Overview

Dataset statistics

Number of variables9
Number of observations36
Missing cells1
Missing cells (%)0.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.7 KiB
Average record size in memory76.6 B

Variable types

Numeric1
Text5
DateTime1
Categorical2

Dataset

Description대구광역시 동구 소재 가스충전소를 비롯한 에너지 관련업체 현황입니다. 이 데이터는 업소명, 위치, 연락처, 취급품목, 허가일자 등의 항목을 포함합니다.
Author대구광역시 동구
URLhttps://www.data.go.kr/data/3055762/fileData.do

Alerts

용도지역 is highly imbalanced (53.1%)Imbalance
허가일자 has 1 (2.8%) missing valuesMissing
허가번호 has unique valuesUnique
대표자 has unique valuesUnique
소재지 has unique valuesUnique
전화번호 has unique valuesUnique
안전관리자 has unique valuesUnique

Reproduction

Analysis started2024-03-14 14:11:44.650536
Analysis finished2024-03-14 14:11:46.205840
Duration1.56 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

허가번호
Real number (ℝ)

UNIQUE 

Distinct36
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean38.833333
Minimum2
Maximum69
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size452.0 B
2024-03-14T23:11:46.599672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile5.25
Q122.5
median39.5
Q355.5
95-th percentile67.25
Maximum69
Range67
Interquartile range (IQR)33

Descriptive statistics

Standard deviation20.562796
Coefficient of variation (CV)0.52951406
Kurtosis-1.1056403
Mean38.833333
Median Absolute Deviation (MAD)17
Skewness-0.28366579
Sum1398
Variance422.82857
MonotonicityStrictly increasing
2024-03-14T23:11:47.015450image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=36)
ValueCountFrequency (%)
2 1
 
2.8%
41 1
 
2.8%
48 1
 
2.8%
49 1
 
2.8%
52 1
 
2.8%
53 1
 
2.8%
54 1
 
2.8%
55 1
 
2.8%
57 1
 
2.8%
59 1
 
2.8%
Other values (26) 26
72.2%
ValueCountFrequency (%)
2 1
2.8%
3 1
2.8%
6 1
2.8%
8 1
2.8%
10 1
2.8%
13 1
2.8%
15 1
2.8%
17 1
2.8%
21 1
2.8%
23 1
2.8%
ValueCountFrequency (%)
69 1
2.8%
68 1
2.8%
67 1
2.8%
65 1
2.8%
64 1
2.8%
61 1
2.8%
60 1
2.8%
59 1
2.8%
57 1
2.8%
55 1
2.8%

업소명
Text

Distinct35
Distinct (%)97.2%
Missing0
Missing (%)0.0%
Memory size416.0 B
2024-03-14T23:11:47.831998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6.5
Mean length4.9166667
Min length4

Characters and Unicode

Total characters177
Distinct characters58
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique34 ?
Unique (%)94.4%

Sample

1st row삼화가스상사
2nd row선경금호가스
3rd row동양가스
4th row한독가스
5th row대구종합가스
ValueCountFrequency (%)
경북종합가스 2
 
5.6%
혁신가스 1
 
2.8%
이천년가스 1
 
2.8%
태성가스 1
 
2.8%
경북가스 1
 
2.8%
화신가스 1
 
2.8%
우림가스 1
 
2.8%
동양종합가스 1
 
2.8%
혜성가스 1
 
2.8%
삼화가스상사 1
 
2.8%
Other values (25) 25
69.4%
2024-03-14T23:11:49.055067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
가 31
17.5%
스 31
17.5%
대 10
 
5.6%
성 7
 
4.0%
종 6
 
3.4%
합 6
 
3.4%
동 5
 
2.8%
경 4
 
2.3%
지 4
 
2.3%
너 4
 
2.3%
Other values (48) 69
39.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 173
97.7%
Uppercase Letter 3
 
1.7%
Other Symbol 1
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
가 31
17.9%
스 31
17.9%
대 10
 
5.8%
성 7
 
4.0%
종 6
 
3.5%
합 6
 
3.5%
동 5
 
2.9%
경 4
 
2.3%
지 4
 
2.3%
너 4
 
2.3%
Other values (44) 65
37.6%
Uppercase Letter
ValueCountFrequency (%)
L 1
33.3%
P 1
33.3%
G 1
33.3%
Other Symbol
ValueCountFrequency (%)
㈜ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 174
98.3%
Latin 3
 
