Overview

Dataset statistics

Number of variables15
Number of observations30
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.8 KiB
Average record size in memory131.4 B

Variable types

Categorical4
Text1
DateTime4
Numeric6

Dataset

Description샘플 데이터
Author펌프킨
URLhttps://bigdata-region.kr/#/dataset/3fcc81c0-50d1-4f33-983a-921d7511d36d

Alerts

충전소ID has constant value ""Constant
충전기ID has constant value ""Constant
비고 has constant value ""Constant
생산일시 has constant value ""Constant
시작SOC is highly overall correlated with 전력사용요금High correlation
전력사용요금 is highly overall correlated with 시작SOCHigh correlation
전력사용요금경부하 is highly overall correlated with 전력사용요금중부하 and 1 other fieldsHigh correlation
전력사용요금중부하 is highly overall correlated with 전력사용요금경부하High correlation
전력사용요금최대부하 is highly overall correlated with 전력사용요금경부하High correlation
소요시간 has unique valuesUnique
시작일시 has unique valuesUnique
종료일시 has unique valuesUnique
전력사용요금경부하 has 9 (30.0%) zerosZeros
전력사용요금중부하 has 25 (83.3%) zerosZeros
전력사용요금최대부하 has 25 (83.3%) zerosZeros

Reproduction

Analysis started2024-03-13 11:55:30.979907
Analysis finished2024-03-13 11:55:36.127589
Duration5.15 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

충전소ID
Categorical

CONSTANT 

Distinct1
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
KRPPKCP1135
30 

Length

Max length11
Median length11
Mean length11
Min length11

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowKRPPKCP1135
2nd rowKRPPKCP1135
3rd rowKRPPKCP1135
4th rowKRPPKCP1135
5th rowKRPPKCP1135

Common Values

ValueCountFrequency (%)
KRPPKCP1135 30
100.0%

Length

2024-03-13T20:55:36.211959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T20:55:36.323098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
krppkcp1135 30
100.0%

충전기ID
Categorical

CONSTANT 

Distinct1
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
73
30 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row73
2nd row73
3rd row73
4th row73
5th row73

Common Values

ValueCountFrequency (%)
73 30
100.0%

Length

2024-03-13T20:55:36.416648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T20:55:36.514703image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
73 30
100.0%

충전건
Categorical

Distinct2
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
A
20 
B
10 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowA
2nd rowA
3rd rowA
4th rowA
5th rowB

Common Values

ValueCountFrequency (%)
A 20
66.7%
B 10
33.3%

Length

2024-03-13T20:55:36.616630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T20:55:36.720186image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
a 20
66.7%
b 10
33.3%

차량번호
Text

Distinct24
Distinct (%)80.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
2024-03-13T20:55:36.977791image/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

Unique20 ?
Unique (%)66.7%

Sample

1st row7e154d0283ef5fade5495b3a9d5353012559ec3e0abf28434b5a865534f9cdc8
2nd row53c1548663f4fc051285eeb89ad4feb2ca80a2e6ba1ebeefcfb003da416f3d38
3rd row94753088f3fc3725526a93bf55c6e2cfa156b4c142dc1a4802aa4a30b8c719bc
4th rowfd6ec29cd4ffb29c6a233026e3eb9d4d8651dff6c881ba74442e7505ea620e2d
5th rowb8dc97c8a6f42ef8bbc2c2c1ec3ac3aa20b64d961de742d6b2d6d7bd66842c66
ValueCountFrequency (%)
7e154d0283ef5fade5495b3a9d5353012559ec3e0abf28434b5a865534f9cdc8 3
 
10.0%
46da21342dc6e5feee68fe29f2e5dac6824dbf6b4993d4fac6565d28ec4067a7 3
 
10.0%
94753088f3fc3725526a93bf55c6e2cfa156b4c142dc1a4802aa4a30b8c719bc 2
 
6.7%
995591caf55a736cc8d76d3f5293ff8fdc0fe0abc2b51761781e87ba0a0ad03d 2
 
6.7%
9df3d59fae72aa7e69722770b1bd1301c5a7f334c34967b3ad2f9416f13dfdf5 1
 
3.3%
6f72a25e419335c67ccdd4126d3c4fab26bd004ab3282897d12f48503c95e28c 1
 
3.3%
930fb55314203e0141c430e52d1f08c284d96cc283541cd56e04c483a3ec9def 1
 
3.3%
d0e808b40576dbf05d8d63b9aaad002c231c8a04c502d420dd24131542182f6e 1
 
3.3%
1263fb9bff0bb5eefe77bcacea5d2eaca4169b04bec1e55b17a5c9c0f0a78f0a 1
 
3.3%
39e6a7572f9aff6aa56c2f79b4e88f69675bf4eb1b183d7f93c342e6b97c47b4 1
 
3.3%
Other values (14) 14
46.7%
2024-03-13T20:55:37.356824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 152
 
