Overview

Dataset statistics

Number of variables18
Number of observations30
Missing cells62
Missing cells (%)11.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory4.5 KiB
Average record size in memory153.4 B

Variable types

DateTime2
Numeric5
Text7
Categorical4

Dataset

Description샘플 데이터
Author펌프킨
URLhttps://bigdata-region.kr/#/dataset/119d5f19-0b7b-4089-94b7-9aaec57bf816

Alerts

조회년월 has constant value ""Constant
운영시간 is highly overall correlated with 개방충전소ID and 2 other fieldsHigh correlation
충전유형명 is highly overall correlated with 운영시간High correlation
운영기관 is highly overall correlated with 운영시간High correlation
개방충전소ID is highly overall correlated with 개방충전기ID and 1 other fieldsHigh correlation
개방충전기ID is highly overall correlated with 개방충전소IDHigh correlation
위도 is highly overall correlated with 시도명High correlation
경도 is highly overall correlated with 시도명High correlation
시도명 is highly overall correlated with 위도 and 1 other fieldsHigh correlation
운영기관 is highly imbalanced (78.9%)Imbalance
충전유형명 is highly imbalanced (78.9%)Imbalance
읍면동명 has 22 (73.3%) missing valuesMissing
건물명 has 12 (40.0%) missing valuesMissing
상세주소 has 28 (93.3%) missing valuesMissing
개방충전소ID has unique valuesUnique
개방충전기ID has unique valuesUnique
개방충전소이름 has unique valuesUnique
도로명 has unique valuesUnique
위도 has unique valuesUnique
경도 has unique valuesUnique
사용횟수 has 2 (6.7%) zerosZeros

Reproduction

Analysis started2023-12-10 14:23:02.594611
Analysis finished2023-12-10 14:23:06.444060
Duration3.85 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

조회년월
Date

CONSTANT 

Distinct1
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
Minimum2021-04-01 00:00:00
Maximum2021-04-01 00:00:00
2023-12-10T23:23:06.501832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:23:06.604751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

개방충전소ID
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean9817.5
Minimum100
Maximum10288
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:23:06.697903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum100
5-th percentile10008.25
Q110062.25
median10146.5
Q310243.5
95-th percentile10285.1
Maximum10288
Range10188
Interquartile range (IQR)181.25

Descriptive statistics

Standard deviation1837.7972
Coefficient of variation (CV)0.18719605
Kurtosis29.822933
Mean9817.5
Median Absolute Deviation (MAD)89
Skewness-5.4537407
Sum294525
Variance3377498.7
MonotonicityNot monotonic
2023-12-10T23:23:06.807678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
10006 1
 
3.3%
10157 1
 
3.3%
10288 1
 
3.3%
10286 1
 
3.3%
10284 1
 
3.3%
10273 1
 
3.3%
10283 1
 
3.3%
10266 1
 
3.3%
10262 1
 
3.3%
10246 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
100 1
3.3%
10006 1
3.3%
10011 1
3.3%
10021 1
3.3%
10028 1
3.3%
10051 1
3.3%
10058 1
3.3%
10062 1
3.3%
10063 1
3.3%
10066 1
3.3%
ValueCountFrequency (%)
10288 1
3.3%
10286 1
3.3%
10284 1
3.3%
10283 1
3.3%
10273 1
3.3%
10266 1
3.3%
10262 1
3.3%
10246 1
3.3%
10236 1
3.3%
10221 1
3.3%

개방충전기ID
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1241.8333
Minimum1
Maximum8820
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:23:06.921990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile87.35
Q1478.75
median699.5
Q31310
95-th percentile4054.7
Maximum8820
Range8819
Interquartile range (IQR)831.25

Descriptive statistics

Standard deviation1789.0466
Coefficient of variation (CV)1.4406495
Kurtosis12.795423
Mean1241.8333
Median Absolute Deviation (MAD)386
Skewness3.5152411
Sum37255
Variance3200687.7
MonotonicityNot monotonic
2023-12-10T23:23:07.027020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
538 1
 
3.3%
1340 1
 
3.3%
1473 1
 
3.3%
1447 1
 
3.3%
1432 1
 
3.3%
1220 1
 
3.3%
1345 1
 
3.3%
1210 1
 
3.3%
1204 1
 
3.3%
916 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
1 1
3.3%
77 1
3.3%
100 1
3.3%
336 1
3.3%
355 1
3.3%
365 1
3.3%
446 1
3.3%
459 1
3.3%
538 1
3.3%
620 1
3.3%
ValueCountFrequency (%)
8820 1
3.3%
6167 1
3.3%
1473 1
3.3%
1447 1
3.3%
1432 1
3.3%
1416 1
3.3%
1345 1
3.3%
1340 1
3.3%
1220 1
3.3%
1210 1
3.3%

개방충전소이름
Text

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-12-10T23:23:07.220023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length10
Mean length6.6
Min length4

