Overview

Dataset statistics

Number of variables7
Number of observations89
Missing cells6
Missing cells (%)1.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory5.0 KiB
Average record size in memory57.5 B

Variable types

Text3
Categorical1
Unsupported3

Dataset

Description춘천시 관내 주유소의 유류가격 동향정보 제공
Author강원도 춘천시
URLhttps://www.data.go.kr/data/3033672/fileData.do

Alerts

Unnamed: 2 has 3 (3.4%) missing valuesMissing
Unnamed: 3 has 3 (3.4%) missing valuesMissing
주유소 유류가격 현황(2013. 10. 24.) has unique valuesUnique
Unnamed: 4 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 5 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 6 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2023-12-12 10:57:06.197632
Analysis finished2023-12-12 10:57:07.367229
Duration1.17 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

주유소 유류가격 현황(2013. 10. 24.)
Text

UNIQUE 

Distinct89
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size844.0 B
2023-12-12T19:57:07.714322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length13
Mean length6.4044944
Min length3

Characters and Unicode

Total characters570
Distinct characters159
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique89 ?
Unique (%)100.0%

Sample

1st row업소명
2nd row(유)동성피엔앨신포지점
3rd row가람주유소
4th row강남주유소
5th row강변주유소
ValueCountFrequency (%)
업소명 1
 
1.1%
㈜중부에너지신동주유소충전소 1
 
1.1%
㈜가스코 1
 
1.1%
제일주유소 1
 
1.1%
잼버리주유소 1
 
1.1%
장학주유소 1
 
1.1%
장미주유소 1
 
1.1%
인형극장주유소 1
 
1.1%
위도현대주유소 1
 
1.1%
원일유통춘천(상)주유소 1
 
1.1%
Other values (81) 81
89.0%
2023-12-12T19:57:08.444445image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
소 82
 
14.4%
유 82
 
14.4%
주 79
 
13.9%
천 12
 
2.1%
( 10
 
1.8%
) 10
 
1.8%
동 10
 
1.8%
춘 8
 
1.4%
지 8
 
1.4%
대 6
 
1.1%
Other values (149) 263
46.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 532
93.3%
Open Punctuation 10
 
1.8%
Close Punctuation 10
 
1.8%
Uppercase Letter 7
 
1.2%
Other Punctuation 3
 
0.5%
Space Separator 3
 
0.5%
Lowercase Letter 3
 
0.5%
Other Symbol 2
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
소 82
 
15.4%
유 82
 
15.4%
주 79
 
14.8%
천 12
 
2.3%
동 10
 
1.9%
춘 8
 
1.5%
지 8
 
1.5%
대 6
 
1.1%
에 6
 
1.1%
가 5
 
0.9%
Other values (135) 234
44.0%
Uppercase Letter
ValueCountFrequency (%)
S 2
28.6%
K 1
14.3%
O 1
14.3%
C 1
14.3%
I 1
14.3%
G 1
14.3%
Lowercase Letter
ValueCountFrequency (%)
f 1
33.3%
l 1
33.3%
e 1
33.3%
Open Punctuation
ValueCountFrequency (%)
( 10
100.0%
Close Punctuation
ValueCountFrequency (%)
) 10
100.0%
Other Punctuation
ValueCountFrequency (%)
. 3
100.0%
Space Separator
ValueCountFrequency (%)
3
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 534
93.7%
Common 26
 
4.6%
Latin 10
 
1.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
소 82
 
15.4%
유 82
 
15.4%
주 79
 
14.8%
천 12
 
2.2%
동 10
 
1.9%
춘 8
 
1.5%
지 8
 
1.5%
대 6
 
1.1%
에 6
 
1.1%
가 5
 
0.9%
Other values (136) 236
44.2%
Latin
ValueCountFrequency (%)
S 2
20.0%
K 1
10.0%
f 1
10.0%
l 1
10.0%
e 1
10.0%
O 1
10.0%
C 1
10.0%
I 1
10.0%
G 1
10.0%
Common
ValueCountFrequency (%)
( 10
38.5%
) 10
38.5%
. 3
 
