Overview

Dataset statistics

Number of variables10
Number of observations952
Missing cells9
Missing cells (%)0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory77.3 KiB
Average record size in memory83.1 B

Variable types

Text4
Boolean1
Numeric3
DateTime2

Dataset

Description주유소의 요소수 판매가격(지역별)
Author한국석유공사
URLhttps://data.gg.go.kr/portal/data/service/selectServicePage.do?&infId=16AV5FE8FIJYWJVBRG2532452510&infSeq=1

Alerts

판매단가(원/리터) is highly overall correlated with 재고유무High correlation
재고유무 is highly overall correlated with 판매단가(원/리터)High correlation
재고유무 is highly imbalanced (97.8%)Imbalance

Reproduction

Analysis started2024-05-17 20:16:45.834149
Analysis finished2024-05-17 20:16:50.894210
Duration5.06 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

주유소명
Text

Distinct932
Distinct (%)97.9%
Missing0
Missing (%)0.0%
Memory size7.6 KiB
2024-05-18T05:16:51.441989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length20
Mean length10.705882
Min length3

Characters and Unicode

Total characters10192
Distinct characters411
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

Unique914 ?
Unique (%)96.0%

Sample

1st row대신농협클린주유소
2nd row예멋Self주유소
3rd row세종대왕농협주유소
4th row지에스칼텍스㈜ 만호주유소
5th row송전휴게소주유소/충전소
ValueCountFrequency (%)
hd현대오일뱅크㈜직영 84
 
6.3%
sk에너지(주 11
 
0.8%
주유소 10
 
0.8%
주식회사 10
 
0.8%
삼미상사(주 8
 
0.6%
구도일주유소 8
 
0.6%
직영 6
 
0.5%
지에스칼텍스㈜ 6
 
0.5%
㈜삼표에너지 4
 
0.3%
경원주유소 4
 
0.3%
Other values (1098) 1174
88.6%
2024-05-18T05:16:52.630270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 1190
 
11.7%
유 982
 
9.6%
소 927
 
9.1%
373
 
3.7%
) 306
 
3.0%
( 306
 
3.0%
지 210
 
2.1%
대 210
 
2.1%
일 182
 
1.8%
에 181
 
1.8%
Other values (401) 5325
52.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8549
83.9%
Space Separator 373
 
3.7%
Uppercase Letter 364
 
3.6%
Close Punctuation 306
 
3.0%
Open Punctuation 306
 
3.0%
Other Symbol 167
 
1.6%
Lowercase Letter 72
 
0.7%
Decimal Number 29
 
0.3%
Other Punctuation 24
 
0.2%
Dash Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 1190
 
13.9%
유 982
 
11.5%
소 927
 
10.8%
지 210
 
2.5%
대 210
 
2.5%
일 182
 
2.1%
에 181
 
2.1%
프 146
 
1.7%
현 144
 
1.7%
셀 139
 
1.6%
Other values (360) 4238
49.6%
Uppercase Letter
ValueCountFrequency (%)
H 90
24.7%
D 87
23.9%
S 54
14.8%
K 39
10.7%
C 30
 
8.2%
I 27
 
7.4%
G 9
 
2.5%
T 6
 
1.6%
J 4
 
1.1%
Y 2
 
0.5%
Other values (10) 16
 
4.4%
Decimal Number
ValueCountFrequency (%)
2 11
37.9%
1 5
17.2%
4 5
17.2%
5 4
 
13.8%
9 1
 
3.4%
8 1
 
3.4%
6 1
 
3.4%
3 1
 
3.4%
Lowercase Letter
ValueCountFrequency (%)
e 20
27.8%
f 19
26.4%
l 19
26.4%
s 12
16.7%
k 2
 
2.8%
Other Punctuation
ValueCountFrequency (%)
/ 21
87.5%
. 2
 
8.3%
＆ 1
 
4.2%
Space Separator
ValueCountFrequency (%)
373
100.0%
Close Punctuation
ValueCountFrequency (%)
) 306
100.0%
Open Punctuation
ValueCountFrequency (%)
( 306
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 167
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 8716
85.5%
Common 1040
 