Characters and Unicode

Total characters198
Distinct characters95
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique30 ?
Unique (%)100.0%

Sample

1st row서초지사
2nd row거문오름
3rd row서귀포지사
4th row창원스포츠파크
5th row내서읍사무소
ValueCountFrequency (%)
서초지사 1
 
2.9%
서울관 1
 
2.9%
현대백화점 1
 
2.9%
천호점 1
 
2.9%
고척근린공원 1
 
2.9%
지하주차장 1
 
2.9%
한경119센터 1
 
2.9%
국립현대미술관 1
 
2.9%
보령지사 1
 
2.9%
면목3동 1
 
2.9%
Other values (25) 25
71.4%
2023-12-10T23:23:07.541429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
사 14
 
7.1%
지 13
 
6.6%
대 6
 
3.0%
주 6
 
3.0%
산 6
 
3.0%
관 5
 
2.5%
5
 
2.5%
장 5
 
2.5%
동 4
 
2.0%
차 4
 
2.0%
Other values (85) 130
65.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 187
94.4%
Space Separator 5
 
2.5%
Decimal Number 4
 
2.0%
Open Punctuation 1
 
0.5%
Close Punctuation 1
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 14
 
7.5%
지 13
 
7.0%
대 6
 
3.2%
주 6
 
3.2%
산 6
 
3.2%
관 5
 
2.7%
장 5
 
2.7%
동 4
 
2.1%
차 4
 
2.1%
공 4
 
2.1%
Other values (79) 120
64.2%
Decimal Number
ValueCountFrequency (%)
1 2
50.0%
9 1
25.0%
3 1
25.0%
Space Separator
ValueCountFrequency (%)
5
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 187
94.4%
Common 11
 
5.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 14
 
7.5%
지 13
 
7.0%
대 6
 
3.2%
주 6
 
3.2%
산 6
 
3.2%
관 5
 
2.7%
장 5
 
2.7%
동 4
 
2.1%
차 4
 
2.1%
공 4
 
2.1%
Other values (79) 120
64.2%
Common
ValueCountFrequency (%)
5
45.5%
1 2
 
18.2%
9 1
 
9.1%
( 1
 
9.1%
) 1
 
9.1%
3 1
 
9.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 187
94.4%
ASCII 11
 
5.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
사 14
 
7.5%
지 13
 
7.0%
대 6
 
3.2%
주 6
 
3.2%
산 6
 
3.2%
관 5
 
2.7%
장 5
 
2.7%
동 4
 
2.1%
차 4
 
2.1%
공 4
 
2.1%
Other values (79) 120
64.2%
ASCII
ValueCountFrequency (%)
5
45.5%
1 2
 
18.2%
9 1
 
9.1%
( 1
 
9.1%
) 1
 
9.1%
3 1
 
9.1%

운영기관
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
한국전력
29 
환경부
 
1

Length

Max length4
Median length4
Mean length3.9666667
Min length3

Unique

Unique1 ?
Unique (%)3.3%

Sample

1st row한국전력
2nd row환경부
3rd row한국전력
4th row한국전력
5th row한국전력

Common Values

ValueCountFrequency (%)
한국전력 29
96.7%
환경부 1
 
3.3%

Length

2023-12-10T23:23:07.889645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:23:07.974999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
한국전력 29
96.7%
환경부 1
 
3.3%

시도명
Categorical

HIGH CORRELATION 

Distinct11
Distinct (%)36.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
서울특별시
6 
제주특별자치도
6 
경상남도
4 
경기도
4 
부산광역시
3 
Other values (6)
7 

Length

Max length7
Median length5
Mean length4.8333333
Min length3

Unique

Unique5 ?
Unique (%)16.7%

Sample

1st row서울특별시
2nd row제주특별자치도
3rd row제주특별자치도
4th row경상남도
5th row경상남도

Common Values

ValueCountFrequency (%)
서울특별시 6
20.0%
제주특별자치도 6
20.0%
경상남도 4
13.3%
경기도 4
13.3%
부산광역시 3
10.0%
대구광역시 2
 
6.7%
강원도 1
 
3.3%
충청북도 1
 
3.3%
대전광역시 1
 
3.3%
충청남도 1
 
3.3%

Length

2023-12-10T23:23:08.086648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
서울특별시 6
20.0%
제주특별자치도 6
20.0%
경상남도 4
13.3%
경기도 4
13.3%
부산광역시 3
10.0%
대구광역시 2
 
6.7%
강원도 1
 
3.3%
충청북도 1
 
3.3%
대전광역시 1
 
3.3%
충청남도 1
 
3.3%

시군구명
Text

Distinct25
Distinct (%)83.3%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-12-10T23:23:08.246600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length3
Mean length3.6333333
Min length2

