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/898c2f27-1a29-4a2a-bf6e-094a7109cd70

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 전력사용량High correlation
전력사용량 is highly overall correlated with 시작SOC and 1 other fieldsHigh correlation
전력사용량경부하 is highly overall correlated with 전력사용량 and 2 other fieldsHigh correlation
전력사용량중부하 is highly overall correlated with 전력사용량경부하High correlation
전력사용량최대부하 is highly overall correlated with 전력사용량경부하High correlation
소요시간 has unique valuesUnique
시작일시 has unique valuesUnique
종료일시 has unique valuesUnique
전력사용량경부하 has 11 (36.7%) zerosZeros
전력사용량중부하 has 24 (80.0%) zerosZeros
전력사용량최대부하 has 24 (80.0%) zerosZeros

Reproduction

Analysis started2024-03-13 11:59:17.551488
Analysis finished2024-03-13 11:59:23.195155
Duration5.64 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

2024-03-13T20:59:23.281214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T20:59:23.401352image/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

2024-03-13T20:59:23.530233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T20:59:23.623077image/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
18 
B
12 

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 18
60.0%
B 12
40.0%

Length

2024-03-13T20:59:23.729653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T20:59:23.848910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
a 18
60.0%
b 12
40.0%

차량번호
Text

Distinct24
Distinct (%)80.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
2024-03-13T20:59:24.117244image/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

Unique21 ?
Unique (%)70.0%

Sample

1st row7e154d0283ef5fade5495b3a9d5353012559ec3e0abf28434b5a865534f9cdc8
2nd row53c1548663f4fc051285eeb89ad4feb2ca80a2e6ba1ebeefcfb003da416f3d38
3rd row94753088f3fc3725526a93bf55c6e2cfa156b4c142dc1a4802aa4a30b8c719bc
4th rowfd6ec29cd4ffb29c6a233026e3eb9d4d8651dff6c881ba74442e7505ea620e2d
5th rowb8dc97c8a6f42ef8bbc2c2c1ec3ac3aa20b64d961de742d6b2d6d7bd66842c66
ValueCountFrequency (%)
7e154d0283ef5fade5495b3a9d5353012559ec3e0abf28434b5a865534f9cdc8 4
 
13.3%
46da21342dc6e5feee68fe29f2e5dac6824dbf6b4993d4fac6565d28ec4067a7 3
 
10.0%
94753088f3fc3725526a93bf55c6e2cfa156b4c142dc1a4802aa4a30b8c719bc 2
 
6.7%
24b3f54dcac7459a97c7e21b1e256bc5d8dcdeedf214ab0b3ff86f9ef696cd59 1
 
3.3%
995591caf55a736cc8d76d3f5293ff8fdc0fe0abc2b51761781e87ba0a0ad03d 1
 
3.3%
d0e808b40576dbf05d8d63b9aaad002c231c8a04c502d420dd24131542182f6e 1
 
3.3%
1263fb9bff0bb5eefe77bcacea5d2eaca4169b04bec1e55b17a5c9c0f0a78f0a 1
 
3.3%
4cad751f09e478e6a0e0cb62dfeecc9c81320b16d1072aacba5ffe61376a3753 1
 
3.3%
22292afb451a3e55f480ff98afb25730ffd6e4c57d46751c920a5eaaba9d5c1f 1
 
3.3%
19fadea50940b038c2a4e7f1e83deee1c41c003d5366b6cedcf79cc7fc15574e 1
 
3.3%
Other values (14) 14
46.7%
2024-03-13T20:59:24.572300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 159
 
8.3%
c 140
 
7.3%
f 136
 
7.1%
d 130
 
6.8%
3 128
 
6.7%
e 127
 
6.6%
4 127
 
6.6%
2 125
 
6.5%
a 123
 
6.4%
6 122
 
6.4%
Other values (6) 603
31.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1158
60.3%
Lowercase Letter 762
39.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 159
13.7%
3 128
11.1%
4 127
11.0%
2 125
10.8%
6 122
10.5%
1 110
9.5%
0 107
9.2%
8 101
8.7%
9 93
8.0%
7 86
7.4%
Lowercase Letter
ValueCountFrequency (%)
c 140
18.4%
f 136
17.8%
d 130
17.1%
e 127
16.7%
a 123
16.1%
b 106
13.9%

