Overview

Dataset statistics

Number of variables5
Number of observations61
Missing cells10
Missing cells (%)3.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.6 KiB
Average record size in memory43.2 B

Variable types

Text4
Numeric1

Dataset

Description2017년 6월 대구동구 주유소현황
Author대구광역시 동구
URLhttp://data.daegu.go.kr/open/data/dataView.do?dataSetId=3057600&dataSetDetailId=305760019cfb0aa1a81f_201809201502&provdMethod=FILE

Alerts

도로명전체주소 has 3 (4.9%) missing valuesMissing
소재지면적 has 1 (1.6%) missing valuesMissing
전화번호 has 6 (9.8%) missing valuesMissing

Reproduction

Analysis started2024-04-22 00:36:38.388456
Analysis finished2024-04-22 00:36:39.428787
Duration1.04 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

사업장명
Text

Distinct60
Distinct (%)98.4%
Missing0
Missing (%)0.0%
Memory size620.0 B
2024-04-22T09:36:39.587124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length5
Mean length7.4098361
Min length5

Characters and Unicode

Total characters452
Distinct characters124
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

Unique59 ?
Unique (%)96.7%

Sample

1st row기지주유소
2nd rowe 편한주유소
3rd row동도주유소
4th row상호주유소
5th row대성산업(주)하이웨이주유소
ValueCountFrequency (%)
동도주유소 2
 
3.0%
현대오일뱅크(주)직영 1
 
1.5%
경동에너지(주)직영 1
 
1.5%
동부주유소 1
 
1.5%
율하주유소 1
 
1.5%
대원주유소 1
 
1.5%
효목주유소 1
 
1.5%
sk네트웍스(주)공항셀프주유소 1
 
1.5%
팔공산주유소 1
 
1.5%
대원석유(주)대신주유소 1
 
1.5%
Other values (56) 56
83.6%
2024-04-22T09:36:39.942376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 72
 
15.9%
유 62
 
13.7%
소 61
 
13.5%
동 16
 
3.5%
대 14
 
3.1%
( 11
 
2.4%
) 11
 
2.4%
산 8
 
1.8%
공 6
 
1.3%
에 6
 
1.3%
Other values (114) 185
40.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 411
90.9%
Open Punctuation 11
 
2.4%
Close Punctuation 11
 
2.4%
Uppercase Letter 8
 
1.8%
Space Separator 6
 
1.3%
Lowercase Letter 3
 
0.7%
Letter Number 1
 
0.2%
Decimal Number 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 72
17.5%
유 62
 
15.1%
소 61
 
14.8%
동 16
 
3.9%
대 14
 
3.4%
산 8
 
1.9%
공 6
 
1.5%
에 6
 
1.5%
이 6
 
1.5%
스 4
 
1.0%
Other values (101) 156
38.0%
Uppercase Letter
ValueCountFrequency (%)
S 3
37.5%
K 2
25.0%
I 1
 
12.5%
C 1
 
12.5%
G 1
 
12.5%
Lowercase Letter
ValueCountFrequency (%)
s 1
33.3%
e 1
33.3%
k 1
33.3%
Open Punctuation
ValueCountFrequency (%)
( 11
100.0%
Close Punctuation
ValueCountFrequency (%)
) 11
100.0%
Space Separator
ValueCountFrequency (%)
6
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 1
100.0%
Decimal Number
ValueCountFrequency (%)
2 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 411
90.9%
Common 29
 
6.4%
Latin 12
 
2.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 72
17.5%
유 62
 
15.1%
소 61
 
14.8%
동 16
 
3.9%
대 14
 
3.4%
산 8
 
1.9%
공 6
 
1.5%
에 6
 
1.5%
이 6
 
1.5%
스 4
 
1.0%
Other values (101) 156
38.0%
Latin
ValueCountFrequency (%)
S 3
25.0%
K 2
16.7%
Ⅱ 1
 