7.9%
c 143
 
7.4%
f 142
 
7.4%
3 136
 
7.1%
d 131
 
6.8%
e 125
 
6.5%
6 125
 
6.5%
4 119
 
6.2%
2 118
 
6.1%
a 118
 
6.1%
Other values (6) 611
31.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1155
60.2%
Lowercase Letter 765
39.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 152
13.2%
3 136
11.8%
6 125
10.8%
4 119
10.3%
2 118
10.2%
1 109
9.4%
0 102
8.8%
9 100
8.7%
8 99
8.6%
7 95
8.2%
Lowercase Letter
ValueCountFrequency (%)
c 143
18.7%
f 142
18.6%
d 131
17.1%
e 125
16.3%
a 118
15.4%
b 106
13.9%

Most occurring scripts

ValueCountFrequency (%)
Common 1155
60.2%
Latin 765
39.8%

Most frequent character per script

Common
ValueCountFrequency (%)
5 152
13.2%
3 136
11.8%
6 125
10.8%
4 119
10.3%
2 118
10.2%
1 109
9.4%
0 102
8.8%
9 100
8.7%
8 99
8.6%
7 95
8.2%
Latin
ValueCountFrequency (%)
c 143
18.7%
f 142
18.6%
d 131
17.1%
e 125
16.3%
a 118
15.4%
b 106
13.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1920
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 152
 
7.9%
c 143
 
7.4%
f 142
 
7.4%
3 136
 
7.1%
d 131
 
6.8%
e 125
 
6.5%
6 125
 
6.5%
4 119
 
6.2%
2 118
 
6.1%
a 118
 
6.1%
Other values (6) 611
31.8%

소요시간
Date

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
Minimum2024-03-13 00:13:49
Maximum2024-03-13 01:13:23
2024-03-13T20:55:37.491439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:55:37.611705image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)

시작일시
Date

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
Minimum2023-10-01 03:35:13
Maximum2023-10-14 18:03:38
2024-03-13T20:55:37.727592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:55:37.841131image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)

종료일시
Date

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
Minimum2023-10-01 04:14:39
Maximum2023-10-14 18:40:55
2024-03-13T20:55:37.966290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:55:38.104897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)

시작SOC
Real number (ℝ)

HIGH CORRELATION 

Distinct24
Distinct (%)80.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean45.666667
Minimum17
Maximum73
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2024-03-13T20:55:38.237331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum17
5-th percentile18.9
Q132.75
median43.5
Q358.75
95-th percentile69.65
Maximum73
Range56
Interquartile range (IQR)26

Descriptive statistics

Standard deviation16.161541
Coefficient of variation (CV)0.35390235
Kurtosis-1.0469052
Mean45.666667
Median Absolute Deviation (MAD)12.5
Skewness-0.029829422
Sum1370
Variance261.1954
MonotonicityNot monotonic
2024-03-13T20:55:38.375243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
32 2
 
6.7%
31 2
 
6.7%
35 2
 
6.7%
56 2
 
6.7%
49 2
 
6.7%
36 2
 
6.7%
44 1
 
3.3%
30 1
 
3.3%
59 1
 
3.3%
43 1
 
3.3%
Other values (14) 14
46.7%
ValueCountFrequency (%)
17 1
3.3%
18 1
3.3%
20 1
3.3%
30 1
3.3%
31 2
6.7%
32 2
6.7%
35 2
6.7%
36 2
6.7%
40 1
3.3%
42 1
3.3%
ValueCountFrequency (%)
73 1
3.3%
71 1
3.3%
68 1
3.3%
66 1
3.3%
65 1
3.3%
61 1
3.3%
60 1
3.3%
59 1
3.3%
58 1
3.3%
57 1
3.3%

