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 memory130.4 B

Variable types

Categorical6
Text3
Numeric5
DateTime1

Dataset

Description샘플 데이터
Author펌프킨
URLhttps://bigdata-region.kr/#/dataset/4c18bd03-8d7e-4df8-991b-e7c34b1bd1f6

Alerts

비고 has constant value ""Constant
생산_일시 has constant value ""Constant
시도_명 is highly overall correlated with 시도_코드 and 3 other fieldsHigh correlation
충전건 is highly overall correlated with 종료_일시High correlation
종료_일시 is highly overall correlated with 시도_코드 and 7 other fieldsHigh correlation
충전_일시 is highly overall correlated with 종료_일시High correlation
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
시작_SOC is highly overall correlated with 종료_일시High correlation
공급_전압 is highly overall correlated with 종료_일시High correlation
공급_전류 is highly overall correlated with 시도_명 and 1 other fieldsHigh correlation

Reproduction

Analysis started2023-12-10 14:09:50.367186
Analysis finished2023-12-10 14:09:56.994662
Duration6.63 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

충전_일시
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-07-01 00:00:00
26 
2023-07-01 00:00:01
4 

Length

Max length19
Median length19
Mean length19
Min length19

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-07-01 00:00:00
2nd row2023-07-01 00:00:00
3rd row2023-07-01 00:00:00
4th row2023-07-01 00:00:00
5th row2023-07-01 00:00:00

Common Values

ValueCountFrequency (%)
2023-07-01 00:00:00 26
86.7%
2023-07-01 00:00:01 4
 
13.3%

Length

2023-12-10T23:09:57.084096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:09:57.238155image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-07-01 30
50.0%
00:00:00 26
43.3%
00:00:01 4
 
6.7%

충전소_ID
Text

Distinct23
Distinct (%)76.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-12-10T23:09:57.516320image/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

Unique18 ?
Unique (%)60.0%

Sample

1st rowKRPPKCS0153
2nd rowKRPPKCS0113
3rd rowKRPPKCS0123
4th rowKRPPKCS0083
5th rowKRPPKCS0005
ValueCountFrequency (%)
krppkcs0087 3
 
10.0%
krppkcs0097 3
 
10.0%
krppkcs0083 2
 
6.7%
krppkcs0090 2
 
6.7%
krppkcs0149 2
 
6.7%
krppkcs0027 1
 
3.3%
krppkcs0153 1
 
3.3%
krppkcs0116 1
 
3.3%
krppkcs0051 1
 
3.3%
krppkcs0028 1
 
3.3%
Other values (13) 13
43.3%
2023-12-10T23:09:58.060843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
K 60
18.2%
P 60
18.2%
0 57
17.3%
R 30
9.1%
C 30
9.1%
S 30
9.1%
1 13
 
3.9%
8 11
 
3.3%
7 9
 
2.7%
9 9
 
2.7%
Other values (5) 21
 
6.4%

Most occurring categories

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

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 57
47.5%
1 13
 
10.8%
8 11
 
9.2%
7 9
 
7.5%
9 9
 
7.5%
3 6
 
5.0%
5 5
 
4.2%
4 4
 
3.3%
2 3
 
2.5%
6 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 57
47.5%
1 13
 
10.8%
8 11
 
9.2%
7 9
 
7.5%
9 9
 
7.5%
3 6
 
5.0%
5 5
 
4.2%
4 4
 
3.3%
2 3
 
2.5%
6 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 57
17.3%
R 30
9.1%
C 30
9.1%
S 30
9.1%
1 13
 
3.9%
8 11
 
3.3%
7 9
 
2.7%
9 9
 
2.7%
Other values (5) 21
 
6.4%

충전기_ID
Text

Distinct29
Distinct (%)96.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-12-10T23:09:58.391528image/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

Unique28 ?
Unique (%)93.3%

Sample

1st rowKRPPKCP1051
2nd rowKRPPKCP0797
3rd rowKRPPKCP0845
4th rowKRPPKCP0635
5th rowKRPPKCP0029
ValueCountFrequency (%)
krppkcp0711 2
 
6.7%
krppkcp1051 1
 
3.3%
krppkcp0650 1
 
3.3%
krppkcp1036 1
 
3.3%
krppkcp0325 1
 
3.3%
krppkcp0196 1
 
3.3%
krppkcp0658 1
 
3.3%
krppkcp0634 1
 
3.3%
krppkcp0604 1
 
3.3%
krppkcp0478 1
 
3.3%
Other values (19) 19
63.3%
2023-12-10T23:09:59.124692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
P 90
27.3%
K 60
18.2%
0 35
 