Characters and Unicode

Total characters109
Distinct characters41
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
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 row서초구
2nd row제주시
3rd row서귀포시
4th row창원시 성산구
5th row창원시 마산회원구
ValueCountFrequency (%)
제주시 4
 
11.8%
서귀포시 2
 
5.9%
창원시 2
 
5.9%
강동구 2
 
5.9%
대덕구 1
 
2.9%
서초구 1
 
2.9%
수성구 1
 
2.9%
양주시 1
 
2.9%
김해시 1
 
2.9%
나주시 1
 
2.9%
Other values (18) 18
52.9%
2023-12-10T23:23:08.584418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
시 18
16.5%
구 16
 
14.7%
주 6
 
5.5%
제 5
 
4.6%
산 5
 
4.6%
원 4
 
3.7%
서 4
 
3.7%
4
 
3.7%
안 3
 
2.8%
성 3
 
2.8%
Other values (31) 41
37.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 105
96.3%
Space Separator 4
 
3.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 18
17.1%
구 16
15.2%
주 6
 
5.7%
제 5
 
4.8%
산 5
 
4.8%
원 4
 
3.8%
서 4
 
3.8%
안 3
 
2.9%
성 3
 
2.9%
양 3
 
2.9%
Other values (30) 38
36.2%
Space Separator
ValueCountFrequency (%)
4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 105
96.3%
Common 4
 
3.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 18
17.1%
구 16
15.2%
주 6
 
5.7%
제 5
 
4.8%
산 5
 
4.8%
원 4
 
3.8%
서 4
 
3.8%
안 3
 
2.9%
성 3
 
2.9%
양 3
 
2.9%
Other values (30) 38
36.2%
Common
ValueCountFrequency (%)
4
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 105
96.3%
ASCII 4
 
3.7%

Most frequent character per block

Hangul
ValueCountFrequency (%)
시 18
17.1%
구 16
15.2%
주 6
 
5.7%
제 5
 
4.8%
산 5
 
4.8%
원 4
 
3.8%
서 4
 
3.8%
안 3
 
2.9%
성 3
 
2.9%
양 3
 
2.9%
Other values (30) 38
36.2%
ASCII
ValueCountFrequency (%)
4
100.0%

읍면동명
Text

MISSING 

Distinct8
Distinct (%)100.0%
Missing22
Missing (%)73.3%
Memory size372.0 B
2023-12-10T23:23:08.781919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters24
Distinct characters18
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

Unique8 ?
Unique (%)100.0%

Sample

1st row조천읍
2nd row내서읍
3rd row현풍읍
4th row한경면
5th row반남면
ValueCountFrequency (%)
조천읍 1
12.5%
내서읍 1
12.5%
현풍읍 1
12.5%
한경면 1
12.5%
반남면 1
12.5%
진례면 1
12.5%
광적면 1
12.5%
구좌읍 1
12.5%
2023-12-10T23:23:09.101088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
면 4
16.7%
읍 4
16.7%
반 1
 
4.2%
구 1
 
4.2%
적 1
 
4.2%
광 1
 
4.2%
례 1
 
4.2%
진 1
 
4.2%
남 1
 
4.2%
조 1
 
4.2%
Other values (8) 8
33.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 24
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
면 4
16.7%
읍 4
16.7%
반 1
 
4.2%
구 1
 
4.2%
적 1
 
4.2%
광 1
 
4.2%
례 1
 
4.2%
진 1
 
4.2%
남 1
 
4.2%
조 1
 
4.2%
Other values (8) 8
33.3%

Most occurring scripts

ValueCountFrequency (%)
Hangul 24
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
면 4
16.7%
읍 4
16.7%
반 1
 
4.2%
구 1
 
4.2%
적 1
 
4.2%
광 1
 
4.2%
례 1
 
4.2%
진 1
 
4.2%
남 1
 
4.2%
조 1
 
4.2%
Other values (8) 8
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 24
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
면 4
16.7%
읍 4
16.7%
반 1
 
4.2%
구 1
 
4.2%
적 1
 
4.2%
광 1
 
4.2%
례 1
 
4.2%
진 1
 
4.2%
남 1
 
4.2%
조 1
 
4.2%
Other values (8) 8
33.3%

도로명
Text

UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-12-10T23:23:09.301600image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length8
Mean length4.4333333
Min length3

Characters and Unicode

Total characters133
Distinct characters62
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique30 ?
Unique (%)100.0%

Sample

1st row서운로9길
2nd row선화길
3rd row신중로
4th row원이대로
5th row중리상곡로
ValueCountFrequency (%)
서운로9길 1
 
3.3%
선화길 1
 
3.3%
중산간동로 1
 
3.3%
일주동로 1
 
3.3%
중앙대로 1
 
3.3%
삼일로 1
 
3.3%
진례로 1
 
3.3%
고분로 1
 
3.3%
옥마로 1
 
3.3%
삼청로 1
 
3.3%
Other values (20) 20
66.7%
2023-12-10T23:23:09.651395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
로 29
21.8%
대 8
 
