Overview

Dataset statistics

Number of variables15
Number of observations30
Missing cells27
Missing cells (%)6.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.8 KiB
Average record size in memory130.4 B

Variable types

Categorical6
Text2
Numeric5
DateTime2

Dataset

Description샘플 데이터
Author펌프킨
URLhttps://bigdata-region.kr/#/dataset/2e5fb439-e0fd-46b6-9de9-213883cd925b

Alerts

비고 has constant value ""Constant
생산_일시 has constant value ""Constant
시도_코드 is highly overall correlated with 시도_명 and 1 other fieldsHigh correlation
시군구_코드 is highly overall correlated with 시도_명 and 1 other fieldsHigh correlation
공급_전압 is highly overall correlated with 시도_명 and 1 other fieldsHigh correlation
공급_전류 is highly overall correlated with 시군구_명High correlation
시도_명 is highly overall correlated with 시도_코드 and 3 other fieldsHigh correlation
시군구_명 is highly overall correlated with 시도_코드 and 4 other fieldsHigh correlation
종료_일시 has 27 (90.0%) missing valuesMissing

Reproduction

Analysis started2024-03-13 12:00:31.833438
Analysis finished2024-03-13 12:00:35.028623
Duration3.2 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

충전_일시
Categorical

Distinct3
Distinct (%)10.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-10-01 00:00:01
14 
2023-10-01 00:00:00
10 
2023-10-01 00:00:02
6 

Length

Max length19
Median length19
Mean length19
Min length19

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-10-01 00:00:00
2nd row2023-10-01 00:00:00
3rd row2023-10-01 00:00:00
4th row2023-10-01 00:00:00
5th row2023-10-01 00:00:00

Common Values

ValueCountFrequency (%)
2023-10-01 00:00:01 14
46.7%
2023-10-01 00:00:00 10
33.3%
2023-10-01 00:00:02 6
20.0%

Length

2024-03-13T21:00:35.098750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T21:00:35.218506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-10-01 30
50.0%
00:00:01 14
23.3%
00:00:00 10
 
16.7%
00:00:02 6
 
10.0%

충전소_ID
Text

Distinct18
Distinct (%)60.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
2024-03-13T21:00:35.659381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length11
Mean length11
Min length11

Characters and Unicode

Total characters330
Distinct characters15
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

Unique12 ?
Unique (%)40.0%

Sample

1st rowKRPPKCS0024
2nd rowKRPPKCS0064
3rd rowKRPPKCS0090
4th rowKRPPKCS0169
5th rowKRPPKCS0116
ValueCountFrequency (%)
krppkcs0084 4
13.3%
krppkcs0089 3
 
10.0%
krppkcs0113 3
 
10.0%
krppkcs0149 3
 
10.0%
krppkcs0087 3
 
10.0%
krppkcs0010 2
 
6.7%
krppkcs0153 1
 
3.3%
krppkcs0024 1
 
3.3%
krppkcs0152 1
 
3.3%
krppkcs0127 1
 
3.3%
Other values (8) 8
26.7%
2024-03-13T21:00:35.958565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
K 60
18.2%
P 60
18.2%
0 52
15.8%
R 30
9.1%
C 30
9.1%
S 30
9.1%
1 21
 
6.4%
8 10
 
3.0%
4 10
 
3.0%
9 9
 
2.7%
Other values (5) 18
 
5.5%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 210
63.6%
Decimal Number 120
36.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 52
43.3%
1 21
17.5%
8 10
 
8.3%
4 10
 
8.3%
9 9
 
7.5%
7 5
 
4.2%
3 4
 
3.3%
6 3
 
2.5%
5 3
 
2.5%
2 3
 
2.5%
Uppercase Letter
ValueCountFrequency (%)
K 60
28.6%
P 60
28.6%
R 30
14.3%
C 30
14.3%
S 30
14.3%