10.6%
R 30
 
9.1%
C 30
 
9.1%
6 19
 
5.8%
1 13
 
3.9%
3 11
 
3.3%
7 9
 
2.7%
5 9
 
2.7%
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 35
29.2%
6 19
15.8%
1 13
 
10.8%
3 11
 
9.2%
7 9
 
7.5%
5 9
 
7.5%
4 7
 
5.8%
9 7
 
5.8%
8 5
 
4.2%
2 5
 
4.2%
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 35
29.2%
6 19
15.8%
1 13
 
10.8%
3 11
 
9.2%
7 9
 
7.5%
5 9
 
7.5%
4 7
 
5.8%
9 7
 
5.8%
8 5
 
4.2%
2 5
 
4.2%
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 35
 
10.6%
R 30
 
9.1%
C 30
 
9.1%
6 19
 
5.8%
1 13
 
3.9%
3 11
 
3.3%
7 9
 
2.7%
5 9
 
2.7%
Other values (4) 24
 
7.3%

충전건
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
1
16 
2
14 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
1 16
53.3%
2 14
46.7%

Length

2023-12-10T23:09:59.489033image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:09:59.819831image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 16
53.3%
2 14
46.7%

시도_코드
Real number (ℝ)

HIGH CORRELATION 

Distinct6
Distinct (%)20.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.033333
Minimum11
Maximum48
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:10:00.003927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum11
5-th percentile11
Q128.5
median41
Q341
95-th percentile48
Maximum48
Range37
Interquartile range (IQR)12.5

Descriptive statistics

Standard deviation11.481569
Coefficient of variation (CV)0.32773271
Kurtosis0.28141503
Mean35.033333
Median Absolute Deviation (MAD)3.5
Skewness-1.117554
Sum1051
Variance131.82644
MonotonicityNot monotonic
2023-12-10T23:10:00.213732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
41 15
50.0%
48 4
 
13.3%
11 4
 
13.3%
28 3
 
10.0%
30 3
 
10.0%
26 1
 
3.3%
ValueCountFrequency (%)
11 4
 
13.3%
26 1
 
3.3%
28 3
 
10.0%
30 3
 
10.0%
41 15
50.0%
48 4
 
13.3%
ValueCountFrequency (%)
48 4
 
13.3%
41 15
50.0%
30 3
 
10.0%
28 3
 
10.0%
26 1
 
3.3%
11 4
 
13.3%

시군구_코드
Real number (ℝ)

HIGH CORRELATION 

Distinct17
Distinct (%)56.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean311.5
Minimum111
Maximum670
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:10:00.435233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum111
5-th percentile117
Q1150
median215
Q3450
95-th percentile650
Maximum670
Range559
Interquartile range (IQR)300

Descriptive statistics

Standard deviation200.67984
Coefficient of variation (CV)0.64423703
Kurtosis-1.0654784
Mean311.5
Median Absolute Deviation (MAD)95
Skewness0.75180532
Sum9345
Variance40272.397
MonotonicityNot monotonic
2023-12-10T23:10:00.622116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=17)
ValueCountFrequency (%)
260 3
10.0%
117 3
10.0%
590 3
10.0%
150 3
10.0%
650 3
10.0%
200 2
 
6.7%
450 2
 
6.7%
170 2
 
6.7%
410 1
 
3.3%
360 1
 
3.3%
Other values (7) 7
23.3%
ValueCountFrequency (%)
111 1
 
3.3%
117 3
10.0%
123 1
 
3.3%
125 1
 
3.3%
150 3
10.0%
170 2
6.7%
185 1
 
3.3%
190 1
 
3.3%
200 2
6.7%
230 1
 
3.3%
ValueCountFrequency (%)
670 1
 
3.3%
650 3
10.0%
590 3
10.0%
450 2
6.7%
410 1
 
3.3%
360 1
 
3.3%
260 3
10.0%
230 1
 
3.3%
200 2
6.7%
190 1
 
3.3%

시도_명
Categorical

HIGH CORRELATION 

Distinct6
Distinct (%)20.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
경기도
15 
경상남도
4 
서울특별시
4 
인천광역시
3 
대전광역시
3 