1.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
가 31
17.8%
스 31
17.8%
대 10
 
5.7%
성 7
 
4.0%
종 6
 
3.4%
합 6
 
3.4%
동 5
 
2.9%
경 4
 
2.3%
지 4
 
2.3%
너 4
 
2.3%
Other values (45) 66
37.9%
Latin
ValueCountFrequency (%)
L 1
33.3%
P 1
33.3%
G 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 173
97.7%
ASCII 3
 
1.7%
None 1
 
0.6%

Most frequent character per block

Hangul
ValueCountFrequency (%)
가 31
17.9%
스 31
17.9%
대 10
 
5.8%
성 7
 
4.0%
종 6
 
3.5%
합 6
 
3.5%
동 5
 
2.9%
경 4
 
2.3%
지 4
 
2.3%
너 4
 
2.3%
Other values (44) 65
37.6%
ASCII
ValueCountFrequency (%)
L 1
33.3%
P 1
33.3%
G 1
33.3%
None
ValueCountFrequency (%)
㈜ 1
100.0%

대표자
Text

UNIQUE 

Distinct36
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size416.0 B
2024-03-14T23:11:49.921265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length3
Mean length3.3611111
Min length3

Characters and Unicode

Total characters121
Distinct characters72
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

Unique36 ?
Unique (%)100.0%

Sample

1st row서봉교
2nd row이종한
3rd row이준희
4th row권오형
5th row배기택
ValueCountFrequency (%)
서봉교 1
 
2.6%
이순란 1
 
2.6%
김근택 1
 
2.6%
이근원 1
 
2.6%
이용권 1
 
2.6%
박중섭 1
 
2.6%
이상국 1
 
2.6%
장순덕 1
 
2.6%
송미경 1
 
2.6%
양호왕 1
 
2.6%
Other values (28) 28
73.7%
2024-03-14T23:11:51.180921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
이 9
 
7.4%
수 6
 
5.0%
김 6
 
5.0%
경 4
 
3.3%
서 3
 
2.5%
순 3
 
2.5%
권 3
 
2.5%
호 3
 
2.5%
, 2
 
1.7%
지 2
 
1.7%
Other values (62) 80
66.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 116
95.9%
Other Punctuation 2
 
1.7%
Space Separator 2
 
1.7%
Decimal Number 1
 
0.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 9
 
7.8%
수 6
 
5.2%
김 6
 
5.2%
경 4
 
3.4%
서 3
 
2.6%
순 3
 
2.6%
권 3
 
2.6%
호 3
 
2.6%
지 2
 
1.7%
고 2
 
1.7%
Other values (59) 75
64.7%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%
Decimal Number
ValueCountFrequency (%)
1 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 116
95.9%
Common 5
 
4.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 9
 
7.8%
수 6
 
5.2%
김 6
 
5.2%
경 4
 
3.4%
서 3
 
2.6%
순 3
 
2.6%
권 3
 
2.6%
호 3
 
2.6%
지 2
 
1.7%
고 2
 
1.7%
Other values (59) 75
64.7%
Common
ValueCountFrequency (%)
, 2
40.0%
2
40.0%
1 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 116
95.9%
ASCII 5
 
4.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
이 9
 
7.8%
수 6
 
5.2%
김 6
 
5.2%
경 4
 
3.4%
서 3
 
2.6%
순 3
 
2.6%
권 3
 
2.6%
호 3
 
2.6%
지 2
 
1.7%
고 2
 
1.7%
Other values (59) 75
64.7%
ASCII
ValueCountFrequency (%)
, 2
40.0%
2
40.0%
1 1
20.0%

소재지
Text

UNIQUE 

Distinct36
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size416.0 B
2024-03-14T23:11:52.394829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length23
Mean length20.416667
Min length7

Characters and Unicode

Total characters735
Distinct characters56
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

Unique36 ?
Unique (%)100.0%

Sample

1st row송라로 35-1 (신천1동 740-12)
2nd row아양로52길 16 (효목1동 82-32)
3rd row동촌로 130 (검사동 960-134)
4th row효신로5길 99 (신천4동 442-2)
5th row해동로5길 9 (지저동 774-1)
ValueCountFrequency (%)
검사동 4
 