Most occurring scripts

ValueCountFrequency (%)
Latin 210
63.6%
Common 120
36.4%

Most frequent character per script

Common
ValueCountFrequency (%)
0 52
43.3%
1 21
17.5%
8 10
 
8.3%
4 10
 
8.3%
9 9
 
7.5%
7 5
 
4.2%
3 4
 
3.3%
6 3
 
2.5%
5 3
 
2.5%
2 3
 
2.5%
Latin
ValueCountFrequency (%)
K 60
28.6%
P 60
28.6%
R 30
14.3%
C 30
14.3%
S 30
14.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 330
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
K 60
18.2%
P 60
18.2%
0 52
15.8%
R 30
9.1%
C 30
9.1%
S 30
9.1%
1 21
 
6.4%
8 10
 
3.0%
4 10
 
3.0%
9 9
 
2.7%
Other values (5) 18
 
5.5%

충전기_ID
Text

Distinct26
Distinct (%)86.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
2024-03-13T21:00:36.156172image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length11
Mean length11
Min length11

Characters and Unicode

Total characters330
Distinct characters14
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

Unique22 ?
Unique (%)73.3%

Sample

1st rowKRPPKCP0172
2nd rowKRPPKCP0463
3rd rowKRPPKCP0662
4th rowKRPPKCP1097
5th rowKRPPKCP0816
ValueCountFrequency (%)
krppkcp0643 2
 
6.7%
krppkcp0797 2
 
6.7%
krppkcp0659 2
 
6.7%
krppkcp0639 2
 
6.7%
krppkcp0463 1
 
3.3%
krppkcp0172 1
 
3.3%
krppkcp0407 1
 
3.3%
krppkcp0082 1
 
3.3%
krppkcp0660 1
 
3.3%
krppkcp0653 1
 
3.3%
Other values (16) 16
53.3%
2024-03-13T21:00:36.486085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
P 90
27.3%
K 60
18.2%
0 39
11.8%
R 30
 
9.1%
C 30
 
9.1%
6 17
 
5.2%
9 10
 
3.0%
7 10
 
3.0%
5 10
 
3.0%
1 10
 
3.0%
Other values (4) 24
 
7.3%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 210
63.6%
Decimal Number 120
36.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 39
32.5%
6 17
14.2%
9 10
 
8.3%
7 10
 
8.3%
5 10
 
8.3%
1 10
 
8.3%
3 9
 
7.5%
4 6
 
5.0%
2 6
 
5.0%
8 3
 
2.5%
Uppercase Letter
ValueCountFrequency (%)
P 90
42.9%
K 60
28.6%
R 30
 
14.3%
C 30
 
14.3%

Most occurring scripts

ValueCountFrequency (%)
Latin 210
63.6%
Common 120
36.4%

Most frequent character per script

Common
ValueCountFrequency (%)
0 39
32.5%
6 17
14.2%
9 10
 
8.3%
7 10
 
8.3%
5 10
 
8.3%
1 10
 
8.3%
3 9
 
7.5%
4 6
 
5.0%
2 6
 
5.0%
8 3
 
2.5%
Latin
ValueCountFrequency (%)
P 90
42.9%
K 60
28.6%
R 30
 
14.3%
C 30
 
14.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 330
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
P 90
27.3%
K 60
18.2%
0 39
11.8%
R 30
 
9.1%
C 30
 
9.1%
6 17
 
5.2%
9 10
 
3.0%
7 10
 
3.0%
5 10
 
3.0%
1 10
 
3.0%
Other values (4) 24
 
7.3%

충전건
Categorical

Distinct2
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
2
17 
1
13 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row2
3rd row1
4th row2
5th row2

Common Values

ValueCountFrequency (%)
2 17
56.7%
1 13
43.3%

Length

2024-03-13T21:00:36.617621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T21:00:36.707744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 17
56.7%
1 13
43.3%

시도_코드
Real number (ℝ)

HIGH CORRELATION 

Distinct6
Distinct (%)20.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean36.733333
Minimum11
Maximum48
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2024-03-13T21:00:36.798144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum11
5-th percentile11
Q132.75
median41
Q341
95-th percentile48
Maximum48
Range37
Interquartile range (IQR)8.25