Length

Max length5
Median length4.5
Mean length3.8666667
Min length3

Unique

Unique1 ?
Unique (%)3.3%

Sample

1st row부산광역시
2nd row경상남도
3rd row인천광역시
4th row경기도
5th row경기도

Common Values

ValueCountFrequency (%)
경기도 15
50.0%
경상남도 4
 
13.3%
서울특별시 4
 
13.3%
인천광역시 3
 
10.0%
대전광역시 3
 
10.0%
부산광역시 1
 
3.3%

Length

2023-12-10T23:10:00.824984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:10:01.018893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
경기도 15
50.0%
경상남도 4
 
13.3%
서울특별시 4
 
13.3%
인천광역시 3
 
10.0%
대전광역시 3
 
10.0%
부산광역시 1
 
3.3%

시군구_명
Text

Distinct16
Distinct (%)53.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-12-10T23:10:01.275398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length3.0666667
Min length2

Characters and Unicode

Total characters92
Distinct characters26
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique7 ?
Unique (%)23.3%

Sample

1st row금정구
2nd row창원시
3rd row서구
4th row수원시
5th row화성시
ValueCountFrequency (%)
수원시 4
13.3%
화성시 3
10.0%
의정부시 3
10.0%
서초구 3
10.0%
창원시 2
 
6.7%
서구 2
 
6.7%
유성구 2
 
6.7%
하남시 2
 
6.7%
진주시 2
 
6.7%
금정구 1
 
3.3%
Other values (6) 6
20.0%
2023-12-10T23:10:01.773653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
시 19
20.7%
구 11
12.0%
원 6
 
6.5%
수 5
 
5.4%
성 5
 
5.4%
서 5
 
5.4%
정 4
 
4.3%
부 4
 
4.3%
주 4
 
4.3%
남 3
 
3.3%
Other values (16) 26
28.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 92
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 19
20.7%
구 11
12.0%
원 6
 
6.5%
수 5
 
5.4%
성 5
 
5.4%
서 5
 
5.4%
정 4
 
4.3%
부 4
 
4.3%
주 4
 
4.3%
남 3
 
3.3%
Other values (16) 26
28.3%

Most occurring scripts

ValueCountFrequency (%)
Hangul 92
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 19
20.7%
구 11
12.0%
원 6
 
6.5%
수 5
 
5.4%
성 5
 
5.4%
서 5
 
5.4%
정 4
 
4.3%
부 4
 
4.3%
주 4
 
4.3%
남 3
 
3.3%
Other values (16) 26
28.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 92
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
시 19
20.7%
구 11
12.0%
원 6
 
6.5%
수 5
 
5.4%
성 5
 
5.4%
서 5
 
5.4%
정 4
 
4.3%
부 4
 
4.3%
주 4
 
4.3%
남 3
 
3.3%
Other values (16) 26
28.3%

시작_일시
Date

Distinct16
Distinct (%)53.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
Minimum2023-06-30 21:56:54
Maximum2023-07-01 00:00:01
2023-12-10T23:10:01.967432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:10:02.188175image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)

종료_일시
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
<NA>
26 
2023-07-01 00:00:00
4 

Length

Max length19
Median length4
Mean length6
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-07-01 00:00:00
2nd row2023-07-01 00:00:00
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 26
86.7%
2023-07-01 00:00:00 4
 
13.3%

Length

2023-12-10T23:10:02.378386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:10:02.580374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 26
76.5%
2023-07-01 4
 
11.8%
00:00:00 4
 
11.8%

시작_SOC
Real number (ℝ)

HIGH CORRELATION 

Distinct23
Distinct (%)76.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean58
Minimum10
Maximum98
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:10:02.743770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10
5-th percentile21.3
Q146
median58.5
Q377
95-th percentile91.95
Maximum98
Range88
Interquartile range (IQR)31

Descriptive statistics

Standard deviation22.618272
Coefficient of variation (CV)0.3899702
Kurtosis-0.462042
Mean58
Median Absolute Deviation (MAD)15
Skewness-0.18103813
Sum1740
Variance511.58621
MonotonicityNot monotonic
2023-12-10T23:10:02.933942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
62 3
 
