Overview

Dataset statistics

Number of variables8
Number of observations94
Missing cells97
Missing cells (%)12.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.2 KiB
Average record size in memory67.4 B

Variable types

Text4
Categorical2
Numeric2

Dataset

Description전라북도 전주시 내 병원을 제공하며 사업장명, 인허가일자, 영업상황, 전화번호, 주소 등을 제공합니다.
Author전라북도
URLhttps://www.bigdatahub.go.kr/index.jeonbuk?startPage=1&menuCd=DOM_000000103007001000&pListTypeStr=&pId=15060746

Alerts

의료기관우편번호(도로명) has 5 (5.3%) missing valuesMissing
팩스번호 has 92 (97.9%) missing valuesMissing
의료기관명 has unique valuesUnique
병상수 has 2 (2.1%) zerosZeros

Reproduction

Analysis started2024-03-14 02:31:47.854251
Analysis finished2024-03-14 02:31:49.002223
Duration1.15 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

의료기관명
Text

UNIQUE 

Distinct94
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size884.0 B
2024-03-14T11:31:49.164524image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length20.5
Mean length8.1914894
Min length3

Characters and Unicode

Total characters770
Distinct characters153
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique94 ?
Unique (%)100.0%

Sample

1st row우리노인전문병원
2nd row전주샘물아동병원
3rd row온누리안과병원
4th row박종혁믿음병원
5th row전주문병원
ValueCountFrequency (%)
의료법인 4
 
3.6%
한빛의료소비자생활협동조합 2
 
1.8%
한사랑요양병원 1
 
0.9%
전주고려병원 1
 
0.9%
대자인병원 1
 
0.9%
성모요양병원 1
 
0.9%
의료법인계산재단문실버요양병원 1
 
0.9%
전주시노인복지병원 1
 
0.9%
한마음요양병원 1
 
0.9%
한국노인요양병원 1
 
0.9%
Other values (97) 97
87.4%
2024-03-14T11:31:49.615500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
원 96
 
12.5%
병 95
 
12.3%
양 34
 
4.4%
요 33
 
4.3%
한 31
 
4.0%
전 27
 
3.5%
의 24
 
3.1%
주 23
 
3.0%
방 22
 
2.9%
료 20
 
2.6%
Other values (143) 365
47.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 751
97.5%
Space Separator 17
 
2.2%
Decimal Number 2
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
원 96
 
12.8%
병 95
 
12.6%
양 34
 
4.5%
요 33
 
4.4%
한 31
 
4.1%
전 27
 
3.6%
의 24
 
3.2%
주 23
 
3.1%
방 22
 
2.9%
료 20
 
2.7%
Other values (140) 346
46.1%
Decimal Number
ValueCountFrequency (%)
1 1
50.0%
2 1
50.0%
Space Separator
ValueCountFrequency (%)
17
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 751
97.5%
Common 19
 
2.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
원 96
 
12.8%
병 95
 
12.6%
양 34
 
4.5%
요 33
 
4.4%
한 31
 
4.1%
전 27
 
3.6%
의 24
 
3.2%
주 23
 
3.1%
방 22
 
2.9%
료 20
 
2.7%
Other values (140) 346
46.1%
Common
ValueCountFrequency (%)
17
89.5%
1 1
 
5.3%
2 1
 
5.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 751
97.5%
ASCII 19
 
2.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
원 96
 
12.8%
병 95
 
12.6%
양 34
 
4.5%
요 33
 
4.4%
한 31
 
4.1%
전 27
 
3.6%
의 24
 
3.2%
주 23
 
3.1%
방 22
 
2.9%
료 20
 
2.7%
Other values (140) 346
46.1%
ASCII
ValueCountFrequency (%)
17
89.5%
1 1
 
5.3%
2 1
 
5.3%

개설자명
Categorical

Distinct29
Distinct (%)30.9%
Missing0
Missing (%)0.0%
Memory size884.0 B
김*****
14 
이*****
12 
최*****
11 
박*****
8 
정*****
7 
Other values (24)
42 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique14 ?
Unique (%)14.9%

Sample

1st row정*****
2nd row박*****
3rd row문*****
4th row박*****
5th row문*****

Common Values

ValueCountFrequency (%)
김***** 14
14.9%
이***** 12
12.8%
최***** 11
11.7%
박***** 8
 
8.5%
정***** 7
 
7.4%
문***** 4
 
4.3%
허***** 4
 
4.3%
안***** 3
 
3.2%
서***** 3
 
3.2%
조***** 3
 
3.2%
Other values (19) 25
26.6%

Length

2024-03-14T11:31:49.722415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
김 14
14.9%
이 12
12.8%
최 11
11.7%
박 8
 