Descriptive statistics

Standard deviation11.720696
Coefficient of variation (CV)0.31907521
Kurtosis0.88677728
Mean36.733333
Median Absolute Deviation (MAD)0
Skewness-1.3963114
Sum1102
Variance137.37471
MonotonicityNot monotonic
2024-03-13T21:00:36.911407image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
41 16
53.3%
48 6
 
20.0%
11 4
 
13.3%
30 2
 
6.7%
28 1
 
3.3%
26 1
 
3.3%
ValueCountFrequency (%)
11 4
 
13.3%
26 1
 
3.3%
28 1
 
3.3%
30 2
 
6.7%
41 16
53.3%
48 6
 
20.0%
ValueCountFrequency (%)
48 6
 
20.0%
41 16
53.3%
30 2
 
6.7%
28 1
 
3.3%
26 1
 
3.3%
11 4
 
13.3%

시군구_코드
Real number (ℝ)

HIGH CORRELATION 

Distinct14
Distinct (%)46.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean334.8
Minimum111
Maximum670
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2024-03-13T21:00:37.066382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum111
5-th percentile113.7
Q1150
median205
Q3590
95-th percentile670
Maximum670
Range559
Interquartile range (IQR)440

Descriptive statistics

Standard deviation223.01808
Coefficient of variation (CV)0.66612328
Kurtosis-1.6421505
Mean334.8
Median Absolute Deviation (MAD)84
Skewness0.50840784
Sum10044
Variance49737.062
MonotonicityNot monotonic
2024-03-13T21:00:37.184450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=14)
ValueCountFrequency (%)
170 4
13.3%
590 4
13.3%
150 3
10.0%
670 3
10.0%
125 3
10.0%
200 2
6.7%
620 2
6.7%
210 2
6.7%
111 2
6.7%
260 1
 
3.3%
Other values (4) 4
13.3%
ValueCountFrequency (%)
111 2
6.7%
117 1
 
3.3%
125 3
10.0%
150 3
10.0%
170 4
13.3%
200 2
6.7%
210 2
6.7%
260 1
 
3.3%
410 1
 
3.3%
450 1
 
3.3%
ValueCountFrequency (%)
670 3
10.0%
650 1
 
3.3%
620 2
6.7%
590 4
13.3%
450 1
 
3.3%
410 1
 
3.3%
260 1
 
3.3%
210 2
6.7%
200 2
6.7%
170 4
13.3%

시도_명
Categorical

HIGH CORRELATION 

Distinct6
Distinct (%)20.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
경기도
16 
경상남도
6 
서울특별시
4 
대전광역시
2 
인천광역시
 
1

Length

Max length5
Median length3
Mean length3.7333333
Min length3

Unique

Unique2 ?
Unique (%)6.7%

Sample

1st row인천광역시
2nd row경기도
3rd row경기도
4th row대전광역시
5th row대전광역시

Common Values

ValueCountFrequency (%)
경기도 16
53.3%
경상남도 6
 
20.0%
서울특별시 4
 
13.3%
대전광역시 2
 
6.7%
인천광역시 1
 
3.3%
부산광역시 1
 
3.3%

Length

2024-03-13T21:00:37.343009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T21:00:37.464977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경기도 16
53.3%
경상남도 6
 
20.0%
서울특별시 4
 
13.3%
대전광역시 2
 
6.7%
인천광역시 1
 
3.3%
부산광역시 1
 
3.3%

시군구_명
Categorical

HIGH CORRELATION 

Distinct14
Distinct (%)46.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
화성시
4 
수원시
3 
의정부시
3 
여주시
3 
창원시
3 
Other values (9)
14 

Length

Max length4
Median length3
Mean length3.0666667
Min length2

Unique

Unique5 ?
Unique (%)16.7%

Sample

1st row서구
2nd row수원시
3rd row하남시
4th row유성구
5th row유성구

Common Values

ValueCountFrequency (%)
화성시 4
13.3%
수원시 3
10.0%
의정부시 3
10.0%
여주시 3
10.0%
창원시 3
10.0%
진주시 3
10.0%
유성구 2
6.7%
관악구 2
6.7%
광명시 2
6.7%
서구 1
 