6.0%
길 7
 
5.3%
동 4
 
3.0%
중 4
 
3.0%
고 4
 
3.0%
0 4
 
3.0%
양 3
 
2.3%
일 3
 
2.3%
번 3
 
2.3%
Other values (52) 64
48.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 118
88.7%
Decimal Number 15
 
11.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 29
24.6%
대 8
 
6.8%
길 7
 
5.9%
동 4
 
3.4%
중 4
 
3.4%
고 4
 
3.4%
양 3
 
2.5%
일 3
 
2.5%
번 3
 
2.5%
서 2
 
1.7%
Other values (44) 51
43.2%
Decimal Number
ValueCountFrequency (%)
0 4
26.7%
1 2
13.3%
4 2
13.3%
3 2
13.3%
5 2
13.3%
9 1
 
6.7%
2 1
 
6.7%
7 1
 
6.7%

Most occurring scripts

ValueCountFrequency (%)
Hangul 118
88.7%
Common 15
 
11.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 29
24.6%
대 8
 
6.8%
길 7
 
5.9%
동 4
 
3.4%
중 4
 
3.4%
고 4
 
3.4%
양 3
 
2.5%
일 3
 
2.5%
번 3
 
2.5%
서 2
 
1.7%
Other values (44) 51
43.2%
Common
ValueCountFrequency (%)
0 4
26.7%
1 2
13.3%
4 2
13.3%
3 2
13.3%
5 2
13.3%
9 1
 
6.7%
2 1
 
6.7%
7 1
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 118
88.7%
ASCII 15
 
11.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
로 29
24.6%
대 8
 
6.8%
길 7
 
5.9%
동 4
 
3.4%
중 4
 
3.4%
고 4
 
3.4%
양 3
 
2.5%
일 3
 
2.5%
번 3
 
2.5%
서 2
 
1.7%
Other values (44) 51
43.2%
ASCII
ValueCountFrequency (%)
0 4
26.7%
1 2
13.3%
4 2
13.3%
3 2
13.3%
5 2
13.3%
9 1
 
6.7%
2 1
 
6.7%
7 1
 
6.7%

도로명번호
Text

Distinct29
Distinct (%)96.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
2023-12-10T23:23:09.829372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length2
Mean length2.7666667
Min length1

Characters and Unicode

Total characters83
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
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 row38
2nd row20-28
3rd row56
4th row450
5th row75
ValueCountFrequency (%)
20 2
 
6.7%
38 1
 
3.3%
173 1
 
3.3%
2210 1
 
3.3%
17 1
 
3.3%
1603 1
 
3.3%
275-51 1
 
3.3%
756 1
 
3.3%
60 1
 
3.3%
30 1
 
3.3%
Other values (19) 19
63.3%
2023-12-10T23:23:10.154825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 12
14.5%
2 11
13.3%
1 10
12.0%
3 9
10.8%
0 8
9.6%
6 8
9.6%
4 8
9.6%
7 8
9.6%
8 5
6.0%
- 3
 
3.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 80
96.4%
Dash Punctuation 3
 
3.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 12
15.0%
2 11
13.8%
1 10
12.5%
3 9
11.2%
0 8
10.0%
6 8
10.0%
4 8
10.0%
7 8
10.0%
8 5
6.2%
9 1
 
1.2%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 83
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 12
14.5%
2 11
13.3%
1 10
12.0%
3 9
10.8%
0 8
9.6%
6 8
9.6%
4 8
9.6%
7 8
9.6%
8 5
6.0%
- 3
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 83
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 12
14.5%
2 11
13.3%
1 10
12.0%
3 9
10.8%
0 8
9.6%
6 8
9.6%
4 8
9.6%
7 8
9.6%
8 5
6.0%
- 3
 
3.6%

건물명
Text

MISSING 

Distinct17
Distinct (%)94.4%
Missing12
Missing (%)40.0%
Memory size372.0 B
2023-12-10T23:23:10.331084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length11
Median length7.5
Mean length6.8333333
Min length2

Characters and Unicode

Total characters123
Distinct characters73
Distinct categories4 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique16 ?
Unique (%)88.9%

Sample

1st row한국전력서귀포지점
2nd row주택
3rd row한국전력 강동송파지사
4th row한국전력공사
5th row한국전력
ValueCountFrequency (%)
한국전력공사 3
15.0%
한국전력 2
 
10.0%
수연one 1
 
5.0%
대덕구청 1
 
5.0%
국립제주박물관 1
 
5.0%
삼성디지털프라자 1
 
5.0%
클레이아크 1
 
5.0%
나주신촌리고분군 1
 
5.0%
한경119센터 1
 
5.0%
범어유림노르웨이숲2차 1
 
5.0%
Other values (7) 7
35.0%
2023-12-10T23:23:10.641467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
한 8
 