11.5%
3
 
11.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 532
93.3%
ASCII 36
 
6.3%
None 2
 
0.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
소 82
 
15.4%
유 82
 
15.4%
주 79
 
14.8%
천 12
 
2.3%
동 10
 
1.9%
춘 8
 
1.5%
지 8
 
1.5%
대 6
 
1.1%
에 6
 
1.1%
가 5
 
0.9%
Other values (135) 234
44.0%
ASCII
ValueCountFrequency (%)
( 10
27.8%
) 10
27.8%
. 3
 
8.3%
3
 
8.3%
S 2
 
5.6%
K 1
 
2.8%
f 1
 
2.8%
l 1
 
2.8%
e 1
 
2.8%
O 1
 
2.8%
Other values (3) 3
 
8.3%
None
ValueCountFrequency (%)
㈜ 2
100.0%

Unnamed: 1
Categorical

Distinct15
Distinct (%)16.9%
Missing0
Missing (%)0.0%
Memory size844.0 B
SK
32 
GS
17 
현대
12 
SK(직영)
8 
S-OIL
5 
Other values (10)
15 

Length

Max length9
Median length2
Mean length3.011236
Min length2

Unique

Unique7 ?
Unique (%)7.9%

Sample

1st row상 표
2nd rowSOL
3rd rowGS
4th row현대
5th row현대

Common Values

ValueCountFrequency (%)
SK 32
36.0%
GS 17
19.1%
현대 12
 
13.5%
SK(직영) 8
 
9.0%
S-OIL 5
 
5.6%
GS(직영) 3
 
3.4%
<NA> 3
 
3.4%
현대(직영) 2
 
2.2%
상 표 1
 
1.1%
SOL 1
 
1.1%
Other values (5) 5
 
5.6%

Length

2023-12-12T19:57:08.730867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
sk 32
35.6%
gs 17
18.9%
현대 12
 
13.3%
sk(직영 8
 
8.9%
s-oil 5
 
5.6%
gs(직영 3
 
3.3%
na 3
 
3.3%
현대(직영 2
 
2.2%
상 1
 
1.1%
표 1
 
1.1%
Other values (6) 6
 
6.7%

Unnamed: 2
Text

MISSING 

Distinct86
Distinct (%)100.0%
Missing3
Missing (%)3.4%
Memory size844.0 B
2023-12-12T19:57:09.180787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length8
Mean length8.0465116
Min length4

Characters and Unicode

Total characters692
Distinct characters17
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

Unique86 ?
Unique (%)100.0%

Sample

1st row전화번호
2nd row243-5188
3rd row252-5161
4th row251-5170
5th row263-2210
ValueCountFrequency (%)
255-0710+3 1
 
1.2%
261-3351 1
 
1.2%
244-5188 1
 
1.2%
242-0067 1
 
1.2%
255-9283 1
 
1.2%
256-8951 1
 
1.2%
242-3700 1
 
1.2%
264-0391 1
 
1.2%
257-5182 1
 
1.2%
252-2464 1
 
1.2%
Other values (76) 76
88.4%
2023-12-12T19:57:09.911036image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 143
20.7%
- 85
12.3%
5 79
11.4%
1 71
10.3%
4 64
9.2%
6 61
8.8%
0 48
 
6.9%
3 41
 
5.9%
8 37
 
5.3%
7 30
 
4.3%
Other values (7) 33
 
4.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 596
86.1%
Dash Punctuation 85
 
12.3%
Space Separator 6
 
0.9%
Other Letter 4
 
0.6%
Math Symbol 1
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 143
24.0%
5 79
13.3%
1 71
11.9%
4 64
10.7%
6 61
10.2%
0 48
 
