Overview

Dataset statistics

Number of variables9
Number of observations83
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.1 KiB
Average record size in memory75.5 B

Variable types

Categorical4
Text3
Numeric2

Dataset

Description대구광역시 동구_의약품 도매상 현황_20220822
Author대구광역시 동구
URLhttp://data.daegu.go.kr/open/data/dataView.do?dataSetId=15077924&dataSetDetailId=1507792418c0f940ac236&provdMethod=FILE

Alerts

영업종 has constant value ""Constant
데이터기준일 has constant value ""Constant
위도 is highly overall correlated with 행정동명 and 1 other fieldsHigh correlation
경도 is highly overall correlated with 행정동명 and 1 other fieldsHigh correlation
행정동명 is highly overall correlated with 위도 and 2 other fieldsHigh correlation
법정동명 is highly overall correlated with 위도 and 2 other fieldsHigh correlation
영업소명 has unique valuesUnique
도로명주소 has unique valuesUnique

Reproduction

Analysis started2024-04-21 13:05:10.603497
Analysis finished2024-04-21 13:05:12.253347
Duration1.65 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

영업종
Categorical

CONSTANT 

Distinct1
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size792.0 B
일반종합도매
83 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
일반종합도매 83
100.0%

Length

2024-04-21T22:05:12.358579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T22:05:12.521423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반종합도매 83
100.0%

영업소명
Text

UNIQUE 

Distinct83
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size792.0 B
2024-04-21T22:05:13.280211image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length5.3855422
Min length2

Characters and Unicode

Total characters447
Distinct characters118
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique83 ?
Unique (%)100.0%

Sample

1st row대주팜
2nd row일일약품
3rd row주식회사 대용
4th row에스비파마
5th row비엠팜
ValueCountFrequency (%)
주식회사 4
 
4.6%
대주팜 1
 
1.1%
주)경승메디칼 1
 
1.1%
주)명성팜 1
 
1.1%
메디칼팜 1
 
1.1%
주)프라임덴탈 1
 
1.1%
주)메디팜약품 1
 
1.1%
주)기화팜 1
 
1.1%
동아제약(주)대구지점 1
 
1.1%
동아에스티(주)대구지점 1
 
1.1%
Other values (74) 74
85.1%
2024-04-21T22:05:14.308733image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
팜 34
 
7.6%
주 26
 
5.8%
약 25
 
5.6%
품 24
 
5.4%
) 21
 
4.7%
스 20
 
4.5%
( 19
 
4.3%
메 17
 
3.8%
디 15
 
3.4%
이 12
 
2.7%
Other values (108) 234
52.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 397
88.8%
Close Punctuation 21
 
4.7%
Open Punctuation 19
 
4.3%
Other Symbol 6
 
1.3%
Space Separator 4
 
0.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
팜 34
 
8.6%
주 26
 
6.5%
약 25
 
6.3%
품 24
 
6.0%
스 20
 
5.0%
메 17
 
4.3%
디 15
 
3.8%
이 12
 
3.0%
에 11
 
2.8%
칼 8
 
2.0%
Other values (104) 205
51.6%
Close Punctuation
ValueCountFrequency (%)
) 21
100.0%
Open Punctuation
ValueCountFrequency (%)
( 19
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 6
100.0%
Space Separator
ValueCountFrequency (%)
4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 403
90.2%
Common 44
 
9.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
팜 34
 
8.4%
주 26
 
6.5%
약 25
 
6.2%
품 24
 
6.0%
스 20
 
5.0%
메 17
 
4.2%
디 15
 
3.7%
이 12
 
3.0%
에 11
 
2.7%
칼 8
 
2.0%
Other values (105) 211
52.4%
Common
ValueCountFrequency (%)
) 21
47.7%
( 19
43.2%
4
 
9.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 397
88.8%
ASCII 44
 
9.8%
None 6
 
1.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
팜 34
 
8.6%
주 26
 
6.5%
약 25
 
6.3%
품 24
 
6.0%
스 20
 
5.0%
메 17
 
4.3%
디 15
 
3.8%
이 12
 
3.0%
에 11
 
2.8%
칼 8
 
2.0%
Other values (104) 205
51.6%
ASCII
ValueCountFrequency (%)
) 21
47.7%
( 19
43.2%
4
 
9.1%
None
ValueCountFrequency (%)
㈜ 6
100.0%

도로명주소
Text

UNIQUE 

Distinct83
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size792.0 B
2024-04-21T22:05:15.475013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length50
Median length40
Mean length31.048193
Min length21