Most occurring scripts

ValueCountFrequency (%)
Common 1158
60.3%
Latin 762
39.7%

Most frequent character per script

Common
ValueCountFrequency (%)
5 159
13.7%
3 128
11.1%
4 127
11.0%
2 125
10.8%
6 122
10.5%
1 110
9.5%
0 107
9.2%
8 101
8.7%
9 93
8.0%
7 86
7.4%
Latin
ValueCountFrequency (%)
c 140
18.4%
f 136
17.8%
d 130
17.1%
e 127
16.7%
a 123
16.1%
b 106
13.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1920
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 159
 
8.3%
c 140
 
7.3%
f 136
 
7.1%
d 130
 
6.8%
3 128
 
6.7%
e 127
 
6.6%
4 127
 
6.6%
2 125
 
6.5%
a 123
 
6.4%
6 122
 
6.4%
Other values (6) 603
31.4%

소요시간
Date

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
Minimum2024-03-13 00:13:49
Maximum2024-03-13 00:59:43
2024-03-13T20:59:24.708202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:59:24.820829image/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 12:34:12
2024-03-13T20:59:24.936687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:59:25.061900image/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 13:05:01
2024-03-13T20:59:25.201604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:59:25.437215image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)

시작SOC
Real number (ℝ)

HIGH CORRELATION 

Distinct26
Distinct (%)86.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean48.7
Minimum18
Maximum73
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2024-03-13T20:59:25.544496image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum18
5-th percentile24.5
Q136
median50
Q360.75
95-th percentile69.65
Maximum73
Range55
Interquartile range (IQR)24.75

Descriptive statistics

Standard deviation15.277096
Coefficient of variation (CV)0.31369807
Kurtosis-0.91965
Mean48.7
Median Absolute Deviation (MAD)13
Skewness-0.29501308
Sum1461
Variance233.38966
MonotonicityNot monotonic
2024-03-13T20:59:25.666007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
31 2
 
6.7%
49 2
 
6.7%
36 2
 
6.7%
63 2
 
6.7%
32 1
 
3.3%
40 1
 
3.3%
30 1
 
3.3%
51 1
 
3.3%
59 1
 
3.3%
43 1
 
3.3%
Other values (16) 16
53.3%
ValueCountFrequency (%)
18 1
3.3%
20 1
3.3%
30 1
3.3%
31 2
6.7%
32 1
3.3%
35 1
3.3%
36 2
6.7%
40 1
3.3%
42 1
3.3%
43 1
3.3%
ValueCountFrequency (%)
73 1
3.3%
71 1
3.3%
68 1
3.3%
66 1
3.3%
65 1
3.3%
63 2
6.7%
61 1
3.3%
60 1
3.3%
59 1
3.3%
58 1
3.3%

종료SOC
Real number (ℝ)

Distinct11
Distinct (%)36.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean89.1
Minimum74
Maximum100
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2024-03-13T20:59:25.776831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum74
5-th percentile79.9
Q186
median90
Q390
95-th percentile100
Maximum100
Range26
Interquartile range (IQR)4

Descriptive statistics

Standard deviation6.0988976
Coefficient of variation (CV)0.068450029
Kurtosis0.6543553
Mean89.1
Median Absolute Deviation (MAD)1.5
Skewness-0.049287584
Sum2673
Variance37.196552
MonotonicityNot monotonic
2024-03-13T20:59:25.884804image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
90 14
46.7%
100 4
 
