Overview

Dataset statistics

Number of variables19
Number of observations892
Missing cells347
Missing cells (%)2.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory137.8 KiB
Average record size in memory158.1 B

Variable types

Numeric4
Text3
Categorical12

Dataset

Description대전광역시 유성구 전기차 충전소 현황에 대한 데이터로 충전소이름, 충전기타입, 이용가능시간 등의 항목을 제공합니다.
Author대전광역시 유성구
URLhttps://www.data.go.kr/data/15108928/fileData.do

Alerts

시도코드 has constant value ""Constant
시도이름 has constant value ""Constant
시군구코드 has constant value ""Constant
시군구이름 has constant value ""Constant
기준일자 has constant value ""Constant
행정동이름 is highly overall correlated with 번호 and 4 other fieldsHigh correlation
충전기타입 is highly overall correlated with 급속충전량 and 1 other fieldsHigh correlation
운영기관 is highly overall correlated with 충전기타입 and 3 other fieldsHigh correlation
급속충전량 is highly overall correlated with 충전기아이디 and 3 other fieldsHigh correlation
법정동이름 is highly overall correlated with 번호 and 3 other fieldsHigh correlation
번호 is highly overall correlated with 행정동코드 and 2 other fieldsHigh correlation
충전기아이디 is highly overall correlated with 급속충전량High correlation
행정동코드 is highly overall correlated with 번호 and 3 other fieldsHigh correlation
법정동코드 is highly overall correlated with 행정동코드 and 2 other fieldsHigh correlation
이용가능시간 is highly overall correlated with 운영기관 and 1 other fieldsHigh correlation
비고 is highly overall correlated with 이용가능시간 and 1 other fieldsHigh correlation
충전기타입 is highly imbalanced (61.9%)Imbalance
이용가능시간 is highly imbalanced (61.7%)Imbalance
급속충전량 is highly imbalanced (88.3%)Imbalance
상세위치 has 347 (38.9%) missing valuesMissing
번호 has unique valuesUnique

Reproduction

Analysis started2023-12-12 15:59:45.339872
Analysis finished2023-12-12 15:59:48.884749
Duration3.54 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct892
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean446.5
Minimum1
Maximum892
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size8.0 KiB
2023-12-13T00:59:48.978151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile45.55
Q1223.75
median446.5
Q3669.25
95-th percentile847.45
Maximum892
Range891
Interquartile range (IQR)445.5

Descriptive statistics

Standard deviation257.64252
Coefficient of variation (CV)0.57702691
Kurtosis-1.2
Mean446.5
Median Absolute Deviation (MAD)223
Skewness0
Sum398278
Variance66379.667
MonotonicityNot monotonic
2023-12-13T00:59:49.152951image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
12 1
 
0.1%
190 1
 
0.1%
124 1
 
0.1%
125 1
 
0.1%
126 1
 
0.1%
127 1
 
0.1%
128 1
 
0.1%
129 1
 
0.1%
143 1
 
0.1%
151 1
 
0.1%
Other values (882) 882
98.9%
ValueCountFrequency (%)
1 1
0.1%
2 1
0.1%
3 1
0.1%
4 1
0.1%
5 1
0.1%
6 1
0.1%
7 1
0.1%
8 1
0.1%
9 1
0.1%
10 1
0.1%
ValueCountFrequency (%)
892 1
0.1%
891 1
0.1%
890 1
0.1%
889 1
0.1%
888 1
0.1%
887 1
0.1%
886 1
0.1%
885 1
0.1%
884 1
0.1%
883 1
0.1%

충전소이름
Text

Distinct292
Distinct (%)32.7%
Missing0
Missing (%)0.0%
Memory size7.1 KiB
2023-12-13T00:59:49.461818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length24
Mean length10.982063
Min length3

Characters and Unicode

Total characters9796
Distinct characters318
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique68 ?
Unique (%)7.6%

Sample

1st row롯데마트 대덕테크노밸리점
2nd row대전테크노파크 주차장
3rd rowKT가정빌딩
4th row현대자동차(반석점)
5th row롯데마트 노은점
ValueCountFrequency (%)
대전유성 50
 
3.9%
아파트 46
 
3.6%
유성구 42
 
3.3%
대전시 40
 
3.1%
대전 33
 
2.6%
신세계백화점 19
 
1.5%
송림마을5단지e그리운아파트 16
 
1.2%
입주자대표회의 14
 
1.1%
죽동대원칸타빌아파트 13
 
1.0%
주차장 11
 
0.9%
Other values (327) 996
77.8%
2023-12-13T00:59:49.916908image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
389
 
4.0%
트 385
 
3.9%
아 375
 
3.8%
대 364
 
3.7%
파 358
 
3.7%
지 351
 
3.6%
단 273
 
2.8%
전 220
 
2.2%
1 188
 
1.9%
마 168
 
1.7%
Other values (308) 6725
68.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8485
86.6%
Decimal Number 683
 