8.1%
3 41
 
6.9%
8 37
 
6.2%
7 30
 
5.0%
9 22
 
3.7%
Other Letter
ValueCountFrequency (%)
전 1
25.0%
화 1
25.0%
번 1
25.0%
호 1
25.0%
Dash Punctuation
ValueCountFrequency (%)
- 85
100.0%
Space Separator
ValueCountFrequency (%)
6
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 688
99.4%
Hangul 4
 
0.6%

Most frequent character per script

Common
ValueCountFrequency (%)
2 143
20.8%
- 85
12.4%
5 79
11.5%
1 71
10.3%
4 64
9.3%
6 61
8.9%
0 48
 
7.0%
3 41
 
6.0%
8 37
 
5.4%
7 30
 
4.4%
Other values (3) 29
 
4.2%
Hangul
ValueCountFrequency (%)
전 1
25.0%
화 1
25.0%
번 1
25.0%
호 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 688
99.4%
Hangul 4
 
0.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 143
20.8%
- 85
12.4%
5 79
11.5%
1 71
10.3%
4 64
9.3%
6 61
8.9%
0 48
 
7.0%
3 41
 
6.0%
8 37
 
5.4%
7 30
 
4.4%
Other values (3) 29
 
4.2%
Hangul
ValueCountFrequency (%)
전 1
25.0%
화 1
25.0%
번 1
25.0%
호 1
25.0%

Unnamed: 3
Text

MISSING 

Distinct86
Distinct (%)100.0%
Missing3
Missing (%)3.4%
Memory size844.0 B
2023-12-12T19:57:10.423372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length16.5
Mean length12.965116
Min length5

Characters and Unicode

Total characters1115
Distinct characters103
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique86 ?
Unique (%)100.0%

Sample

1st row소 재 지
2nd row사북면 지촌리 100-3
3rd row심일로 301(사농동 291)
4th row온의동 155-1
5th row서면 경춘대로 918(서면 100)
ValueCountFrequency (%)
동면 9
 
4.0%
서면 8
 
3.5%
경춘대로 6
 
2.6%
동내면 6
 
2.6%
신동면 4
 
1.8%
호반순환로 4
 
1.8%
남산면 4
 
1.8%
만천리 3
 
1.3%
신북읍 3
 
1.3%
김유정로 3
 
1.3%
Other values (158) 177
78.0%
2023-12-12T19:57:11.192246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
142
 
12.7%
1 83
 
7.4%
동 65
 
5.8%
2 47
 
4.2%
7 40
 
3.6%
면 40
 
3.6%
로 39
 
3.5%
0 39
 
3.5%
3 36
 
3.2%
- 36
 
3.2%
Other values (93) 548
49.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 467
41.9%
Decimal Number 402
36.1%
Space Separator 142
 
12.7%
Dash Punctuation 36
 
3.2%
Open Punctuation 34
 
3.0%
Close Punctuation 34
 
3.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 65
 
13.9%
면 40
 
8.6%
로 39
 
8.4%
리 31
 
6.6%
서 11
 
2.4%
신 11
 
2.4%
사 11
 
2.4%
후 10
 
2.1%
석 8
 
1.7%
내 8
 
1.7%
Other values (79) 233
49.9%
Decimal Number
ValueCountFrequency (%)
1 83
20.6%
2 47
11.7%
7 40
10.0%
0 39
9.7%
3 36
9.0%
5 35
8.7%
8 33
 
8.2%
4 32
 
8.0%
6 32
 
8.0%
9 25
 
6.2%
Space Separator
ValueCountFrequency (%)
142
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 36
100.0%
Open Punctuation
ValueCountFrequency (%)
( 34
100.0%
Close Punctuation
ValueCountFrequency (%)
) 34
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 648
58.1%
Hangul 467
41.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 65
 