3.3%
Other values (4) 4
13.3%

Length

2024-03-13T21:00:37.612473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
화성시 4
13.3%
수원시 3
10.0%
의정부시 3
10.0%
여주시 3
10.0%
창원시 3
10.0%
진주시 3
10.0%
유성구 2
6.7%
관악구 2
6.7%
광명시 2
6.7%
서구 1
 
3.3%
Other values (4) 4
13.3%

시작_일시
Date

Distinct19
Distinct (%)63.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
Minimum2023-09-30 22:31:57
Maximum2023-10-01 00:00:02
2024-03-13T21:00:37.752289image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:00:37.893113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)

종료_일시
Date

MISSING 

Distinct2
Distinct (%)66.7%
Missing27
Missing (%)90.0%
Memory size372.0 B
Minimum2023-10-01 00:00:00
Maximum2023-10-01 00:00:01
2024-03-13T21:00:38.000391image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:00:38.108717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=2)

시작_SOC
Real number (ℝ)

Distinct23
Distinct (%)76.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean68.866667
Minimum13
Maximum98
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2024-03-13T21:00:38.223499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum13
5-th percentile23.15
Q153.75
median76.5
Q386
95-th percentile94
Maximum98
Range85
Interquartile range (IQR)32.25

Descriptive statistics

Standard deviation22.848426
Coefficient of variation (CV)0.33177773
Kurtosis0.14502865
Mean68.866667
Median Absolute Deviation (MAD)13
Skewness-0.98419717
Sum2066
Variance522.05057
MonotonicityNot monotonic
2024-03-13T21:00:38.336860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
86 3
 
10.0%
61 2
 
6.7%
94 2
 
6.7%
47 2
 
6.7%
80 2
 
6.7%
75 2
 
6.7%
39 1
 
3.3%
72 1
 
3.3%
20 1
 
3.3%
91 1
 
3.3%
Other values (13) 13
43.3%
ValueCountFrequency (%)
13 1
3.3%
20 1
3.3%
27 1
3.3%
39 1
3.3%
47 2
6.7%
51 1
3.3%
53 1
3.3%
56 1
3.3%
61 2
6.7%
72 1
3.3%
ValueCountFrequency (%)
98 1
 
3.3%
94 2
6.7%
91 1
 
3.3%
88 1
 
3.3%
87 1
 
3.3%
86 3
10.0%
84 1
 
3.3%
82 1
 
3.3%
81 1
 
3.3%
80 2
6.7%

공급_전압
Real number (ℝ)

HIGH CORRELATION 

Distinct20
Distinct (%)66.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean637.93333
Minimum391
Maximum742
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2024-03-13T21:00:38.447776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum391
5-th percentile404
Q1612.25
median656
Q3708.25
95-th percentile738.85
Maximum742
Range351
Interquartile range (IQR)96

Descriptive statistics

Standard deviation93.457692
Coefficient of variation (CV)0.14650072
Kurtosis2.3944362
Mean637.93333
Median Absolute Deviation (MAD)44
Skewness-1.5514597
Sum19138
Variance8734.3402
MonotonicityNot monotonic
2024-03-13T21:00:38.593632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
612 4
 
13.3%
613 3
 
10.0%
663 2
 
6.7%
735 2
 
6.7%
742 2
 
6.7%
619 2
 
6.7%
404 2
 
6.7%
706 1
 
3.3%
711 1
 
3.3%
652 1
 
3.3%
Other values (10) 10
33.3%
ValueCountFrequency (%)
391 1
 
3.3%
404 2
6.7%
606 1
 
3.3%
612 4
13.3%
613 3
10.0%
616 1
 
3.3%
619 2
6.7%
652 1
 
3.3%
660 1
 
3.3%
663 2
6.7%
ValueCountFrequency (%)
742 2
6.7%
735 2
6.7%
729 1
3.3%
712 1
3.3%
711 1
3.3%
709 1
3.3%
706 1
3.3%
683 1
3.3%
681 1
3.3%
669 1
3.3%