7.0%
Space Separator 389
 
4.0%
Uppercase Letter 100
 
1.0%
Dash Punctuation 50
 
0.5%
Open Punctuation 24
 
0.2%
Close Punctuation 24
 
0.2%
Lowercase Letter 21
 
0.2%
Connector Punctuation 13
 
0.1%
Other Symbol 7
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
트 385
 
4.5%
아 375
 
4.4%
대 364
 
4.3%
파 358
 
4.2%
지 351
 
4.1%
단 273
 
3.2%
전 220
 
2.6%
마 168
 
2.0%
성 165
 
1.9%
유 158
 
1.9%
Other values (271) 5668
66.8%
Uppercase Letter
ValueCountFrequency (%)
S 17
17.0%
L 15
15.0%
K 12
12.0%
B 9
9.0%
G 8
8.0%
H 8
8.0%
J 6
 
6.0%
C 5
 
5.0%
I 4
 
4.0%
T 4
 
4.0%
Other values (6) 12
12.0%
Decimal Number
ValueCountFrequency (%)
1 188
27.5%
2 118
17.3%
0 80
11.7%
7 49
 
7.2%
6 47
 
6.9%
3 45
 
6.6%
4 43
 
6.3%
5 42
 
6.1%
8 36
 
5.3%
9 35
 
5.1%
Lowercase Letter
ValueCountFrequency (%)
e 17
81.0%
t 1
 
4.8%
s 1
 
4.8%
o 1
 
4.8%
v 1
 
4.8%
Space Separator
ValueCountFrequency (%)
389
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 50
100.0%
Open Punctuation
ValueCountFrequency (%)
( 24
100.0%
Close Punctuation
ValueCountFrequency (%)
) 24
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 13
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 8492
86.7%
Common 1183
 
12.1%
Latin 121
 
1.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
트 385
 
4.5%
아 375
 
4.4%
대 364
 
4.3%
파 358
 
4.2%
지 351
 
4.1%
단 273
 
3.2%
전 220
 
2.6%
마 168
 
2.0%
성 165
 
1.9%
유 158
 
1.9%
Other values (272) 5675
66.8%
Latin
ValueCountFrequency (%)
S 17
14.0%
e 17
14.0%
L 15
12.4%
K 12
9.9%
B 9
7.4%
G 8
 
6.6%
H 8
 
6.6%
J 6
 
5.0%
C 5
 
4.1%
I 4
 
3.3%
Other values (11) 20
16.5%
Common
ValueCountFrequency (%)
389
32.9%
1 188
15.9%
2 118
 
10.0%
0 80
 
6.8%
- 50
 
4.2%
7 49
 
4.1%
6 47
 
4.0%
3 45
 
3.8%
4 43
 
3.6%
5 42
 
3.6%
Other values (5) 132
 
11.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 8485
86.6%
ASCII 1304
 
13.3%
None 7
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
389
29.8%
1 188
14.4%
2 118
 
9.0%
0 80
 
6.1%
- 50
 
3.8%
7 49
 
3.8%
6 47
 
3.6%
3 45
 
3.5%
4 43
 
3.3%
5 42
 
3.2%
Other values (26) 253
19.4%
Hangul
ValueCountFrequency (%)
트 385
 
4.5%
아 375
 
4.4%
대 364
 
4.3%
파 358
 
4.2%
지 351
 
4.1%
단 273
 
3.2%
전 220
 
2.6%
마 168
 
2.0%
성 165
 
1.9%
유 158
 
1.9%
Other values (271) 5668
66.8%
None
ValueCountFrequency (%)
㈜ 7
100.0%

충전기타입
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct4
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size7.1 KiB
AC완속
770 
DC차데모+AC3상+DC콤보
 
66
DC콤보
 
42
DC차데모+DC콤보
 
14

Length

Max length15
Median length4
Mean length4.9080717
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowDC차데모+AC3상+DC콤보
2nd rowDC차데모+AC3상+DC콤보
3rd rowDC차데모+AC3상+DC콤보
4th rowDC차데모+AC3상+DC콤보
5th rowDC차데모+AC3상+DC콤보

Common Values

ValueCountFrequency (%)
AC완속 770
86.3%
DC차데모+AC3상+DC콤보 66
 
7.4%
DC콤보 42
 
4.7%
DC차데모+DC콤보 14
 
1.6%

Length

2023-12-13T00:59:50.111753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T00:59:50.233136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
ac완속 770
86.3%
dc차데모+ac3상+dc콤보 66
 
7.4%
dc콤보 42
 
4.7%
dc차데모+dc콤보 14
 
1.6%

충전기아이디
Real number (ℝ)

HIGH CORRELATION 

Distinct27
Distinct (%)3.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.5302691
Minimum1
Maximum44
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size8.0 KiB
2023-12-13T00:59:50.384361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile1
Q11
median2
Q34
95-th percentile10
Maximum44
Range43
Interquartile range (IQR)3

Descriptive statistics

Standard deviation4.5512646
Coefficient of variation (CV)1.2892118
Kurtosis31.050915
Mean3.5302691
Median Absolute Deviation (MAD)1
Skewness4.7908213
Sum3149
Variance20.71401
MonotonicityNot monotonic
2023-12-13T00:59:50.917665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
1 289
32.4%
2 220
24.7%
3 122
13.7%
4 76
 