10.0%
49 3
 
10.0%
29 2
 
6.7%
46 2
 
6.7%
83 2
 
6.7%
44 1
 
3.3%
96 1
 
3.3%
10 1
 
3.3%
98 1
 
3.3%
50 1
 
3.3%
Other values (13) 13
43.3%
ValueCountFrequency (%)
10 1
 
3.3%
15 1
 
3.3%
29 2
6.7%
34 1
 
3.3%
37 1
 
3.3%
44 1
 
3.3%
46 2
6.7%
49 3
10.0%
50 1
 
3.3%
52 1
 
3.3%
ValueCountFrequency (%)
98 1
3.3%
96 1
3.3%
87 1
3.3%
83 2
6.7%
82 1
3.3%
80 1
3.3%
78 1
3.3%
74 1
3.3%
72 1
3.3%
65 1
3.3%

공급_전압
Real number (ℝ)

HIGH CORRELATION 

Distinct25
Distinct (%)83.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean683.1
Minimum406
Maximum794
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:10:03.164680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum406
5-th percentile602.8
Q1639.25
median702
Q3730
95-th percentile772.5
Maximum794
Range388
Interquartile range (IQR)90.75

Descriptive statistics

Standard deviation76.414636
Coefficient of variation (CV)0.11186449
Kurtosis4.7050258
Mean683.1
Median Absolute Deviation (MAD)38.5
Skewness-1.6536796
Sum20493
Variance5839.1966
MonotonicityNot monotonic
2023-12-10T23:10:03.392768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
702 2
 
6.7%
716 2
 
6.7%
731 2
 
6.7%
607 2
 
6.7%
696 2
 
6.7%
611 1
 
3.3%
643 1
 
3.3%
748 1
 
3.3%
638 1
 
3.3%
794 1
 
3.3%
Other values (15) 15
50.0%
ValueCountFrequency (%)
406 1
3.3%
601 1
3.3%
605 1
3.3%
607 2
6.7%
611 1
3.3%
612 1
3.3%
638 1
3.3%
643 1
3.3%
666 1
3.3%
670 1
3.3%
ValueCountFrequency (%)
794 1
3.3%
786 1
3.3%
756 1
3.3%
748 1
3.3%
744 1
3.3%
743 1
3.3%
731 2
6.7%
727 1
3.3%
726 1
3.3%
721 1
3.3%

공급_전류
Real number (ℝ)

HIGH CORRELATION 

Distinct11
Distinct (%)36.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean131.63333
Minimum25
Maximum150
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:10:03.580688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum25
5-th percentile90
Q1124.25
median149
Q3150
95-th percentile150
Maximum150
Range125
Interquartile range (IQR)25.75

Descriptive statistics

Standard deviation27.894485
Coefficient of variation (CV)0.2119105
Kurtosis6.3701848
Mean131.63333
Median Absolute Deviation (MAD)1
Skewness-2.2337542
Sum3949
Variance778.1023
MonotonicityNot monotonic
2023-12-10T23:10:03.794689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=11)
ValueCountFrequency (%)
150 10
33.3%
149 7
23.3%
125 3
 
10.0%
115 2
 
6.7%
90 2
 
6.7%
25 1
 
3.3%
99 1
 
3.3%
129 1
 
3.3%
124 1
 
3.3%
111 1
 
3.3%
ValueCountFrequency (%)
25 1
 
3.3%
90 2
 
6.7%
99 1
 
3.3%
111 1
 
3.3%
115 2
 
6.7%
124 1
 
3.3%
125 3
10.0%
129 1
 
3.3%
133 1
 
3.3%
149 7
23.3%
ValueCountFrequency (%)
150 10
33.3%
149 7
23.3%
133 1
 
3.3%
129 1
 
3.3%
125 3
 
10.0%
124 1
 
3.3%
115 2
 
6.7%
111 1
 
3.3%
99 1
 
3.3%
90 2
 
6.7%

비고
Categorical

CONSTANT 

Distinct1
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-10-16 전기차 배터리 충전 공급 전압/전류
30 

Length

Max length30
Median length30
Mean length30
Min length30

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-10-16 전기차 배터리 충전 공급 전압/전류
2nd row2023-10-16 전기차 배터리 충전 공급 전압/전류
3rd row2023-10-16 전기차 배터리 충전 공급 전압/전류
4th row2023-10-16 전기차 배터리 충전 공급 전압/전류
5th row2023-10-16 전기차 배터리 충전 공급 전압/전류

Common Values

ValueCountFrequency (%)
2023-10-16 전기차 배터리 충전 공급 전압/전류 30
100.0%

Length

2023-12-10T23:10:04.027816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:10:04.200553image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-10-16 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
2023-10-16 13:33:31
30 