Characters and Unicode

Total characters2577
Distinct characters117
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique83 ?
Unique (%)100.0%

Sample

1st row대구광역시 동구 율하동로17길 20-1, 1층 (율하동)
2nd row대구광역시 동구 금강로16길 47, 2층 (신서동)
3rd row대구광역시 동구 동부로30길 69-13, 지상1층 (신천동)
4th row대구광역시 동구 율하서로 40, 4층 402호 (율하동)
5th row대구광역시 동구 과학로17길 5, 1층 (각산동)
ValueCountFrequency (%)
대구광역시 83
 
15.4%
동구 83
 
15.4%
신천동 29
 
5.4%
2층 20
 
3.7%
3층 15
 
2.8%
율하동 14
 
2.6%
동부로22길 13
 
2.4%
4층 12
 
2.2%
1층 11
 
2.0%
효목동 8
 
1.5%
Other values (155) 252
46.7%
2024-04-21T22:05:16.897777image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
457
17.7%
동 225
 
8.7%
구 167
 
6.5%
2 98
 
3.8%
, 97
 
3.8%
로 89
 
3.5%
대 88
 
3.4%
광 84
 
3.3%
역 84
 
3.3%
) 83
 
3.2%
Other values (107) 1105
42.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1394
54.1%
Space Separator 457
 
17.7%
Decimal Number 445
 
17.3%
Other Punctuation 97
 
3.8%
Close Punctuation 83
 
3.2%
Open Punctuation 83
 
3.2%
Dash Punctuation 14
 
0.5%
Uppercase Letter 3
 
0.1%
Lowercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 225
16.1%
구 167
12.0%
로 89
 
6.4%
대 88
 
6.3%
광 84
 
6.0%
역 84
 
6.0%
시 83
 
6.0%
층 67
 
4.8%
신 47
 
3.4%
길 43
 
3.1%
Other values (88) 417
29.9%
Decimal Number
ValueCountFrequency (%)
2 98
22.0%
3 70
15.7%
1 69
15.5%
0 58
13.0%
4 41
9.2%
5 30
 
6.7%
8 25
 
5.6%
6 25
 
5.6%
7 24
 
5.4%
9 5
 
1.1%
Uppercase Letter
ValueCountFrequency (%)
A 1
33.3%
H 1
33.3%
L 1
33.3%
Space Separator
ValueCountFrequency (%)
457
100.0%
Other Punctuation
ValueCountFrequency (%)
, 97
100.0%
Close Punctuation
ValueCountFrequency (%)
) 83
100.0%
Open Punctuation
ValueCountFrequency (%)
( 83
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 14
100.0%
Lowercase Letter
ValueCountFrequency (%)
e 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1394
54.1%
Common 1179
45.8%
Latin 4
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 225
16.1%
구 167
12.0%
로 89
 
6.4%
대 88
 
6.3%
광 84
 
6.0%
역 84
 
6.0%
시 83
 
6.0%
층 67
 
4.8%
신 47
 
3.4%
길 43
 
3.1%
Other values (88) 417
29.9%
Common
ValueCountFrequency (%)
457
38.8%
2 98
 
8.3%
, 97
 
8.2%
) 83
 
7.0%
( 83
 
7.0%
3 70
 
5.9%
1 69
 
5.9%
0 58
 
4.9%
4 41
 
3.5%
5 30
 
2.5%
Other values (5) 93
 
7.9%
Latin
ValueCountFrequency (%)
A 1
25.0%
e 1
25.0%
H 1
25.0%
L 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1394
54.1%
ASCII 1183
45.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
457
38.6%
2 98
 
8.3%
, 97
 
8.2%
) 83
 
7.0%
( 83
 
7.0%
3 70
 
5.9%
1 69
 
5.8%
0 58
 
4.9%
4 41
 
3.5%
5 30
 
2.5%
Other values (9) 97
 
8.2%
Hangul
ValueCountFrequency (%)
동 225
16.1%
구 167
12.0%
로 89
 
6.4%
대 88
 
6.3%
광 84
 
6.0%
역 84
 
6.0%
시 83
 
6.0%
층 67
 
4.8%
신 47
 
3.4%
길 43
 
3.1%
Other values (88) 417
29.9%

행정동명
Categorical

HIGH CORRELATION 

Distinct17
Distinct (%)20.5%
Missing0
Missing (%)0.0%
Memory size792.0 B
신천4동
23 
안심1동
15 
혁신동
8 
안심4동
6 
효목1동
5 
Other values (12)
26 