8.5%
5 50
 
5.6%
6 32
 
3.6%
7 22
 
2.5%
8 18
 
2.0%
9 12
 
1.3%
12 8
 
0.9%
Other values (17) 43
 
4.8%
ValueCountFrequency (%)
1 289
32.4%
2 220
24.7%
3 122
13.7%
4 76
 
8.5%
5 50
 
5.6%
6 32
 
3.6%
7 22
 
2.5%
8 18
 
2.0%
9 12
 
1.3%
10 8
 
0.9%
ValueCountFrequency (%)
44 1
 
0.1%
43 1
 
0.1%
42 1
 
0.1%
41 1
 
0.1%
32 2
0.2%
31 2
0.2%
22 4
0.4%
21 4
0.4%
19 1
 
0.1%
18 1
 
0.1%

이용가능시간
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct19
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Memory size7.1 KiB
24시간 이용가능
603 
<NA>
128 
09:00~18:00
101 
정상영업 10:30~20:00 연장영업 10:30~20:30
 
19
~
 
7
Other values (14)
 
34

Length

Max length33
Median length9
Mean length9.0100897
Min length1

Unique

Unique5 ?
Unique (%)0.6%

Sample

1st row24시간 이용가능
2nd row24시간 이용가능
3rd row24시간 이용가능
4th row24시간 이용가능
5th row10:00~23:00

Common Values

ValueCountFrequency (%)
24시간 이용가능 603
67.6%
<NA> 128
 
14.3%
09:00~18:00 101
 
11.3%
정상영업 10:30~20:00 연장영업 10:30~20:30 19
 
2.1%
~ 7
 
0.8%
09시~18시 5
 
0.6%
주중:09시~18시 4
 
0.4%
주중/주말 : 06시~23시 4
 
0.4%
09:00~18:30 4
 
0.4%
09:00~16:30 3
 
0.3%
Other values (9) 14
 
1.6%

Length

2023-12-13T00:59:51.095770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
24시간 603
38.6%
이용가능 603
38.6%
na 128
 
8.2%
09:00~18:00 101
 
6.5%
정상영업 19
 
1.2%
10:30~20:00 19
 
1.2%
연장영업 19
 
1.2%
10:30~20:30 19
 
1.2%
11
 
0.7%
09시~18시 5
 
0.3%
Other values (15) 34
 
2.2%

급속충전량
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct6
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size7.1 KiB
<NA>
858 
급속(200kW동시)
 
14
급속(50kW)
 
13
급속(400kW동시)
 
4
급속(100kW동시)
 
2

Length

Max length11
Median length4
Mean length4.2230942
Min length4

Unique

Unique1 ?
Unique (%)0.1%

Sample

1st row급속(50kW)
2nd row급속(50kW)
3rd row급속(50kW)
4th row급속(50kW)
5th row급속(50kW)

Common Values

ValueCountFrequency (%)
<NA> 858
96.2%
급속(200kW동시) 14
 
1.6%
급속(50kW) 13
 
1.5%
급속(400kW동시) 4
 
0.4%
급속(100kW동시) 2
 
0.2%
급속(100kW멀티) 1
 
0.1%

Length

2023-12-13T00:59:51.288686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T00:59:51.436884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 858
96.2%
급속(200kw동시 14
 
1.6%
급속(50kw 13
 
1.5%
급속(400kw동시 4
 
0.4%
급속(100kw동시 2
 
0.2%
급속(100kw멀티 1
 
0.1%

운영기관
Categorical

HIGH CORRELATION 

Distinct22
Distinct (%)2.5%
Missing0
Missing (%)0.0%
Memory size7.1 KiB
파워큐브
227 
한국전력
133 
차지비
118 
에버온
112 
대영채비
67 
Other values (17)
235 

Length

Max length14
Median length4
Mean length4.6704036
Min length2

Unique

Unique3 ?
Unique (%)0.3%

Sample

1st row환경부(한국자동차환경협회)
2nd row환경부(한국자동차환경협회)
3rd row환경부(한국자동차환경협회)
4th row환경부(한국자동차환경협회)
5th row환경부(한국자동차환경협회)

Common Values

ValueCountFrequency (%)
파워큐브 227
25.4%
한국전력 133
14.9%
차지비 118
13.2%
에버온 112
12.6%
대영채비 67
 
7.5%
지커넥트 42
 
4.7%
환경부(한국자동차환경협회) 34
 
3.8%
제주전기자동차서비스 31
 
3.5%
한국전기차충전서비스 25
 
2.8%
스타코프 24
 
2.7%
Other values (12) 79
 
8.9%

Length

2023-12-13T00:59:51.601052image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
파워큐브 227
25.4%
한국전력 133
14.9%
차지비 118
13.2%
에버온 112
12.6%
대영채비 67
 
7.5%
지커넥트 42
 
4.7%
환경부(한국자동차환경협회 34
 
3.8%
제주전기자동차서비스 31
 
3.5%
한국전기차충전서비스 25
 
2.8%
스타코프 24
 
2.7%
Other values (12) 79
 
8.9%

비고
Categorical

HIGH CORRELATION 

Distinct18
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size7.1 KiB
거주자외 출입제한
294 
<NA>
240 
시설 상황에 따라 이용이 제한될 수 있음
151 
입주민만 사용가능 거주자외 출입제한
102 
입주민 등 거주자 외 출입 제한
 
29
Other values (13)
76 

Length

Max length31
Median length30
Mean length12.054933
Min length4

Unique

Unique3 ?
Unique (%)0.3%

Sample

1st row주차요금 별도
2nd row주차요금 별도
3rd row주차요금 별도
4th row주차요금 별도
5th row주차요금 별도

Common Values

ValueCountFrequency (%)
거주자외 출입제한 294
33.0%
<NA> 240
26.9%
시설 상황에 따라 이용이 제한될 수 있음 151
16.9%
입주민만 사용가능 거주자외 출입제한 102
 