종료SOC
Real number (ℝ)

Distinct12
Distinct (%)40.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean89.166667
Minimum74
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2024-03-13T20:55:38.497590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum74
5-th percentile79.45
Q186
median90
Q390
95-th percentile100
Maximum100
Range26
Interquartile range (IQR)4

Descriptive statistics

Standard deviation6.4705345
Coefficient of variation (CV)0.072566742
Kurtosis0.25169677
Mean89.166667
Median Absolute Deviation (MAD)2
Skewness-0.024032859
Sum2675
Variance41.867816
MonotonicityNot monotonic
2024-03-13T20:55:38.601805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
90 13
43.3%
100 5
 
16.7%
84 2
 
6.7%
86 2
 
6.7%
82 1
 
3.3%
74 1
 
3.3%
89 1
 
3.3%
88 1
 
3.3%
80 1
 
3.3%
92 1
 
3.3%
Other values (2) 2
 
6.7%
ValueCountFrequency (%)
74 1
 
3.3%
79 1
 
3.3%
80 1
 
3.3%
81 1
 
3.3%
82 1
 
3.3%
84 2
 
6.7%
86 2
 
6.7%
88 1
 
3.3%
89 1
 
3.3%
90 13
43.3%
ValueCountFrequency (%)
100 5
 
16.7%
92 1
 
3.3%
90 13
43.3%
89 1
 
3.3%
88 1
 
3.3%
86 2
 
6.7%
84 2
 
6.7%
82 1
 
3.3%
81 1
 
3.3%
80 1
 
3.3%

전력사용요금
Real number (ℝ)

HIGH CORRELATION 

Distinct29
Distinct (%)96.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2627.7
Minimum901
Maximum4455
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2024-03-13T20:55:38.723493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum901
5-th percentile1090.55
Q11885.5
median2830.5
Q33346.75
95-th percentile3887.1
Maximum4455
Range3554
Interquartile range (IQR)1461.25

Descriptive statistics

Standard deviation988.37942
Coefficient of variation (CV)0.37613861
Kurtosis-1.0811677
Mean2627.7
Median Absolute Deviation (MAD)739
Skewness-0.18330958
Sum78831
Variance976893.87
MonotonicityNot monotonic
2024-03-13T20:55:38.875127image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)
ValueCountFrequency (%)
2273 2
 
6.7%
3256 1
 
3.3%
3314 1
 
3.3%
3079 1
 
3.3%
2904 1
 
3.3%
3624 1
 
3.3%
1464 1
 
3.3%
3467 1
 
3.3%
3347 1
 
3.3%
3346 1
 
3.3%
Other values (19) 19
63.3%
ValueCountFrequency (%)
901 1
3.3%
992 1
3.3%
1211 1
3.3%
1267 1
3.3%
1446 1
3.3%
1464 1
3.3%
1566 1
3.3%
1858 1
3.3%
1968 1
3.3%
1998 1
3.3%
ValueCountFrequency (%)
4455 1
3.3%
3888 1
3.3%
3886 1
3.3%
3841 1
3.3%
3624 1
3.3%
3485 1
3.3%
3467 1
3.3%
3347 1
3.3%
3346 1
3.3%
3314 1
3.3%

전력사용요금경부하
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct22
Distinct (%)73.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1793
Minimum0
Maximum4455
Zeros9
Zeros (%)30.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2024-03-13T20:55:38.996944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median1912
Q33072
95-th percentile3864.75
Maximum4455
Range4455
Interquartile range (IQR)3072

Descriptive statistics

Standard deviation1470.8492
Coefficient of variation (CV)0.82032863
Kurtosis-1.3900336
Mean1793
Median Absolute Deviation (MAD)1372.5
Skewness0.06872955
Sum53790
Variance2163397.4
MonotonicityNot monotonic
2024-03-13T20:55:39.110841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
0 9
30.0%
3255 1
 