8.5%
정 7
 
7.4%
문 4
 
4.3%
허 4
 
4.3%
안 3
 
3.2%
서 3
 
3.2%
조 3
 
3.2%
Other values (19) 25
26.6%

의료기관우편번호(도로명)
Real number (ℝ)

MISSING 

Distinct67
Distinct (%)75.3%
Missing5
Missing (%)5.3%
Infinite0
Infinite (%)0.0%
Mean54984.674
Minimum54810
Maximum55144
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size978.0 B
2024-03-14T11:31:49.816320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum54810
5-th percentile54835.8
Q154910
median54985
Q355071
95-th percentile55124.4
Maximum55144
Range334
Interquartile range (IQR)161

Descriptive statistics

Standard deviation93.092668
Coefficient of variation (CV)0.0016930657
Kurtosis-0.99709001
Mean54984.674
Median Absolute Deviation (MAD)80
Skewness-0.012647383
Sum4893636
Variance8666.2449
MonotonicityNot monotonic
2024-03-14T11:31:49.943628image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
54899 3
 
3.2%
54969 3
 
3.2%
54985 3
 
3.2%
54987 3
 
3.2%
54966 2
 
2.1%
55086 2
 
2.1%
55000 2
 
2.1%
55065 2
 
2.1%
54907 2
 
2.1%
54910 2
 
2.1%
Other values (57) 65
69.1%
(Missing) 5
 
5.3%
ValueCountFrequency (%)
54810 1
1.1%
54816 1
1.1%
54822 1
1.1%
54823 1
1.1%
54835 1
1.1%
54837 1
1.1%
54838 1
1.1%
54840 1
1.1%
54850 2
2.1%
54852 1
1.1%
ValueCountFrequency (%)
55144 1
1.1%
55135 1
1.1%
55134 1
1.1%
55132 1
1.1%
55126 1
1.1%
55122 2
2.1%
55121 1
1.1%
55120 1
1.1%
55119 1
1.1%
55114 1
1.1%

의료기관주소(도로명)
Text

Distinct93
Distinct (%)98.9%
Missing0
Missing (%)0.0%
Memory size884.0 B
2024-03-14T11:31:50.191555image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length53
Median length41
Mean length30.202128
Min length25

Characters and Unicode

Total characters2839
Distinct characters157
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique92 ?
Unique (%)97.9%

Sample

1st row전라북도 전주시 덕진구 정여립로 978 (만성동)
2nd row전라북도 전주시 완산구 세내로 285, 샘물아동병원 5층 (효자동3가)
3rd row전라북도 전주시 완산구 백제대로 325, 온누리안과 (중화산동2가)
4th row전라북도 전주시 완산구 홍산로 250-0 (효자동3가)
5th row전라북도 전주시 완산구 용머리로 106-0, 0동 (효자동1가,전주문병원)
ValueCountFrequency (%)
전라북도 94
 
16.1%
전주시 94
 
16.1%
완산구 57
 
9.8%
덕진구 37
 
6.3%
백제대로 13
 
2.2%
금암동 9
 
1.5%
중화산동2가 8
 
1.4%
효자동2가 7
 
1.2%
평화동1가 6
 
1.0%
장승배기로 5
 
0.9%
Other values (182) 253
43.4%
2024-03-14T11:31:50.584026image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
489
 
17.2%
전 197
 
6.9%
동 101
 
3.6%
주 100
 
3.5%
북 97
 
3.4%
구 97
 
3.4%
) 95
 
3.3%
( 95
 
3.3%
라 95
 
3.3%
도 94
 
3.3%
Other values (147) 1379
48.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1753
61.7%
Space Separator 489
 
17.2%
Decimal Number 365
 
12.9%
Close Punctuation 95
 
3.3%
Open Punctuation 95
 
3.3%
Other Punctuation 22
 
0.8%
Dash Punctuation 18
 
0.6%
Math Symbol 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
전 197
 
11.2%
동 101
 
5.8%
주 100
 
5.7%
북 97
 
5.5%
구 97
 
5.5%
라 95
 
5.4%
도 94
 
5.4%
시 94
 
5.4%
산 77
 
4.4%
로 76
 
4.3%
Other values (131) 725
41.4%
Decimal Number
ValueCountFrequency (%)
1 76
20.8%
2 68
18.6%
3 49
13.4%
0 40
11.0%
7 27
 