11.4%
입주민 등 거주자 외 출입 제한 29
 
3.3%
사업장 거주자외 출입제한 21
 
2.4%
해당 시설 정책에 따라 이용이 불가할 수 있습니다. 10
 
1.1%
입주자외 출입제한 (긴급상황 이용가능) 10
 
1.1%
공동주택 입주민 전용 8
 
0.9%
해당 시설 정책에 따라 이용이 불가할 수 있습니다 6
 
0.7%
Other values (8) 21
 
2.4%

Length

2023-12-13T00:59:51.783162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
출입제한 430
15.2%
거주자외 420
14.9%
na 240
8.5%
수 176
 
6.2%
시설 172
 
6.1%
따라 171
 
6.1%
이용이 171
 
6.1%
제한될 160
 
5.7%
상황에 155
 
5.5%
있음 155
 
5.5%
Other values (31) 576
20.4%

주소
Text

Distinct222
Distinct (%)24.9%
Missing0
Missing (%)0.0%
Memory size7.1 KiB
2023-12-13T00:59:52.109154image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length25
Mean length18.210762
Min length15

Characters and Unicode

Total characters16244
Distinct characters95
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique43 ?
Unique (%)4.8%

Sample

1st row대전광역시 유성구 관평동 887
2nd row대전광역시 유성구 테크노 9로 35
3rd row대전광역시 유성구 가정로 168
4th row대전광역시 유성구 반석동 665-2
5th row대전광역시 유성구 하기동 519
ValueCountFrequency (%)
대전광역시 892
24.9%
유성구 892
24.9%
배울2로 49
 
1.4%
엑스포로 45
 
1.3%
가정로 42
 
1.2%
지족로 37
 
1.0%
대학로 32
 
0.9%
은구비남로 31
 
0.9%
유성대로 28
 
0.8%
죽동로 26
 
0.7%
Other values (278) 1508
42.1%
2023-12-13T00:59:52.628910image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2737
16.8%
대 1085
 
6.7%
성 940
 
5.8%
유 938
 
5.8%
구 930
 
5.7%
전 902
 
5.6%
광 892
 
5.5%
역 892
 
5.5%
시 892
 
5.5%
로 858
 
5.3%
Other values (85) 5178
31.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 10584
65.2%
Decimal Number 2848
 
17.5%
Space Separator 2737
 
16.8%
Dash Punctuation 75
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
대 1085
10.3%
성 940
8.9%
유 938
8.9%
구 930
8.8%
전 902
8.5%
광 892
8.4%
역 892
8.4%
시 892
8.4%
로 858
8.1%
번 174
 
1.6%
Other values (73) 2081
19.7%
Decimal Number
ValueCountFrequency (%)
1 578
20.3%
2 382
13.4%
3 369
13.0%
4 283
9.9%
5 264
9.3%
6 236
8.3%
9 234
8.2%
8 187
 
6.6%
0 166
 
5.8%
7 149
 
5.2%
Space Separator
ValueCountFrequency (%)
2737
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 75
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 10584
65.2%
Common 5660
34.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
대 1085
10.3%
성 940
8.9%
유 938
8.9%
구 930
8.8%
전 902
8.5%
광 892
8.4%
역 892
8.4%
시 892
8.4%
로 858
8.1%
번 174
 
1.6%
Other values (73) 2081
19.7%
Common
ValueCountFrequency (%)
2737
48.4%
1 578
 
10.2%
2 382
 
6.7%
3 369
 
6.5%
4 283
 
5.0%
5 264
 
4.7%
6 236
 
4.2%
9 234
 
4.1%
8 187
 
3.3%
0 166
 
2.9%
Other values (2) 224
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 10584
65.2%
ASCII 5660
34.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2737
48.4%
1 578
 
10.2%
2 382
 
6.7%
3 369
 
6.5%
4 283
 
5.0%
5 264
 
4.7%
6 236
 
4.2%
9 234
 
4.1%
8 187
 
3.3%
0 166
 
2.9%
Other values (2) 224
 
4.0%
Hangul
ValueCountFrequency (%)
대 1085
10.3%
성 940
8.9%
유 938
8.9%
구 930
8.8%
전 902
8.5%
광 892
8.4%
역 892
8.4%
시 892
8.4%
로 858
8.1%
번 174
 
1.6%
Other values (73) 2081
19.7%

상세위치
Text

MISSING 

Distinct144
Distinct (%)26.4%
Missing347
Missing (%)38.9%
Memory size7.1 KiB
2023-12-13T00:59:52.932838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length51
Median length26
Mean length13.084404
Min length2

Characters and Unicode

Total characters7131
Distinct characters240
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique26 ?
Unique (%)4.8%

Sample

1st row옥외주차장 검품장 근처
2nd row입구 국기계양대 왼쪽
3rd row입구 경비실 앞 주차장
4th row전시장 뒤편 사무실 입구 주차장
5th row지상4층 주차장 430기둥 옆
ValueCountFrequency (%)
주차장 72
 