Length

Max length6
Median length4
Mean length3.8795181
Min length3

Unique

Unique4 ?
Unique (%)4.8%

Sample

1st row안심1동
2nd row안심3동
3rd row신천4동
4th row안심1동
5th row혁신동

Common Values

ValueCountFrequency (%)
신천4동 23
27.7%
안심1동 15
18.1%
혁신동 8
 
9.6%
안심4동 6
 
7.2%
효목1동 5
 
6.0%
신천3동 4
 
4.8%
방촌동 4
 
4.8%
신암4동 3
 
3.6%
효목2동 3
 
3.6%
해안동 2
 
2.4%
Other values (7) 10
12.0%

Length

2024-04-21T22:05:17.134137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
신천4동 23
27.7%
안심1동 15
18.1%
혁신동 8
 
9.6%
안심4동 6
 
7.2%
효목1동 5
 
6.0%
신천3동 4
 
4.8%
방촌동 4
 
4.8%
효목2동 3
 
3.6%
신암4동 3
 
3.6%
해안동 2
 
2.4%
Other values (7) 10
12.0%

법정동명
Categorical

HIGH CORRELATION 

Distinct15
Distinct (%)18.1%
Missing0
Missing (%)0.0%
Memory size792.0 B
신천동
29 
율하동
14 
효목동
8 
신서동
5 
각산동
5 
Other values (10)
22 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique6 ?
Unique (%)7.2%

Sample

1st row율하동
2nd row신서동
3rd row신천동
4th row율하동
5th row각산동

Common Values

ValueCountFrequency (%)
신천동 29
34.9%
율하동 14
16.9%
효목동 8
 
9.6%
신서동 5
 
6.0%
각산동 5
 
6.0%
방촌동 5
 
6.0%
동호동 5
 
6.0%
신암동 4
 
4.8%
용계동 2
 
2.4%
지저동 1
 
1.2%
Other values (5) 5
 
6.0%

Length

2024-04-21T22:05:17.338107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
신천동 29
34.9%
율하동 14
16.9%
효목동 8
 
9.6%
신서동 5
 
6.0%
각산동 5
 
6.0%
방촌동 5
 
6.0%
동호동 5
 
6.0%
신암동 4
 
4.8%
용계동 2
 
2.4%
지저동 1
 
1.2%
Other values (5) 5
 
6.0%

전화번호
Text

Distinct69
Distinct (%)83.1%
Missing0
Missing (%)0.0%
Memory size792.0 B
2024-04-21T22:05:18.125387image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters996
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

Unique68 ?
Unique (%)81.9%

Sample

1st row053-000-0000
2nd row053-964-4999
3rd row053-000-0000
4th row053-964-8917
5th row053-964-6651
ValueCountFrequency (%)
053-000-0000 15
 
18.1%
053-795-1197 1
 
1.2%
053-755-8901 1
 
1.2%
053-213-1700 1
 
1.2%
053-965-9802 1
 
1.2%
053-424-2821 1
 
1.2%
053-986-4000 1
 
1.2%
053-743-7511 1
 
1.2%
053-746-1061 1
 
1.2%
053-260-1100 1
 
1.2%
Other values (59) 59
71.1%
2024-04-21T22:05:19.399771image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 236
23.7%
- 166
16.7%
5 142
14.3%
3 116
11.6%
9 60
 
6.0%
1 51
 
5.1%
6 46
 
4.6%
8 46
 
4.6%
7 45
 
4.5%
4 44
 
4.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 830
83.3%
Dash Punctuation 166
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 236
28.4%
5 142
17.1%
3 116
14.0%
9 60
 
7.2%
1 51
 
6.1%
6 46
 
5.5%
8 46
 
5.5%
7 45
 
5.4%
4 44
 
5.3%
2 44
 
5.3%
Dash Punctuation
ValueCountFrequency (%)
- 166
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 996
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 236
23.7%
- 166
16.7%
5 142
14.3%
3 116
11.6%
9 60
 
6.0%
1 51
 
5.1%
6 46
 
4.6%
8 46
 
4.6%
7 45
 
4.5%
4 44
 
4.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 996
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 236
23.7%
- 166
16.7%
5 142
14.3%
3 116
11.6%
9 60
 
6.0%
1 51
 
5.1%
6 46
 
4.6%
8 46
 
4.6%
7 45
 
4.5%
4 44
 
4.4%

위도
Real number (ℝ)