10.2%
Latin 436
 
4.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 1190
 
13.7%
유 982
 
11.3%
소 927
 
10.6%
지 210
 
2.4%
대 210
 
2.4%
일 182
 
2.1%
에 181
 
2.1%
㈜ 167
 
1.9%
프 146
 
1.7%
현 144
 
1.7%
Other values (361) 4377
50.2%
Latin
ValueCountFrequency (%)
H 90
20.6%
D 87
20.0%
S 54
12.4%
K 39
8.9%
C 30
 
6.9%
I 27
 
6.2%
e 20
 
4.6%
f 19
 
4.4%
l 19
 
4.4%
s 12
 
2.8%
Other values (15) 39
8.9%
Common
ValueCountFrequency (%)
373
35.9%
) 306
29.4%
( 306
29.4%
/ 21
 
2.0%
2 11
 
1.1%
1 5
 
0.5%
4 5
 
0.5%
5 4
 
0.4%
- 2
 
0.2%
. 2
 
0.2%
Other values (5) 5
 
0.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 8549
83.9%
ASCII 1475
 
14.5%
None 168
 
1.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 1190
 
13.9%
유 982
 
11.5%
소 927
 
10.8%
지 210
 
2.5%
대 210
 
2.5%
일 182
 
2.1%
에 181
 
2.1%
프 146
 
1.7%
현 144
 
1.7%
셀 139
 
1.6%
Other values (360) 4238
49.6%
ASCII
ValueCountFrequency (%)
373
25.3%
) 306
20.7%
( 306
20.7%
H 90
 
6.1%
D 87
 
5.9%
S 54
 
3.7%
K 39
 
2.6%
C 30
 
2.0%
I 27
 
1.8%
/ 21
 
1.4%
Other values (29) 142
 
9.6%
None
ValueCountFrequency (%)
㈜ 167
99.4%
＆ 1
 
0.6%

전화번호
Text

Distinct946
Distinct (%)99.4%
Missing0
Missing (%)0.0%
Memory size7.6 KiB
2024-05-18T05:16:53.152935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length12.015756
Min length9

Characters and Unicode

Total characters11439
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

Unique945 ?
Unique (%)99.3%

Sample

1st row031-884-3948
2nd row031-527-6171
3rd row031-881-4322
4th row031-681-1800
5th row031-335-4194
ValueCountFrequency (%)
031-000-0000 7
 
0.7%
031-634-5108 1
 
0.1%
031-952-6366 1
 
0.1%
031-358-5155 1
 
0.1%
031-774-1245 1
 
0.1%
031-293-5454 1
 
0.1%
031-573-0951 1
 
0.1%
031-681-5022 1
 
0.1%
031-862-1915 1
 
0.1%
031-682-6003 1
 
0.1%
Other values (936) 936
98.3%
2024-05-18T05:16:54.043702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 1903
16.6%
1 1737
15.2%
3 1621
14.2%
0 1525
13.3%
5 1068
9.3%
8 671
 
5.9%
2 626
 
5.5%
6 622
 
5.4%
7 583
 
5.1%
4 552
 
4.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 9536
83.4%
Dash Punctuation 1903
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 1737
18.2%
3 1621
17.0%
0 1525
16.0%
5 1068
11.2%
8 671
 
7.0%
2 626
 
6.6%
6 622
 
6.5%
7 583
 
6.1%
4 552
 
5.8%
9 531
 
5.6%
Dash Punctuation
ValueCountFrequency (%)
- 1903
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 11439
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 1903
16.6%
1 1737
15.2%
3 1621
14.2%
0 1525
13.3%
5 1068
9.3%
8 671
 
5.9%
2 626
 
5.5%
6 622
 
5.4%
7 583
 
5.1%
4 552
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11439
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 1903
16.6%
1 1737
15.2%
3 1621
14.2%
0 1525
13.3%
5 1068
9.3%
8 671
 