6.5%
국 8
 
6.5%
전 7
 
5.7%
력 7
 
5.7%
사 4
 
3.3%
주 4
 
3.3%
지 4
 
3.3%
공 3
 
2.4%
대 3
 
2.4%
제 2
 
1.6%
Other values (63) 73
59.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 114
92.7%
Decimal Number 4
 
3.3%
Lowercase Letter 3
 
2.4%
Space Separator 2
 
1.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
한 8
 
7.0%
국 8
 
7.0%
전 7
 
6.1%
력 7
 
6.1%
사 4
 
3.5%
주 4
 
3.5%
지 4
 
3.5%
공 3
 
2.6%
대 3
 
2.6%
제 2
 
1.8%
Other values (56) 64
56.1%
Decimal Number
ValueCountFrequency (%)
1 2
50.0%
9 1
25.0%
2 1
25.0%
Lowercase Letter
ValueCountFrequency (%)
e 1
33.3%
o 1
33.3%
n 1
33.3%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 114
92.7%
Common 6
 
4.9%
Latin 3
 
2.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
한 8
 
7.0%
국 8
 
7.0%
전 7
 
6.1%
력 7
 
6.1%
사 4
 
3.5%
주 4
 
3.5%
지 4
 
3.5%
공 3
 
2.6%
대 3
 
2.6%
제 2
 
1.8%
Other values (56) 64
56.1%
Common
ValueCountFrequency (%)
1 2
33.3%
2
33.3%
9 1
16.7%
2 1
16.7%
Latin
ValueCountFrequency (%)
e 1
33.3%
o 1
33.3%
n 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 114
92.7%
ASCII 9
 
7.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
한 8
 
7.0%
국 8
 
7.0%
전 7
 
6.1%
력 7
 
6.1%
사 4
 
3.5%
주 4
 
3.5%
지 4
 
3.5%
공 3
 
2.6%
대 3
 
2.6%
제 2
 
1.8%
Other values (56) 64
56.1%
ASCII
ValueCountFrequency (%)
1 2
22.2%
2
22.2%
9 1
11.1%
2 1
11.1%
e 1
11.1%
o 1
11.1%
n 1
11.1%

상세주소
Text

MISSING 

Distinct2
Distinct (%)100.0%
Missing28
Missing (%)93.3%
Memory size372.0 B
2023-12-10T23:23:10.791454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length5
Median length5
Mean length5
Min length5

Characters and Unicode

Total characters10
Distinct characters7
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

Unique2 ?
Unique (%)100.0%

Sample

1st row소형주차장
2nd row지사주차장
ValueCountFrequency (%)
소형주차장 1
50.0%
지사주차장 1
50.0%
2023-12-10T23:23:11.035555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 2
20.0%
차 2
20.0%
장 2
20.0%
소 1
10.0%
형 1
10.0%
지 1
10.0%
사 1
10.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 10
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 2
20.0%
차 2
20.0%
장 2
20.0%
소 1
10.0%
형 1
10.0%
지 1
10.0%
사 1
10.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 10
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 2
20.0%
차 2
20.0%
장 2
20.0%
소 1
10.0%
형 1
10.0%
지 1
10.0%
사 1
10.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 10
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 2
20.0%
차 2
20.0%
장 2
20.0%
소 1
10.0%
형 1
10.0%
지 1
10.0%
사 1
10.0%

위도
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.860617
Minimum33.251056
Maximum37.820975
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:23:11.166190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum33.251056
5-th percentile33.294209
Q135.11644
median35.776246
Q337.460651
95-th percentile37.691753
Maximum37.820975
Range4.569919
Interquartile range (IQR)2.3442117

Descriptive statistics

Standard deviation1.5895505
Coefficient of variation (CV)0.044325798
Kurtosis-1.1962426
Mean35.860617
Median Absolute Deviation (MAD)1.5760746
Skewness-0.37456434
Sum1075.8185
Variance2.5266706
MonotonicityNot monotonic
2023-12-10T23:23:11.278815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
37.486213904 1
 
3.3%
36.346201 1
 
3.3%
33.251056 1
 
3.3%
33.471628 1
 
3.3%
33.514248 1
 
3.3%
35.227695782 1
 
3.3%
37.820975 1
 
3.3%
35.251125382 1
 
3.3%
34.914573 1
 
3.3%
36.337558 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
33.251056 1
3.3%
33.254374 1
3.3%
33.342896 1
3.3%
33.454821 1
3.3%
33.471628 1
3.3%
33.514248 1
3.3%
34.914573 1
3.3%
35.098925948 1
3.3%
35.168981 1
3.3%
35.227695782 1
3.3%
ValueCountFrequency (%)
37.820975 1
3.3%
37.78242209 1
3.3%
37.580936 1
3.3%
37.579613 1
3.3%
37.539426 1
3.3%
37.523865159 1
3.3%
37.503986 1
3.3%
37.486213904 1
3.3%
37.383964 1
3.3%
37.320678132 1
3.3%

