Overview

Dataset statistics

Number of variables9
Number of observations41
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory3.1 KiB
Average record size in memory76.2 B

Variable types

Numeric1
Text5
DateTime1
Categorical2

Dataset

Description대구광역시_동구_에너지관련정보_20200428
Author대구광역시 동구
URLhttp://data.daegu.go.kr/open/data/dataView.do?dataSetId=3055762&dataSetDetailId=30557623f56bb92bfea6&provdMethod=FILE

Alerts

용도지역 is highly imbalanced (53.3%)Imbalance
허가번호 has unique valuesUnique
소재지 has unique valuesUnique
전화번호 has unique valuesUnique
안전관리자 has unique valuesUnique

Reproduction

Analysis started2023-12-10 18:53:27.261113
Analysis finished2023-12-10 18:53:28.293840
Duration1.03 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

허가번호
Real number (ℝ)

UNIQUE 

Distinct41
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.317073
Minimum2
Maximum69
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size501.0 B
2023-12-11T03:53:28.418689image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2
5-th percentile6
Q119
median38
Q355
95-th percentile67
Maximum69
Range67
Interquartile range (IQR)36

Descriptive statistics

Standard deviation20.723705
Coefficient of variation (CV)0.55534112
Kurtosis-1.2790667
Mean37.317073
Median Absolute Deviation (MAD)19
Skewness-0.11063899
Sum1530
Variance429.47195
MonotonicityStrictly increasing
2023-12-11T03:53:28.580766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=41)
ValueCountFrequency (%)
2 1
 
2.4%
57 1
 
2.4%
41 1
 
2.4%
46 1
 
2.4%
48 1
 
2.4%
49 1
 
2.4%
52 1
 
2.4%
53 1
 
2.4%
54 1
 
2.4%
55 1
 
2.4%
Other values (31) 31
75.6%
ValueCountFrequency (%)
2 1
2.4%
3 1
2.4%
6 1
2.4%
8 1
2.4%
9 1
2.4%
10 1
2.4%
13 1
2.4%
15 1
2.4%
17 1
2.4%
18 1
2.4%
ValueCountFrequency (%)
69 1
2.4%
68 1
2.4%
67 1
2.4%
65 1
2.4%
64 1
2.4%
62 1
2.4%
61 1
2.4%
60 1
2.4%
59 1
2.4%
57 1
2.4%

업소명
Text

Distinct40
Distinct (%)97.6%
Missing0
Missing (%)0.0%
Memory size460.0 B
2023-12-11T03:53:28.890415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length7
Mean length4.9268293
Min length4

Characters and Unicode

Total characters202
Distinct characters61
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique39 ?
Unique (%)95.1%

Sample

1st row삼화가스상사
2nd row선경금호가스
3rd row동양가스
4th row한독가스
5th row원양가스
ValueCountFrequency (%)
경북종합가스 2
 
4.9%
삼화가스상사 1
 
2.4%
동양종합가스 1
 
2.4%
선경금호가스 1
 
2.4%
혁신가스 1
 
2.4%
혜성가스 1
 
2.4%
태성가스 1
 
2.4%
동아린나이 1
 
2.4%
화신가스 1
 
2.4%
우림가스 1
 
2.4%
Other values (30) 30
73.2%
2023-12-11T03:53:29.346372image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
가 34
16.8%
스 34
16.8%
대 11
 
5.4%
성 9
 
4.5%
종 6
 
3.0%
합 6
 
3.0%
동 6
 
3.0%
에 5
 
2.5%
너 5
 
2.5%
지 5
 
2.5%
Other values (51) 81
40.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 199
98.5%
Uppercase Letter 3
 
1.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
가 34
17.1%
스 34
17.1%
대 11
 
5.5%
성 9
 
4.5%
종 6
 
3.0%
합 6
 
3.0%
동 6
 
3.0%
에 5
 
2.5%
너 5
 
2.5%
지 5
 
2.5%
Other values (48) 78
39.2%
Uppercase Letter
ValueCountFrequency (%)
G 1
33.3%
L 1
33.3%
P 1
33.3%