5.9%
2 626
 
5.5%
6 622
 
5.4%
7 583
 
5.1%
4 552
 
4.8%

재고유무
Boolean

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
True
950 
False
 
2
ValueCountFrequency (%)
True 950
99.8%
False 2
 
0.2%
2024-05-18T05:16:54.378130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

판매단가(원/리터)
Real number (ℝ)

HIGH CORRELATION 

Distinct36
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1673.0221
Minimum0
Maximum3000
Zeros2
Zeros (%)0.2%
Negative0
Negative (%)0.0%
Memory size8.5 KiB
2024-05-18T05:16:54.679592image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1200
Q11500
median1600
Q32000
95-th percentile2200
Maximum3000
Range3000
Interquartile range (IQR)500

Descriptive statistics

Standard deviation339.02429
Coefficient of variation (CV)0.20264185
Kurtosis2.0384909
Mean1673.0221
Median Absolute Deviation (MAD)200
Skewness0.22695985
Sum1592717
Variance114937.47
MonotonicityNot monotonic
2024-05-18T05:16:55.116071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=36)
ValueCountFrequency (%)
1500 224
23.5%
2000 175
18.4%
1800 118
12.4%
1600 96
10.1%
1300 56
 
5.9%
1700 55
 
5.8%
1400 50
 
5.3%
1200 31
 
3.3%
1900 28
 
2.9%
2200 24
 
2.5%
Other values (26) 95
10.0%
ValueCountFrequency (%)
0 2
 
0.2%
700 2
 
0.2%
790 2
 
0.2%
800 1
 
0.1%
890 2
 
0.2%
899 1
 
0.1%
900 1
 
0.1%
990 4
 
0.4%
1000 12
1.3%
1080 1
 
0.1%
ValueCountFrequency (%)
3000 6
 
0.6%
2500 17
 
1.8%
2400 12
 
1.3%
2300 3
 
0.3%
2200 24
 
2.5%
2100 3
 
0.3%
2000 175
18.4%
1998 1
 
0.1%
1900 28
 
2.9%
1800 118
12.4%

결제일자
Date

Distinct167
Distinct (%)17.5%
Missing0
Missing (%)0.0%
Memory size7.6 KiB
Minimum2022-04-07 00:00:00
Maximum2024-05-17 00:00:00
2024-05-18T05:16:55.556921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T05:16:55.978400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

결제시간
Date

Distinct937
Distinct (%)98.4%
Missing0
Missing (%)0.0%
Memory size7.6 KiB
Minimum2024-05-18 00:16:56
Maximum2024-05-18 23:50:40
2024-05-18T05:16:56.609386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T05:16:57.013440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

정제도로명주소
Text

Distinct946
Distinct (%)99.7%
Missing3
Missing (%)0.3%
Memory size7.6 KiB
2024-05-18T05:16:57.445076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length27
Mean length19.046365
Min length13

Characters and Unicode

Total characters18075
Distinct characters256
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

Unique943 ?
Unique (%)99.4%

Sample

1st row경기도 여주시 대신면 여양로 1537
2nd row경기도 남양주시 진접읍 금강로 1897
3rd row경기도 여주시 세종대왕면 마장로 9
4th row경기도 평택시 포승읍 서동대로 771
5th row경기도 용인시 처인구 이동읍 남북대로 2616
ValueCountFrequency (%)
경기도 949
 
21.0%
용인시 101
 
2.2%
화성시 90
 
2.0%
평택시 59
 
1.3%
처인구 53
 
1.2%
남양주시 45
 
1.0%
고양시 44
 
1.0%
안산시 43
 
1.0%
이천시 43
 
1.0%
시흥시 42
 
0.9%
Other values (1250) 3042
67.4%
2024-05-18T05:16:58.175869image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3562
19.7%
경 1041
 