7.4%
6 25
 
6.8%
4 24
 
6.6%
5 23
 
6.3%
8 21
 
5.8%
9 12
 
3.3%
Space Separator
ValueCountFrequency (%)
489
100.0%
Close Punctuation
ValueCountFrequency (%)
) 95
100.0%
Open Punctuation
ValueCountFrequency (%)
( 95
100.0%
Other Punctuation
ValueCountFrequency (%)
, 22
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 18
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1753
61.7%
Common 1086
38.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
전 197
 
11.2%
동 101
 
5.8%
주 100
 
5.7%
북 97
 
5.5%
구 97
 
5.5%
라 95
 
5.4%
도 94
 
5.4%
시 94
 
5.4%
산 77
 
4.4%
로 76
 
4.3%
Other values (131) 725
41.4%
Common
ValueCountFrequency (%)
489
45.0%
) 95
 
8.7%
( 95
 
8.7%
1 76
 
7.0%
2 68
 
6.3%
3 49
 
4.5%
0 40
 
3.7%
7 27
 
2.5%
6 25
 
2.3%
4 24
 
2.2%
Other values (6) 98
 
9.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1753
61.7%
ASCII 1086
38.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
489
45.0%
) 95
 
8.7%
( 95
 
8.7%
1 76
 
7.0%
2 68
 
6.3%
3 49
 
4.5%
0 40
 
3.7%
7 27
 
2.5%
6 25
 
2.3%
4 24
 
2.2%
Other values (6) 98
 
9.0%
Hangul
ValueCountFrequency (%)
전 197
 
11.2%
동 101
 
5.8%
주 100
 
5.7%
북 97
 
5.5%
구 97
 
5.5%
라 95
 
5.4%
도 94
 
5.4%
시 94
 
5.4%
산 77
 
4.4%
로 76
 
4.3%
Other values (131) 725
41.4%

병상수
Real number (ℝ)

ZEROS 

Distinct76
Distinct (%)80.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean167.82979
Minimum0
Maximum1115
Zeros2
Zeros (%)2.1%
Negative0
Negative (%)0.0%
Memory size978.0 B
2024-03-14T11:31:50.704990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile38.95
Q172.25
median124.5
Q3207.5
95-th percentile357.2
Maximum1115
Range1115
Interquartile range (IQR)135.25

Descriptive statistics

Standard deviation163.64784
Coefficient of variation (CV)0.97508222
Kurtosis14.055867
Mean167.82979
Median Absolute Deviation (MAD)60.5
Skewness3.2344735
Sum15776
Variance26780.616
MonotonicityNot monotonic
2024-03-14T11:31:50.813500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
299 3
 
3.2%
287 3
 
3.2%
72 3
 
3.2%
128 3
 
3.2%
100 2
 
2.1%
0 2
 
2.1%
82 2
 
2.1%
78 2
 
2.1%
134 2
 
2.1%
191 2
 
2.1%
Other values (66) 70
74.5%
ValueCountFrequency (%)
0 2
2.1%
30 2
2.1%
37 1
1.1%
40 1
1.1%
43 1
1.1%
47 1
1.1%
50 1
1.1%
51 1
1.1%
54 1
1.1%
56 2
2.1%
ValueCountFrequency (%)
1115 1
 
1.1%
760 1
 
1.1%
750 1
 
1.1%
527 1
 
1.1%
404 1
 
1.1%
332 1
 
1.1%
330 1
 
1.1%
315 1
 
1.1%
299 3
3.2%
296 1
 
1.1%

전화번호
Text

Distinct93
Distinct (%)98.9%
Missing0
Missing (%)0.0%
Memory size884.0 B
2024-03-14T11:31:51.006962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.010638
Min length12

Characters and Unicode

Total characters1129
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

Unique92 ?
Unique (%)97.9%

Sample

1st row063-210-3600
2nd row063-230-7200
3rd row063-277-2774
4th row063-224-5100
5th row063-286-0000
ValueCountFrequency (%)
063-220-8300 2
 