8.3%
I 1
 
8.3%
C 1
 
8.3%
s 1
 
8.3%
G 1
 
8.3%
e 1
 
8.3%
k 1
 
8.3%
Common
ValueCountFrequency (%)
( 11
37.9%
) 11
37.9%
6
20.7%
2 1
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 411
90.9%
ASCII 40
 
8.8%
Number Forms 1
 
0.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 72
17.5%
유 62
 
15.1%
소 61
 
14.8%
동 16
 
3.9%
대 14
 
3.4%
산 8
 
1.9%
공 6
 
1.5%
에 6
 
1.5%
이 6
 
1.5%
스 4
 
1.0%
Other values (101) 156
38.0%
ASCII
ValueCountFrequency (%)
( 11
27.5%
) 11
27.5%
6
15.0%
S 3
 
7.5%
K 2
 
5.0%
I 1
 
2.5%
C 1
 
2.5%
s 1
 
2.5%
G 1
 
2.5%
2 1
 
2.5%
Other values (2) 2
 
5.0%
Number Forms
ValueCountFrequency (%)
Ⅱ 1
100.0%

소재지전체주소
Text

Distinct60
Distinct (%)98.4%
Missing0
Missing (%)0.0%
Memory size620.0 B
2024-04-22T09:36:40.151119image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length45
Median length34
Mean length26
Min length13

Characters and Unicode

Total characters1586
Distinct characters70
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique59 ?
Unique (%)96.7%

Sample

1st row대구광역시 동구 입석동 675번지
2nd row대구광역시 동구 신암동 147-1, 144-35번지
3rd row대구광역시 동구 용계동 763번지
4th row대구광역시 동구 각산동 111번지
5th row대구광역시 동구 신천동 (3동) 148-2,3번지
ValueCountFrequency (%)
대구광역시 61
21.8%
동구 58
20.7%
용계동 9
 
3.2%
신암동 5
 
1.8%
방촌동 5
 
1.8%
지저동 4
 
1.4%
효목동 4
 
1.4%
봉무동 4
 
1.4%
검사동 3
 
1.1%
수성구 3
 
1.1%
Other values (108) 124
44.3%
2024-04-22T09:36:40.498891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
280
17.7%
동 126
 
7.9%
구 122
 
7.7%
1 83
 
5.2%
- 80
 
5.0%
지 69
 
4.4%
4 63
 
4.0%
대 62
 
3.9%
광 61
 
3.8%
역 61
 
3.8%
Other values (60) 579
36.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 765
48.2%
Decimal Number 416
26.2%
Space Separator 280
 
17.7%
Dash Punctuation 80
 
5.0%
Other Punctuation 31
 
2.0%
Open Punctuation 7
 
0.4%
Close Punctuation 7
 
0.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 126
16.5%
구 122
15.9%
지 69
9.0%
대 62
8.1%
광 61
8.0%
역 61
8.0%
시 61
8.0%
번 59
7.7%
용 10
 
1.3%
신 10
 
1.3%
Other values (44) 124
16.2%
Decimal Number
ValueCountFrequency (%)
1 83
20.0%
4 63
15.1%
6 54
13.0%
2 43
10.3%
3 34
8.2%
5 31
 
7.5%
8 30
 
7.2%
0 27
 
6.5%
7 26
 
6.2%
9 25
 
6.0%
Other Punctuation
ValueCountFrequency (%)
, 25
80.6%
. 6
 
19.4%
Space Separator
ValueCountFrequency (%)
280
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 80
100.0%
Open Punctuation
ValueCountFrequency (%)
( 7
100.0%
Close Punctuation
ValueCountFrequency (%)
) 7
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 821
51.8%
Hangul 765
48.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 126
16.5%
구 122
15.9%
지 69
9.0%
대 62
8.1%
광 61
8.0%
역 61
8.0%
시 61
8.0%
번 59
7.7%
용 10
 
1.3%
신 10
 
1.3%
Other values (44) 124
16.2%
Common
ValueCountFrequency (%)
280
34.1%
1 83
 
10.1%
- 80
 
9.7%
4 63
 
7.7%
6 54
 
6.6%
2 43
 
5.2%
3 34
 
4.1%
5 31
 
3.8%
8 30
 
3.7%
0 27
 
3.3%
Other values (6) 96
 
11.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 821
51.8%
Hangul 765
48.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
280
34.1%
1 83
 
