Overview

Dataset statistics

Number of variables4
Number of observations85
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.9 KiB
Average record size in memory34.6 B

Variable types

Numeric1
Text3

Dataset

Description경상북도 영천시 소재의 석유판매업(주유소)에 대한 데이터로 영천시에 등록된 주유소의 상호와 주소, 전화번호를 제공하는 데이터입니다.
URLhttps://www.data.go.kr/data/15004640/fileData.do

Alerts

연번 has unique valuesUnique
상호 has unique valuesUnique
주소 has unique valuesUnique

Reproduction

Analysis started2023-12-12 20:04:04.053438
Analysis finished2023-12-12 20:04:04.660073
Duration0.61 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct85
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean43
Minimum1
Maximum85
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size897.0 B
2023-12-13T05:04:04.770338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile5.2
Q122
median43
Q364
95-th percentile80.8
Maximum85
Range84
Interquartile range (IQR)42

Descriptive statistics

Standard deviation24.681302
Coefficient of variation (CV)0.57398377
Kurtosis-1.2
Mean43
Median Absolute Deviation (MAD)21
Skewness0
Sum3655
Variance609.16667
MonotonicityStrictly increasing
2023-12-13T05:04:04.989694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.2%
55 1
 
1.2%
63 1
 
1.2%
62 1
 
1.2%
61 1
 
1.2%
60 1
 
1.2%
59 1
 
1.2%
58 1
 
1.2%
57 1
 
1.2%
56 1
 
1.2%
Other values (75) 75
88.2%
ValueCountFrequency (%)
1 1
1.2%
2 1
1.2%
3 1
1.2%
4 1
1.2%
5 1
1.2%
6 1
1.2%
7 1
1.2%
8 1
1.2%
9 1
1.2%
10 1
1.2%
ValueCountFrequency (%)
85 1
1.2%
84 1
1.2%
83 1
1.2%
82 1
1.2%
81 1
1.2%
80 1
1.2%
79 1
1.2%
78 1
1.2%
77 1
1.2%
76 1
1.2%

상호
Text

UNIQUE 

Distinct85
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size812.0 B
2023-12-13T05:04:05.314607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length5
Mean length7.2823529
Min length5

Characters and Unicode

Total characters619
Distinct characters120
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

Unique85 ?
Unique (%)100.0%

Sample

1st row공단주유소
2nd row영천농협클린주유소
3rd row대창IC주유소
4th row임고농협클린주유소
5th row(주)장원에너지 신녕IC주유소
ValueCountFrequency (%)
북안주유소 2
 
2.2%
주)장원에너지 2
 
2.2%
영천주유소 2
 
2.2%
공단주유소 1
 
1.1%
청수주유소 1
 
1.1%
제이엠 1
 
1.1%
안심주유소 1
 
1.1%
우덕주유소 1
 
1.1%
하나고속주유소 1
 
1.1%
경동주유소 1
 
1.1%
Other values (79) 79
85.9%
2023-12-13T05:04:05.804453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 97
 
15.7%
유 84
 
13.6%
소 82
 
13.2%
) 17
 
2.7%
( 17
 
2.7%
영 15
 
2.4%
천 13
 
2.1%
에 11
 
1.8%
이 10
 
1.6%
C 8
 
1.3%
Other values (110) 265
42.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 552
89.2%
Close Punctuation 17
 
2.7%
Open Punctuation 17
 
2.7%
Uppercase Letter 16
 
2.6%
Space Separator 7
 
1.1%
Decimal Number 6
 
1.0%
Lowercase Letter 4
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 97
17.6%
유 84
 
15.2%
소 82
 
14.9%
영 15
 
2.7%
천 13
 
2.4%
에 11
 
2.0%
이 10
 
1.8%
지 8
 
1.4%
대 8
 
1.4%
신 7
 
1.3%
Other values (100) 217
39.3%
Decimal Number
ValueCountFrequency (%)
1 3
50.0%
5 1
 
16.7%
3 1
 
16.7%
2 1
 
16.7%
Uppercase Letter
ValueCountFrequency (%)
C 8
50.0%
I 8
50.0%
Close Punctuation
ValueCountFrequency (%)
) 17
100.0%
Open Punctuation
ValueCountFrequency (%)
( 17
100.0%
Space Separator
ValueCountFrequency (%)
7
100.0%
Lowercase Letter
ValueCountFrequency (%)
k 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 552
89.2%
Common 47
 
7.6%
Latin 20
 
3.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 97
17.6%
유 84
 
15.2%
소 82
 
14.9%
영 15
 
2.7%
천 13
 
2.4%
에 11
 
2.0%
이 10
 
1.8%
지 8
 
1.4%
대 8
 
1.4%
신 7
 
1.3%
Other values (100) 217
39.3%
Common
ValueCountFrequency (%)
) 17
36.2%
( 17
36.2%
7
14.9%
1 3
 