3.0%
신기동 3
 
2.2%
효목1동 3
 
2.2%
신천4동 2
 
1.5%
동촌로 2
 
1.5%
신평동 2
 
1.5%
효동로 2
 
1.5%
용계동 2
 
1.5%
신암1동 2
 
1.5%
평화로 2
 
1.5%
Other values (105) 111
82.2%
2024-03-14T23:11:54.072188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
101
 
13.7%
1 64
 
8.7%
동 48
 
6.5%
- 43
 
5.9%
2 37
 
5.0%
로 36
 
4.9%
( 34
 
4.6%
) 34
 
4.6%
3 30
 
4.1%
5 28
 
3.8%
Other values (46) 280
38.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 283
38.5%
Other Letter 240
32.7%
Space Separator 101
 
13.7%
Dash Punctuation 43
 
5.9%
Open Punctuation 34
 
4.6%
Close Punctuation 34
 
4.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 48
20.0%
로 36
15.0%
길 20
 
8.3%
신 14
 
5.8%
촌 12
 
5.0%
효 8
 
3.3%
방 8
 
3.3%
평 7
 
2.9%
율 6
 
2.5%
공 5
 
2.1%
Other values (32) 76
31.7%
Decimal Number
ValueCountFrequency (%)
1 64
22.6%
2 37
13.1%
3 30
10.6%
5 28
9.9%
6 26
9.2%
7 24
 
8.5%
4 23
 
8.1%
8 19
 
6.7%
9 16
 
5.7%
0 16
 
5.7%
Space Separator
ValueCountFrequency (%)
101
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 43
100.0%
Open Punctuation
ValueCountFrequency (%)
( 34
100.0%
Close Punctuation
ValueCountFrequency (%)
) 34
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 495
67.3%
Hangul 240
32.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 48
20.0%
로 36
15.0%
길 20
 
8.3%
신 14
 
5.8%
촌 12
 
5.0%
효 8
 
3.3%
방 8
 
3.3%
평 7
 
2.9%
율 6
 
2.5%
공 5
 
2.1%
Other values (32) 76
31.7%
Common
ValueCountFrequency (%)
101
20.4%
1 64
12.9%
- 43
8.7%
2 37
 
7.5%
( 34
 
6.9%
) 34
 
6.9%
3 30
 
6.1%
5 28
 
5.7%
6 26
 
5.3%
7 24
 
4.8%
Other values (4) 74
14.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 495
67.3%
Hangul 240
32.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
101
20.4%
1 64
12.9%
- 43
8.7%
2 37
 
7.5%
( 34
 
6.9%
) 34
 
6.9%
3 30
 
6.1%
5 28
 
5.7%
6 26
 
5.3%
7 24
 
4.8%
Other values (4) 74
14.9%
Hangul
ValueCountFrequency (%)
동 48
20.0%
로 36
15.0%
길 20
 
8.3%
신 14
 
5.8%
촌 12
 
5.0%
효 8
 
3.3%
방 8
 
3.3%
평 7
 
2.9%
율 6
 
2.5%
공 5
 
2.1%
Other values (32) 76
31.7%

허가일자
Date

MISSING 

Distinct34
Distinct (%)97.1%
Missing1
Missing (%)2.8%
Memory size416.0 B
Minimum1973-11-19 00:00:00
Maximum2014-01-16 00:00:00
2024-03-14T23:11:54.454877image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T23:11:54.857003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)

전화번호
Text

UNIQUE 

Distinct36
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size416.0 B
2024-03-14T23:11:55.710895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters432
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

Unique36 ?
Unique (%)100.0%

Sample

1st row053-424-0304
2nd row053-955-3033
3rd row053-985-5200
4th row053-752-3163
5th row053-984-6000
ValueCountFrequency (%)
053-424-0304 1
 
2.8%
053-955-3033 1
 
2.8%
053-982-2758 1
 
2.8%
053-963-7200 1
 
2.8%
053-984-6014 1
 
2.8%
053-963-7800 1
 
2.8%
053-741-5556 1
 
2.8%
053-982-8882 1
 
2.8%
053-981-8084 1
 
2.8%
053-942-7888 1
 
2.8%
Other values (26) 26
72.2%
2024-03-14T23:11:56.944017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 72
16.7%
0 67
15.5%
3 66
15.3%
5 65
15.0%
9 36
8.3%
8 36
8.3%
2 24
 
