Overview

Dataset statistics

Number of variables8
Number of observations52
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.5 KiB
Average record size in memory69.5 B

Variable types

Numeric3
Categorical2
Text3

Dataset

Description대구광역시 북구 관내에서 운영 중인 가스사업자현황(가스사업자 업종, 업소명, 전화번호, 주소 등)정보를 제공합니다.
URLhttps://www.data.go.kr/data/15030569/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
연번 is highly overall correlated with 업종High correlation
업종 is highly overall correlated with 연번High correlation
전화번호 has unique valuesUnique

Reproduction

Analysis started2023-12-12 18:54:17.959105
Analysis finished2023-12-12 18:54:20.192603
Duration2.23 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

HIGH CORRELATION 

Distinct51
Distinct (%)98.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean26.961538
Minimum1
Maximum52
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size600.0 B
2023-12-13T03:54:20.337309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile3.55
Q113.75
median27.5
Q340.25
95-th percentile49.45
Maximum52
Range51
Interquartile range (IQR)26.5

Descriptive statistics

Standard deviation15.225059
Coefficient of variation (CV)0.56469547
Kurtosis-1.2183602
Mean26.961538
Median Absolute Deviation (MAD)13.5
Skewness-0.072041136
Sum1402
Variance231.80241
MonotonicityIncreasing
2023-12-13T03:54:20.603482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
41 2
 
3.8%
2 1
 
1.9%
30 1
 
1.9%
31 1
 
1.9%
32 1
 
1.9%
33 1
 
1.9%
34 1
 
1.9%
35 1
 
1.9%
36 1
 
1.9%
37 1
 
1.9%
Other values (41) 41
78.8%
ValueCountFrequency (%)
1 1
1.9%
2 1
1.9%
3 1
1.9%
4 1
1.9%
5 1
1.9%
6 1
1.9%
7 1
1.9%
8 1
1.9%
9 1
1.9%
10 1
1.9%
ValueCountFrequency (%)
52 1
1.9%
51 1
1.9%
50 1
1.9%
49 1
1.9%
48 1
1.9%
47 1
1.9%
46 1
1.9%
45 1
1.9%
44 1
1.9%
43 1
1.9%

업종
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)3.8%
Missing0
Missing (%)0.0%
Memory size548.0 B
가스판매소
40 
가스충전소
12 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row가스판매소
2nd row가스판매소
3rd row가스판매소
4th row가스판매소
5th row가스판매소

Common Values

ValueCountFrequency (%)
가스판매소 40
76.9%
가스충전소 12
 
23.1%

Length

2023-12-13T03:54:20.820440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T03:54:20.984049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
가스판매소 40
76.9%
가스충전소 12
 
23.1%

업소명
Text

Distinct51
Distinct (%)98.1%
Missing0
Missing (%)0.0%
Memory size548.0 B
2023-12-13T03:54:21.288943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length18
Median length13
Mean length6.25
Min length3

Characters and Unicode

Total characters325
Distinct characters95
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique50 ?
Unique (%)96.2%

Sample

1st row대도가스
2nd row성창종합가스
3rd row보건종합가스
4th row성용종합가스
5th row삼성성일가스
ValueCountFrequency (%)
㈜한신가스 2
 
3.8%
대흥가스 1
 
1.9%
에어젠 1
 
1.9%
안전가스상사 1
 
1.9%
대풍가스 1
 
1.9%
대한가스 1
 
1.9%
대풍에너지 1
 
1.9%
창우종합가스 1
 
1.9%
검단종합가스 1
 
1.9%
제일종합에너지 1
 
1.9%
Other values (42) 42
79.2%
2023-12-13T03:54:22.294920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
가 39
 
12.0%
스 39
 
12.0%
대 17
 
5.2%
합 14
 
4.3%
종 12
 
3.7%
성 11
 
3.4%
전 10
 
3.1%
충 9
 
2.8%
소 9
 
2.8%
사 8
 
2.5%
Other values (85) 157
48.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 301
92.6%
Uppercase Letter 16
 