10.1%
- 80
 
9.7%
4 63
 
7.7%
6 54
 
6.6%
2 43
 
5.2%
3 34
 
4.1%
5 31
 
3.8%
8 30
 
3.7%
0 27
 
3.3%
Other values (6) 96
 
11.7%
Hangul
ValueCountFrequency (%)
동 126
16.5%
구 122
15.9%
지 69
9.0%
대 62
8.1%
광 61
8.0%
역 61
8.0%
시 61
8.0%
번 59
7.7%
용 10
 
1.3%
신 10
 
1.3%
Other values (44) 124
16.2%

도로명전체주소
Text

MISSING 

Distinct56
Distinct (%)96.6%
Missing3
Missing (%)4.9%
Memory size620.0 B
2024-04-22T09:36:40.751781image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length24
Median length22
Mean length22.189655
Min length20

Characters and Unicode

Total characters1287
Distinct characters78
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

Unique55 ?
Unique (%)94.8%

Sample

1st row대구광역시 동구 아양로 139 (신암동)
2nd row대구광역시 동구 안심로 30 (용계동)
3rd row대구광역시 동구 국채보상로 849 (신천동)
4th row대구광역시 동구 동부로 80 (신천동)
5th row대구광역시 동구 화랑로 490 (용계동)
ValueCountFrequency (%)
대구광역시 58
20.0%
동구 58
20.0%
안심로 10
 
3.4%
용계동 10
 
3.4%
화랑로 8
 
2.8%
동촌로 7
 
2.4%
팔공로 5
 
1.7%
공항로 5
 
1.7%
신천동 5
 
1.7%
방촌동 5
 
1.7%
Other values (88) 119
41.0%
2024-04-22T09:36:41.157354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
232
18.0%
동 134
 
10.4%
구 116
 
9.0%
대 60
 
4.7%
로 60
 
4.7%
시 58
 
4.5%
역 58
 
4.5%
광 58
 
4.5%
( 58
 
4.5%
) 58
 
4.5%
Other values (68) 395
30.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 766
59.5%
Space Separator 232
 
18.0%
Decimal Number 171
 
13.3%
Open Punctuation 58
 
4.5%
Close Punctuation 58
 
4.5%
Dash Punctuation 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 134
17.5%
구 116
15.1%
대 60
 
7.8%
로 60
 
7.8%
시 58
 
7.6%
역 58
 
7.6%
광 58
 
7.6%
공 14
 
1.8%
신 14
 
1.8%
촌 12
 
1.6%
Other values (54) 182
23.8%
Decimal Number
ValueCountFrequency (%)
4 28
16.4%
3 24
14.0%
1 24
14.0%
2 20
11.7%
8 16
9.4%
5 14
8.2%
7 14
8.2%
6 12
7.0%
0 10
 
5.8%
9 9
 
5.3%
Space Separator
ValueCountFrequency (%)
232
100.0%
Open Punctuation
ValueCountFrequency (%)
( 58
100.0%
Close Punctuation
ValueCountFrequency (%)
) 58
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 766
59.5%
Common 521
40.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 134
17.5%
구 116
15.1%
대 60
 
7.8%
로 60
 
7.8%
시 58
 
7.6%
역 58
 
7.6%
광 58
 
7.6%
공 14
 
1.8%
신 14
 
1.8%
촌 12
 
1.6%
Other values (54) 182
23.8%
Common
ValueCountFrequency (%)
232
44.5%
( 58
 
11.1%
) 58
 
11.1%
4 28
 
5.4%
3 24
 
4.6%
1 24
 
4.6%
2 20
 
3.8%
8 16
 
3.1%
5 14
 
2.7%
7 14
 
2.7%
Other values (4) 33
 
6.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 766
59.5%
ASCII 521
40.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
232
44.5%
( 58
 