5.6%
4 22
 
5.1%
1 18
 
4.2%
6 16
 
3.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 360
83.3%
Dash Punctuation 72
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 67
18.6%
3 66
18.3%
5 65
18.1%
9 36
10.0%
8 36
10.0%
2 24
 
6.7%
4 22
 
6.1%
1 18
 
5.0%
6 16
 
4.4%
7 10
 
2.8%
Dash Punctuation
ValueCountFrequency (%)
- 72
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 432
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 72
16.7%
0 67
15.5%
3 66
15.3%
5 65
15.0%
9 36
8.3%
8 36
8.3%
2 24
 
5.6%
4 22
 
5.1%
1 18
 
4.2%
6 16
 
3.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 432
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 72
16.7%
0 67
15.5%
3 66
15.3%
5 65
15.0%
9 36
8.3%
8 36
8.3%
2 24
 
5.6%
4 22
 
5.1%
1 18
 
4.2%
6 16
 
3.7%

용도지역
Categorical

IMBALANCE 

Distinct5
Distinct (%)13.9%
Missing0
Missing (%)0.0%
Memory size416.0 B
주거
29 
상업
 
2
녹지
 
2
준주거
 
2
근상
 
1

Length

Max length3
Median length2
Mean length2.0555556
Min length2

Unique

Unique1 ?
Unique (%)2.8%

Sample

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

Common Values

ValueCountFrequency (%)
주거 29
80.6%
상업 2
 
5.6%
녹지 2
 
5.6%
준주거 2
 
5.6%
근상 1
 
2.8%

Length

2024-03-14T23:11:57.375393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T23:11:57.724946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
주거 29
80.6%
상업 2
 
5.6%
녹지 2
 
5.6%
준주거 2
 
5.6%
근상 1
 
2.8%

안전관리자
Text

UNIQUE 

Distinct36
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size416.0 B
2024-03-14T23:11:58.566785image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length2.9722222
Min length2

Characters and Unicode

Total characters107
Distinct characters64
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique36 ?
Unique (%)100.0%

Sample

1st row허문자
2nd row이종한
3rd row박진형
4th row최병욱
5th row전영길
ValueCountFrequency (%)
허문자 1
 
2.8%
이종한 1
 
2.8%
차은주 1
 
2.8%
이승희 1
 
2.8%
이용권 1
 
2.8%
박중섭 1
 
2.8%
이상국 1
 
2.8%
나현욱 1
 
2.8%
남승완 1
 
2.8%
정연우 1
 
2.8%
Other values (26) 26
72.2%
2024-03-14T23:11:59.854892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
김 7
 
6.5%
이 5
 
4.7%
정 4
 
3.7%
박 4
 
3.7%
경 3
 
2.8%
현 3
 
2.8%
수 3
 
2.8%
호 3
 
2.8%
은 3
 
2.8%
남 3
 
2.8%
Other values (54) 69
64.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 107
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 7
 
6.5%
이 5
 
4.7%
정 4
 
3.7%
박 4
 
3.7%
경 3
 
2.8%
현 3
 
2.8%
수 3
 
2.8%
호 3
 
2.8%
은 3
 
2.8%
남 3
 
2.8%
Other values (54) 69
64.5%

Most occurring scripts

ValueCountFrequency (%)
Hangul 107
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 7
 
6.5%
이 5
 
4.7%
정 4
 
3.7%
박 4
 
3.7%
경 3
 
2.8%
현 3
 
2.8%
수 3
 
2.8%
호 3
 
2.8%
은 3
 
2.8%
남 3
 
2.8%
Other values (54) 69
64.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 107
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
김 7
 
6.5%
이 5
 
4.7%
정 4
 
3.7%
박 4
 
3.7%
경 3
 
2.8%
현 3
 
2.8%
수 3
 
2.8%
호 3
 
2.8%
은 3
 
2.8%
남 3
 
2.8%
Other values (54) 69
64.5%

취급가스
Categorical

Distinct3
Distinct (%)8.3%
Missing0
Missing (%)0.0%
Memory size416.0 B
액화
28 
액화 고압
7 
액화
 