5.8%
지하2층 69
 
5.6%
지하1층 39
 
3.1%
지하 23
 
1.9%
우측 20
 
1.6%
백화점 19
 
1.5%
5층 19
 
1.5%
좌측 17
 
1.4%
지하주차장 16
 
1.3%
송림마을5단지아파트 16
 
1.3%
Other values (232) 930
75.0%
2023-12-13T00:59:53.354486image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
695
 
9.7%
지 403
 
5.7%
1 328
 
4.6%
2 293
 
4.1%
하 251
 
3.5%
주 195
 
2.7%
0 184
 
2.6%
동 176
 
2.5%
장 173
 
2.4%
트 172
 
2.4%
Other values (230) 4261
59.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4835
67.8%
Decimal Number 1259
 
17.7%
Space Separator 695
 
9.7%
Other Punctuation 115
 
1.6%
Uppercase Letter 115
 
1.6%
Math Symbol 68
 
1.0%
Close Punctuation 15
 
0.2%
Open Punctuation 15
 
0.2%
Dash Punctuation 14
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 403
 
8.3%
하 251
 
5.2%
주 195
 
4.0%
동 176
 
3.6%
장 173
 
3.6%
트 172
 
3.6%
차 169
 
3.5%
층 166
 
3.4%
아 147
 
3.0%
파 144
 
3.0%
Other values (201) 2839
58.7%
Uppercase Letter
ValueCountFrequency (%)
A 31
27.0%
B 22
19.1%
T 12
 
10.4%
K 12
 
10.4%
L 10
 
8.7%
C 7
 
6.1%
G 7
 
6.1%
E 5
 
4.3%
D 4
 
3.5%
H 3
 
2.6%
Other values (2) 2
 
1.7%
Decimal Number
ValueCountFrequency (%)
1 328
26.1%
2 293
23.3%
0 184
14.6%
5 95
 
7.5%
3 84
 
6.7%
7 81
 
6.4%
4 69
 
5.5%
6 58
 
4.6%
9 34
 
2.7%
8 33
 
2.6%
Other Punctuation
ValueCountFrequency (%)
, 107
93.0%
/ 8
 
7.0%
Space Separator
ValueCountFrequency (%)
695
100.0%
Math Symbol
ValueCountFrequency (%)
~ 68
100.0%
Close Punctuation
ValueCountFrequency (%)
) 15
100.0%
Open Punctuation
ValueCountFrequency (%)
( 15
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 14
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4835
67.8%
Common 2181
30.6%
Latin 115
 
1.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 403
 
8.3%
하 251
 
5.2%
주 195
 
4.0%
동 176
 
3.6%
장 173
 
3.6%
트 172
 
3.6%
차 169
 
3.5%
층 166
 
3.4%
아 147
 
3.0%
파 144
 
3.0%
Other values (201) 2839
58.7%
Common
ValueCountFrequency (%)
695
31.9%
1 328
15.0%
2 293
13.4%
0 184
 
8.4%
, 107
 
4.9%
5 95
 
4.4%
3 84
 
3.9%
7 81
 
3.7%
4 69
 
3.2%
~ 68
 
3.1%
Other values (7) 177
 
8.1%
Latin
ValueCountFrequency (%)
A 31
27.0%
B 22
19.1%
T 12
 
10.4%
K 12
 
10.4%
L 10
 
8.7%
C 7
 
6.1%
G 7
 
6.1%
E 5
 
4.3%
D 4
 
3.5%
H 3
 
2.6%
Other values (2) 2
 
1.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4835
67.8%
ASCII 2296
32.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
695
30.3%
1 328
14.3%
2 293
12.8%
0 184
 
8.0%
, 107
 
4.7%
5 95
 
4.1%
3 84
 
3.7%
7 81
 
3.5%
4 69
 
3.0%
~ 68
 
3.0%
Other values (19) 292
12.7%
Hangul
ValueCountFrequency (%)
지 403
 
8.3%
하 251
 
5.2%
주 195
 
4.0%
동 176
 
3.6%
장 173
 
3.6%
트 172
 
3.6%
차 169
 
3.5%
층 166
 
3.4%
아 147
 
3.0%
파 144
 
3.0%
Other values (201) 2839
58.7%

시도코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size7.1 KiB
3000000000
892 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3000000000
2nd row3000000000
3rd row3000000000
4th row3000000000
5th row3000000000

Common Values

ValueCountFrequency (%)
3000000000 892
100.0%

Length

2023-12-13T00:59:53.487762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T00:59:53.617210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3000000000 892
100.0%

시도이름
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size7.1 KiB
대전광역시
892 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
대전광역시 892
100.0%

Length

2023-12-13T00:59:53.736860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T00:59:53.830565image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
대전광역시 892
100.0%

시군구코드
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size7.1 KiB
3020000000
892 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row3020000000
2nd row3020000000
3rd row3020000000
4th row3020000000
5th row3020000000

Common Values

ValueCountFrequency (%)
3020000000 892
100.0%

Length

2023-12-13T00:59:53.919153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T00:59:54.004817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3020000000 892
100.0%

시군구이름
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size7.1 KiB
유성구
892 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
유성구 892
100.0%

Length

2023-12-13T00:59:54.099692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T00:59:54.190579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
유성구 892
100.0%

행정동코드
Real number (ℝ)