4.9%
Other Symbol 4
 
1.2%
Space Separator 2
 
0.6%
Decimal Number 2
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
가 39
 
13.0%
스 39
 
13.0%
대 17
 
5.6%
합 14
 
4.7%
종 12
 
4.0%
성 11
 
3.7%
전 10
 
3.3%
충 9
 
3.0%
소 9
 
3.0%
사 8
 
2.7%
Other values (74) 133
44.2%
Uppercase Letter
ValueCountFrequency (%)
L 4
25.0%
P 4
25.0%
G 4
25.0%
C 1
 
6.2%
I 1
 
6.2%
S 1
 
6.2%
K 1
 
6.2%
Decimal Number
ValueCountFrequency (%)
5 1
50.0%
2 1
50.0%
Other Symbol
ValueCountFrequency (%)
㈜ 4
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 305
93.8%
Latin 16
 
4.9%
Common 4
 
1.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
가 39
 
12.8%
스 39
 
12.8%
대 17
 
5.6%
합 14
 
4.6%
종 12
 
3.9%
성 11
 
3.6%
전 10
 
3.3%
충 9
 
3.0%
소 9
 
3.0%
사 8
 
2.6%
Other values (75) 137
44.9%
Latin
ValueCountFrequency (%)
L 4
25.0%
P 4
25.0%
G 4
25.0%
C 1
 
6.2%
I 1
 
6.2%
S 1
 
6.2%
K 1
 
6.2%
Common
ValueCountFrequency (%)
2
50.0%
5 1
25.0%
2 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 301
92.6%
ASCII 20
 
6.2%
None 4
 
1.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
가 39
 
13.0%
스 39
 
13.0%
대 17
 
5.6%
합 14
 
4.7%
종 12
 
4.0%
성 11
 
3.7%
전 10
 
3.3%
충 9
 
3.0%
소 9
 
3.0%
사 8
 
2.7%
Other values (74) 133
44.2%
ASCII
ValueCountFrequency (%)
L 4
20.0%
P 4
20.0%
G 4
20.0%
2
10.0%
5 1
 
5.0%
C 1
 
5.0%
I 1
 
5.0%
2 1
 
5.0%
S 1
 
5.0%
K 1
 
5.0%
None
ValueCountFrequency (%)
㈜ 4
100.0%

전화번호
Text

UNIQUE 

Distinct52
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size548.0 B
2023-12-13T03:54:22.612697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters624
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

Unique52 ?
Unique (%)100.0%

Sample

1st row053-955-3336
2nd row053-351-0321
3rd row053-357-8552
4th row053-381-7333
5th row053-956-6100
ValueCountFrequency (%)
053-955-3336 1
 
1.9%
053-351-0321 1
 
1.9%
053-424-1312 1
 
1.9%
053-384-3600 1
 
1.9%
053-325-8040 1
 
1.9%
053-323-6118 1
 
1.9%
053-353-8524 1
 
1.9%
053-358-4204 1
 
1.9%
053-354-6601 1
 
1.9%
053-382-0119 1
 
1.9%
Other values (42) 42
80.8%
2023-12-13T03:54:23.059342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 128
20.5%
- 104
16.7%
5 101
16.2%
0 87
13.9%
1 44
 
7.1%
2 39
 
6.2%
4 37
 
5.9%
8 24
 
3.8%
9 22
 
3.5%
7 20
 
3.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 520
83.3%
Dash Punctuation 104
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 128
24.6%
5 101
19.4%
0 87
16.7%
1 44
 
8.5%
2 39
 
7.5%
4 37
 
7.1%
8 24
 
4.6%
9 22
 
4.2%
7 20
 
3.8%
6 18
 
3.5%
Dash Punctuation
ValueCountFrequency (%)
- 104
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 624
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 128
20.5%
- 104
16.7%
5 101
16.2%
0 87
13.9%
1 44
 
7.1%
2 39
 
6.2%
4 37
 
5.9%
8 24
 
3.8%
9 22
 
3.5%
7 20
 
3.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 624
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 128
20.5%
- 104
16.7%
5 101
16.2%
0 87
13.9%
1 44
 