1

Length

Max length5
Median length2
Mean length2.6111111
Min length2

Unique

Unique1 ?
Unique (%)2.8%

Sample

1st row액화 고압
2nd row액화
3rd row액화
4th row액화
5th row액화

Common Values

ValueCountFrequency (%)
액화 28
77.8%
액화 고압 7
 
19.4%
액화 1
 
2.8%

Length

2024-03-14T23:12:00.104913image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T23:12:00.296933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
액화 36
83.7%
고압 7
 
16.3%

Interactions

2024-03-14T23:11:45.226750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-14T23:12:00.426487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
허가번호업소명대표자소재지허가일자전화번호용도지역안전관리자취급가스
허가번호1.0000.8821.0001.0001.0001.0000.0001.0000.000
업소명0.8821.0001.0001.0000.9931.0001.0001.0001.000
대표자1.0001.0001.0001.0001.0001.0001.0001.0001.000
소재지1.0001.0001.0001.0001.0001.0001.0001.0001.000
허가일자1.0000.9931.0001.0001.0001.0000.0001.0001.000
전화번호1.0001.0001.0001.0001.0001.0001.0001.0001.000
용도지역0.0001.0001.0001.0000.0001.0001.0001.0000.000
안전관리자1.0001.0001.0001.0001.0001.0001.0001.0001.000
취급가스0.0001.0001.0001.0001.0001.0000.0001.0001.000
2024-03-14T23:12:00.624080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
취급가스용도지역
취급가스1.0000.000
용도지역0.0001.000
2024-03-14T23:12:00.784620image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
허가번호용도지역취급가스
허가번호1.0000.0000.000
용도지역0.0001.0000.000
취급가스0.0000.0001.000

Missing values

2024-03-14T23:11:45.582813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T23:11:46.031637image/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

허가번호업소명대표자소재지허가일자전화번호용도지역안전관리자취급가스
02삼화가스상사서봉교송라로 35-1 (신천1동 740-12)1980-04-23053-424-0304주거허문자액화 고압
13선경금호가스이종한아양로52길 16 (효목1동 82-32)1979-01-05053-955-3033주거이종한액화
26동양가스이준희동촌로 130 (검사동 960-134)1973-11-19053-985-5200주거박진형액화
38한독가스권오형효신로5길 99 (신천4동 442-2)1980-04-26053-752-3163주거최병욱액화
410대구종합가스배기택해동로5길 9 (지저동 774-1)1980-10-27053-984-6000주거전영길액화
513삼성가스상사김대열평화로 23 (신암1동 722-272)1981-06-08053-954-2500주거김대열액화
615동덕가스장영훈반야월로34길 6 (신기동 117-5)1979-08-16053-963-0963상업박은옥액화 고압
717대광가스김석구효동로 65 (효목1동 137-2)1982-03-19053-954-8800주거김정희액화
821동아가스이진수효목로1길 15-2 (효목2동 528-6)1982-09-13053-745-8588주거이재곤액화
923아주가스김창호동부로34길 15-1 (신천4동 394-14)1983-09-23053-753-4151주거김창호액화
허가번호업소명대표자소재지허가일자전화번호용도지역안전관리자취급가스
2655동양종합가스김근택동촌로6길 35 (검사동 1025-29)1995-07-06053-982-2758주거차은주액화 고압
2757이천년가스이순란효동로 31-1 (효목1동 171-31)1999-09-22053-942-7888주거정연우액화
2859북일가스김종백반야월북로12길 17 (율암동 360-10)2000-01-24053-965-0022주거김종백액화
2960대신삼도에너지우현선, 최인동용계동 6-22000-07-18053-963-9232주거최인동액화
3061대흥LPG남현길입석로1길 96 (입석동 888-5)2000-07-28053-755-1695주거남현길액화
3164해안가스류재락방촌로 167 (방촌동 862-57)2001-02-01053-983-8383주거류재락액화
3265대현에너지김천수동촌로1길 20-1 (입석동 961-18)2001-07-11053-957-3646주거김학하액화
3367대일에너지최광수외1인팔공산로 275 (덕곡동 205-1)2003-06-16053-981-1001녹지김수철액화
3468한국대영가스양호왕신평로 158 (신평동 308-2)2007-04-20053-983-4000준주거양호완액화
3569㈜대성가스산업봉성수방촌로18 (검사동756-368)2014-01-16053-983-1058준주거김현액화