Most occurring scripts

ValueCountFrequency (%)
Hangul 199
98.5%
Latin 3
 
1.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
가 34
17.1%
스 34
17.1%
대 11
 
5.5%
성 9
 
4.5%
종 6
 
3.0%
합 6
 
3.0%
동 6
 
3.0%
에 5
 
2.5%
너 5
 
2.5%
지 5
 
2.5%
Other values (48) 78
39.2%
Latin
ValueCountFrequency (%)
G 1
33.3%
L 1
33.3%
P 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 199
98.5%
ASCII 3
 
1.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
가 34
17.1%
스 34
17.1%
대 11
 
5.5%
성 9
 
4.5%
종 6
 
3.0%
합 6
 
3.0%
동 6
 
3.0%
에 5
 
2.5%
너 5
 
2.5%
지 5
 
2.5%
Other values (48) 78
39.2%
ASCII
ValueCountFrequency (%)
G 1
33.3%
L 1
33.3%
P 1
33.3%

대표자
Text

Distinct39
Distinct (%)95.1%
Missing0
Missing (%)0.0%
Memory size460.0 B
2023-12-11T03:53:29.610254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length8
Median length3
Mean length3.4390244
Min length3

Characters and Unicode

Total characters141
Distinct characters71
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

Unique37 ?
Unique (%)90.2%

Sample

1st row서봉교
2nd row이종한
3rd row이준희
4th row권오형
5th row정광한
ValueCountFrequency (%)
이진수 2
 
4.5%
김석구 2
 
4.5%
송미경 1
 
2.3%
최광수외1인 1
 
2.3%
이순란 1
 
2.3%
서경태 1
 
2.3%
이근원 1
 
2.3%
이용권 1
 
2.3%
박원필 1
 
2.3%
황경수 1
 
2.3%
Other values (32) 32
72.7%
2023-12-11T03:53:30.046126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
이 10
 
7.1%
수 8
 
5.7%
김 8
 
5.7%
경 5
 
3.5%
재 4
 
2.8%
현 4
 
2.8%
한 3
 
2.1%
, 3
 
2.1%
순 3
 
2.1%
호 3
 
2.1%
Other values (61) 90
63.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 134
95.0%
Other Punctuation 3
 
2.1%
Space Separator 3
 
2.1%
Decimal Number 1
 
0.7%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 10
 
7.5%
수 8
 
6.0%
김 8
 
6.0%
경 5
 
3.7%
재 4
 
3.0%
현 4
 
3.0%
한 3
 
2.2%
순 3
 
2.2%
호 3
 
2.2%
장 3
 
2.2%
Other values (58) 83
61.9%
Other Punctuation
ValueCountFrequency (%)
, 3
100.0%
Space Separator
ValueCountFrequency (%)
3
100.0%
Decimal Number
ValueCountFrequency (%)
1 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 134
95.0%
Common 7
 
5.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 10
 
7.5%
수 8
 
6.0%
김 8
 
6.0%
경 5
 
3.7%
재 4
 
3.0%
현 4
 
3.0%
한 3
 
2.2%
순 3
 
2.2%
호 3
 
2.2%
장 3
 
2.2%
Other values (58) 83
61.9%
Common
ValueCountFrequency (%)
, 3
42.9%
3
42.9%
1 1
 
14.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 134
95.0%
ASCII 7
 
5.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
이 10
 
7.5%
수 8
 
6.0%
김 8
 
6.0%
경 5
 
3.7%
재 4
 
3.0%
현 4
 
3.0%
한 3
 
2.2%
순 3
 
2.2%
호 3
 
2.2%
장 3
 
2.2%
Other values (58) 83
61.9%
ASCII
ValueCountFrequency (%)
, 3
42.9%
3
42.9%
1 1
 
14.3%

소재지
Text

UNIQUE 

Distinct41
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size460.0 B
2023-12-11T03:53:30.497879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length23
Mean length21.02439
Min length7