3.3%
1565 1
 
3.3%
3079 1
 
3.3%
2904 1
 
3.3%
3466 1
 
3.3%
2273 1
 
3.3%
992 1
 
3.3%
3885 1
 
3.3%
3314 1
 
3.3%
Other values (12) 12
40.0%
ValueCountFrequency (%)
0 9
30.0%
901 1
 
3.3%
992 1
 
3.3%
1210 1
 
3.3%
1266 1
 
3.3%
1565 1
 
3.3%
1857 1
 
3.3%
1967 1
 
3.3%
1997 1
 
3.3%
2272 1
 
3.3%
ValueCountFrequency (%)
4455 1
3.3%
3885 1
3.3%
3840 1
3.3%
3484 1
3.3%
3466 1
3.3%
3314 1
3.3%
3255 1
3.3%
3079 1
3.3%
3051 1
3.3%
2904 1
3.3%

전력사용요금중부하
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct6
Distinct (%)20.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean457.56667
Minimum0
Maximum3887
Zeros25
Zeros (%)83.3%
Negative0
Negative (%)0.0%
Memory size402.0 B
2024-03-13T20:55:39.218538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile3241.6
Maximum3887
Range3887
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1111.8257
Coefficient of variation (CV)2.429866
Kurtosis4.0831813
Mean457.56667
Median Absolute Deviation (MAD)0
Skewness2.3135357
Sum13727
Variance1236156.4
MonotonicityNot monotonic
2024-03-13T20:55:39.324440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 25
83.3%
3887 1
 
3.3%
2146 1
 
3.3%
1234 1
 
3.3%
3114 1
 
3.3%
3346 1
 
3.3%
ValueCountFrequency (%)
0 25
83.3%
1234 1
 
3.3%
2146 1
 
3.3%
3114 1
 
3.3%
3346 1
 
3.3%
3887 1
 
3.3%
ValueCountFrequency (%)
3887 1
 
3.3%
3346 1
 
3.3%
3114 1
 
3.3%
2146 1
 
3.3%
1234 1
 
3.3%
0 25
83.3%

전력사용요금최대부하
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct6
Distinct (%)20.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean376.5
Minimum0
Maximum3623
Zeros25
Zeros (%)83.3%
Negative0
Negative (%)0.0%
Memory size402.0 B
2024-03-13T20:55:39.474344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile3033.25
Maximum3623
Range3623
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1004.9
Coefficient of variation (CV)2.6690571
Kurtosis5.7105743
Mean376.5
Median Absolute Deviation (MAD)0
Skewness2.6256106
Sum11295
Variance1009824
MonotonicityNot monotonic
2024-03-13T20:55:39.610954image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0 25
83.3%
2651 1
 
3.3%
211 1
 
3.3%
3346 1
 
3.3%
1464 1
 
3.3%
3623 1
 
3.3%
ValueCountFrequency (%)
0 25
83.3%
211 1
 
3.3%
1464 1
 
3.3%
2651 1
 
3.3%
3346 1
 
3.3%
3623 1
 
3.3%
ValueCountFrequency (%)
3623 1
 
3.3%
3346 1
 
3.3%
2651 1
 
3.3%
1464 1
 
3.3%
211 1
 
3.3%
0 25
83.3%

비고
Categorical

CONSTANT 

Distinct1
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
2024-01-03 개방충전소(택시) 사용요금
30 

Length

Max length25
Median length25
Mean length25
Min length25

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2024-01-03 개방충전소(택시) 사용요금
2nd row2024-01-03 개방충전소(택시) 사용요금
3rd row2024-01-03 개방충전소(택시) 사용요금
4th row2024-01-03 개방충전소(택시) 사용요금
5th row2024-01-03 개방충전소(택시) 사용요금

Common Values

ValueCountFrequency (%)
2024-01-03 개방충전소(택시) 사용요금 30
100.0%

Length

2024-03-13T20:55:39.738968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T20:55:39.850636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2024-01-03 30
33.3%
개방충전소(택시 30
33.3%
사용요금 30
33.3%

