Overview

Dataset statistics

Number of variables10
Number of observations971
Missing cells12
Missing cells (%)0.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory78.8 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 (96.1%)Imbalance

Reproduction

Analysis started2024-07-13 13:48:10.858711
Analysis finished2024-07-13 13:48:17.994429
Duration7.14 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

Distinct949
Distinct (%)97.7%
Missing0
Missing (%)0.0%
Memory size7.7 KiB
2024-07-13T22:48:19.037136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length20
Mean length10.684861
Min length3

Characters and Unicode

Total characters10375
Distinct characters417
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

Unique929 ?
Unique (%)95.7%

Sample

1st row도계주유소
2nd row역동주유소
3rd row고속주유소
4th row경원주유소
5th row매송주유소(서울방향)
ValueCountFrequency (%)
hd현대오일뱅크㈜직영 81
 
6.0%
sk에너지(주 11
 
0.8%
주유소 11
 
0.8%
주식회사 11
 
0.8%
삼미상사(주 8
 
0.6%
지에스칼텍스㈜ 7
 
0.5%
구도일주유소 7
 
0.5%
직영 7
 
0.5%
그린주유소 4
 
0.3%
㈜삼표에너지 4
 
0.3%
Other values (1118) 1200
88.8%
2024-07-13T22:48:21.190205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1210
 
11.7%
1000
 
9.6%
946
 
9.1%
380
 
3.7%
) 315
 
3.0%
( 315
 
3.0%
210
 
2.0%
209
 
2.0%
183
 
1.8%
180
 
1.7%
Other values (407) 5427
52.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8697
83.8%
Space Separator 380
 
3.7%
Uppercase Letter 366
 
3.5%
Close Punctuation 315
 
3.0%
Open Punctuation 315
 
3.0%
Other Symbol 169
 
1.6%
Lowercase Letter 76
 
0.7%
Decimal Number 29
 
0.3%
Other Punctuation 26
 
0.3%
Dash Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1210
 
13.9%
1000
 
11.5%
946
 
10.9%
210
 
2.4%
209
 
2.4%
183
 
2.1%
180
 
2.1%
149
 
1.7%
141
 
1.6%
141
 
1.6%
Other values (365) 4328
49.8%
Uppercase Letter
ValueCountFrequency (%)
H 87
23.8%
D 84
23.0%
S 55
15.0%
K 39
10.7%
C 32
 
8.7%
I 29
 
7.9%
G 10
 
2.7%
T 6
 
1.6%
J 5
 
1.4%
B 2
 
0.5%
Other values (11) 17
 
4.6%
Decimal Number
ValueCountFrequency (%)
2 11
37.9%
1 5
17.2%
4 5
17.2%
5 4
 
13.8%
6 1
 
3.4%
3 1
 
3.4%
8 1
 
3.4%
9 1
 
3.4%
Lowercase Letter
ValueCountFrequency (%)
e 21
27.6%
l 20
26.3%
f 20
26.3%
s 13
17.1%
k 2
 
2.6%
Other Punctuation
ValueCountFrequency (%)
/ 23
88.5%
. 2
 
7.7%
1
 
3.8%
Space Separator
ValueCountFrequency (%)
380
100.0%
Close Punctuation
ValueCountFrequency (%)
) 315
100.0%
Open Punctuation
ValueCountFrequency (%)
( 315
100.0%
Other Symbol
ValueCountFrequency (%)
169
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 8866
85.5%
Common 1067
 
10.3%
Latin 442
 
4.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1210
 
13.6%
1000
 
11.3%
946
 
10.7%
210
 
2.4%
209
 
2.4%
183
 
2.1%
180
 
2.0%
169
 
1.9%
149
 
1.7%
141
 
1.6%
Other values (366) 4469
50.4%
Latin
ValueCountFrequency (%)
H 87
19.7%
D 84
19.0%
S 55
12.4%
K 39
8.8%
C 32
 
7.2%
I 29
 
6.6%
e 21
 
4.8%
l 20
 
4.5%
f 20
 
4.5%
s 13
 
2.9%
Other values (16) 42
9.5%
Common
ValueCountFrequency (%)
380
35.6%
) 315
29.5%
( 315
29.5%
/ 23
 
2.2%
2 11
 
1.0%
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 8697
83.8%
ASCII 1508
 
14.5%
None 170
 
1.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
1210
 
13.9%
1000
 
11.5%
946
 
10.9%
210
 
2.4%
209
 
2.4%
183
 
2.1%
180
 
2.1%
149
 
1.7%
141
 
1.6%
141
 
1.6%
Other values (365) 4328
49.8%
ASCII
ValueCountFrequency (%)
380
25.2%
) 315
20.9%
( 315
20.9%
H 87
 