HIGH CORRELATION 

Distinct13
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.0200555 × 109
Minimum3.020052 × 109
Maximum3.020061 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size8.0 KiB
2023-12-13T00:59:54.276506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.020052 × 109
5-th percentile3.020052 × 109
Q13.020054 × 109
median3.0200548 × 109
Q33.020057 × 109
95-th percentile3.02006 × 109
Maximum3.020061 × 109
Range9000
Interquartile range (IQR)3000

Descriptive statistics

Standard deviation2495.3973
Coefficient of variation (CV)8.2627534 × 10-7
Kurtosis-0.17822604
Mean3.0200555 × 109
Median Absolute Deviation (MAD)800
Skewness0.91524481
Sum2.6938895 × 1012
Variance6227007.9
MonotonicityNot monotonic
2023-12-13T00:59:54.377592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)
ValueCountFrequency (%)
3020055000 141
15.8%
3020054000 122
13.7%
3020060000 113
12.7%
3020054800 92
10.3%
3020057000 78
8.7%
3020054700 67
7.5%
3020054600 63
7.1%
3020053000 57
6.4%
3020052000 54
 
6.1%
3020061000 36
 
4.0%
Other values (3) 69
7.7%
ValueCountFrequency (%)
3020052000 54
 
6.1%
3020052600 30
 
3.4%
3020052700 22
 
2.5%
3020053000 57
6.4%
3020054000 122
13.7%
3020054600 63
7.1%
3020054700 67
7.5%
3020054800 92
10.3%
3020055000 141
15.8%
3020057000 78
8.7%
ValueCountFrequency (%)
3020061000 36
 
4.0%
3020060000 113
12.7%
3020058000 17
 
1.9%
3020057000 78
8.7%
3020055000 141
15.8%
3020054800 92
10.3%
3020054700 67
7.5%
3020054600 63
7.1%
3020054000 122
13.7%
3020053000 57
6.4%

행정동이름
Categorical

HIGH CORRELATION 

Distinct13
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size7.1 KiB
신성동
141 
온천2동
122 
관평동
113 
노은3동
92 
전민동
78 
Other values (8)
346 

Length

Max length4
Median length3
Mean length3.4899103
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row관평동
2nd row관평동
3rd row신성동
4th row노은2동
5th row노은2동

Common Values

ValueCountFrequency (%)
신성동 141
15.8%
온천2동 122
13.7%
관평동 113
12.7%
노은3동 92
10.3%
전민동 78
8.7%
노은2동 67
7.5%
노은1동 63
7.1%
온천1동 57
6.4%
진잠동 54
 
6.1%
원신흥동 36
 
4.0%
Other values (3) 69
7.7%

Length

2023-12-13T00:59:54.492209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
신성동 141
15.8%
온천2동 122
13.7%
관평동 113
12.7%
노은3동 92
10.3%
전민동 78
8.7%
노은2동 67
7.5%
노은1동 63
7.1%
온천1동 57
6.4%
진잠동 54
 
6.1%
원신흥동 36
 
4.0%
Other values (3) 69
7.7%

법정동코드
Real number (ℝ)

HIGH CORRELATION 

Distinct35
Distinct (%)3.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.0200125 × 109
Minimum3.0200101 × 109
Maximum3.0200147 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size8.0 KiB
2023-12-13T00:59:54.620892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.0200101 × 109
5-th percentile3.0200103 × 109
Q13.0200117 × 109
median3.0200123 × 109
Q33.0200139 × 109
95-th percentile3.0200146 × 109
Maximum3.0200147 × 109
Range4600
Interquartile range (IQR)2200

Descriptive statistics

Standard deviation1274.1282
Coefficient of variation (CV)4.2189502 × 10-7
Kurtosis-0.8574738
Mean3.0200125 × 109
Median Absolute Deviation (MAD)900
Skewness0.13726352
Sum2.6938512 × 1012
Variance1623402.8
MonotonicityNot monotonic
2023-12-13T00:59:54.736847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=35)
ValueCountFrequency (%)
3020012000 105
 
11.8%
3020014600 80
 
9.0%
3020011100 66
 
7.4%
3020012700 65
 
7.3%
3020014100 45
 
5.0%
3020011900 39
 
4.4%
3020013200 39
 
4.4%
3020011700 38
 
4.3%
3020012300 36
 
4.0%
3020012600 34
 
3.8%
Other values (25) 345
38.7%
ValueCountFrequency (%)
3020010100 29
3.3%
3020010200 15
 
1.7%
3020010300 10
 
1.1%
3020010600 13
 
1.5%
3020011100 66
7.4%
3020011200 4
 
0.4%
3020011300 17
 
1.9%
3020011400 23
 
2.6%
3020011500 22
 
2.5%
3020011700 38
4.3%
ValueCountFrequency (%)
3020014700 9
 
1.0%
3020014600 80
9.0%
3020014500 8
 
0.9%
3020014400 27
 
3.0%
3020014300 6
 
0.7%
3020014200 7
 
0.8%
3020014100 45
5.0%
3020014000 26
 
2.9%
3020013900 22
 
2.5%
3020013600 6
 
0.7%

법정동이름
Categorical

HIGH CORRELATION 

Distinct35
Distinct (%)3.9%
Missing0
Missing (%)0.0%
Memory size7.1 KiB
지족동
105 
관평동
80 
봉명동
66 
도룡동
65 
전민동
 
45
Other values (30)
531 

Length

Max length4
Median length3
Mean length2.9573991
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row관평동
2nd row탑립동
3rd row가정동
4th row반석동
5th row하기동