13.3%
84 3
 
10.0%
86 2
 
6.7%
82 1
 
3.3%
74 1
 
3.3%
89 1
 
3.3%
88 1
 
3.3%
96 1
 
3.3%
79 1
 
3.3%
ValueCountFrequency (%)
74 1
 
3.3%
79 1
 
3.3%
81 1
 
3.3%
82 1
 
3.3%
84 3
 
10.0%
86 2
 
6.7%
88 1
 
3.3%
89 1
 
3.3%
90 14
46.7%
96 1
 
3.3%
ValueCountFrequency (%)
100 4
 
13.3%
96 1
 
3.3%
90 14
46.7%
89 1
 
3.3%
88 1
 
3.3%
86 2
 
6.7%
84 3
 
10.0%
82 1
 
3.3%
81 1
 
3.3%
79 1
 
3.3%

전력사용량
Real number (ℝ)

HIGH CORRELATION 

Distinct21
Distinct (%)70.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean28.9
Minimum11
Maximum48
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2024-03-13T20:59:25.987861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum11
5-th percentile13.35
Q120
median28
Q338
95-th percentile45.2
Maximum48
Range37
Interquartile range (IQR)18

Descriptive statistics

Standard deviation11.027708
Coefficient of variation (CV)0.38158159
Kurtosis-1.1663096
Mean28.9
Median Absolute Deviation (MAD)10
Skewness-0.029449024
Sum867
Variance121.61034
MonotonicityNot monotonic
2024-03-13T20:59:26.118693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)
ValueCountFrequency (%)
15 5
16.7%
38 3
 
10.0%
24 2
 
6.7%
36 2
 
6.7%
28 2
 
6.7%
40 1
 
3.3%
48 1
 
3.3%
27 1
 
3.3%
25 1
 
3.3%
35 1
 
3.3%
Other values (11) 11
36.7%
ValueCountFrequency (%)
11 1
 
3.3%
12 1
 
3.3%
15 5
16.7%
19 1
 
3.3%
23 1
 
3.3%
24 2
 
6.7%
25 1
 
3.3%
26 1
 
3.3%
27 1
 
3.3%
28 2
 
6.7%
ValueCountFrequency (%)
48 1
 
3.3%
47 1
 
3.3%
43 1
 
3.3%
42 1
 
3.3%
41 1
 
3.3%
40 1
 
3.3%
38 3
10.0%
36 2
6.7%
35 1
 
3.3%
34 1
 
3.3%

전력사용량경부하
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct16
Distinct (%)53.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean18.8
Minimum0
Maximum48
Zeros11
Zeros (%)36.7%
Negative0
Negative (%)0.0%
Memory size402.0 B
2024-03-13T20:59:26.231536image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median17
Q335.5
95-th percentile45.2
Maximum48
Range48
Interquartile range (IQR)35.5

Descriptive statistics

Standard deviation17.325285
Coefficient of variation (CV)0.92155774
Kurtosis-1.4745918
Mean18.8
Median Absolute Deviation (MAD)17
Skewness0.23190798
Sum564
Variance300.16552
MonotonicityNot monotonic
2024-03-13T20:59:26.383257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
0 11
36.7%
38 2
 
6.7%
24 2
 
6.7%
15 2
 
6.7%
28 2
 
6.7%
40 1
 
3.3%
34 1
 
3.3%
36 1
 
3.3%
12 1
 
3.3%
48 1
 
3.3%
Other values (6) 6
20.0%
ValueCountFrequency (%)
0 11
36.7%
11 1
 
3.3%
12 1
 
3.3%
15 2
 
6.7%
19 1
 
3.3%
23 1
 
3.3%
24 2
 
6.7%
28 2
 
6.7%
34 1
 
3.3%
36 1
 
3.3%
ValueCountFrequency (%)
48 1
3.3%
47 1
3.3%
43 1
3.3%
41 1
3.3%
40 1
3.3%
38 2
6.7%
36 1
3.3%
34 1
3.3%
28 2
6.7%
24 2
6.7%