5.8%
기 1009
 
5.6%
도 1002
 
5.5%
시 969
 
5.4%
로 931
 
5.2%
1 633
 
3.5%
2 417
 
2.3%
구 330
 
1.8%
3 287
 
1.6%
Other values (246) 7894
43.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 11395
63.0%
Space Separator 3562
 
19.7%
Decimal Number 3081
 
17.0%
Dash Punctuation 35
 
0.2%
Other Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
경 1041
 
9.1%
기 1009
 
8.9%
도 1002
 
8.8%
시 969
 
8.5%
로 931
 
8.2%
구 330
 
2.9%
양 268
 
2.4%
대 265
 
2.3%
면 222
 
1.9%
성 215
 
1.9%
Other values (233) 5143
45.1%
Decimal Number
ValueCountFrequency (%)
1 633
20.5%
2 417
13.5%
3 287
9.3%
6 280
9.1%
4 272
8.8%
5 264
8.6%
7 252
 
8.2%
9 245
 
8.0%
0 220
 
7.1%
8 211
 
6.8%
Space Separator
ValueCountFrequency (%)
3562
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 35
100.0%
Other Punctuation
ValueCountFrequency (%)
. 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 11395
63.0%
Common 6680
37.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
경 1041
 
9.1%
기 1009
 
8.9%
도 1002
 
8.8%
시 969
 
8.5%
로 931
 
8.2%
구 330
 
2.9%
양 268
 
2.4%
대 265
 
2.3%
면 222
 
1.9%
성 215
 
1.9%
Other values (233) 5143
45.1%
Common
ValueCountFrequency (%)
3562
53.3%
1 633
 
9.5%
2 417
 
6.2%
3 287
 
4.3%
6 280
 
4.2%
4 272
 
4.1%
5 264
 
4.0%
7 252
 
3.8%
9 245
 
3.7%
0 220
 
3.3%
Other values (3) 248
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 11395
63.0%
ASCII 6680
37.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3562
53.3%
1 633
 
9.5%
2 417
 
6.2%
3 287
 
4.3%
6 280
 
4.2%
4 272
 
4.1%
5 264
 
4.0%
7 252
 
3.8%
9 245
 
3.7%
0 220
 
3.3%
Other values (3) 248
 
3.7%
Hangul
ValueCountFrequency (%)
경 1041
 
9.1%
기 1009
 
8.9%
도 1002
 
8.8%
시 969
 
8.5%
로 931
 
8.2%
구 330
 
2.9%
양 268
 
2.4%
대 265
 
2.3%
면 222
 
1.9%
성 215
 
1.9%
Other values (233) 5143
45.1%

정제지번주소
Text

Distinct949
Distinct (%)99.7%
Missing0
Missing (%)0.0%
Memory size7.6 KiB
2024-05-18T05:16:58.694888image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length26
Mean length21.820378
Min length16

Characters and Unicode

Total characters20773
Distinct characters259
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

Unique946 ?
Unique (%)99.4%

Sample

1st row경기도 여주시 대신면 보통리 127번지
2nd row경기도 남양주시 진접읍 팔야리 558-1번지
3rd row경기도 여주시 세종대왕면 번도리 861-35번지
4th row경기도 평택시 포승읍 만호리 400-3번지
5th row경기도 용인시 처인구 이동읍 송전리 169-5번지
ValueCountFrequency (%)
경기도 949
 
21.0%
용인시 103
 
2.3%
화성시 90
 
2.0%
평택시 59
 
1.3%
처인구 54
 
1.2%
남양주시 45
 
1.0%
고양시 44
 
1.0%
안산시 43
 
0.9%
이천시 43
 
0.9%
포천시 42
 
0.9%
Other values (1633) 3056
67.5%
2024-05-18T05:16:59.460419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3576
 
17.2%
지 1000
 
4.8%
기 998
 
4.8%
도 986
 
4.7%
시 956
 
4.6%
경 952
 
4.6%
번 952
 
4.6%
- 764
 
3.7%
1 678
 
3.3%
동 618
 
3.0%
Other values (249) 9293
44.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 12737
61.3%
Decimal Number 3696
 