5.8%
D 84
 
5.6%
S 55
 
3.6%
K 39
 
2.6%
C 32
 
2.1%
I 29
 
1.9%
/ 23
 
1.5%
Other values (30) 149
 
9.9%
None
ValueCountFrequency (%)
169
99.4%
1
 
0.6%
Distinct966
Distinct (%)99.5%
Missing0
Missing (%)0.0%
Memory size7.7 KiB
2024-07-13T22:48:22.283832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length12.016478
Min length9

Characters and Unicode

Total characters11668
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

Unique964 ?
Unique (%)99.3%

Sample

1st row031-691-2235
2nd row031-762-8155
3rd row031-401-5151
4th row031-761-0551
5th row031-295-1509
ValueCountFrequency (%)
031-000-0000 5
 
0.5%
010-3981-0398 2
 
0.2%
031-962-5182 1
 
0.1%
031-751-6051 1
 
0.1%
031-358-0168 1
 
0.1%
031-885-9764 1
 
0.1%
032-663-1010 1
 
0.1%
031-771-5125 1
 
0.1%
031-835-1233 1
 
0.1%
031-233-3161 1
 
0.1%
Other values (956) 956
98.5%
2024-07-13T22:48:23.926292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 1941
16.6%
1 1772
15.2%
3 1654
14.2%
0 1544
13.2%
5 1099
9.4%
8 684
 
5.9%
2 635
 
5.4%
6 629
 
5.4%
7 589
 
5.0%
4 562
 
4.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 9727
83.4%
Dash Punctuation 1941
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 1772
18.2%
3 1654
17.0%
0 1544
15.9%
5 1099
11.3%
8 684
 
7.0%
2 635
 
6.5%
6 629
 
6.5%
7 589
 
6.1%
4 562
 
5.8%
9 559
 
5.7%
Dash Punctuation
ValueCountFrequency (%)
- 1941
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 11668
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 1941
16.6%
1 1772
15.2%
3 1654
14.2%
0 1544
13.2%
5 1099
9.4%
8 684
 
5.9%
2 635
 
5.4%
6 629
 
5.4%
7 589
 
5.0%
4 562
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 11668
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 1941
16.6%
1 1772
15.2%
3 1654
14.2%
0 1544
13.2%
5 1099
9.4%
8 684
 
5.9%
2 635
 
5.4%
6 629
 
5.4%
7 589
 
5.0%
4 562
 
4.8%

재고유무
Boolean

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size1.1 KiB
True
967 
False
 
4
ValueCountFrequency (%)
True 967
99.6%
False 4
 
0.4%
2024-07-13T22:48:24.499319image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

판매단가(원/리터)
Real number (ℝ)

HIGH CORRELATION 

Distinct38
Distinct (%)3.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1646.0978
Minimum0
Maximum5000
Zeros4
Zeros (%)0.4%
Negative0
Negative (%)0.0%
Memory size8.7 KiB
2024-07-13T22:48:25.015646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1125
Q11500
median1600
Q31900
95-th percentile2200
Maximum5000
Range5000
Interquartile range (IQR)400

Descriptive statistics

Standard deviation365.33045
Coefficient of variation (CV)0.22193726
Kurtosis8.86949
Mean1646.0978
Median Absolute Deviation (MAD)200
Skewness0.76061906
Sum1598361
Variance133466.34
MonotonicityNot monotonic
2024-07-13T22:48:25.499562image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=38)
ValueCountFrequency (%)
1500 231
23.8%
2000 166
17.1%
1800 115
11.8%
1600 95
9.8%
1300 70
 
7.2%
1400 52
 
5.4%
1700 51
 
5.3%
1200 39
 
4.0%
1900 28
 
2.9%
2200 23
 
2.4%
Other values (28) 101
10.4%
ValueCountFrequency (%)
0 4
0.4%
700 2
0.2%
750 1
 
0.1%
790 3
0.3%
800 1
 
0.1%
870 1
 
0.1%
890 2
0.2%
899 1
 
0.1%
900 3
0.3%
990 4
0.4%
ValueCountFrequency (%)
5000 1
 
0.1%
3000 5
 
0.5%
2500 16
 
1.6%
2400 9
 
0.9%
2300 3
 
0.3%
2200 23
 
2.4%
2100 3
 
0.3%
2000 166
17.1%
1998 1
 
0.1%
1900 28
 
2.9%
Distinct188
Distinct (%)19.4%
Missing0
Missing (%)0.0%
Memory size7.7 KiB
Minimum2022-04-07 00:00:00
Maximum2024-07-13 00:00:00
2024-07-13T22:48:26.260173image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-07-13T22:48:26.871809image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/