Overview

Dataset statistics

Number of variables8
Number of observations34
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.4 KiB
Average record size in memory72.9 B

Variable types

Numeric1
Categorical5
Text2

Dataset

Description경상남도 양산시 전기자동차 공용충전시설 현황에 대한 자료로 설치기관, 설치연도, 충전소명, 위치, 충전기 수 등의 정보를 제공합니다.
Author경상남도 양산시
URLhttps://www.data.go.kr/data/15105401/fileData.do

Alerts

급속 is highly overall correlated with 합계High correlation
설치기관 is highly overall correlated with 연번 and 1 other fieldsHigh correlation
완속 is highly overall correlated with 연번 and 3 other fieldsHigh correlation
설치연도 is highly overall correlated with 연번 and 1 other fieldsHigh correlation
합계 is highly overall correlated with 급속 and 1 other fieldsHigh correlation
연번 is highly overall correlated with 설치기관 and 2 other fieldsHigh correlation
연번 has unique valuesUnique

Reproduction

Analysis started2023-12-12 00:26:33.671174
Analysis finished2023-12-12 00:26:34.277191
Duration0.61 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct34
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean17.764706
Minimum1
Maximum35
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size438.0 B
2023-12-12T09:26:34.332112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2.65
Q19.25
median17.5
Q326.5
95-th percentile33.35
Maximum35
Range34
Interquartile range (IQR)17.25

Descriptive statistics

Standard deviation10.304629
Coefficient of variation (CV)0.58006191
Kurtosis-1.1934921
Mean17.764706
Median Absolute Deviation (MAD)9
Skewness0.057730206
Sum604
Variance106.18538
MonotonicityStrictly increasing
2023-12-12T09:26:34.440901image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
1 1
 
2.9%
28 1
 
2.9%
21 1
 
2.9%
22 1
 
2.9%
23 1
 
2.9%
24 1
 
2.9%
25 1
 
2.9%
27 1
 
2.9%
29 1
 
2.9%
19 1
 
2.9%
Other values (24) 24
70.6%
ValueCountFrequency (%)
1 1
2.9%
2 1
2.9%
3 1
2.9%
4 1
2.9%
5 1
2.9%
6 1
2.9%
7 1
2.9%
8 1
2.9%
9 1
2.9%
10 1
2.9%
ValueCountFrequency (%)
35 1
2.9%
34 1
2.9%
33 1
2.9%
32 1
2.9%
31 1
2.9%
30 1
2.9%
29 1
2.9%
28 1
2.9%
27 1
2.9%
25 1
2.9%

설치기관
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)14.7%
Missing0
Missing (%)0.0%
Memory size404.0 B
환경부
17 
한전
7 
양산시
6 
포스코ICT
3 
현대 자동차
 
1

Length

Max length6
Median length3
Mean length3.1470588
Min length2

Unique

Unique1 ?
Unique (%)2.9%

Sample

1st row포스코ICT
2nd row포스코ICT
3rd row포스코ICT
4th row한전
5th row현대 자동차

Common Values

ValueCountFrequency (%)
환경부 17
50.0%
한전 7
20.6%
양산시 6
 
17.6%
포스코ICT 3
 
8.8%
현대 자동차 1
 
2.9%

Length

2023-12-12T09:26:34.576772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T09:26:34.696102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
환경부 17
48.6%
한전 7
20.0%
양산시 6
 
17.1%
포스코ict 3
 
8.6%
현대 1
 
2.9%
자동차 1
 
2.9%

설치연도
Categorical

HIGH CORRELATION 

Distinct5
Distinct (%)14.7%
Missing0
Missing (%)0.0%
Memory size404.0 B
2018
23 
2015
5 
2017
4 
2016
 
1
2014
 
1

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique2 ?
Unique (%)5.9%

Sample

1st row2015
2nd row2015
3rd row2015
4th row2016
5th row2015

Common Values

ValueCountFrequency (%)
2018 23
67.6%
2015 5
 
14.7%
2017 4
 
11.8%
2016 1
 
2.9%
2014 1
 
2.9%

Length

2023-12-12T09:26:34.803945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T09:26:34.912435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2018 23
67.6%
2015 5
 