7.1%
2 39
 
6.2%
4 37
 
5.9%
8 24
 
3.8%
9 22
 
3.5%
7 20
 
3.2%

소재지도로명주소
Text

Distinct50
Distinct (%)96.2%
Missing0
Missing (%)0.0%
Memory size548.0 B
2023-12-13T03:54:23.416103image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length25
Mean length24.019231
Min length20

Characters and Unicode

Total characters1249
Distinct characters68
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

Unique48 ?
Unique (%)92.3%

Sample

1st row대구광역시 북구 신천동로 634-1 (대현동)
2nd row대구광역시 북구 옥산로3길 11 (노원동1가)
3rd row대구광역시 북구 노원로10길 158 (노원동2가)
4th row대구광역시 북구 동북로 49 (산격동)
5th row대구광역시 북구 호국로 29 (산격동)
ValueCountFrequency (%)
대구광역시 52
20.5%
북구 52
20.5%
산격동 12
 
4.7%
침산동 9
 
3.5%
노원동3가 6
 
2.4%
호국로 5
 
2.0%
29 4
 
1.6%
동북로 4
 
1.6%
18 3
 
1.2%
칠성동2가 3
 
1.2%
Other values (88) 104
40.9%
2023-12-13T03:54:24.095360image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
222
17.8%
구 105
 
8.4%
북 61
 
4.9%
동 60
 
4.8%
대 59
 
4.7%
시 53
 
4.2%
( 52
 
4.2%
역 52
 
4.2%
광 52
 
4.2%
) 52
 
4.2%
Other values (58) 481
38.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 732
58.6%
Space Separator 222
 
17.8%
Decimal Number 182
 
14.6%
Open Punctuation 52
 
4.2%
Close Punctuation 52
 
4.2%
Dash Punctuation 9
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 105
14.3%
북 61
 
8.3%
동 60
 
8.2%
대 59
 
8.1%
시 53
 
7.2%
역 52
 
7.1%
광 52
 
7.1%
로 50
 
6.8%
길 26
 
3.6%
산 26
 
3.6%
Other values (44) 188
25.7%
Decimal Number
ValueCountFrequency (%)
2 40
22.0%
1 31
17.0%
3 28
15.4%
4 17
9.3%
6 14
 
7.7%
7 14
 
7.7%
5 13
 
7.1%
0 11
 
6.0%
9 10
 
5.5%
8 4
 
2.2%
Space Separator
ValueCountFrequency (%)
222
100.0%
Open Punctuation
ValueCountFrequency (%)
( 52
100.0%
Close Punctuation
ValueCountFrequency (%)
) 52
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 9
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 732
58.6%
Common 517
41.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 105
14.3%
북 61
 
8.3%
동 60
 
8.2%
대 59
 
8.1%
시 53
 
7.2%
역 52
 
7.1%
광 52
 
7.1%
로 50
 
6.8%
길 26
 
3.6%
산 26
 
3.6%
Other values (44) 188
25.7%
Common
ValueCountFrequency (%)
222
42.9%
( 52
 
10.1%
) 52
 
10.1%
2 40
 
7.7%
1 31
 
6.0%
3 28
 
5.4%
4 17
 
3.3%
6 14
 
2.7%
7 14
 
2.7%
5 13
 
2.5%
Other values (4) 34
 
6.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 732
58.6%
ASCII 517
41.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
222
42.9%
( 52
 
10.1%
) 52
 
10.1%
2 40
 
7.7%
1 31
 
6.0%
3 28
 
5.4%
4 17
 
3.3%
6 14
 
2.7%
7 14
 
2.7%
5 13
 
2.5%
Other values (4) 34
 
6.6%
Hangul
ValueCountFrequency (%)
구 105
14.3%
북 61
 
8.3%
동 60
 
8.2%
대 59
 
8.1%
시 53
 
7.2%
역 52
 
7.1%
광 52
 
7.1%
로 50
 
6.8%
길 26
 
3.6%
산 26
 
3.6%
Other values (44) 188
25.7%

위도
Real number (ℝ)