11.1%
) 58
 
11.1%
4 28
 
5.4%
3 24
 
4.6%
1 24
 
4.6%
2 20
 
3.8%
8 16
 
3.1%
5 14
 
2.7%
7 14
 
2.7%
Other values (4) 33
 
6.3%
Hangul
ValueCountFrequency (%)
동 134
17.5%
구 116
15.1%
대 60
 
7.8%
로 60
 
7.8%
시 58
 
7.6%
역 58
 
7.6%
광 58
 
7.6%
공 14
 
1.8%
신 14
 
1.8%
촌 12
 
1.6%
Other values (54) 182
23.8%

소재지면적
Real number (ℝ)

MISSING 

Distinct59
Distinct (%)98.3%
Missing1
Missing (%)1.6%
Infinite0
Infinite (%)0.0%
Mean1214.8443
Minimum1.76
Maximum6063
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size681.0 B
2024-04-22T09:36:41.299381image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1.76
5-th percentile314.25
Q1711.75
median1020.5
Q31451
95-th percentile2336.23
Maximum6063
Range6061.24
Interquartile range (IQR)739.25

Descriptive statistics

Standard deviation896.18047
Coefficient of variation (CV)0.73769161
Kurtosis14.587654
Mean1214.8443
Median Absolute Deviation (MAD)355.5
Skewness3.1704682
Sum72890.66
Variance803139.43
MonotonicityNot monotonic
2024-04-22T09:36:41.443535image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
665.0 2
 
3.3%
789.0 1
 
1.6%
996.0 1
 
1.6%
640.0 1
 
1.6%
1028.0 1
 
1.6%
1583.49 1
 
1.6%
1366.0 1
 
1.6%
1492.0 1
 
1.6%
2713.0 1
 
1.6%
1185.0 1
 
1.6%
Other values (49) 49
80.3%
ValueCountFrequency (%)
1.76 1
1.6%
200.0 1
1.6%
281.0 1
1.6%
316.0 1
1.6%
407.0 1
1.6%
450.0 1
1.6%
525.0 1
1.6%
597.0 1
1.6%
635.7 1
1.6%
640.0 1
1.6%
ValueCountFrequency (%)
6063.0 1
1.6%
3766.0 1
1.6%
2713.0 1
1.6%
2316.4 1
1.6%
2184.0 1
1.6%
2013.0 1
1.6%
1978.0 1
1.6%
1869.0 1
1.6%
1814.0 1
1.6%
1677.0 1
1.6%

전화번호
Text

MISSING 

Distinct54
Distinct (%)98.2%
Missing6
Missing (%)9.8%
Memory size620.0 B
2024-04-22T09:36:41.663601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters660
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

Unique53 ?
Unique (%)96.4%

Sample

1st row053-989-2125
2nd row053-952-4800
3rd row053-965-9600
4th row053-755-1055
5th row053-752-2220
ValueCountFrequency (%)
053-943-0077 2
 
3.6%
053-962-5052 1
 
1.8%
053-981-1007 1
 
1.8%
053-989-2125 1
 
1.8%
053-952-5152 1
 
1.8%
053-984-5500 1
 
1.8%
053-953-0077 1
 
1.8%
053-742-8178 1
 
1.8%
053-981-8000 1
 
1.8%
053-982-8808 1
 
1.8%
Other values (44) 44
80.0%
2024-04-22T09:36:42.001482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 110
16.7%
0 107
16.2%
5 106
16.1%
3 77
11.7%
9 58
8.8%
8 51
7.7%
2 44
 
6.7%
1 36
 
5.5%
4 24
 
3.6%
7 24
 
3.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 550
83.3%
Dash Punctuation 110
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 107
19.5%
5 106
19.3%
3 77
14.0%
9 58
10.5%
8 51
9.3%
2 44
8.0%
1 36
 
6.5%
4 24
 
4.4%
7 24
 
4.4%
6 23
 
4.2%
Dash Punctuation
ValueCountFrequency (%)
- 110
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 660
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 110
16.7%
0 107
16.2%
5 106
16.1%
3 77
11.7%
9 58
8.8%
8 51
7.7%
2 44
 