공급_전류
Real number (ℝ)

HIGH CORRELATION 

Distinct10
Distinct (%)33.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean129.2
Minimum60
Maximum150
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2024-03-13T21:00:38.729338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum60
5-th percentile62.45
Q1117.25
median149
Q3149
95-th percentile150
Maximum150
Range90
Interquartile range (IQR)31.75

Descriptive statistics

Standard deviation33.844879
Coefficient of variation (CV)0.26195727
Kurtosis0.17996581
Mean129.2
Median Absolute Deviation (MAD)0.5
Skewness-1.3792631
Sum3876
Variance1145.4759
MonotonicityNot monotonic
2024-03-13T21:00:38.829994image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
149 15
50.0%
150 3
 
10.0%
63 3
 
10.0%
115 2
 
6.7%
148 2
 
6.7%
124 1
 
3.3%
147 1
 
3.3%
60 1
 
3.3%
83 1
 
3.3%
62 1
 
3.3%
ValueCountFrequency (%)
60 1
 
3.3%
62 1
 
3.3%
63 3
 
10.0%
83 1
 
3.3%
115 2
 
6.7%
124 1
 
3.3%
147 1
 
3.3%
148 2
 
6.7%
149 15
50.0%
150 3
 
10.0%
ValueCountFrequency (%)
150 3
 
10.0%
149 15
50.0%
148 2
 
6.7%
147 1
 
3.3%
124 1
 
3.3%
115 2
 
6.7%
83 1
 
3.3%
63 3
 
10.0%
62 1
 
3.3%
60 1
 
3.3%

비고
Categorical

CONSTANT 

Distinct1
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
2024-01-11 전기차 배터리 충전 공급 전압/전류
30 

Length

Max length30
Median length30
Mean length30
Min length30

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2024-01-11 전기차 배터리 충전 공급 전압/전류
2nd row2024-01-11 전기차 배터리 충전 공급 전압/전류
3rd row2024-01-11 전기차 배터리 충전 공급 전압/전류
4th row2024-01-11 전기차 배터리 충전 공급 전압/전류
5th row2024-01-11 전기차 배터리 충전 공급 전압/전류

Common Values

ValueCountFrequency (%)
2024-01-11 전기차 배터리 충전 공급 전압/전류 30
100.0%

Length

2024-03-13T21:00:38.943129image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T21:00:39.033161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2024-01-11 30
16.7%
전기차 30
16.7%
배터리 30
16.7%
충전 30
16.7%
공급 30
16.7%
전압/전류 30
16.7%

생산_일시
Categorical

CONSTANT 

Distinct1
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
2024-01-11 12:26:17
30 

Length

Max length19
Median length19
Mean length19
Min length19

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2024-01-11 12:26:17
2nd row2024-01-11 12:26:17
3rd row2024-01-11 12:26:17
4th row2024-01-11 12:26:17
5th row2024-01-11 12:26:17

Common Values

ValueCountFrequency (%)
2024-01-11 12:26:17 30
100.0%

Length

2024-03-13T21:00:39.134028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-13T21:00:39.255810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2024-01-11 30
50.0%
12:26:17 30
50.0%