Length

Max length19
Median length19
Mean length19
Min length19

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-10-16 13:33:31
2nd row2023-10-16 13:33:31
3rd row2023-10-16 13:33:31
4th row2023-10-16 13:33:31
5th row2023-10-16 13:33:31

Common Values

ValueCountFrequency (%)
2023-10-16 13:33:31 30
100.0%

Length

2023-12-10T23:10:04.470293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:10:04.610965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-10-16 30
50.0%
13:33:31 30
50.0%

Interactions

2023-12-10T23:09:55.152654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:09:51.207454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:09:51.942770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:09:53.064239image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:09:54.060051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:09:55.323920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:09:51.385584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:09:52.170530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:09:53.327887image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:09:54.329489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:09:55.869594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:09:51.515653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:09:52.359153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:09:53.480244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:09:54.552987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:09:56.063456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:09:51.638491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:09:52.599863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:09:53.631315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:09:54.740725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:09:56.259484image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:09:51.807773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:09:52.806350image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:09:53.815650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:09:54.948524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T23:10:04.741904image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
충전_일시충전소_ID충전기_ID충전건시도_코드시군구_코드시도_명시군구_명시작_일시시작_SOC공급_전압공급_전류
충전_일시1.0000.0000.0000.0000.2680.0000.3700.0000.8670.0000.0000.000
충전소_ID0.0001.0001.0000.6501.0001.0001.0001.0000.9160.7660.8660.975
충전기_ID0.0001.0001.0001.0001.0001.0001.0001.0000.0000.9331.0001.000
충전건0.0000.6501.0001.0000.3780.0000.5850.4570.9810.4190.3330.432
시도_코드0.2681.0001.0000.3781.0000.6221.0001.0000.8520.3480.6590.586
시군구_코드0.0001.0001.0000.0000.6221.0000.7671.0000.7120.4140.4830.794
시도_명0.3701.0001.0000.5851.0000.7671.0001.0000.9060.5170.6590.922
시군구_명0.0001.0001.0000.4571.0001.0001.0001.0000.8580.5760.6730.933
시작_일시0.8670.9160.0000.9810.8520.7120.9060.8581.0000.7150.7480.833
시작_SOC0.0000.7660.9330.4190.3480.4140.5170.5760.7151.0000.7440.623
공급_전압0.0000.8661.0000.3330.6590.4830.6590.6730.7480.7441.0000.711
공급_전류0.0000.9751.0000.4320.5860.7940.9220.9330.8330.6230.7111.000
2023-12-10T23:10:04.945647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시도_명충전건종료_일시충전_일시
시도_명1.0000.3871.0000.235
충전건0.3871.0001.0000.000
종료_일시1.0001.0001.0001.000
충전_일시0.2350.0001.0001.000
2023-12-10T23:10:05.114024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시도_코드시군구_코드시작_SOC공급_전압공급_전류충전_일시충전건시도_명종료_일시
시도_코드1.000-0.4910.245-0.0500.1180.3020.4310.9801.000
시군구_코드-0.4911.0000.039-0.0850.2590.0000.0000.5341.000
시작_SOC0.2450.0391.0000.4130.3000.0000.3520.2481.000
공급_전압-0.050-0.0850.4131.000-0.1020.0000.3760.4911.000
공급_전류0.1180.2590.300-0.1021.0000.0000.2790.5961.000
충전_일시0.3020.0000.0000.0000.0001.0000.0000.2351.000
충전건0.4310.0000.3520.3760.2790.0001.0000.3871.000
시도_명0.9800.5340.2480.4910.5960.2350.3871.0001.000
종료_일시1.0001.0001.0001.0001.0001.0001.0001.0001.000