생산일시
Date

CONSTANT 

Distinct1
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
Minimum2024-01-03 16:10:19
Maximum2024-01-03 16:10:19
2024-03-13T20:55:39.938519image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:55:40.035534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2024-03-13T20:55:35.206510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:55:31.350068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:55:32.104441image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:55:33.055444image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:55:33.744549image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:55:34.262720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:55:35.302906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:55:31.444728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:55:32.248550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:55:33.194425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:55:33.831198image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:55:34.352094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:55:35.385821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:55:31.543295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:55:32.398137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:55:33.324731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:55:33.905821image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:55:34.436975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:55:35.485455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:55:31.659329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:55:32.552629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:55:33.437932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:55:33.993639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:55:34.545746image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:55:35.570141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:55:31.754966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:55:32.724315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:55:33.531676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:55:34.070164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:55:34.636413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:55:35.677004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:55:31.914816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:55:32.895772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:55:33.636408image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:55:34.182385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:55:34.770472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-13T20:55:40.135721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
충전건차량번호소요시간시작일시종료일시시작SOC종료SOC전력사용요금전력사용요금경부하전력사용요금중부하전력사용요금최대부하
충전건1.0000.0001.0001.0001.0000.0000.0000.0000.4450.0000.000
차량번호0.0001.0001.0001.0001.0000.0000.9480.0000.9260.0000.218
소요시간1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
시작일시1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
종료일시1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
시작SOC0.0000.0001.0001.0001.0001.0000.0000.7440.8860.3410.000
종료SOC0.0000.9481.0001.0001.0000.0001.0000.4300.2330.0000.870
전력사용요금0.0000.0001.0001.0001.0000.7440.4301.0000.8250.0000.674
전력사용요금경부하0.4450.9261.0001.0001.0000.8860.2330.8251.0000.0000.000
전력사용요금중부하0.0000.0001.0001.0001.0000.3410.0000.0000.0001.0000.000
전력사용요금최대부하0.0000.2181.0001.0001.0000.0000.8700.6740.0000.0001.000
2024-03-13T20:55:40.272238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시작SOC종료SOC전력사용요금전력사용요금경부하전력사용요금중부하전력사용요금최대부하충전건
시작SOC1.000-0.076-0.894-0.491-0.0460.1280.000
종료SOC-0.0761.0000.3590.297-0.027-0.0340.000
전력사용요금-0.8940.3591.0000.3960.139-0.0070.000
전력사용요금경부하-0.4910.2970.3961.000-0.547-0.5470.376
전력사용요금중부하-0.046-0.0270.139-0.5471.000-0.0200.000
전력사용요금최대부하0.128-0.034-0.007-0.547-0.0201.0000.000
충전건0.0000.0000.0000.3760.0000.0001.000

Missing values

2024-03-13T20:55:35.821200image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-13T20:55:36.051441image/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