Distinct49
Distinct (%)94.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.902296
Minimum35.877314
Maximum35.960578
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size600.0 B
2023-12-13T03:54:24.326590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.877314
5-th percentile35.881525
Q135.893576
median35.901456
Q335.907536
95-th percentile35.928345
Maximum35.960578
Range0.08326371
Interquartile range (IQR)0.013959905

Descriptive statistics

Standard deviation0.016177846
Coefficient of variation (CV)0.00045060757
Kurtosis4.650691
Mean35.902296
Median Absolute Deviation (MAD)0.00770285
Skewness1.7101976
Sum1866.9194
Variance0.00026172271
MonotonicityNot monotonic
2023-12-13T03:54:24.568918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=49)
ValueCountFrequency (%)
35.90505006 3
 
5.8%
35.90290517 2
 
3.8%
35.89086806 1
 
1.9%
35.9586008 1
 
1.9%
35.90130472 1
 
1.9%
35.90160806 1
 
1.9%
35.91210729 1
 
1.9%
35.9021129 1
 
1.9%
35.91166176 1
 
1.9%
35.90018113 1
 
1.9%
Other values (39) 39
75.0%
ValueCountFrequency (%)
35.87731402 1
1.9%
35.87753986 1
1.9%
35.8813802 1
1.9%
35.88164428 1
1.9%
35.88356583 1
1.9%
35.88560619 1
1.9%
35.88776932 1
1.9%
35.88925489 1
1.9%
35.89036283 1
1.9%
35.89086806 1
1.9%
ValueCountFrequency (%)
35.96057773 1
1.9%
35.9586008 1
1.9%
35.92996196 1
1.9%
35.92702269 1
1.9%
35.92345889 1
1.9%
35.91485821 1
1.9%
35.91334383 1
1.9%
35.91254743 1
1.9%
35.91210729 1
1.9%
35.91166176 1
1.9%

경도
Real number (ℝ)

Distinct49
Distinct (%)94.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean128.58454
Minimum128.52519
Maximum128.62746
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size600.0 B
2023-12-13T03:54:24.851160image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum128.52519
5-th percentile128.53891
Q1128.56696
median128.58842
Q3128.60245
95-th percentile128.62136
Maximum128.62746
Range0.1022671
Interquartile range (IQR)0.0354835

Descriptive statistics

Standard deviation0.026402955
Coefficient of variation (CV)0.00020533538
Kurtosis-0.48828185
Mean128.58454
Median Absolute Deviation (MAD)0.0175864
Skewness-0.54042821
Sum6686.3961
Variance0.00069711604
MonotonicityNot monotonic
2023-12-13T03:54:25.147174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=49)
ValueCountFrequency (%)
128.602408 3
 
5.8%
128.585425 2
 
3.8%
128.5580902 1
 
1.9%
128.5674119 1
 
1.9%
128.5710378 1
 
1.9%
128.584873 1
 
1.9%
128.627462 1
 
1.9%
128.5970921 1
 
1.9%
128.6104504 1
 
1.9%
128.5656194 1
 
1.9%
Other values (39) 39
75.0%
ValueCountFrequency (%)
128.5251949 1
1.9%
128.5256065 1
1.9%
128.5381624 1
1.9%
128.5395269 1
1.9%
128.5400244 1
1.9%
128.5482304 1
1.9%
128.5501563 1
1.9%
128.552103 1
1.9%
128.5522794 1
1.9%
128.5539627 1
1.9%
ValueCountFrequency (%)
128.627462 1
1.9%
128.6259902 1
1.9%
128.6253351 1
1.9%
128.6181025 1
1.9%
128.6149841 1
1.9%
128.6135905 1
1.9%
128.6121319 1
1.9%
128.6104504 1
1.9%
128.609219 1
1.9%
128.6089229 1
1.9%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)1.9%
Missing0
Missing (%)0.0%
Memory size548.0 B
2023-06-22
52 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-06-22
2nd row2023-06-22
3rd row2023-06-22
4th row2023-06-22
5th row2023-06-22

Common Values

ValueCountFrequency (%)
2023-06-22 52
100.0%

Length

2023-12-13T03:54:25.395655image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-13T03:54:25.576308image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-06-22 52
100.0%