Characters and Unicode

Total characters862
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

Unique41 ?
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 row동북로 374 (신암4동 133-109)
ValueCountFrequency (%)
검사동 4
 
2.5%
효목2동 3
 
1.9%
신평동 3
 
1.9%
방촌동 3
 
1.9%
효목1동 3
 
1.9%
신기동 3
 
1.9%
신암4동 3
 
1.9%
신천4동 2
 
1.3%
입석동 2
 
1.3%
평화로 2
 
1.3%
Other values (123) 131
82.4%
2023-12-11T03:53:31.137677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
120
 
13.9%
1 73
 
8.5%
동 54
 
6.3%
- 51
 
5.9%
2 46
 
5.3%
로 41
 
4.8%
( 39
 
4.5%
) 39
 
4.5%
3 37
 
4.3%
4 34
 
3.9%
Other values (46) 328
38.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 339
39.3%
Other Letter 274
31.8%
Space Separator 120
 
13.9%
Dash Punctuation 51
 
5.9%
Open Punctuation 39
 
4.5%
Close Punctuation 39
 
4.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 54
19.7%
로 41
15.0%
길 24
 
8.8%
신 18
 
6.6%
효 12
 
4.4%
촌 12
 
4.4%
방 8
 
2.9%
목 8
 
2.9%
암 7
 
2.6%
평 7
 
2.6%
Other values (32) 83
30.3%
Decimal Number
ValueCountFrequency (%)
1 73
21.5%
2 46
13.6%
3 37
10.9%
4 34
10.0%
7 29
 
8.6%
5 29
 
8.6%
6 28
 
8.3%
8 22
 
6.5%
9 21
 
6.2%
0 20
 
5.9%
Space Separator
ValueCountFrequency (%)
120
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 51
100.0%
Open Punctuation
ValueCountFrequency (%)
( 39
100.0%
Close Punctuation
ValueCountFrequency (%)
) 39
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 588
68.2%
Hangul 274
31.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 54
19.7%
로 41
15.0%
길 24
 
8.8%
신 18
 
6.6%
효 12
 
4.4%
촌 12
 
4.4%
방 8
 
2.9%
목 8
 
2.9%
암 7
 
2.6%
평 7
 
2.6%
Other values (32) 83
30.3%
Common
ValueCountFrequency (%)
120
20.4%
1 73
12.4%
- 51
8.7%
2 46
 
7.8%
( 39
 
6.6%
) 39
 
6.6%
3 37
 
6.3%
4 34
 
5.8%
7 29
 
4.9%
5 29
 
4.9%
Other values (4) 91
15.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 588
68.2%
Hangul 274
31.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
120
20.4%
1 73
12.4%
- 51
8.7%
2 46
 
7.8%
( 39
 
6.6%
) 39
 
6.6%
3 37
 
6.3%
4 34
 
5.8%
7 29
 
4.9%
5 29
 
4.9%
Other values (4) 91
15.5%
Hangul
ValueCountFrequency (%)
동 54
19.7%
로 41
15.0%
길 24
 
8.8%
신 18
 
6.6%
효 12
 
4.4%
촌 12
 
4.4%
방 8
 
2.9%
목 8
 
2.9%
암 7
 
2.6%
평 7
 
2.6%
Other values (32) 83
30.3%

허가일자
Date

Distinct40
Distinct (%)97.6%
Missing0
Missing (%)0.0%
Memory size460.0 B
Minimum1973-11-19 00:00:00
Maximum2014-01-16 00:00:00
2023-12-11T03:53:31.325342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T03:53:31.546152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=40)

전화번호
Text

UNIQUE 

Distinct41
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size460.0 B
2023-12-11T03:53:31.879604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters492
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

Unique41 ?
Unique (%)100.0%

Sample

1st row053-424-0304
2nd row053-955-3033
3rd row053-985-5200
4th row053-752-3163
5th row053-952-4980
ValueCountFrequency (%)
053-424-0304 1
 