전력사용량중부하
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct7
Distinct (%)23.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.2333333
Minimum0
Maximum42
Zeros24
Zeros (%)80.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2024-03-13T20:59:26.492786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile31.5
Maximum42
Range42
Interquartile range (IQR)0

Descriptive statistics

Standard deviation11.646172
Coefficient of variation (CV)2.2253833
Kurtosis3.7940841
Mean5.2333333
Median Absolute Deviation (MAD)0
Skewness2.186032
Sum157
Variance135.63333
MonotonicityNot monotonic
2024-03-13T20:59:26.603554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0 24
80.0%
42 1
 
3.3%
15 1
 
3.3%
26 1
 
3.3%
13 1
 
3.3%
25 1
 
3.3%
36 1
 
3.3%
ValueCountFrequency (%)
0 24
80.0%
13 1
 
3.3%
15 1
 
3.3%
25 1
 
3.3%
26 1
 
3.3%
36 1
 
3.3%
42 1
 
3.3%
ValueCountFrequency (%)
42 1
 
3.3%
36 1
 
3.3%
26 1
 
3.3%
25 1
 
3.3%
15 1
 
3.3%
13 1
 
3.3%
0 24
80.0%

전력사용량최대부하
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct7
Distinct (%)23.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.8666667
Minimum0
Maximum38
Zeros24
Zeros (%)80.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2024-03-13T20:59:26.714707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile32.3
Maximum38
Range38
Interquartile range (IQR)0

Descriptive statistics

Standard deviation11.382786
Coefficient of variation (CV)2.3389286
Kurtosis3.3156613
Mean4.8666667
Median Absolute Deviation (MAD)0
Skewness2.1765298
Sum146
Variance129.56782
MonotonicityNot monotonic
2024-03-13T20:59:26.863416image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=7)
ValueCountFrequency (%)
0 24
80.0%
29 1
 
3.3%
2 1
 
3.3%
35 1
 
3.3%
15 1
 
3.3%
27 1
 
3.3%
38 1
 
3.3%
ValueCountFrequency (%)
0 24
80.0%
2 1
 
3.3%
15 1
 
3.3%
27 1
 
3.3%
29 1
 
3.3%
35 1
 
3.3%
38 1
 
3.3%
ValueCountFrequency (%)
38 1
 
3.3%
35 1
 
3.3%
29 1
 
3.3%
27 1
 
3.3%
15 1
 
3.3%
2 1
 
3.3%
0 24
80.0%

비고
Categorical

CONSTANT 

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

Length

Max length25
Median length25
Mean length25
Min length25

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

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

Length

2024-03-13T20:59:27.263462image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T20:59:27.392666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2024-01-03 30
33.3%
개방충전소(택시 30
33.3%
사용전력 30
33.3%