Interactions

2023-12-13T03:54:19.490431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:54:18.603899image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:54:19.066569image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:54:19.614646image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:54:18.737606image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:54:19.223371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:54:19.747218image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:54:18.882989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T03:54:19.354989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-13T03:54:25.705539image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번업종업소명전화번호소재지도로명주소위도경도
연번1.0000.9960.9291.0000.8250.1710.316
업종0.9961.0000.0001.0001.0000.0000.000
업소명0.9290.0001.0001.0000.9901.0001.000
전화번호1.0001.0001.0001.0001.0001.0001.000
소재지도로명주소0.8251.0000.9901.0001.0001.0001.000
위도0.1710.0001.0001.0001.0001.0000.489
경도0.3160.0001.0001.0001.0000.4891.000
2023-12-13T03:54:25.914985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
연번위도경도업종
연번1.0000.493-0.1790.865
위도0.4931.0000.0010.000
경도-0.1790.0011.0000.194
업종0.8650.0000.1941.000

Missing values

2023-12-13T03:54:19.908358image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T03:54:20.113611image/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

연번업종업소명전화번호소재지도로명주소위도경도데이터기준일자
01가스판매소대도가스053-955-3336대구광역시 북구 신천동로 634-1 (대현동)35.877314128.6062112023-06-22
12가스판매소성창종합가스053-351-0321대구광역시 북구 옥산로3길 11 (노원동1가)35.887769128.5785662023-06-22
23가스판매소보건종합가스053-357-8552대구광역시 북구 노원로10길 158 (노원동2가)35.890363128.5758822023-06-22
34가스판매소성용종합가스053-381-7333대구광역시 북구 동북로 49 (산격동)35.902459128.5993172023-06-22
45가스판매소삼성성일가스053-956-6100대구광역시 북구 호국로 29 (산격동)35.90505128.6024082023-06-22
56가스판매소유공대창가스053-953-3040대구광역시 북구 대동로 52 (산격동)35.896224128.6121322023-06-22
67가스판매소제일종합가스053-358-5833대구광역시 북구 성북로15길 13 (침산동)35.893635128.5912282023-06-22
78가스판매소대우산업가스053-353-7745대구광역시 북구 3공단로 254-1 (노원동3가)35.902996128.5782422023-06-22
89가스판매소경북육일가스053-351-6161대구광역시 북구 오봉로2길 26 (노원동1가)35.889255128.5791662023-06-22
910가스판매소선진종합가스053-424-7766대구광역시 북구 대현로13길 22 (대현동)35.885606128.6073782023-06-22
연번업종업소명전화번호소재지도로명주소위도경도데이터기준일자
4243가스충전소대평제2LPG충전소053-952-9000대구광역시 북구 동북로 212 (복현동)35.897252128.6149842023-06-22
4344가스충전소㈜한신가스053-341-0041대구광역시 북구 노원로 229 (침산동)35.901292128.5846912023-06-22
4445가스충전소북대구LPG충전소053-384-5177대구광역시 북구 동북로 3 (산격동)35.901671128.5940272023-06-22
4546가스충전소㈜팔달에너지053-314-4001대구광역시 북구 칠곡중앙대로 132 (매천동)35.907526128.548232023-06-22
4647가스충전소서변LPG충전소053-939-1991대구광역시 북구 호국로 129 (서변동)35.913344128.5990442023-06-22
4748가스충전소남경대성충전소053-311-0311대구광역시 북구 사수로 406 (금호동)35.897504128.5251952023-06-22
4849가스충전소읍내IC충전소053-321-0095대구광역시 북구 칠곡중앙대로 736 (읍내동)35.960578128.5522792023-06-22
4950가스충전소대구개인택시조합충전소053-382-6300대구광역시 북구 검단로174(검단동)35.910036128.6253352023-06-22
5051가스충전소경원LPG충전소053-312-2552대구광역시 북구 사수로 432(금호동)35.895523128.5256072023-06-22
5152가스충전소주식회사칠곡아이씨충전소053-327-2277대구광역시 북구 매천로307(태전동)35.923459128.5381622023-06-22