Common Values

ValueCountFrequency (%)
지족동 105
 
11.8%
관평동 80
 
9.0%
봉명동 66
 
7.4%
도룡동 65
 
7.3%
전민동 45
 
5.0%
노은동 39
 
4.4%
하기동 39
 
4.4%
장대동 38
 
4.3%
어은동 36
 
4.0%
가정동 34
 
3.8%
Other values (25) 345
38.7%

Length

2023-12-13T00:59:54.873676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
지족동 105
 
11.8%
관평동 80
 
9.0%
봉명동 66
 
7.4%
도룡동 65
 
7.3%
전민동 45
 
5.0%
노은동 39
 
4.4%
하기동 39
 
4.4%
장대동 38
 
4.3%
어은동 36
 
4.0%
가정동 34
 
3.8%
Other values (25) 345
38.7%

기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size7.1 KiB
2021-10-01
892 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2021-10-01
2nd row2021-10-01
3rd row2021-10-01
4th row2021-10-01
5th row2021-10-01

Common Values

ValueCountFrequency (%)
2021-10-01 892
100.0%

Length

2023-12-13T00:59:55.003211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T00:59:55.090225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2021-10-01 892
100.0%

Interactions

2023-12-13T00:59:47.980417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:59:46.733179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:59:47.191543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:59:47.576844image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:59:48.081959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:59:46.861423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:59:47.280493image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:59:47.671731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:59:48.226957image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:59:46.979084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:59:47.380495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:59:47.780874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:59:48.358009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:59:47.094121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:59:47.473667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T00:59:47.876613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T00:59:55.160969image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호충전기타입충전기아이디이용가능시간급속충전량운영기관비고행정동코드행정동이름법정동코드법정동이름
번호1.0000.3440.2460.5100.1980.6790.6030.9020.9560.9540.989
충전기타입0.3441.0000.7070.6811.0000.8300.6580.2860.3240.3110.499
충전기아이디0.2460.7071.0000.3530.6180.5180.5100.0000.1830.2170.330
이용가능시간0.5100.6810.3531.0000.0000.9210.9540.3760.4640.4350.729
급속충전량0.1981.0000.6180.0001.000NaN0.0000.2710.7130.4920.677
운영기관0.6790.8300.5180.921NaN1.0000.9420.5880.6710.6290.821
비고0.6030.6580.5100.9540.0000.9421.0000.4750.5840.5500.799
행정동코드0.9020.2860.0000.3760.2710.5880.4751.0001.0000.8820.999
행정동이름0.9560.3240.1830.4640.7130.6710.5841.0001.0000.9480.995
법정동코드0.9540.3110.2170.4350.4920.6290.5500.8820.9481.0001.000
법정동이름0.9890.4990.3300.7290.6770.8210.7990.9990.9951.0001.000
2023-12-13T00:59:55.296968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
이용가능시간행정동이름충전기타입비고운영기관급속충전량법정동이름
이용가능시간1.0000.1780.4410.8130.5740.0000.276
행정동이름0.1781.0000.1930.2460.2900.5090.934
충전기타입0.4410.1931.0000.4260.6050.9520.273
비고0.8130.2460.4261.0000.7060.0000.353
운영기관0.5740.2900.6050.7061.0001.0000.340
급속충전량0.0000.5090.9520.0001.0001.0000.346
법정동이름0.2760.9340.2730.3530.3400.3461.000
2023-12-13T00:59:55.403073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
번호충전기아이디행정동코드법정동코드충전기타입이용가능시간급속충전량운영기관비고행정동이름법정동이름
번호1.000-0.025-0.524-0.4820.2120.2210.0800.3260.2830.8270.884
충전기아이디-0.0251.0000.1190.1260.3800.1470.5350.2380.2560.0830.132
행정동코드-0.5240.1191.0000.7480.1330.1720.1490.2700.2240.9970.934
법정동코드-0.4820.1260.7481.0000.1880.1840.3420.2820.2350.8010.986
충전기타입0.2120.3800.1330.1881.0000.4410.9520.6050.4260.1930.273
이용가능시간0.2210.1470.1720.1840.4411.0000.0000.5740.8130.1780.276
급속충전량0.0800.5350.1490.3420.9520.0001.0001.0000.0000.5090.346
운영기관0.3260.2380.2700.2820.6050.5741.0001.0000.7060.2900.340
비고0.2830.2560.2240.2350.4260.8130.0000.7061.0000.2460.353
행정동이름0.8270.0830.9970.8010.1930.1780.5090.2900.2461.0000.934
법정동이름0.8840.1320.9340.9860.2730.2760.3460.3400.3530.9341.000

Missing values

2023-12-13T00:59:48.513728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T00:59:48.785280image/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