14.7%
2017 4
 
11.8%
2016 1
 
2.9%
2014 1
 
2.9%

충전소명
Text

Distinct31
Distinct (%)91.2%
Missing0
Missing (%)0.0%
Memory size404.0 B
2023-12-12T09:26:35.109041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length15
Mean length7.9705882
Min length4

Characters and Unicode

Total characters271
Distinct characters105
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique28 ?
Unique (%)82.4%

Sample

1st row이마트트레이더스 양산점
2nd row이마트 양산점
3rd row양산시 LG BESTSHOP(양산북정점)
4th row양산지사
5th row하북점 블루핸즈
ValueCountFrequency (%)
양산시청 3
 
7.1%
양산디자인공원 2
 
4.8%
양산점 2
 
4.8%
양산종합운동장 2
 
4.8%
영어도서관 1
 
2.4%
상북면행정복지센터 1
 
2.4%
제1공영주차장 1
 
2.4%
강서주민편의시설 1
 
2.4%
제2청사 1
 
2.4%
롯데마트 1
 
2.4%
Other values (27) 27
64.3%
2023-12-12T09:26:35.454206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
산 18
 
6.6%
양 15
 
5.5%
8
 
3.0%
동 7
 
2.6%
지 7
 
2.6%
소 7
 
2.6%
시 6
 
2.2%
상 6
 
2.2%
원 6
 
2.2%
주 5
 
1.8%
Other values (95) 186
68.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 243
89.7%
Uppercase Letter 10
 
3.7%
Space Separator 8
 
3.0%
Close Punctuation 3
 
1.1%
Open Punctuation 3
 
1.1%
Connector Punctuation 2
 
0.7%
Decimal Number 2
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 18
 
7.4%
양 15
 
6.2%
동 7
 
2.9%
지 7
 
2.9%
소 7
 
2.9%
시 6
 
2.5%
상 6
 
2.5%
원 6
 
2.5%
주 5
 
2.1%
센 5
 
2.1%
Other values (80) 161
66.3%
Uppercase Letter
ValueCountFrequency (%)
S 2
20.0%
P 1
10.0%
E 1
10.0%
O 1
10.0%
G 1
10.0%
L 1
10.0%
T 1
10.0%
H 1
10.0%
B 1
10.0%
Decimal Number
ValueCountFrequency (%)
1 1
50.0%
2 1
50.0%
Space Separator
ValueCountFrequency (%)
8
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 243
89.7%
Common 18
 
6.6%
Latin 10
 
3.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 18
 
7.4%
양 15
 
6.2%
동 7
 
2.9%
지 7
 
2.9%
소 7
 
2.9%
시 6
 
2.5%
상 6
 
2.5%
원 6
 
2.5%
주 5
 
2.1%
센 5
 
2.1%
Other values (80) 161
66.3%
Latin
ValueCountFrequency (%)
S 2
20.0%
P 1
10.0%
E 1
10.0%
O 1
10.0%
G 1
10.0%
L 1
10.0%
T 1
10.0%
H 1
10.0%
B 1
10.0%
Common
ValueCountFrequency (%)
8
44.4%
) 3
 
16.7%
( 3
 
16.7%
_ 2
 
11.1%
1 1
 
5.6%
2 1
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 243
89.7%
ASCII 28
 
10.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
산 18
 
7.4%
양 15
 
6.2%
동 7
 
2.9%
지 7
 
2.9%
소 7
 
2.9%
시 6
 
2.5%
상 6
 
2.5%
원 6
 
2.5%
주 5
 
2.1%
센 5
 
2.1%
Other values (80) 161
66.3%
ASCII
ValueCountFrequency (%)
8
28.6%
) 3
 
10.7%
( 3
 
10.7%
_ 2
 
7.1%
S 2
 
7.1%
1 1
 
3.6%
P 1
 
3.6%
2 1
 
3.6%
E 1
 
3.6%
O 1
 
3.6%
Other values (5) 5
17.9%

위치
Text

Distinct30
Distinct (%)88.2%
Missing0
Missing (%)0.0%
Memory size404.0 B
2023-12-12T09:26:35.707818image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length22
Mean length19.088235
Min length15

Characters and Unicode

Total characters649
Distinct characters76
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