13.9%
면 40
 
8.6%
로 39
 
8.4%
리 31
 
6.6%
서 11
 
2.4%
신 11
 
2.4%
사 11
 
2.4%
후 10
 
2.1%
석 8
 
1.7%
내 8
 
1.7%
Other values (79) 233
49.9%
Common
ValueCountFrequency (%)
142
21.9%
1 83
12.8%
2 47
 
7.3%
7 40
 
6.2%
0 39
 
6.0%
3 36
 
5.6%
- 36
 
5.6%
5 35
 
5.4%
( 34
 
5.2%
) 34
 
5.2%
Other values (4) 122
18.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 648
58.1%
Hangul 467
41.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
142
21.9%
1 83
12.8%
2 47
 
7.3%
7 40
 
6.2%
0 39
 
6.0%
3 36
 
5.6%
- 36
 
5.6%
5 35
 
5.4%
( 34
 
5.2%
) 34
 
5.2%
Other values (4) 122
18.8%
Hangul
ValueCountFrequency (%)
동 65
 
13.9%
면 40
 
8.6%
로 39
 
8.4%
리 31
 
6.6%
서 11
 
2.4%
신 11
 
2.4%
사 11
 
2.4%
후 10
 
2.1%
석 8
 
1.7%
내 8
 
1.7%
Other values (79) 233
49.9%

Unnamed: 4
Unsupported

REJECTED  UNSUPPORTED 

Missing0
Missing (%)0.0%
Memory size844.0 B

Unnamed: 5
Unsupported

REJECTED  UNSUPPORTED 

Missing0
Missing (%)0.0%
Memory size844.0 B

Unnamed: 6
Unsupported

REJECTED  UNSUPPORTED 

Missing0
Missing (%)0.0%
Memory size844.0 B

Correlations

2023-12-12T19:57:11.357346image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
주유소 유류가격 현황(2013. 10. 24.)Unnamed: 1Unnamed: 2Unnamed: 3
주유소 유류가격 현황(2013. 10. 24.)\n1.0001.0001.0001.000
Unnamed: 11.0001.0001.0001.000
Unnamed: 21.0001.0001.0001.000
Unnamed: 31.0001.0001.0001.000

Missing values

2023-12-12T19:57:06.826642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T19:57:07.054420image/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.
2023-12-12T19:57:07.263349image/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

주유소 유류가격 현황(2013. 10. 24.)Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6
0업소명상 표전화번호소 재 지휘발유경유실내등유
1(유)동성피엔앨신포지점SOL243-5188사북면 지촌리 100-3188916991235
2가람주유소GS252-5161심일로 301(사농동 291)191717291300
3강남주유소현대251-5170온의동 155-118651679-
4강변주유소현대263-2210서면 경춘대로 918(서면 100)18691659-
5강원주유소SK(직영)254-2227금강로 22(소양로3가 182)204518561392
6개나리주유소SK(직영)264-0370퇴계로 303(석사동 818)18751685-
7거두GS주유소GS(직영)264-7600동내면 거두리 910 1500189517291350
8거북이주유소현대253-5182근화동 266188516951400
9고속터미널주유소현대(직영)243-8288경춘대로 110(온의동 512-1)188417381350
주유소 유류가격 현황(2013. 10. 24.)Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6
79행복한주유소SK252-5149후평동717-18185916691260
80현대주유소SK(직영)254-7186중앙로 225(근화동709)204118461442
81현진주유소(구.동부)SK254-4437금강로 160(운교동 174)185916691275
82호원주유소(춘천지점)알뜰주유소263-8584서면 안보리 636-1185016471310
83화성주유소SK262-4234김유정로 19(퇴계동783)196817791350
84황골주유소현대263-7363남면778193917391450
85OK주유소SK(직영)253-4951후평3동 701198918541345
86평균가격<NA><NA><NA>1911.3647061722.8352941330.938462
87최고가격<NA><NA><NA>204818561468
88최저가격<NA><NA><NA>184916471195