HIGH CORRELATION 

Distinct67
Distinct (%)80.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.874626
Minimum35.862188
Maximum35.916111
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size875.0 B
2024-04-21T22:05:19.826513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.862188
5-th percentile35.864297
Q135.868971
median35.873969
Q335.878011
95-th percentile35.885193
Maximum35.916111
Range0.05392365
Interquartile range (IQR)0.009040085

Descriptive statistics

Standard deviation0.0080275348
Coefficient of variation (CV)0.00022376637
Kurtosis7.9614202
Mean35.874626
Median Absolute Deviation (MAD)0.004145
Skewness1.9263693
Sum2977.5939
Variance6.4441316 × 10-5
MonotonicityNot monotonic
2024-04-21T22:05:20.275366image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35.87416745 5
 
6.0%
35.88375842 4
 
4.8%
35.87763365 2
 
2.4%
35.86429705 2
 
2.4%
35.86439497 2
 
2.4%
35.87244762 2
 
2.4%
35.87376159 2
 
2.4%
35.86869749 2
 
2.4%
35.87747745 2
 
2.4%
35.87229477 2
 
2.4%
Other values (57) 58
69.9%
ValueCountFrequency (%)
35.86218785 1
1.2%
35.86302221 1
1.2%
35.86358508 1
1.2%
35.86403993 1
1.2%
35.86429705 2
2.4%
35.86439497 2
2.4%
35.86593987 1
1.2%
35.86621757 1
1.2%
35.86656739 1
1.2%
35.86726095 1
1.2%
ValueCountFrequency (%)
35.9161115 1
 
1.2%
35.89706819 1
 
1.2%
35.8902797 1
 
1.2%
35.88551183 1
 
1.2%
35.88533065 1
 
1.2%
35.88395761 1
 
1.2%
35.88375842 4
4.8%
35.8831231 1
 
1.2%
35.8821325 1
 
1.2%
35.88190565 1
 
1.2%

경도
Real number (ℝ)

HIGH CORRELATION 

Distinct67
Distinct (%)80.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean128.66423
Minimum128.61305
Maximum128.74879
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size875.0 B
2024-04-21T22:05:20.694863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum128.61305
5-th percentile128.62341
Q1128.62768
median128.64216
Q3128.70096
95-th percentile128.73122
Maximum128.74879
Range0.1357436
Interquartile range (IQR)0.07327675

Descriptive statistics

Standard deviation0.039584333
Coefficient of variation (CV)0.00030765608
Kurtosis-1.4165008
Mean128.66423
Median Absolute Deviation (MAD)0.0218395
Skewness0.41345298
Sum10679.131
Variance0.0015669194
MonotonicityNot monotonic
2024-04-21T22:05:21.357960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
128.6264383 5
 
6.0%
128.6365262 4
 
4.8%
128.6639977 2
 
2.4%
128.6906049 2
 
2.4%
128.7333135 2
 
2.4%
128.6261146 2
 
2.4%
128.6264904 2
 
2.4%
128.6964899 2
 
2.4%
128.6311822 2
 
2.4%
128.7146937 2
 
2.4%
Other values (57) 58
69.9%
ValueCountFrequency (%)
128.6130497 1
 
1.2%
128.6164854 1
 
1.2%
128.6193771 1
 
1.2%
128.6219126 1
 
1.2%
128.6233197 1
 
1.2%
128.6242318 1
 
1.2%
128.6258282 1
 
1.2%
128.6261146 2
 
2.4%
128.6264367 2
 
2.4%
128.6264383 5
6.0%
ValueCountFrequency (%)
128.7487933 1
1.2%
128.7333135 2
2.4%
128.7320094 1
1.2%
128.7319164 1
1.2%
128.7249452 1
1.2%
128.7200847 1
1.2%
128.7176026 1
1.2%
128.7146937 2
2.4%
128.714367 1
1.2%
128.713856 1
1.2%

데이터기준일
Categorical

CONSTANT 

Distinct1
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size792.0 B
2022-08-22
83 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2022-08-22
2nd row2022-08-22
3rd row2022-08-22
4th row2022-08-22
5th row2022-08-22

Common Values

ValueCountFrequency (%)
2022-08-22 83
100.0%

Length

2024-04-21T22:05:21.762475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T22:05:22.065461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022-08-22 83
100.0%