충전소ID충전기ID충전건차량번호소요시간시작일시종료일시시작SOC종료SOC전력사용요금전력사용요금경부하전력사용요금중부하전력사용요금최대부하비고생산일시
0KRPPKCP113573A7e154d0283ef5fade5495b3a9d5353012559ec3e0abf28434b5a865534f9cdc800:51:322023-10-01 14:13:032023-10-01 15:04:35329032563255002024-01-03 개방충전소(택시) 사용요금2024-01-03 16:10:19
1KRPPKCP113573A53c1548663f4fc051285eeb89ad4feb2ca80a2e6ba1ebeefcfb003da416f3d3800:53:272023-10-01 04:34:162023-10-01 05:27:433610034853484002024-01-03 개방충전소(택시) 사용요금2024-01-03 16:10:19
2KRPPKCP113573A94753088f3fc3725526a93bf55c6e2cfa156b4c142dc1a4802aa4a30b8c719bc00:45:082023-10-02 10:13:182023-10-02 10:58:26359038880388702024-01-03 개방충전소(택시) 사용요금2024-01-03 16:10:19
3KRPPKCP113573Afd6ec29cd4ffb29c6a233026e3eb9d4d8651dff6c881ba74442e7505ea620e2d00:39:262023-10-01 03:35:132023-10-01 04:14:39429030523051002024-01-03 개방충전소(택시) 사용요금2024-01-03 16:10:19
4KRPPKCP113573Bb8dc97c8a6f42ef8bbc2c2c1ec3ac3aa20b64d961de742d6b2d6d7bd66842c6600:37:342023-10-01 20:11:312023-10-01 20:49:05569019981997002024-01-03 개방충전소(택시) 사용요금2024-01-03 16:10:19
5KRPPKCP113573A995591caf55a736cc8d76d3f5293ff8fdc0fe0abc2b51761781e87ba0a0ad03d00:37:042023-10-04 20:24:082023-10-04 21:01:12569021460214602024-01-03 개방충전소(택시) 사용요금2024-01-03 16:10:19
6KRPPKCP113573B46da21342dc6e5feee68fe29f2e5dac6824dbf6b4993d4fac6565d28ec4067a700:23:392023-10-01 22:13:572023-10-01 22:37:36668412111210002024-01-03 개방충전소(택시) 사용요금2024-01-03 16:10:19
7KRPPKCP113573B46da21342dc6e5feee68fe29f2e5dac6824dbf6b4993d4fac6565d28ec4067a700:22:032023-10-03 03:05:402023-10-03 03:27:43618212671266002024-01-03 개방충전소(택시) 사용요금2024-01-03 16:10:19
8KRPPKCP113573Bc05b548c7e78dede6b81613fcf3fb69321233108544602bc0d0bdd7e627f154b00:57:592023-10-02 03:31:152023-10-02 04:29:14189038413840002024-01-03 개방충전소(택시) 사용요금2024-01-03 16:10:19
9KRPPKCP113573A0c15e75d1570ab37b58754edf19e2763f5c8ed69f9a83159ba7058c9c12f339f00:52:332023-10-03 06:19:112023-10-03 07:11:446510019681967002024-01-03 개방충전소(택시) 사용요금2024-01-03 16:10:19
충전소ID충전기ID충전건차량번호소요시간시작일시종료일시시작SOC종료SOC전력사용요금전력사용요금경부하전력사용요금중부하전력사용요금최대부하비고생산일시
20KRPPKCP113573A7e154d0283ef5fade5495b3a9d5353012559ec3e0abf28434b5a865534f9cdc800:42:442023-10-07 14:32:172023-10-07 15:15:015810026520026512024-01-03 개방충전소(택시) 사용요금2024-01-03 16:10:19
21KRPPKCP113573Afa65d97d0199a43444b1ceab55c10c2851c84d8db3c0bd5a7d3cf13dd72bcbd500:30:492023-10-14 12:34:122023-10-14 13:05:0168901446012342112024-01-03 개방충전소(택시) 사용요금2024-01-03 16:10:19
22KRPPKCP113573A5f5a937f13894bc516d9396ffc3e414c167a28ec555ce1e33dcb990b6f373afd00:37:172023-10-14 18:03:382023-10-14 18:40:55328031150311402024-01-03 개방충전소(택시) 사용요금2024-01-03 16:10:19
23KRPPKCP113573A19fadea50940b038c2a4e7f1e83deee1c41c003d5366b6cedcf79cc7fc15574e00:48:092023-10-02 14:34:542023-10-02 15:23:03439033460033462024-01-03 개방충전소(택시) 사용요금2024-01-03 16:10:19
24KRPPKCP113573A4cad751f09e478e6a0e0cb62dfeecc9c81320b16d1072aacba5ffe61376a375300:50:232023-10-04 12:07:192023-10-04 12:57:42369033470334602024-01-03 개방충전소(택시) 사용요금2024-01-03 16:10:19
25KRPPKCP113573B39e6a7572f9aff6aa56c2f79b4e88f69675bf4eb1b183d7f93c342e6b97c47b400:44:502023-10-08 02:53:012023-10-08 03:37:51359234673466002024-01-03 개방충전소(택시) 사용요금2024-01-03 16:10:19
26KRPPKCP113573A1263fb9bff0bb5eefe77bcacea5d2eaca4169b04bec1e55b17a5c9c0f0a78f0a00:20:022023-10-02 14:08:382023-10-02 14:28:40597914640014642024-01-03 개방충전소(택시) 사용요금2024-01-03 16:10:19
27KRPPKCP113573Ad0e808b40576dbf05d8d63b9aaad002c231c8a04c502d420dd24131542182f6e00:46:352023-10-04 16:34:092023-10-04 17:20:44318636240036232024-01-03 개방충전소(택시) 사용요금2024-01-03 16:10:19
28KRPPKCP113573A930fb55314203e0141c430e52d1f08c284d96cc283541cd56e04c483a3ec9def00:38:192023-10-08 04:36:462023-10-08 05:15:05308129042904002024-01-03 개방충전소(택시) 사용요금2024-01-03 16:10:19
29KRPPKCP113573A2d3683cf242f5182503ca7e4f1324a766caee59cacf124303145d0b456408f6b00:59:272023-10-01 20:09:152023-10-01 21:08:42448630793079002024-01-03 개방충전소(택시) 사용요금2024-01-03 16:10:19