Missing values

2023-12-10T23:09:56.568633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T23:09:56.882757image/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
02023-07-01 00:00:00KRPPKCS0153KRPPKCP1051226410부산광역시금정구2023-06-30 22:52:382023-07-01 00:00:0044406252023-10-16 전기차 배터리 충전 공급 전압/전류2023-10-16 13:33:31
12023-07-01 00:00:00KRPPKCS0113KRPPKCP0797148125경상남도창원시2023-06-30 23:48:312023-07-01 00:00:00836661492023-10-16 전기차 배터리 충전 공급 전압/전류2023-10-16 13:33:31
22023-07-01 00:00:00KRPPKCS0123KRPPKCP0845228260인천광역시서구2023-06-30 22:46:43<NA>56677992023-10-16 전기차 배터리 충전 공급 전압/전류2023-10-16 13:33:31
32023-07-01 00:00:00KRPPKCS0083KRPPKCP0635141117경기도수원시2023-06-30 23:59:59<NA>617431252023-10-16 전기차 배터리 충전 공급 전압/전류2023-10-16 13:33:31
42023-07-01 00:00:00KRPPKCS0005KRPPKCP0029241590경기도화성시2023-06-30 23:31:00<NA>627161502023-10-16 전기차 배터리 충전 공급 전압/전류2023-10-16 13:33:31
52023-07-01 00:00:00KRPPKCS0169KRPPKCP1097230200대전광역시유성구2023-06-30 21:56:54<NA>297311152023-10-16 전기차 배터리 충전 공급 전압/전류2023-10-16 13:33:31
62023-07-01 00:00:00KRPPKCS0087KRPPKCP0657141150경기도의정부시2023-07-01 00:00:00<NA>877861502023-10-16 전기차 배터리 충전 공급 전압/전류2023-10-16 13:33:31
72023-07-01 00:00:00KRPPKCS0084KRPPKCP0639141590경기도화성시2023-06-30 23:59:59<NA>466051502023-10-16 전기차 배터리 충전 공급 전압/전류2023-10-16 13:33:31
82023-07-01 00:00:00KRPPKCS0087KRPPKCP0656241150경기도의정부시2023-07-01 00:00:00<NA>786121492023-10-16 전기차 배터리 충전 공급 전압/전류2023-10-16 13:33:31
92023-07-01 00:00:00KRPPKCS0085KRPPKCP0645141590경기도화성시2023-06-30 23:59:59<NA>657561252023-10-16 전기차 배터리 충전 공급 전압/전류2023-10-16 13:33:31
충전_일시충전소_ID충전기_ID충전건시도_코드시군구_코드시도_명시군구_명시작_일시종료_일시시작_SOC공급_전압공급_전류비고생산_일시
202023-07-01 00:00:00KRPPKCS0149KRPPKCP1039148170경상남도진주시2023-07-01 00:00:00<NA>747151492023-10-16 전기차 배터리 충전 공급 전압/전류2023-10-16 13:33:31
212023-07-01 00:00:00KRPPKCS0064KRPPKCP0478141117경기도수원시2023-06-30 23:05:58<NA>156701292023-10-16 전기차 배터리 충전 공급 전압/전류2023-10-16 13:33:31
222023-07-01 00:00:00KRPPKCS0075KRPPKCP0604211260서울특별시중랑구2023-06-30 23:31:00<NA>627161502023-10-16 전기차 배터리 충전 공급 전압/전류2023-10-16 13:33:31
232023-07-01 00:00:00KRPPKCS0083KRPPKCP0634141117경기도수원시2023-07-01 00:00:00<NA>377211242023-10-16 전기차 배터리 충전 공급 전압/전류2023-10-16 13:33:31
242023-07-01 00:00:00KRPPKCS0088KRPPKCP0658141360경기도남양주시2023-06-30 23:59:58<NA>837941112023-10-16 전기차 배터리 충전 공급 전압/전류2023-10-16 13:33:31
252023-07-01 00:00:00KRPPKCS0028KRPPKCP0196228185인천광역시연수구2023-06-30 23:01:47<NA>49702902023-10-16 전기차 배터리 충전 공급 전압/전류2023-10-16 13:33:31
262023-07-01 00:00:01KRPPKCS0097KRPPKCP0711211650서울특별시서초구2023-07-01 00:00:01<NA>626961502023-10-16 전기차 배터리 충전 공급 전압/전류2023-10-16 13:33:31
272023-07-01 00:00:01KRPPKCS0051KRPPKCP0325248123경상남도창원시2023-06-30 23:27:32<NA>506381502023-10-16 전기차 배터리 충전 공급 전압/전류2023-10-16 13:33:31
282023-07-01 00:00:01KRPPKCS0149KRPPKCP1036148170경상남도진주시2023-06-30 23:59:59<NA>987481332023-10-16 전기차 배터리 충전 공급 전압/전류2023-10-16 13:33:31
292023-07-01 00:00:01KRPPKCS0010KRPPKCP0392241111경기도수원시2023-06-30 23:37:44<NA>106431252023-10-16 전기차 배터리 충전 공급 전압/전류2023-10-16 13:33:31