17.8%
Space Separator 3576
 
17.2%
Dash Punctuation 764
 
3.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
지 1000
 
7.9%
기 998
 
7.8%
도 986
 
7.7%
시 956
 
7.5%
경 952
 
7.5%
번 952
 
7.5%
동 618
 
4.9%
리 428
 
3.4%
구 324
 
2.5%
양 269
 
2.1%
Other values (237) 5254
41.2%
Decimal Number
ValueCountFrequency (%)
1 678
18.3%
2 449
12.1%
3 421
11.4%
4 392
10.6%
5 337
9.1%
6 322
8.7%
7 316
8.5%
8 275
7.4%
9 258
 
7.0%
0 248
 
6.7%
Space Separator
ValueCountFrequency (%)
3576
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 764
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 12737
61.3%
Common 8036
38.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
지 1000
 
7.9%
기 998
 
7.8%
도 986
 
7.7%
시 956
 
7.5%
경 952
 
7.5%
번 952
 
7.5%
동 618
 
4.9%
리 428
 
3.4%
구 324
 
2.5%
양 269
 
2.1%
Other values (237) 5254
41.2%
Common
ValueCountFrequency (%)
3576
44.5%
- 764
 
9.5%
1 678
 
8.4%
2 449
 
5.6%
3 421
 
5.2%
4 392
 
4.9%
5 337
 
4.2%
6 322
 
4.0%
7 316
 
3.9%
8 275
 
3.4%
Other values (2) 506
 
6.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 12737
61.3%
ASCII 8036
38.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3576
44.5%
- 764
 
9.5%
1 678
 
8.4%
2 449
 
5.6%
3 421
 
5.2%
4 392
 
4.9%
5 337
 
4.2%
6 322
 
4.0%
7 316
 
3.9%
8 275
 
3.4%
Other values (2) 506
 
6.3%
Hangul
ValueCountFrequency (%)
지 1000
 
7.9%
기 998
 
7.8%
도 986
 
7.7%
시 956
 
7.5%
경 952
 
7.5%
번 952
 
7.5%
동 618
 
4.9%
리 428
 
3.4%
구 324
 
2.5%
양 269
 
2.1%
Other values (237) 5254
41.2%

정제WGS84위도
Real number (ℝ)

Distinct946
Distinct (%)99.7%
Missing3
Missing (%)0.3%
Infinite0
Infinite (%)0.0%
Mean37.420827
Minimum36.931245
Maximum38.059149
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size8.5 KiB
2024-05-18T05:16:59.765634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.931245
5-th percentile37.022758
Q137.235814
median37.365151
Q337.645737
95-th percentile37.86589
Maximum38.059149
Range1.1279044
Interquartile range (IQR)0.40992306

Descriptive statistics

Standard deviation0.26110762
Coefficient of variation (CV)0.0069776016
Kurtosis-0.76855485
Mean37.420827
Median Absolute Deviation (MAD)0.17447502
Skewness0.34735166
Sum35512.364
Variance0.068177188
MonotonicityNot monotonic
2024-05-18T05:17:00.035731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.044699226 2
 
0.2%
37.2627442492 2
 
0.2%
37.3510830798 2
 
0.2%
37.2782215813 1
 
0.1%
37.2306014975 1
 
0.1%
37.6695755107 1
 
0.1%
36.9778893426 1
 
0.1%
37.8598855943 1
 
0.1%
36.985272569 1
 
0.1%
37.1408700272 1
 
0.1%
Other values (936) 936
98.3%
(Missing) 3
 
0.3%
ValueCountFrequency (%)
36.9312447791 1
0.1%
36.9378641228 1
0.1%
36.9386725033 1
0.1%
36.9429286873 1
0.1%
36.945223949 1
0.1%
36.9459060522 1
0.1%
36.952793833 1
0.1%
36.9543637942 1
0.1%
36.9548526209 1
0.1%
36.9548582999 1
0.1%
ValueCountFrequency (%)
38.0591492054 1
0.1%
38.0492277954 1
0.1%
38.0426800055 1
0.1%
38.0320522906 1
0.1%
38.0310487979 1
0.1%
38.0293376881 1
0.1%
38.0170980214 1
0.1%
38.004631871 1
0.1%
38.004215788 1
0.1%
37.9973917091 1
0.1%