경도
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct30
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.54073
Minimum126.18293
Maximum129.08927
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:23:11.416706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.18293
5-th percentile126.49253
Q1126.7912
median127.08309
Q3128.59906
95-th percentile129.03642
Maximum129.08927
Range2.9063418
Interquartile range (IQR)1.8078594

Descriptive statistics

Standard deviation0.97988164
Coefficient of variation (CV)0.0076828918
Kurtosis-1.4748918
Mean127.54073
Median Absolute Deviation (MAD)0.497271
Skewness0.49017293
Sum3826.2219
Variance0.96016804
MonotonicityNot monotonic
2023-12-10T23:23:11.536022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
127.02781121 1
 
3.3%
127.415896 1
 
3.3%
126.477564 1
 
3.3%
126.77915 1
 
3.3%
126.54897 1
 
3.3%
129.08926984 1
 
3.3%
126.987485 1
 
3.3%
128.74464944 1
 
3.3%
126.660386 1
 
3.3%
126.622671 1
 
3.3%
Other values (20) 20
66.7%
ValueCountFrequency (%)
126.182928 1
3.3%
126.477564 1
3.3%
126.510819 1
3.3%
126.54897 1
3.3%
126.622671 1
3.3%
126.660386 1
3.3%
126.711711 1
3.3%
126.77915 1
3.3%
126.82736233 1
3.3%
126.852453 1
3.3%
ValueCountFrequency (%)
129.08926984 1
3.3%
129.04736457 1
3.3%
129.02304568 1
3.3%
128.989701 1
3.3%
128.9189272 1
3.3%
128.74464944 1
3.3%
128.663252 1
3.3%
128.629358 1
3.3%
128.508176 1
3.3%
128.442582 1
3.3%

운영시간
Categorical

HIGH CORRELATION 

Distinct6
Distinct (%)20.0%
Missing0
Missing (%)0.0%
Memory size372.0 B
주중/주말 : 24시간
14 
24시간
9 
주중/주말 : 06시~23시
4 
24시간 이용가능
 
1
06~23시
 
1

Length

Max length15
Median length12
Mean length9.8
Min length4

Unique

Unique3 ?
Unique (%)10.0%

Sample

1st row주중/주말 : 06시~23시
2nd row24시간 이용가능
3rd row24시간
4th row주중/주말 : 24시간
5th row주중/주말 : 24시간

Common Values

ValueCountFrequency (%)
주중/주말 : 24시간 14
46.7%
24시간 9
30.0%
주중/주말 : 06시~23시 4
 
13.3%
24시간 이용가능 1
 
3.3%
06~23시 1
 
3.3%
주중/주말 : 07시~19시 1
 
3.3%

Length

2023-12-10T23:23:11.680647image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:23:11.791560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
24시간 24
34.8%
주중/주말 19
27.5%
19
27.5%
06시~23시 4
 
5.8%
이용가능 1
 
1.4%
06~23시 1
 
1.4%
07시~19시 1
 
1.4%

충전유형명
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)6.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
DC차데모+AC3상+DC콤보
29 
DC차데모+AC3상
 
1

Length

Max length15
Median length15
Mean length14.833333
Min length10

Unique

Unique1 ?
Unique (%)3.3%

Sample

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

Common Values

ValueCountFrequency (%)
DC차데모+AC3상+DC콤보 29
96.7%
DC차데모+AC3상 1
 
3.3%

Length

2023-12-10T23:23:11.927002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T23:23:12.040089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
dc차데모+ac3상+dc콤보 29
96.7%
dc차데모+ac3상 1
 
3.3%

사용횟수
Real number (ℝ)

ZEROS 

Distinct27
Distinct (%)90.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean73.9
Minimum0
Maximum151
Zeros2
Zeros (%)6.7%
Negative0
Negative (%)0.0%
Memory size402.0 B
2023-12-10T23:23:12.147425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1.8
Q139
median71
Q3120.25
95-th percentile142.75
Maximum151
Range151
Interquartile range (IQR)81.25

Descriptive statistics

Standard deviation47.925481
Coefficient of variation (CV)0.64851801
Kurtosis-1.2750519
Mean73.9
Median Absolute Deviation (MAD)39.5
Skewness0.0033830686
Sum2217
Variance2296.8517
MonotonicityNot monotonic
2023-12-10T23:23:12.262202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
131 2
 
6.7%
0 2
 
6.7%
39 2
 
6.7%
145 1
 
3.3%
85 1
 
3.3%
47 1
 
3.3%
129 1
 
3.3%
118 1
 
3.3%
49 1
 
3.3%
31 1
 
3.3%
Other values (17) 17
56.7%
ValueCountFrequency (%)
0 2
6.7%
4 1
3.3%
5 1
3.3%
14 1
3.3%
31 1
3.3%
32 1
3.3%
39 2
6.7%
44 1
3.3%
47 1
3.3%
49 1
3.3%
ValueCountFrequency (%)
151 1
3.3%
145 1
3.3%
140 1
3.3%
131 2
6.7%
129 1
3.3%
122 1
3.3%
121 1
3.3%
118 1
3.3%
107 1
3.3%
100 1
3.3%