Interactions

2024-03-13T21:00:34.207733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:00:32.353965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:00:32.893443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:00:33.355576image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:00:33.754359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:00:34.295353image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:00:32.451465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:00:33.024675image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:00:33.437227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:00:33.843082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:00:34.381938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:00:32.567275image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:00:33.118465image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:00:33.517513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:00:33.937908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:00:34.453269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:00:32.682161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:00:33.193123image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:00:33.589839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:00:34.025629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:00:34.531633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:00:32.789181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:00:33.279504image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:00:33.675532image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-13T21:00:34.121304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-13T21:00:39.363735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
충전_일시충전소_ID충전기_ID충전건시도_코드시군구_코드시도_명시군구_명시작_일시종료_일시시작_SOC공급_전압공급_전류
충전_일시1.0000.0000.0000.0000.0000.0000.0000.0000.8990.0000.3980.0000.375
충전소_ID0.0001.0001.0000.9021.0001.0001.0001.0000.8930.0000.5630.9721.000
충전기_ID0.0001.0001.0001.0001.0001.0001.0001.0000.9601.0000.9571.0001.000
충전건0.0000.9021.0001.0000.0000.2620.1930.7840.6040.0000.0000.2860.000
시도_코드0.0001.0001.0000.0001.0000.6841.0001.0000.9250.0000.5540.8710.829
시군구_코드0.0001.0001.0000.2620.6841.0000.8121.0000.7290.0000.5070.6640.000
시도_명0.0001.0001.0000.1931.0000.8121.0001.0000.9210.0000.5500.8710.604
시군구_명0.0001.0001.0000.7841.0001.0001.0001.0000.9300.0000.7190.9420.845
시작_일시0.8990.8930.9600.6040.9250.7290.9210.9301.0001.0000.9620.9290.965
종료_일시0.0000.0001.0000.0000.0000.0000.0000.0001.0001.0001.0000.000NaN
시작_SOC0.3980.5630.9570.0000.5540.5070.5500.7190.9621.0001.0000.4820.627
공급_전압0.0000.9721.0000.2860.8710.6640.8710.9420.9290.0000.4821.0000.722
공급_전류0.3751.0001.0000.0000.8290.0000.6040.8450.965NaN0.6270.7221.000
2024-03-13T21:00:39.531196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시도_명충전_일시시군구_명충전건
시도_명1.0000.0000.8160.103
충전_일시0.0001.0000.0000.000
시군구_명0.8160.0001.0000.469
충전건0.1030.0000.4691.000
2024-03-13T21:00:39.632709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시도_코드시군구_코드시작_SOC공급_전압공급_전류충전_일시충전건시도_명시군구_명
시도_코드1.000-0.4450.2240.1880.3410.0000.0000.9800.800
시군구_코드-0.4451.000-0.015-0.4200.3480.0000.2410.6340.834
시작_SOC0.224-0.0151.000-0.1860.0110.1380.0000.2720.329
공급_전압0.188-0.420-0.1861.000-0.0570.0260.3600.5250.682
공급_전류0.3410.3480.011-0.0571.0000.2870.0000.4490.506
충전_일시0.0000.0000.1380.0260.2871.0000.0000.0000.000
충전건0.0000.2410.0000.3600.0000.0001.0000.1030.469
시도_명0.9800.6340.2720.5250.4490.0000.1031.0000.816
시군구_명0.8000.8340.3290.6820.5060.0000.4690.8161.000

Missing values

2024-03-13T21:00:34.654545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-13T21:00:34.918068image/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