정제WGS84경도
Real number (ℝ)

Distinct946
Distinct (%)99.7%
Missing3
Missing (%)0.3%
Infinite0
Infinite (%)0.0%
Mean127.05074
Minimum126.54769
Maximum127.73093
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size8.5 KiB
2024-05-18T05:17:00.302867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.54769
5-th percentile126.71738
Q1126.855
median127.05332
Q3127.20407
95-th percentile127.49701
Maximum127.73093
Range1.1832354
Interquartile range (IQR)0.34907801

Descriptive statistics

Standard deviation0.23784957
Coefficient of variation (CV)0.0018720832
Kurtosis-0.22140792
Mean127.05074
Median Absolute Deviation (MAD)0.1711561
Skewness0.4106867
Sum120571.16
Variance0.056572416
MonotonicityNot monotonic
2024-05-18T05:17:00.578562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
126.9469455917 2
 
0.2%
127.408479871 2
 
0.2%
126.8186314385 2
 
0.2%
127.5786005276 1
 
0.1%
126.9695795968 1
 
0.1%
127.17313728 1
 
0.1%
126.8433545762 1
 
0.1%
127.0561951404 1
 
0.1%
126.8599550153 1
 
0.1%
127.3936851717 1
 
0.1%
Other values (936) 936
98.3%
(Missing) 3
 
0.3%
ValueCountFrequency (%)
126.5476927796 1
0.1%
126.5531212027 1
0.1%
126.5581044324 1
0.1%
126.561031252 1
0.1%
126.5703445675 1
0.1%
126.5760145605 1
0.1%
126.5761510179 1
0.1%
126.5804141545 1
0.1%
126.5805744417 1
0.1%
126.582992125 1
0.1%
ValueCountFrequency (%)
127.7309281352 1
0.1%
127.7278774409 1
0.1%
127.7235581364 1
0.1%
127.7108461042 1
0.1%
127.7046739933 1
0.1%
127.6960511037 1
0.1%
127.6646220446 1
0.1%
127.6585659283 1
0.1%
127.6547990072 1
0.1%
127.6479295815 1
0.1%

Interactions

2024-05-18T05:16:49.017300image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T05:16:47.486603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T05:16:48.274100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T05:16:49.289834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T05:16:47.759812image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T05:16:48.488485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T05:16:49.556096image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T05:16:48.038988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-18T05:16:48.751940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-18T05:17:00.790963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
재고유무판매단가(원/리터)정제WGS84위도정제WGS84경도
재고유무1.0001.0000.0000.000
판매단가(원/리터)1.0001.0000.2400.202
정제WGS84위도0.0000.2401.0000.545
정제WGS84경도0.0000.2020.5451.000
2024-05-18T05:17:00.959259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
판매단가(원/리터)정제WGS84위도정제WGS84경도재고유무
판매단가(원/리터)1.0000.114-0.1710.996
정제WGS84위도0.1141.000-0.1300.000
정제WGS84경도-0.171-0.1301.0000.000
재고유무0.9960.0000.0001.000

Missing values

2024-05-18T05:16:49.931311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-18T05:16:50.410380image/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.
2024-05-18T05:16:50.742353image/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