생산일시
Date

CONSTANT 

Distinct1
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
Minimum2024-01-03 16:09:55
Maximum2024-01-03 16:09:55
2024-03-13T20:59:27.501440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:59:27.642576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2024-03-13T20:59:21.919909image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:59:17.936665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:59:18.498801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:59:19.148529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:59:20.316045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:59:21.189449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:59:22.052805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:59:18.018686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:59:18.604074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:59:19.247563image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:59:20.430472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:59:21.310165image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:59:22.172584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:59:18.118162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:59:18.688436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:59:19.707678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:59:20.562326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:59:21.425104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:59:22.319905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:59:18.204077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:59:18.802558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:59:19.871571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:59:20.734739image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:59:21.570483image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:59:22.440552image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:59:18.283233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:59:18.916301image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:59:20.036870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:59:20.940373image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:59:21.687105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:59:22.554356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:59:18.367748image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:59:19.012068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:59:20.166405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:59:21.063079image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T20:59:21.795564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-13T20:59:27.741197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
충전건차량번호소요시간시작일시종료일시시작SOC종료SOC전력사용량전력사용량경부하전력사용량중부하전력사용량최대부하
충전건1.0000.0001.0001.0001.0000.2740.0000.3680.2860.0000.000
차량번호0.0001.0001.0001.0001.0000.7950.9360.9070.1380.9600.773
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
시작SOC0.2740.7951.0001.0001.0001.0000.0000.8820.6780.2820.000
종료SOC0.0000.9361.0001.0001.0000.0001.0000.7880.5640.0000.659
전력사용량0.3680.9071.0001.0001.0000.8820.7881.0000.8390.0000.000
전력사용량경부하0.2860.1381.0001.0001.0000.6780.5640.8391.0000.0000.000
전력사용량중부하0.0000.9601.0001.0001.0000.2820.0000.0000.0001.0000.000
전력사용량최대부하0.0000.7731.0001.0001.0000.0000.6590.0000.0000.0001.000
2024-03-13T20:59:27.899523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시작SOC종료SOC전력사용량전력사용량경부하전력사용량중부하전력사용량최대부하충전건
시작SOC1.000-0.011-0.903-0.4770.1070.0360.218
종료SOC-0.0111.0000.3360.0780.1410.0180.000
전력사용량-0.9030.3361.0000.510-0.050-0.0530.305
전력사용량경부하-0.4770.0780.5101.000-0.558-0.5580.066
전력사용량중부하0.1070.141-0.050-0.5581.000-0.1040.000
전력사용량최대부하0.0360.018-0.053-0.558-0.1041.0000.000
충전건0.2180.0000.3050.0660.0000.0001.000

Missing values

2024-03-13T20:59:22.734922image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-13T20:59:23.052078image/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