충전시간
Date

Distinct29
Distinct (%)96.7%
Missing0
Missing (%)0.0%
Memory size372.0 B
Minimum2023-12-10 00:00:00
Maximum2023-12-10 22:06:34
2023-12-10T23:23:12.369661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:23:12.491356image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=29)

Interactions

2023-12-10T23:23:05.361663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:23:03.349336image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:23:03.852660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:23:04.364099image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:23:04.816007image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:23:05.468184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:23:03.458964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:23:03.955976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:23:04.462839image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:23:04.934030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:23:05.570580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:23:03.541271image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:23:04.054691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:23:04.547927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:23:05.038668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:23:05.677634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:23:03.633939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:23:04.150214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:23:04.630082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:23:05.139648image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:23:05.764523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:23:03.741815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:23:04.252022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:23:04.705546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-10T23:23:05.242698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T23:23:12.596684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
개방충전소ID개방충전기ID개방충전소이름운영기관시도명시군구명읍면동명도로명도로명번호건물명상세주소위도경도운영시간충전유형명사용횟수충전시간
개방충전소ID1.0000.0001.0000.6550.0000.0001.0001.0001.000NaN0.0000.0000.0001.0000.6550.0001.000
개방충전기ID0.0001.0001.0000.0000.0000.0001.0001.0001.0000.917NaN0.0670.0000.0000.0000.6630.937
개방충전소이름1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0000.0001.0001.0001.0001.0001.0001.000
운영기관0.6550.0001.0001.0000.0000.0001.0001.0001.000NaN0.0000.0000.0001.0000.6550.0001.000
시도명0.0000.0001.0000.0001.0001.0001.0001.0000.5970.9320.0000.9770.8770.0000.0000.0000.965
시군구명0.0000.0001.0000.0001.0001.0001.0001.0000.9550.9270.0001.0000.8850.0000.0000.8980.984
읍면동명1.0001.0001.0001.0001.0001.0001.0001.0001.0001.000NaN1.0001.0001.0001.0001.0001.000
도로명1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0000.0001.0001.0001.0001.0001.0001.000
도로명번호1.0001.0001.0001.0000.5970.9551.0001.0001.0001.0000.0000.7980.0001.0001.0000.9330.990
건물명NaN0.9171.000NaN0.9320.9271.0001.0001.0001.000NaN0.9380.7570.942NaN0.9050.977
상세주소0.000NaN0.0000.0000.0000.000NaN0.0000.000NaN1.0000.0000.0000.0000.0000.0000.000
위도0.0000.0671.0000.0000.9771.0001.0001.0000.7980.9380.0001.0000.7670.0000.0000.0000.951
경도0.0000.0001.0000.0000.8770.8851.0001.0000.0000.7570.0000.7671.0000.0000.0000.0000.964
운영시간1.0000.0001.0001.0000.0000.0001.0001.0001.0000.9420.0000.0000.0001.0001.0000.0000.000
충전유형명0.6550.0001.0000.6550.0000.0001.0001.0001.000NaN0.0000.0000.0001.0001.0000.0001.000
사용횟수0.0000.6631.0000.0000.0000.8981.0001.0000.9330.9050.0000.0000.0000.0000.0001.0001.000
충전시간1.0000.9371.0001.0000.9650.9841.0001.0000.9900.9770.0000.9510.9640.0001.0001.0001.000
2023-12-10T23:23:12.755578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시도명운영시간충전유형명운영기관
시도명1.0000.0000.0000.000
운영시간0.0001.0000.9260.926
충전유형명0.0000.9261.0000.454
운영기관0.0000.9260.4541.000
2023-12-10T23:23:12.865252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
개방충전소ID개방충전기ID위도경도사용횟수운영기관시도명운영시간충전유형명
개방충전소ID1.0000.500-0.132-0.232-0.3650.4540.0000.9260.454
개방충전기ID0.5001.000-0.363-0.2910.0850.0000.0000.0000.000
위도-0.132-0.3631.0000.2490.0760.0000.8560.0000.000
경도-0.232-0.2910.2491.0000.2640.0000.6190.0000.000
사용횟수-0.3650.0850.0760.2641.0000.0000.0000.0000.000
운영기관0.4540.0000.0000.0000.0001.0000.0000.9260.454
시도명0.0000.0000.8560.6190.0000.0001.0000.0000.000
운영시간0.9260.0000.0000.0000.0000.9260.0001.0000.926
충전유형명0.4540.0000.0000.0000.0000.4540.0000.9261.000