충전_일시충전소_ID충전기_ID충전건시도_코드시군구_코드시도_명시군구_명시작_일시종료_일시시작_SOC공급_전압공급_전류비고생산_일시
02023-10-01 00:00:00KRPPKCS0024KRPPKCP0172128260인천광역시서구2023-09-30 23:37:00<NA>567061492024-01-11 전기차 배터리 충전 공급 전압/전류2024-01-11 12:26:17
12023-10-01 00:00:00KRPPKCS0064KRPPKCP0463241117경기도수원시2023-09-30 22:32:56<NA>137091242024-01-11 전기차 배터리 충전 공급 전압/전류2024-01-11 12:26:17
22023-10-01 00:00:00KRPPKCS0090KRPPKCP0662141450경기도하남시2023-09-30 23:59:54<NA>946121492024-01-11 전기차 배터리 충전 공급 전압/전류2024-01-11 12:26:17
32023-10-01 00:00:00KRPPKCS0169KRPPKCP1097230200대전광역시유성구2023-09-30 22:31:57<NA>477351152024-01-11 전기차 배터리 충전 공급 전압/전류2024-01-11 12:26:17
42023-10-01 00:00:00KRPPKCS0116KRPPKCP0816230200대전광역시유성구2023-09-30 22:31:57<NA>477351152024-01-11 전기차 배터리 충전 공급 전압/전류2024-01-11 12:26:17
52023-10-01 00:00:00KRPPKCS0087KRPPKCP0650141150경기도의정부시2023-09-30 23:59:54<NA>946161492024-01-11 전기차 배터리 충전 공급 전압/전류2024-01-11 12:26:17
62023-10-01 00:00:00KRPPKCS0004KRPPKCP0022211170서울특별시용산구2023-09-30 23:42:01<NA>847421482024-01-11 전기차 배터리 충전 공급 전압/전류2024-01-11 12:26:17
72023-10-01 00:00:00KRPPKCS0089KRPPKCP0659141670경기도여주시2023-09-30 23:00:202023-10-01 00:00:00516131502024-01-11 전기차 배터리 충전 공급 전압/전류2024-01-11 12:26:17
82023-10-01 00:00:00KRPPKCS0113KRPPKCP0795248125경상남도창원시2023-09-30 23:49:582023-10-01 00:00:00816601492024-01-11 전기차 배터리 충전 공급 전압/전류2024-01-11 12:26:17
92023-10-01 00:00:00KRPPKCS0097KRPPKCP0710111650서울특별시서초구2023-09-30 23:59:44<NA>536831502024-01-11 전기차 배터리 충전 공급 전압/전류2024-01-11 12:26:17
충전_일시충전소_ID충전기_ID충전건시도_코드시군구_코드시도_명시군구_명시작_일시종료_일시시작_SOC공급_전압공급_전류비고생산_일시
202023-10-01 00:00:01KRPPKCS0084KRPPKCP0639241590경기도화성시2023-10-01 00:00:01<NA>756121492024-01-11 전기차 배터리 충전 공급 전압/전류2024-01-11 12:26:17
212023-10-01 00:00:01KRPPKCS0152KRPPKCP1050211620서울특별시관악구2023-09-30 23:59:55<NA>86404632024-01-11 전기차 배터리 충전 공급 전압/전류2024-01-11 12:26:17
222023-10-01 00:00:01KRPPKCS0087KRPPKCP0653141150경기도의정부시2023-09-30 23:59:55<NA>806061492024-01-11 전기차 배터리 충전 공급 전압/전류2024-01-11 12:26:17
232023-10-01 00:00:01KRPPKCS0089KRPPKCP0660141670경기도여주시2023-10-01 00:00:01<NA>746121492024-01-11 전기차 배터리 충전 공급 전압/전류2024-01-11 12:26:17
242023-10-01 00:00:02KRPPKCS0011KRPPKCP0082241210경기도광명시2023-09-30 23:44:03<NA>88712832024-01-11 전기차 배터리 충전 공급 전압/전류2024-01-11 12:26:17
252023-10-01 00:00:02KRPPKCS0084KRPPKCP0643241590경기도화성시2023-10-01 00:00:01<NA>616191492024-01-11 전기차 배터리 충전 공급 전압/전류2024-01-11 12:26:17
262023-10-01 00:00:02KRPPKCS0113KRPPKCP0797248125경상남도창원시2023-10-01 00:00:02<NA>916631492024-01-11 전기차 배터리 충전 공급 전압/전류2024-01-11 12:26:17
272023-10-01 00:00:02KRPPKCS0010KRPPKCP0407141111경기도수원시2023-09-30 23:02:24<NA>20652622024-01-11 전기차 배터리 충전 공급 전압/전류2024-01-11 12:26:17
282023-10-01 00:00:02KRPPKCS0149KRPPKCP1039148170경상남도진주시2023-09-30 23:59:53<NA>727111492024-01-11 전기차 배터리 충전 공급 전압/전류2024-01-11 12:26:17
292023-10-01 00:00:02KRPPKCS0084KRPPKCP0639241590경기도화성시2023-10-01 00:00:01<NA>756121492024-01-11 전기차 배터리 충전 공급 전압/전류2024-01-11 12:26:17