Interactions

2024-04-21T22:05:11.577629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T22:05:11.283698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T22:05:11.726489image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T22:05:11.427437image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-04-21T22:05:22.254151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
영업소명도로명주소행정동명법정동명전화번호위도경도
영업소명1.0001.0001.0001.0001.0001.0001.000
도로명주소1.0001.0001.0001.0001.0001.0001.000
행정동명1.0001.0001.0000.9740.9180.9570.900
법정동명1.0001.0000.9741.0000.5310.9390.960
전화번호1.0001.0000.9180.5311.0000.9120.000
위도1.0001.0000.9570.9390.9121.0000.511
경도1.0001.0000.9000.9600.0000.5111.000
2024-04-21T22:05:22.526717image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
행정동명법정동명
행정동명1.0000.819
법정동명0.8191.000
2024-04-21T22:05:22.761826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도행정동명법정동명
위도1.000-0.1880.7700.737
경도-0.1881.0000.6140.749
행정동명0.7700.6141.0000.819
법정동명0.7370.7490.8191.000

Missing values

2024-04-21T22:05:11.932179image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-04-21T22:05:12.164121image/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

영업종영업소명도로명주소행정동명법정동명전화번호위도경도데이터기준일
0일반종합도매대주팜대구광역시 동구 율하동로17길 20-1, 1층 (율하동)안심1동율하동053-000-000035.868367128.6990122022-08-22
1일반종합도매일일약품대구광역시 동구 금강로16길 47, 2층 (신서동)안심3동신서동053-964-499935.864395128.7333142022-08-22
2일반종합도매주식회사 대용대구광역시 동구 동부로30길 69-13, 지상1층 (신천동)신천4동신천동053-000-000035.871022128.6297692022-08-22
3일반종합도매에스비파마대구광역시 동구 율하서로 40, 4층 402호 (율하동)안심1동율하동053-964-891735.86594128.6917492022-08-22
4일반종합도매비엠팜대구광역시 동구 과학로17길 5, 1층 (각산동)혁신동각산동053-964-665135.885512128.7200852022-08-22
5일반종합도매랜드메디대구광역시 동구 아양로 218, 301동 2층 209호 (효목동, 진로이스트타운)효목1동효목동053-719-011935.883758128.6365262022-08-22
6일반종합도매주식회사 에스알팜대구광역시 동구 동부로 1, 102동 상가203호 (신천동, 신천LH)신천1.2동신천동053-256-666235.874183128.613052022-08-22
7일반종합도매(주)에센비메디대구광역시 동구 동부로30길 100-5, 5층 (신천동)신천4동신천동053-745-918035.86801128.6284052022-08-22
8일반종합도매참좋은약품대구광역시 동구 경안로 848, 2층 203호 (각산동)혁신동각산동053-965-532235.877831128.7143672022-08-22
9일반종합도매라이노팜대구광역시 동구 율하동로15길 13, 1층 (율하동)안심1동율하동053-741-919235.867261128.7001762022-08-22
영업종영업소명도로명주소행정동명법정동명전화번호위도경도데이터기준일
73일반종합도매건웅메딕스대구광역시 동구 화랑로 365, 4층 (방촌동)방촌동방촌동053-984-088135.877634128.6639982022-08-22
74일반종합도매에스지팜대구광역시 동구 효목로 56, 4층 (효목동)효목2동효목동053-743-031135.878049128.64072022-08-22
75일반종합도매㈜금강메디칼대구광역시 동구 첨단로8길 15, 3층 306호 (신서동)혁신동신서동053-961-980535.879094128.7320092022-08-22
76일반종합도매㈜영남지오영대구지점대구광역시 동구 팔공로37길 42, A동 2층 (불로동)불로.봉무동불로동053-984-555535.916111128.6390022022-08-22
77일반종합도매두산약품대구광역시 동구 동대구로 425, 2층 (신천동)신천3동신천동053-751-467035.86842128.6258282022-08-22
78일반종합도매우림약품대구광역시 동구 송라로 52 (신천동)신천3동신천동053-744-883135.871861128.6193772022-08-22
79일반종합도매㈜동보약품대구광역시 동구 동부로22길 28 (신천동)신천4동신천동053-755-444435.874167128.6264382022-08-22
80일반종합도매㈜효성약품대구광역시 동구 화랑로 205 (효목동)효목1동효목동053-955-890035.877922128.6475432022-08-22
81일반종합도매㈜부림약품대구광역시 동구 반야월로 239, 3층 (동호동)안심4동동호동053-757-450035.872295128.7146942022-08-22
82일반종합도매(주)신라약품대구광역시 동구 동부로26길 33, 1,4,5층 (신천동)신천4동신천동053-754-444435.872834128.6280112022-08-22