Unique26 ?
Unique (%)76.5%

Sample

1st row경상남도 양산시 평산로 16
2nd row경상남도 양산시 양산역6길 12
3rd row경상남도 양산시 양산대로 915 옥외주차장
4th row경상남도 양산시 고향의봄로 42
5th row경상남도 양산시 하북면 양산대로 2627
ValueCountFrequency (%)
경상남도 34
21.7%
양산시 34
21.7%
양산대로 7
 
4.5%
동면 4
 
2.5%
물금읍 4
 
2.5%
40 3
 
1.9%
하북면 3
 
1.9%
진등길 2
 
1.3%
주차장 2
 
1.3%
상북면 2
 
1.3%
Other values (54) 62
39.5%
2023-12-12T09:26:36.120786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
123
19.0%
산 45
 
6.9%
양 42
 
6.5%
상 37
 
5.7%
경 35
 
5.4%
도 35
 
5.4%
남 35
 
5.4%
시 34
 
5.2%
로 23
 
3.5%
1 22
 
3.4%
Other values (66) 218
33.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 419
64.6%
Space Separator 123
 
19.0%
Decimal Number 100
 
15.4%
Dash Punctuation 7
 
1.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 45
 
10.7%
양 42
 
10.0%
상 37
 
8.8%
경 35
 
8.4%
도 35
 
8.4%
남 35
 
8.4%
시 34
 
8.1%
로 23
 
5.5%
면 10
 
2.4%
동 10
 
2.4%
Other values (54) 113
27.0%
Decimal Number
ValueCountFrequency (%)
1 22
22.0%
3 14
14.0%
0 10
10.0%
4 10
10.0%
9 9
9.0%
2 9
9.0%
5 8
 
8.0%
6 7
 
7.0%
7 6
 
6.0%
8 5
 
5.0%
Space Separator
ValueCountFrequency (%)
123
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 419
64.6%
Common 230
35.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 45
 
10.7%
양 42
 
10.0%
상 37
 
8.8%
경 35
 
8.4%
도 35
 
8.4%
남 35
 
8.4%
시 34
 
8.1%
로 23
 
5.5%
면 10
 
2.4%
동 10
 
2.4%
Other values (54) 113
27.0%
Common
ValueCountFrequency (%)
123
53.5%
1 22
 
9.6%
3 14
 
6.1%
0 10
 
4.3%
4 10
 
4.3%
9 9
 
3.9%
2 9
 
3.9%
5 8
 
3.5%
6 7
 
3.0%
- 7
 
3.0%
Other values (2) 11
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 419
64.6%
ASCII 230
35.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
123
53.5%
1 22
 
9.6%
3 14
 
6.1%
0 10
 
4.3%
4 10
 
4.3%
9 9
 
3.9%
2 9
 
3.9%
5 8
 
3.5%
6 7
 
3.0%
- 7
 
3.0%
Other values (2) 11
 
4.8%
Hangul
ValueCountFrequency (%)
산 45
 
10.7%
양 42
 
10.0%
상 37
 
8.8%
경 35
 
8.4%
도 35
 
8.4%
남 35
 
8.4%
시 34
 
8.1%
로 23
 
5.5%
면 10
 
2.4%
동 10
 
2.4%
Other values (54) 113
27.0%

합계
Categorical

HIGH CORRELATION 

Distinct3
Distinct (%)8.8%
Missing0
Missing (%)0.0%
Memory size404.0 B
1
22 
2
11 
3
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)2.9%

Sample

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

Common Values

ValueCountFrequency (%)
1 22
64.7%
2 11
32.4%
3 1
 
2.9%

Length

2023-12-12T09:26:36.270053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T09:26:36.385643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 22
64.7%
2 11
32.4%
3 1
 
2.9%

급속
Categorical

HIGH CORRELATION 

Distinct4
Distinct (%)11.8%
Missing0
Missing (%)0.0%
Memory size404.0 B
1
18 
2
11 
<NA>
4 
3
 
1

Length

Max length4
Median length1
Mean length1.3529412
Min length1

Unique

Unique1 ?
Unique (%)2.9%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row2
5th row<NA>