6.7%
1 36
 
5.5%
4 24
 
3.6%
7 24
 
3.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 660
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 110
16.7%
0 107
16.2%
5 106
16.1%
3 77
11.7%
9 58
8.8%
8 51
7.7%
2 44
 
6.7%
1 36
 
5.5%
4 24
 
3.6%
7 24
 
3.6%

Interactions

2024-04-22T09:36:38.818072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-22T09:36:42.100357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
사업장명소재지전체주소도로명전체주소소재지면적전화번호
사업장명1.0000.9980.9920.8580.997
소재지전체주소0.9981.0000.9921.0000.997
도로명전체주소0.9920.9921.0000.9901.000
소재지면적0.8581.0000.9901.0000.979
전화번호0.9970.9971.0000.9791.000

Missing values

2024-04-22T09:36:39.188440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-22T09:36:39.284463image/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.
2024-04-22T09:36:39.376279image/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

사업장명소재지전체주소도로명전체주소소재지면적전화번호
0기지주유소대구광역시 동구 입석동 675번지<NA>789.0053-989-2125
1e 편한주유소대구광역시 동구 신암동 147-1, 144-35번지대구광역시 동구 아양로 139 (신암동)727.0053-952-4800
2동도주유소대구광역시 동구 용계동 763번지대구광역시 동구 안심로 30 (용계동)1443.0053-965-9600
3상호주유소대구광역시 동구 각산동 111번지<NA><NA><NA>
4대성산업(주)하이웨이주유소대구광역시 동구 신천동 (3동) 148-2,3번지대구광역시 동구 국채보상로 849 (신천동)2316.4053-755-1055
5확산주유소대구광역시 동구 각산동<NA>200.0<NA>
6극동주유소대구광역시 동구 신천동 283-2,19번지대구광역시 동구 동부로 80 (신천동)1.76053-752-2220
7에스케이에너지판매(주)만남의광장주유소대구광역시 동구 용계동 444-2번지 463-1, 887-59대구광역시 동구 화랑로 490 (용계동)6063.0053-965-0010
8화랑주유소대구광역시 동구 용계동 447-4번지 447-6,448-4.대구광역시 동구 화랑로 484 (용계동)999.0053-962-8725
9대성산업(주)강촌대성주유소대구광역시 동구 용계동 437-56번지 외 1필지(437-45)대구광역시 동구 화랑로 481 (용계동)1869.0053-985-4222
사업장명소재지전체주소도로명전체주소소재지면적전화번호
51송정주유소대구광역시 동구 괴전동 208-1번지대구광역시 동구 안심로 483 (괴전동)870.0053-963-0184
52팔공GS주유소대구광역시 동구 지묘동 647-1번지대구광역시 동구 파계로 308 (지묘동)665.0053-985-1005
53공항랜드주유소대구광역시 동구 지저동 678-6번지대구광역시 동구 공항로 259 (지저동)923.0053-984-6555
54늘푸른주유소대구광역시 동구 용수동 50-1번지대구광역시 동구 팔공산로 1184 (용수동)937.0053-984-3051
55미니주유소대구광역시 동구 검사동 1024-19번지대구광역시 동구 해동로 171 (검사동)407.0053-981-1007
56계명Ⅱ주유소대구광역시 동구 신서동 1138-1번지대구광역시 동구 이노밸리로 277 (신서동)1167.0<NA>
57팔공산(IC)주유소대구광역시 동구 지저동 662-17번지 662-44, 684-14, 684-16대구광역시 동구 공항로 247 (지저동)450.0<NA>
58국제주유소대구광역시 동구 봉무동 143-2번지대구광역시 동구 팔공로 376 (봉무동)1161.0053-986-5152
59효동로주유소대구광역시 동구 효목동 137-49번지대구광역시 동구 효동로 77 (효목동)635.7053-986-9700
60sk네트웍스(주) 공산주유소대구광역시 동구 지묘동 275번지대구광역시 동구 팔공로 473 (지묘동)907.0<NA>