번호충전소이름충전기타입충전기아이디이용가능시간급속충전량운영기관비고주소상세위치시도코드시도이름시군구코드시군구이름행정동코드행정동이름법정동코드법정동이름기준일자
012롯데마트 대덕테크노밸리점DC차데모+AC3상+DC콤보124시간 이용가능급속(50kW)환경부(한국자동차환경협회)주차요금 별도대전광역시 유성구 관평동 887옥외주차장 검품장 근처3000000000대전광역시3020000000유성구3020060000관평동3020014600관평동2021-10-01
1110대전테크노파크 주차장DC차데모+AC3상+DC콤보124시간 이용가능급속(50kW)환경부(한국자동차환경협회)주차요금 별도대전광역시 유성구 테크노 9로 35입구 국기계양대 왼쪽3000000000대전광역시3020000000유성구3020060000관평동3020014300탑립동2021-10-01
2198KT가정빌딩DC차데모+AC3상+DC콤보124시간 이용가능급속(50kW)환경부(한국자동차환경협회)주차요금 별도대전광역시 유성구 가정로 168입구 경비실 앞 주차장3000000000대전광역시3020000000유성구3020055000신성동3020012600가정동2021-10-01
3613현대자동차(반석점)DC차데모+AC3상+DC콤보124시간 이용가능급속(50kW)환경부(한국자동차환경협회)주차요금 별도대전광역시 유성구 반석동 665-2전시장 뒤편 사무실 입구 주차장3000000000대전광역시3020000000유성구3020054700노은2동3020013900반석동2021-10-01
4640롯데마트 노은점DC차데모+AC3상+DC콤보110:00~23:00급속(50kW)환경부(한국자동차환경협회)주차요금 별도대전광역시 유성구 하기동 519지상4층 주차장 430기둥 옆3000000000대전광역시3020000000유성구3020054700노은2동3020013200하기동2021-10-01
513디티비안 오피스텔 지하1층AC완속124시간 이용가능<NA>제주전기자동차서비스거주자외 출입제한대전광역시 유성구 테크노1로 12-22지하1층3000000000대전광역시3020000000유성구3020060000관평동3020014600관평동2021-10-01
614디티비안 오피스텔 지하1층AC완속224시간 이용가능<NA>제주전기자동차서비스거주자외 출입제한대전광역시 유성구 테크노1로 12-22지하1층3000000000대전광역시3020000000유성구3020060000관평동3020014600관평동2021-10-01
725대덕테크노밸리2단지AC완속124시간 이용가능<NA>파워큐브거주자외 출입제한대전광역시 유성구 배울1로 13대덕테크노밸리2단지아파트3000000000대전광역시3020000000유성구3020060000관평동3020014600관평동2021-10-01
826대덕테크노밸리2단지AC완속824시간 이용가능<NA>파워큐브거주자외 출입제한대전광역시 유성구 배울1로 13대덕테크노밸리2단지아파트3000000000대전광역시3020000000유성구3020060000관평동3020014600관평동2021-10-01
927대덕테크노밸리2단지AC완속724시간 이용가능<NA>파워큐브거주자외 출입제한대전광역시 유성구 배울1로 13대덕테크노밸리2단지아파트3000000000대전광역시3020000000유성구3020060000관평동3020014600관평동2021-10-01
번호충전소이름충전기타입충전기아이디이용가능시간급속충전량운영기관비고주소상세위치시도코드시도이름시군구코드시군구이름행정동코드행정동이름법정동코드법정동이름기준일자
882576백마강민물장어AC완속224시간 이용가능<NA>삼성EVC<NA>대전광역시 유성구 도안대로567번길 3<NA>3000000000대전광역시3020000000유성구3020053000온천1동3020011100봉명동2021-10-01
883590봉명동동아벤처타워AC완속224시간 이용가능<NA>차지비<NA>대전광역시 유성구 온천로 59<NA>3000000000대전광역시3020000000유성구3020053000온천1동3020011100봉명동2021-10-01
884678EV충전소 SK세종셀프주유소 (ev Most)DC콤보107:00-22:00<NA>evMost<NA>대전광역시 유성구 북유성대로 288<NA>3000000000대전광역시3020000000유성구3020054700노은2동3020013200하기동2021-10-01
885723대전지방기상청AC완속124시간 이용가능<NA>대영채비<NA>대전광역시 유성구 대학로 383<NA>3000000000대전광역시3020000000유성구3020054000온천2동3020012400구성동2021-10-01
886724대전지방기상청AC완속224시간 이용가능<NA>대영채비<NA>대전광역시 유성구 대학로 383<NA>3000000000대전광역시3020000000유성구3020054000온천2동3020012400구성동2021-10-01
887751대전 유성구청 부설주차장DC차데모+AC3상+DC콤보124시간 이용가능<NA>한국전력<NA>대전광역시 유성구 대학로 211<NA>3000000000대전광역시3020000000유성구3020054000온천2동3020012300어은동2021-10-01
888763미성카프렌드AC완속124시간 이용가능<NA>제주전기자동차서비스<NA>대전광역시 유성구 장대동 325-1<NA>3000000000대전광역시3020000000유성구3020054000온천2동3020011700장대동2021-10-01
889764미성카프렌드AC완속224시간 이용가능<NA>제주전기자동차서비스<NA>대전광역시 유성구 장대동 325-1<NA>3000000000대전광역시3020000000유성구3020054000온천2동3020011700장대동2021-10-01
890389홈플러스 서대전점DC차데모+AC3상+DC콤보1<NA><NA>한국전력<NA>대전광역시 유성구 대정로 23<NA>3000000000대전광역시3020000000유성구3020052000진잠동3020010300대정동2021-10-01
891591홈플러스 유성점DC차데모+AC3상+DC콤보1<NA><NA>한국전력<NA>대전광역시 유성구 한밭대로 502<NA>3000000000대전광역시3020000000유성구3020053000온천1동3020011100봉명동2021-10-01