Missing values

2023-12-10T23:23:05.928028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T23:23:06.181063image/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.
2023-12-10T23:23:06.370578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

조회년월개방충전소ID개방충전기ID개방충전소이름운영기관시도명시군구명읍면동명도로명도로명번호건물명상세주소위도경도운영시간충전유형명사용횟수충전시간
02021-0410006538서초지사한국전력서울특별시서초구<NA>서운로9길38<NA><NA>37.486214127.027811주중/주말 : 06시~23시DC차데모+AC3상+DC콤보14501:37:25.7
12021-041001거문오름환경부제주특별자치도제주시조천읍선화길20-28<NA>소형주차장33.454821126.71171124시간 이용가능DC차데모+AC3상1405:35:59.6
22021-04100118820서귀포지사한국전력제주특별자치도서귀포시<NA>신중로56한국전력서귀포지점<NA>33.254374126.51081924시간DC차데모+AC3상+DC콤보13111:22:46.8
32021-0410028620창원스포츠파크한국전력경상남도창원시 성산구<NA>원이대로450<NA><NA>35.234108128.663252주중/주말 : 24시간DC차데모+AC3상+DC콤보15107:17:51.1
42021-04100216167내서읍사무소한국전력경상남도창원시 마산회원구내서읍중리상곡로75주택<NA>35.247412128.508176주중/주말 : 24시간DC차데모+AC3상+DC콤보10004:35:18.0
52021-041005177강릉특별지사한국전력강원도강릉시<NA>강릉대로563<NA>지사주차장37.782422128.918927주중/주말 : 06시~23시DC차데모+AC3상+DC콤보5608:32:46.0
62021-0410058336강동송파지사한국전력서울특별시강동구<NA>양재대로1318한국전력 강동송파지사<NA>37.523865127.13566624시간DC차데모+AC3상+DC콤보12202:21:57.2
72021-04100621416안양지사한국전력경기도안양시 동안구<NA>귀인로59<NA><NA>37.383964126.94725324시간DC차데모+AC3상+DC콤보9018:39:28.4
82021-0410063355안산지사(공용)한국전력경기도안산시 단원구<NA>원고잔로25한국전력공사<NA>37.320678126.827362주중/주말 : 24시간DC차데모+AC3상+DC콤보10711:47:50.3
92021-0410066365오산지사한국전력경기도오산시<NA>남부대로334한국전력<NA>37.13571127.072714주중/주말 : 06시~23시DC차데모+AC3상+DC콤보402:39:00.9
조회년월개방충전소ID개방충전기ID개방충전소이름운영기관시도명시군구명읍면동명도로명도로명번호건물명상세주소위도경도운영시간충전유형명사용횟수충전시간
202021-0410221714한경119센터한국전력제주특별자치도제주시한경면일주서로4218한경119센터<NA>33.342896126.182928주중/주말 : 24시간DC차데모+AC3상+DC콤보4402:59:14.4
212021-0410236820국립현대미술관 서울관한국전력서울특별시종로구<NA>삼청로30<NA><NA>37.579613126.98038주중/주말 : 24시간DC차데모+AC3상+DC콤보6214:02:25.2
222021-0410246916보령지사한국전력충청남도보령시<NA>옥마로60<NA><NA>36.337558126.622671주중/주말 : 24시간DC차데모+AC3상+DC콤보3208:21:18.2
232021-04102621204반남국립박물관한국전력전라남도나주시반남면고분로756나주신촌리고분군<NA>34.914573126.660386주중/주말 : 24시간DC차데모+AC3상+DC콤보505:26:00.7
242021-04102661210클레이아크미술관한국전력경상남도김해시진례면진례로275-51클레이아크<NA>35.251125128.74464924시간DC차데모+AC3상+DC콤보3107:13:07.5
252021-04102831345가납공영주차장한국전력경기도양주시광적면삼일로20<NA><NA>37.820975126.987485주중/주말 : 24시간DC차데모+AC3상+DC콤보4901:16:02.7
262021-04102731220부산대남측한국전력부산광역시금정구<NA>중앙대로1603삼성디지털프라자<NA>35.227696129.0892724시간DC차데모+AC3상+DC콤보11822:06:34.7
272021-04102841432국립제주박물관한국전력제주특별자치도제주시<NA>일주동로17국립제주박물관<NA>33.514248126.54897주중/주말 : 07시~19시DC차데모+AC3상+DC콤보000:00:00.0
282021-04102861447송당리사무소한국전력제주특별자치도제주시구좌읍중산간동로2210<NA><NA>33.471628126.77915주중/주말 : 24시간DC차데모+AC3상+DC콤보12916:49:23.4
292021-04102881473대천동주민센터한국전력제주특별자치도서귀포시<NA>도순로44대천동주민센터<NA>33.251056126.477564주중/주말 : 24시간DC차데모+AC3상+DC콤보4710:38:19.4