Common Values

ValueCountFrequency (%)
1 18
52.9%
2 11
32.4%
<NA> 4
 
11.8%
3 1
 
2.9%

Length

2023-12-12T09:26:36.545955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T09:26:36.670037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 18
52.9%
2 11
32.4%
na 4
 
11.8%
3 1
 
2.9%

완속
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)5.9%
Missing0
Missing (%)0.0%
Memory size404.0 B
<NA>
30 
1
4 

Length

Max length4
Median length4
Mean length3.6470588
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row<NA>
5th row1

Common Values

ValueCountFrequency (%)
<NA> 30
88.2%
1 4
 
11.8%

Length

2023-12-12T09:26:36.799601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T09:26:36.915590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 30
88.2%
1 4
 
11.8%

Interactions

2023-12-12T09:26:34.012856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T09:26:36.983223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번설치기관설치연도충전소명위치합계급속
연번1.0000.9470.9320.7870.7530.2240.183
설치기관0.9471.0000.8180.8170.7450.0000.000
설치연도0.9320.8181.0000.0000.0000.3870.284
충전소명0.7870.8170.0001.0001.0000.8400.893
위치0.7530.7450.0001.0001.0000.8060.786
합계0.2240.0000.3870.8400.8061.0001.000
급속0.1830.0000.2840.8930.7861.0001.000
2023-12-12T09:26:37.090101image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
급속설치기관완속설치연도합계
급속1.0000.000NaN0.2041.000
설치기관0.0001.0001.0000.4410.000
완속NaN1.0001.0001.0001.000
설치연도0.2040.4411.0001.0000.302
합계1.0000.0001.0000.3021.000
2023-12-12T09:26:37.207372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번설치기관설치연도합계급속완속
연번1.0000.5820.5860.0000.0001.000
설치기관0.5821.0000.4410.0000.0001.000
설치연도0.5860.4411.0000.3020.2041.000
합계0.0000.0000.3021.0001.0001.000
급속0.0000.0000.2041.0001.0000.000
완속1.0001.0001.0001.0000.0001.000

Missing values

2023-12-12T09:26:34.112953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T09:26:34.229368image/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

연번설치기관설치연도충전소명위치합계급속완속
01포스코ICT2015이마트트레이더스 양산점경상남도 양산시 평산로 161<NA>1
12포스코ICT2015이마트 양산점경상남도 양산시 양산역6길 121<NA>1
23포스코ICT2015양산시 LG BESTSHOP(양산북정점)경상남도 양산시 양산대로 915 옥외주차장1<NA>1
34한전2016양산지사경상남도 양산시 고향의봄로 4222<NA>
45현대 자동차2015하북점 블루핸즈경상남도 양산시 하북면 양산대로 26271<NA>1
56환경부2014양산종합운동장경상남도 양산시 양산대로 849 운동장 앞 주차장11<NA>
67환경부2015내원휴게소경상남도 양산시 하북면 양산대로 196411<NA>
78환경부2017통도사(부산)휴게소_고속도로경상남도 양산시 하북면 경부고속도로 31-133<NA>
89한전2017양산주민편익시설경상남도 양산시 강변로 264-122<NA>
910한전2017양산시청경상남도 양산시 중앙로 3922<NA>
연번설치기관설치연도충전소명위치합계급속완속
2425환경부2018덕계동행정복지센터경상남도 양산시 번영로 3511<NA>
2527환경부2018포유주유소경상남도 양산시 어곡터널로 4011<NA>
2628환경부2018비학에너지경상남도 양산시 상북면 양산대로 151011<NA>
2729환경부2018물금주유소경상남도 양산시 물금읍 황산로 50111<NA>
2830환경부2018롯데마트 웅상점경상남도 양산시 삼호1길 3411<NA>
2931한전2018양산시청 제2청사경상남도 양산시 북안남2길 3622<NA>
3032한전2018강서주민편의시설경상남도 양산시 교동1길 1811<NA>
3133한전2018삼호동 제1공영주차장경상남도 양산시 삼호동 47111<NA>
3234환경부2018평산동행정복지센터경상남도 양산시 평산로 7111<NA>
3335환경부2018양산휴게소(서울방향)_고속도로경상남도 양산시 동면 목장길 15-5011<NA>