대비 에너지 사용량2024-01-12 14:41:15
52023-10-01 05:00:008ce4f1661725aa8e5c739338d7665cb73644ce3cf230342a149e38426dbc480dBSB5200107000107정관센텀시티역26710부산광역시기장군108442522023-10-01 11:10:0028962024-01-12 전기버스 노선 굴곡도 대비 에너지 사용량2024-01-12 14:41:15
62023-10-01 05:00:00e5f83e089328cc6611720bf6862839db7aa9f3c9f919c4b97440bdf00ec33fd3CWB379001080108월영마린애시앙APT대방동종점48120경상남도창원시113442522023-10-01 14:45:0029982024-01-12 전기버스 노선 굴곡도 대비 에너지 사용량2024-01-12 14:41:15
72023-10-01 05:01:0060df9353b4ebf5e1f31f4d3231f5d2d9ad8c02c897e03017e9e423da205a0561SOB1001003467612홍연2교(기점가상)홍연2교현대교통종점11410서울특별시서대문구4711622023-10-01 06:14:008232024-01-12 전기버스 노선 굴곡도 대비 에너지 사용량2024-01-12 14:41:15
82023-10-01 05:08:00eafe60183883c1a456f32aff674895aa8efac196837d6f4c64658741d06ffca7CWB379001050105월영아파트종점대방동종점48120경상남도창원시152523222023-10-01 23:59:00331142024-01-12 전기버스 노선 굴곡도 대비 에너지 사용량2024-01-12 14:41:15
92023-10-01 05:08:0019d8dc179bc42cb5ecab0de0525fc36a271f7a90b56946146b3d3ed852467441SOB1001002865712가산동기점(가상)가산동종점(가상)11545서울특별시금천구90754232023-10-01 07:56:00471642024-01-12 전기버스 노선 굴곡도 대비 에너지 사용량2024-01-12 14:41:15
운행_시작_일시버스번호노선_ID노선_번호기점종점시도_코드시군구_코드시도_명시군구_명정류장_수노선_거리최단_거리굴곡도운행_종료_일시SOC사용량전력_사용량비고생산_일시
202023-10-01 05:30:0054392c1d08926cd2f6a7ec9e4ab5989ce4b9b50bf23493fe2660f0d83bd2bf94CWB379001050105월영아파트종점대방동종점48120경상남도창원시152523222023-10-01 13:46:00331142024-01-12 전기버스 노선 굴곡도 대비 에너지 사용량2024-01-12 14:41:15
212023-10-01 05:30:00db80cca3f15e218f3e37113da11312c3100d3216029b9042f080a8f49d010078BSB5200107000107정관센텀시티역26710부산광역시기장군108442522023-10-01 11:40:0028962024-01-12 전기버스 노선 굴곡도 대비 에너지 사용량2024-01-12 14:41:15
222023-10-01 05:33:0004ebeb0d8551f252a52337657861a696e0e16c10baf99da273ee07900cba7457CWB379001220122성주사역 환승센터월영아파트종점48120경상남도창원시139482922023-10-01 12:45:00311062024-01-12 전기버스 노선 굴곡도 대비 에너지 사용량2024-01-12 14:41:15
232023-10-01 05:35:0099624bb55170fe020ac8e9ddeec4c2debc4322f85fa02e3e2fcba72d27ce98f3SOB1001002865712가산동기점(가상)가산동종점(가상)11545서울특별시금천구90754232023-10-01 08:22:00461652024-01-12 전기버스 노선 굴곡도 대비 에너지 사용량2024-01-12 14:41:15
242023-10-01 05:37:0003a926f07945722a542d41b545e24bebf53907cef807251cbf07bce7694c39a3SOB1001003467612홍연2교(기점가상)홍연2교현대교통종점11410서울특별시서대문구4711622023-10-01 06:54:007232024-01-12 전기버스 노선 굴곡도 대비 에너지 사용량2024-01-12 14:41:15
252023-10-01 05:41:00633e40f03eeea0d33394a1d1da02a88b838e669d1cb6b8cbd0fff29e1cbdedb1SOB1001002735616가산동기점(가상)가산동종점(가상)11545서울특별시금천구113361932023-10-01 08:47:0023792024-01-12 전기버스 노선 굴곡도 대비 에너지 사용량2024-01-12 14:41:15
262023-10-01 05:45:003bf6556f8fe5486859c710c7c29a757b35adbdb9f6ddd2aef64286bd6994a860SOB1001003467612홍연2교(기점가상)홍연2교현대교통종점11410서울특별시서대문구4711622023-10-01 07:06:007232024-01-12 전기버스 노선 굴곡도 대비 에너지 사용량2024-01-12 14:41:15
272023-10-01 05:49:00cdfaaa825235f97f2a9747c8dccc1dffcc07ab5bc50b481dbfe9eaed522a512bCWB37900027027가포고등학교북면종점48120경상남도창원시158563122023-10-01 23:59:00351242024-01-12 전기버스 노선 굴곡도 대비 에너지 사용량2024-01-12 14:41:15
282023-10-01 05:49:0045c0f4cded62e0f8886086c8bc672f82d5e35a3f3f5eab55b1640614a1b032d7CWB37900027027가포고등학교북면종점48120경상남도창원시158563122023-10-01 15:06:00351242024-01-12 전기버스 노선 굴곡도 대비 에너지 사용량2024-01-12 14:41:15
292023-10-01 05:49:0091fdc193d0efee6286217b39b3424fffa0e317f9c87f0407dfef85c6651df54cCWB379002660266월영아파트종점월영아파트종점48120경상남도창원시51161412023-10-01 23:59:0011352024-01-12 전기버스 노선 굴곡도 대비 에너지 사용량2024-01-12 14:41:15