6.4%
5 1
 
2.1%
3 1
 
2.1%
2 1
 
2.1%
Latin
ValueCountFrequency (%)
C 8
40.0%
I 8
40.0%
k 4
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 552
89.2%
ASCII 67
 
10.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 97
17.6%
유 84
 
15.2%
소 82
 
14.9%
영 15
 
2.7%
천 13
 
2.4%
에 11
 
2.0%
이 10
 
1.8%
지 8
 
1.4%
대 8
 
1.4%
신 7
 
1.3%
Other values (100) 217
39.3%
ASCII
ValueCountFrequency (%)
) 17
25.4%
( 17
25.4%
C 8
11.9%
I 8
11.9%
7
10.4%
k 4
 
6.0%
1 3
 
4.5%
5 1
 
1.5%
3 1
 
1.5%
2 1
 
1.5%

주소
Text

UNIQUE 

Distinct85
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size812.0 B
2023-12-13T05:04:06.226905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length25
Mean length21.364706
Min length19

Characters and Unicode

Total characters1816
Distinct characters96
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique85 ?
Unique (%)100.0%

Sample

1st row경상북도 영천시 금호읍 금창로 200
2nd row경상북도 영천시 장천2길 23 (조교동)
3rd row경상북도 영천시 금호읍 금창로 314
4th row경상북도 영천시 임고면 포은로 424
5th row경상북도 영천시 신녕면 완전공단길 2
ValueCountFrequency (%)
경상북도 85
20.0%
영천시 85
20.0%
호국로 16
 
3.8%
천문로 14
 
3.3%
고경면 14
 
3.3%
금호읍 10
 
2.3%
북안면 7
 
1.6%
장수로 7
 
1.6%
금창로 6
 
1.4%
영천i.c로 6
 
1.4%
Other values (127) 176
41.3%
2023-12-13T05:04:06.819162image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
341
18.8%
천 106
 
5.8%
경 104
 
5.7%
북 95
 
5.2%
영 94
 
5.2%
도 92
 
5.1%
시 85
 
4.7%
상 85
 
4.7%
로 81
 
4.5%
1 51
 
2.8%
Other values (86) 682
37.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1116
61.5%
Space Separator 341
 
18.8%
Decimal Number 266
 
14.6%
Open Punctuation 34
 
1.9%
Close Punctuation 34
 
1.9%
Uppercase Letter 12
 
0.7%
Other Punctuation 7
 
0.4%
Dash Punctuation 6
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
천 106
 
9.5%
경 104
 
9.3%
북 95
 
8.5%
영 94
 
8.4%
도 92
 
8.2%
시 85
 
7.6%
상 85
 
7.6%
로 81
 
7.3%
면 41
 
3.7%
동 34
 
3.0%
Other values (68) 299
26.8%
Decimal Number
ValueCountFrequency (%)
1 51
19.2%
2 38
14.3%
3 31
11.7%
4 27
10.2%
6 27
10.2%
7 22
8.3%
9 21
7.9%
5 20
 
7.5%
8 17
 
6.4%
0 12
 
4.5%
Uppercase Letter
ValueCountFrequency (%)
C 6
50.0%
I 6
50.0%
Other Punctuation
ValueCountFrequency (%)
. 6
85.7%
, 1
 
14.3%
Space Separator
ValueCountFrequency (%)
341
100.0%
Open Punctuation
ValueCountFrequency (%)
( 34
100.0%
Close Punctuation
ValueCountFrequency (%)
) 34
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1116
61.5%
Common 688
37.9%
Latin 12
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
천 106
 
9.5%
경 104
 
9.3%
북 95
 
8.5%
영 94
 
8.4%
도 92
 
8.2%
시 85
 
7.6%
상 85
 
7.6%
로 81
 
7.3%
면 41
 
3.7%
동 34
 
3.0%
Other values (68) 299
26.8%
Common
ValueCountFrequency (%)
341
49.6%
1 51
 
7.4%
2 38
 
5.5%
( 34
 
4.9%
) 34
 
4.9%
3 31
 
4.5%
4 27
 
3.9%
6 27
 
3.9%
7 22
 
3.2%
9 21
 
3.1%
Other values (6) 62
 
9.0%
Latin
ValueCountFrequency (%)
C 6
50.0%
I 6
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1116
61.5%
ASCII 700
38.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
341
48.7%
1 51
 