충전소ID충전기ID충전건차량번호소요시간시작일시종료일시시작SOC종료SOC전력사용량전력사용량경부하전력사용량중부하전력사용량최대부하비고생산일시
0KRPPKCP113573A7e154d0283ef5fade5495b3a9d5353012559ec3e0abf28434b5a865534f9cdc800:51:322023-10-01 14:13:032023-10-01 15:04:3532904040002024-01-03 개방충전소(택시) 사용전력2024-01-03 16:09:55
1KRPPKCP113573A53c1548663f4fc051285eeb89ad4feb2ca80a2e6ba1ebeefcfb003da416f3d3800:53:272023-10-01 04:34:162023-10-01 05:27:43361004343002024-01-03 개방충전소(택시) 사용전력2024-01-03 16:09:55
2KRPPKCP113573A94753088f3fc3725526a93bf55c6e2cfa156b4c142dc1a4802aa4a30b8c719bc00:45:082023-10-02 10:13:182023-10-02 10:58:2635904204202024-01-03 개방충전소(택시) 사용전력2024-01-03 16:09:55
3KRPPKCP113573Afd6ec29cd4ffb29c6a233026e3eb9d4d8651dff6c881ba74442e7505ea620e2d00:39:262023-10-01 03:35:132023-10-01 04:14:3942903838002024-01-03 개방충전소(택시) 사용전력2024-01-03 16:09:55
4KRPPKCP113573Bb8dc97c8a6f42ef8bbc2c2c1ec3ac3aa20b64d961de742d6b2d6d7bd66842c6600:37:342023-10-01 20:11:312023-10-01 20:49:0556902424002024-01-03 개방충전소(택시) 사용전력2024-01-03 16:09:55
5KRPPKCP113573A2d3683cf242f5182503ca7e4f1324a766caee59cacf124303145d0b456408f6b00:59:272023-10-01 20:09:152023-10-01 21:08:4244863838002024-01-03 개방충전소(택시) 사용전력2024-01-03 16:09:55
6KRPPKCP113573B46da21342dc6e5feee68fe29f2e5dac6824dbf6b4993d4fac6565d28ec4067a700:23:392023-10-01 22:13:572023-10-01 22:37:3666841515002024-01-03 개방충전소(택시) 사용전력2024-01-03 16:09:55
7KRPPKCP113573B46da21342dc6e5feee68fe29f2e5dac6824dbf6b4993d4fac6565d28ec4067a700:22:032023-10-03 03:05:402023-10-03 03:27:4361821515002024-01-03 개방충전소(택시) 사용전력2024-01-03 16:09:55
8KRPPKCP113573Bc05b548c7e78dede6b81613fcf3fb69321233108544602bc0d0bdd7e627f154b00:57:592023-10-02 03:31:152023-10-02 04:29:1418904747002024-01-03 개방충전소(택시) 사용전력2024-01-03 16:09:55
9KRPPKCP113573A0c15e75d1570ab37b58754edf19e2763f5c8ed69f9a83159ba7058c9c12f339f00:52:332023-10-03 06:19:112023-10-03 07:11:44651002424002024-01-03 개방충전소(택시) 사용전력2024-01-03 16:09:55
충전소ID충전기ID충전건차량번호소요시간시작일시종료일시시작SOC종료SOC전력사용량전력사용량경부하전력사용량중부하전력사용량최대부하비고생산일시
20KRPPKCP113573A7e154d0283ef5fade5495b3a9d5353012559ec3e0abf28434b5a865534f9cdc800:42:442023-10-07 14:32:172023-10-07 15:15:01581002900292024-01-03 개방충전소(택시) 사용전력2024-01-03 16:09:55
21KRPPKCP113573Ab4eaab646bfd5c10fa9c0d97f19f8de275a8524d3ba43f147a2830eaf11eab9c00:41:512023-10-14 08:27:292023-10-14 09:09:2054902602602024-01-03 개방충전소(택시) 사용전력2024-01-03 16:09:55
22KRPPKCP113573Afa65d97d0199a43444b1ceab55c10c2851c84d8db3c0bd5a7d3cf13dd72bcbd500:30:492023-10-14 12:34:122023-10-14 13:05:0168901501322024-01-03 개방충전소(택시) 사용전력2024-01-03 16:09:55
23KRPPKCP113573A19fadea50940b038c2a4e7f1e83deee1c41c003d5366b6cedcf79cc7fc15574e00:48:092023-10-02 14:34:542023-10-02 15:23:0343903500352024-01-03 개방충전소(택시) 사용전력2024-01-03 16:09:55
24KRPPKCP113573B22292afb451a3e55f480ff98afb25730ffd6e4c57d46751c920a5eaaba9d5c1f00:35:132023-10-04 12:05:102023-10-04 12:40:2363962502502024-01-03 개방충전소(택시) 사용전력2024-01-03 16:09:55
25KRPPKCP113573A4cad751f09e478e6a0e0cb62dfeecc9c81320b16d1072aacba5ffe61376a375300:50:232023-10-04 12:07:192023-10-04 12:57:4236903603602024-01-03 개방충전소(택시) 사용전력2024-01-03 16:09:55
26KRPPKCP113573A1263fb9bff0bb5eefe77bcacea5d2eaca4169b04bec1e55b17a5c9c0f0a78f0a00:20:022023-10-02 14:08:382023-10-02 14:28:4059791500152024-01-03 개방충전소(택시) 사용전력2024-01-03 16:09:55
27KRPPKCP113573B7e154d0283ef5fade5495b3a9d5353012559ec3e0abf28434b5a865534f9cdc800:41:152023-10-02 13:51:162023-10-02 14:32:3151902700272024-01-03 개방충전소(택시) 사용전력2024-01-03 16:09:55
28KRPPKCP113573Ad0e808b40576dbf05d8d63b9aaad002c231c8a04c502d420dd24131542182f6e00:46:352023-10-04 16:34:092023-10-04 17:20:4431863800382024-01-03 개방충전소(택시) 사용전력2024-01-03 16:09:55
29KRPPKCP113573A930fb55314203e0141c430e52d1f08c284d96cc283541cd56e04c483a3ec9def00:38:192023-10-08 04:36:462023-10-08 05:15:0530813636002024-01-03 개방충전소(택시) 사용전력2024-01-03 16:09:55