주유소명전화번호재고유무판매단가(원/리터)결제일자결제시간정제도로명주소정제지번주소정제WGS84위도정제WGS84경도
0대신농협클린주유소031-884-3948Y14002024-03-2810:21:26경기도 여주시 대신면 여양로 1537경기도 여주시 대신면 보통리 127번지37.374346127.57826
1예멋Self주유소031-527-6171Y14002024-02-0113:14:07경기도 남양주시 진접읍 금강로 1897경기도 남양주시 진접읍 팔야리 558-1번지37.751486127.213802
2세종대왕농협주유소031-881-4322Y14002024-02-0113:37:49경기도 여주시 세종대왕면 마장로 9경기도 여주시 세종대왕면 번도리 861-35번지37.299367127.56629
3지에스칼텍스㈜ 만호주유소031-681-1800Y14002023-02-2117:25:29경기도 평택시 포승읍 서동대로 771경기도 평택시 포승읍 만호리 400-3번지36.959192126.856141
4송전휴게소주유소/충전소031-335-4194Y14002024-05-1418:01:52경기도 용인시 처인구 이동읍 남북대로 2616경기도 용인시 처인구 이동읍 송전리 169-5번지37.14021127.205751
5(주)세화제2주유소031-404-5189Y14002024-02-0110:59:24경기도 시흥시 동서로 425경기도 시흥시 장현동 78번지37.384101126.794126
6동양산업(주)마도주유소031-357-9909Y14002024-02-0113:20:17경기도 화성시 마도면 화성로 873경기도 화성시 마도면 두곡리 450-1번지37.205129126.784696
7파주아동주유소 ㈜경남오일뱅크031-942-5103Y15002024-02-1410:26:22경기도 파주시 통일로 630경기도 파주시 아동동 107-2번지37.766277126.794119
8선유주유소031-833-5183Y15002024-05-1613:11:14경기도 연천군 전곡읍 양연로 452경기도 연천군 전곡읍 간파리 298-5번지37.947155127.003463
9임진농협 진상지점주유소031-833-8333Y15002024-05-0715:20:55경기도 연천군 군남면 군남로 128경기도 연천군 군남면 진상리 663-3번지38.059149127.018905
주유소명전화번호재고유무판매단가(원/리터)결제일자결제시간정제도로명주소정제지번주소정제WGS84위도정제WGS84경도
942SK에너지(주) SK호매실주유소031-296-8668Y20002024-01-2412:13:58경기도 수원시 권선구 서수원로 453경기도 수원시 권선구 호매실동 1374-1번지37.267037126.961779
943동일석유(주)산업self 주유소031-452-3590Y20002024-05-1614:59:16경기도 군포시 경수대로 457경기도 군포시 당정동 13번지37.363905126.958987
944영화에너지(주)직영 칠칠주유소031-691-6667Y20002024-05-1506:02:00경기도 평택시 팽성읍 부용로 118경기도 평택시 팽성읍 객사리 71-13번지36.965619127.066922
945삼미상사㈜ 보라self주유소031-282-2381Y20002024-05-1609:08:04경기도 용인시 기흥구 용구대로 1835경기도 용인시 기흥구 보라동 459-1번지37.251952127.104575
946BK대명 주유소032-676-5001Y20002024-05-1408:44:31경기도 부천시 오정구 역곡로 449경기도 부천시 오정구 고강동 480-2번지37.524866126.815583
947SK에너지(주) 서해로셀프주유소031-352-5179Y20002023-12-0609:06:43경기도 화성시 팔탄면 서해로 962경기도 화성시 팔탄면 지월리 550-16번지37.147419126.892384
948주식회사 성인석유 거창주유소031-366-6000Y20002024-05-1615:07:30경기도 화성시 팔탄면 마당바위로 113경기도 화성시 팔탄면 구장리 846-7번지37.161444126.910157
949마도IC주유소010-4067-4343Y20002024-05-1511:23:19경기도 화성시 마도면 화성로 667경기도 화성시 마도면 슬항리 214-7번지37.210238126.762345
950소망주유소031-416-5511Y20002024-02-1509:50:52경기도 안산시 상록구 석호로 202경기도 안산시 상록구 사동 1318-3번지37.294995126.853233
951경일석유(주)신신주유소031-903-5633Y20002024-05-1613:15:54경기도 고양시 일산동구 백마로 32경기도 고양시 일산동구 장항동 541-28번지37.642348126.760632