7.3%
2 38
 
5.4%
( 34
 
4.9%
) 34
 
4.9%
3 31
 
4.4%
4 27
 
3.9%
6 27
 
3.9%
7 22
 
3.1%
9 21
 
3.0%
Other values (8) 74
 
10.6%
Hangul
ValueCountFrequency (%)
천 106
 
9.5%
경 104
 
9.3%
북 95
 
8.5%
영 94
 
8.4%
도 92
 
8.2%
시 85
 
7.6%
상 85
 
7.6%
로 81
 
7.3%
면 41
 
3.7%
동 34
 
3.0%
Other values (68) 299
26.8%

전화번호
Text

Distinct83
Distinct (%)97.6%
Missing0
Missing (%)0.0%
Memory size812.0 B
2023-12-13T05:04:07.458117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters1020
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

Unique81 ?
Unique (%)95.3%

Sample

1st row054-000-0000
2nd row054-338-3851
3rd row054-331-9797
4th row054-336-7751
5th row054-336-5150
ValueCountFrequency (%)
054-000-0000 2
 
2.4%
054-338-0037 2
 
2.4%
054-335-7163 1
 
1.2%
054-332-0026 1
 
1.2%
054-338-5189 1
 
1.2%
054-337-4900 1
 
1.2%
054-338-0417 1
 
1.2%
054-336-0120 1
 
1.2%
054-336-3120 1
 
1.2%
054-331-0752 1
 
1.2%
Other values (73) 73
85.9%
2023-12-13T05:04:07.967004image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 201
19.7%
- 170
16.7%
0 152
14.9%
5 145
14.2%
4 111
10.9%
1 64
 
6.3%
7 40
 
3.9%
6 40
 
3.9%
2 40
 
3.9%
8 39
 
3.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 850
83.3%
Dash Punctuation 170
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 201
23.6%
0 152
17.9%
5 145
17.1%
4 111
13.1%
1 64
 
7.5%
7 40
 
4.7%
6 40
 
4.7%
2 40
 
4.7%
8 39
 
4.6%
9 18
 
2.1%
Dash Punctuation
ValueCountFrequency (%)
- 170
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1020
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 201
19.7%
- 170
16.7%
0 152
14.9%
5 145
14.2%
4 111
10.9%
1 64
 
6.3%
7 40
 
3.9%
6 40
 
3.9%
2 40
 
3.9%
8 39
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1020
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 201
19.7%
- 170
16.7%
0 152
14.9%
5 145
14.2%
4 111
10.9%
1 64
 
6.3%
7 40
 
3.9%
6 40
 
3.9%
2 40
 
3.9%
8 39
 
3.8%

Interactions

2023-12-13T05:04:04.378507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T05:04:08.099135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번상호주소전화번호
연번1.0001.0001.0000.975
상호1.0001.0001.0001.000
주소1.0001.0001.0001.000
전화번호0.9751.0001.0001.000

Missing values

2023-12-13T05:04:04.513861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T05:04:04.623006image/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

연번상호주소전화번호
01공단주유소경상북도 영천시 금호읍 금창로 200054-000-0000
12영천농협클린주유소경상북도 영천시 장천2길 23 (조교동)054-338-3851
23대창IC주유소경상북도 영천시 금호읍 금창로 314054-331-9797
34임고농협클린주유소경상북도 영천시 임고면 포은로 424054-336-7751
45(주)장원에너지 신녕IC주유소경상북도 영천시 신녕면 완전공단길 2054-336-5150
56동양주유소경상북도 영천시 영화로 61 (금노동)054-338-1199
67고경농협주유소경상북도 영천시 고경면 호국로 1087054-330-1612
78금호농협 클린주유소경상북도 영천시 금호읍 금창로 76054-338-9190
89한국주유소경상북도 영천시 고경면 거곡로 14-1054-335-4030
910창신주유소경상북도 영천시 청통면 청통로 322054-331-5744
연번상호주소전화번호
7576현대오일뱅크(주)금호주유소경상북도 영천시 화남면 천문로 1806054-337-6566
7677삼부주유소경상북도 영천시 화산면 장수로 580054-334-6100
7778케이케이(주)kk금호주유소경상북도 영천시 북안면 대경로 2166-33054-336-0901
7879동부주유소경상북도 영천시 호국로 101 (망정동)054-334-5100
7980북안주유소경상북도 영천시 북안면 운북로 2027054-333-6815
8081장수주유소경상북도 영천시 금호읍 금호로 38054-332-5424
8182(주)가온경상북도 영천시 천문로 398 (문내동)054-338-7741
8283신일주유소경상북도 영천시 신녕면 장수로 1632054-332-0333
8384영신주유소경상북도 영천시 신녕면 장수로 1672054-332-0026
8485영천2주유소경상북도 영천시 최무선로 188 (화룡동)054-332-5181