2.4%
053-984-3333 1
 
2.4%
053-963-4455 1
 
2.4%
053-963-7200 1
 
2.4%
053-984-6014 1
 
2.4%
053-963-7800 1
 
2.4%
053-985-3651 1
 
2.4%
053-982-8882 1
 
2.4%
053-981-8084 1
 
2.4%
053-982-2758 1
 
2.4%
Other values (31) 31
75.6%
2023-12-11T03:53:32.391413image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 82
16.7%
5 78
15.9%
3 78
15.9%
0 74
15.0%
9 42
8.5%
8 38
7.7%
2 26
 
5.3%
4 24
 
4.9%
6 20
 
4.1%
1 19
 
3.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 410
83.3%
Dash Punctuation 82
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 78
19.0%
3 78
19.0%
0 74
18.0%
9 42
10.2%
8 38
9.3%
2 26
 
6.3%
4 24
 
5.9%
6 20
 
4.9%
1 19
 
4.6%
7 11
 
2.7%
Dash Punctuation
ValueCountFrequency (%)
- 82
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 492
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 82
16.7%
5 78
15.9%
3 78
15.9%
0 74
15.0%
9 42
8.5%
8 38
7.7%
2 26
 
5.3%
4 24
 
4.9%
6 20
 
4.1%
1 19
 
3.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 492
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 82
16.7%
5 78
15.9%
3 78
15.9%
0 74
15.0%
9 42
8.5%
8 38
7.7%
2 26
 
5.3%
4 24
 
4.9%
6 20
 
4.1%
1 19
 
3.9%

용도지역
Categorical

IMBALANCE 

Distinct5
Distinct (%)12.2%
Missing0
Missing (%)0.0%
Memory size460.0 B
주거
33 
상업
 
3
녹지
 
2
준주거
 
2
근상
 
1

Length

Max length3
Median length2
Mean length2.0487805
Min length2

Unique

Unique1 ?
Unique (%)2.4%

Sample

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

Common Values

ValueCountFrequency (%)
주거 33
80.5%
상업 3
 
7.3%
녹지 2
 
4.9%
준주거 2
 
4.9%
근상 1
 
2.4%

Length

2023-12-11T03:53:32.605147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:53:32.765754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
주거 33
80.5%
상업 3
 
7.3%
녹지 2
 
4.9%
준주거 2
 
4.9%
근상 1
 
2.4%

안전관리자
Text

UNIQUE 

Distinct41
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size460.0 B
2023-12-11T03:53:33.070805image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length3
Median length3
Mean length3
Min length3

Characters and Unicode

Total characters123
Distinct characters75
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

Unique41 ?
Unique (%)100.0%

Sample

1st row허문자
2nd row이종한
3rd row박진형
4th row최병욱
5th row정광한
ValueCountFrequency (%)
허문자 1
 
2.4%
심정자 1
 
2.4%
서경태 1
 
2.4%
이근원 1
 
2.4%
오봉수 1
 
2.4%
박중섭 1
 
2.4%
배호철 1
 
2.4%
나현욱 1
 
2.4%
남승환 1
 
2.4%
차은주 1
 
2.4%
Other values (31) 31
75.6%
2023-12-11T03:53:33.590945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
김 6
 
4.9%
이 5
 
4.1%
정 5
 
4.1%
경 5
 
4.1%
수 4
 
3.3%
영 4
 
3.3%
박 4
 
3.3%
남 3
 
2.4%
창 3
 
2.4%
상 3
 
2.4%
Other values (65) 81
65.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 123
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 6
 
4.9%
이 5
 
4.1%
정 5
 
4.1%
경 5
 
4.1%
수 4
 
3.3%
영 4
 
3.3%
박 4
 
3.3%
남 3
 
2.4%
창 3
 
2.4%
상 3
 
2.4%
Other values (65) 81
65.9%

Most occurring scripts

ValueCountFrequency (%)
Hangul 123
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 6
 
4.9%
이 5
 
4.1%
정 5
 
4.1%
경 5
 
4.1%
수 4
 
3.3%
영 4
 
3.3%
박 4
 
3.3%
남 3
 
2.4%
창 3
 
2.4%
상 3
 
2.4%
Other values (65) 81
65.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 123
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
김 6
 
4.9%
이 5
 
4.1%
정 5
 
4.1%
경 5
 
4.1%
수 4
 
3.3%
영 4
 
3.3%
박 4
 
3.3%
남 3
 
2.4%
창 3
 
2.4%
상 3
 
2.4%
Other values (65) 81
65.9%

취급가스
Categorical

Distinct3
Distinct (%)7.3%
Missing0
Missing (%)0.0%
Memory size460.0 B
액화
33 
액화 고압
7 
액화
 
1

Length

Max length5
Median length2
Mean length2.5365854
Min length2

Unique

Unique1 ?
Unique (%)2.4%

Sample

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

Common Values

ValueCountFrequency (%)
액화 33
80.5%
액화 고압 7
 
17.1%
액화 1
 
2.4%

Length

2023-12-11T03:53:33.815192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T03:53:33.993017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
액화 41
85.4%
고압 7
 
14.6%

Interactions

2023-12-11T03:53:27.899873image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-11T03:53:34.103240image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
허가번호업소명대표자소재지허가일자전화번호용도지역안전관리자취급가스
허가번호1.0000.8440.8881.0001.0001.0000.0001.0000.000
업소명0.8441.0000.9841.0000.9951.0001.0001.0001.000
대표자0.8880.9841.0001.0000.9841.0001.0001.0001.000
소재지1.0001.0001.0001.0001.0001.0001.0001.0001.000
허가일자1.0000.9950.9841.0001.0001.0000.0001.0001.000
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
2023-12-11T03:53:34.260683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
용도지역취급가스
용도지역1.0000.000
취급가스0.0001.000
2023-12-11T03:53:34.382359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
허가번호용도지역취급가스
허가번호1.0000.0000.000
용도지역0.0001.0000.000
취급가스0.0000.0001.000

Missing values

2023-12-11T03:53:28.060662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T03:53:28.218146image/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
49원양가스정광한동북로 374 (신암4동 133-109)1980-08-19053-952-4980주거정광한액화
510대구종합가스배기택해동로5길 9 (지저동 774-1)1980-10-27053-984-6000주거박영필액화
613삼성가스상사김대열, 장영호평화로 23 (신암1동 722-272)1981-06-08053-954-2500주거김창수액화
715동덕가스장영훈반야월로34길 6 (신기동 117-5)1979-08-16053-963-0963상업장노식액화 고압
817대광가스김석구효동로 65 (효목1동 137-2)1982-03-19053-954-8800주거권민정액화
918대한가스유재현아양로22길 40 (신암4동 259-4)1982-05-06053-953-6660상업손경아액화
허가번호업소명대표자소재지허가일자전화번호용도지역안전관리자취급가스
3157이천년가스이순란효동로 31-1 (효목1동 171-31)1999-09-22053-942-7888주거김경미액화
3259북일가스김종백반야월북로12길 17 (율암동 360-10)2000-01-24053-965-0022주거김종백액화
3360대신삼도에너지우현선, 최인동용계동 6-22000-07-18053-963-9232주거최인동액화
3461대흥LPG남현길입석로1길 96 (입석동 888-5)2000-07-28053-755-1695주거장기옥액화
3562한국소망가스상사김석구아양로27길 18 (신암4동 143-11)2000-08-08053-954-3339주거김정희액화
3664해안가스류재락방촌로 167 (방촌동 862-57)2001-02-01053-983-8383주거류재락액화
3765대현에너지김천수동촌로1길 20-1 (입석동 961-18)2001-07-11053-957-3646주거김학하액화
3867대일에너지최광수외1인팔공산로 275 (덕곡동 205-1)2003-06-16053-981-1001녹지전상필액화
3968신화에너지김창호신평로 158 (신평동 308-2)2007-04-20053-983-4000준주거김창호액화
4069대성산업가스봉성수방촌로18 (검사동756-368)2014-01-16053-983-1058준주거박건영액화