2.1%
063-715-5119 1
 
1.1%
063-278-8288 1
 
1.1%
063-220-7200 1
 
1.1%
063-240-7300 1
 
1.1%
063-240-2000 1
 
1.1%
063-270-5003 1
 
1.1%
063-282-8833 1
 
1.1%
063-220-9700 1
 
1.1%
063-220-1111 1
 
1.1%
Other values (83) 83
88.3%
2024-03-14T11:31:51.322332image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 262
23.2%
- 188
16.7%
2 140
12.4%
3 135
12.0%
6 112
9.9%
1 82
 
7.3%
7 64
 
5.7%
8 47
 
4.2%
5 41
 
3.6%
4 37
 
3.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 941
83.3%
Dash Punctuation 188
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 262
27.8%
2 140
14.9%
3 135
14.3%
6 112
11.9%
1 82
 
8.7%
7 64
 
6.8%
8 47
 
5.0%
5 41
 
4.4%
4 37
 
3.9%
9 21
 
2.2%
Dash Punctuation
ValueCountFrequency (%)
- 188
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1129
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 262
23.2%
- 188
16.7%
2 140
12.4%
3 135
12.0%
6 112
9.9%
1 82
 
7.3%
7 64
 
5.7%
8 47
 
4.2%
5 41
 
3.6%
4 37
 
3.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1129
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 262
23.2%
- 188
16.7%
2 140
12.4%
3 135
12.0%
6 112
9.9%
1 82
 
7.3%
7 64
 
5.7%
8 47
 
4.2%
5 41
 
3.6%
4 37
 
3.3%

팩스번호
Text

MISSING 

Distinct2
Distinct (%)100.0%
Missing92
Missing (%)97.9%
Memory size884.0 B
2024-03-14T11:31:51.458813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters24
Distinct characters8
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

Unique2 ?
Unique (%)100.0%

Sample

1st row063-224-3550
2nd row063-288-3355
ValueCountFrequency (%)
063-224-3550 1
50.0%
063-288-3355 1
50.0%
2024-03-14T11:31:51.751787image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 5
20.8%
- 4
16.7%
5 4
16.7%
0 3
12.5%
2 3
12.5%
6 2
 
8.3%
8 2
 
8.3%
4 1
 
4.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 20
83.3%
Dash Punctuation 4
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 5
25.0%
5 4
20.0%
0 3
15.0%
2 3
15.0%
6 2
 
10.0%
8 2
 
10.0%
4 1
 
5.0%
Dash Punctuation
ValueCountFrequency (%)
- 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 24
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 5
20.8%
- 4
16.7%
5 4
16.7%
0 3
12.5%
2 3
12.5%
6 2
 
8.3%
8 2
 
8.3%
4 1
 
4.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 24
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 5
20.8%
- 4
16.7%
5 4
16.7%
0 3
12.5%
2 3
12.5%
6 2
 
8.3%
8 2
 
8.3%
4 1
 
4.2%

의료기관종별
Categorical

Distinct6
Distinct (%)6.4%
Missing0
Missing (%)0.0%
Memory size884.0 B
일반요양병원
34 
병원
30 
한방병원
22 
종합병원
5 
치과병원
 
2

Length

Max length6
Median length4
Mean length4.0851064
Min length2

Unique

Unique1 ?
Unique (%)1.1%

Sample

1st row노인병원
2nd row병원
3rd row병원
4th row병원
5th row병원

Common Values

ValueCountFrequency (%)
일반요양병원 34
36.2%
병원 30
31.9%
한방병원 22
23.4%
종합병원 5
 
5.3%
치과병원 2
 
2.1%
노인병원 1
 
1.1%

Length

2024-03-14T11:31:51.880840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T11:31:51.974223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반요양병원 34
36.2%
병원 30
31.9%
한방병원 22
23.4%
종합병원 5
 
5.3%
치과병원 2
 
2.1%
노인병원 1
 
1.1%

Interactions

2024-03-14T11:31:48.392987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T11:31:48.234310image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T11:31:48.465461image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T11:31:48.309963image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-14T11:31:52.039847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
의료기관명개설자명의료기관우편번호(도로명)의료기관주소(도로명)병상수전화번호팩스번호의료기관종별
의료기관명1.0001.0001.0001.0001.0001.0000.0001.000
개설자명1.0001.0000.3941.0000.5141.0000.0000.000
의료기관우편번호(도로명)1.0000.3941.0001.0000.3091.0000.0000.408
의료기관주소(도로명)1.0001.0001.0001.0001.0001.0000.0000.964
병상수1.0000.5140.3091.0001.0001.000NaN0.616
전화번호1.0001.0001.0001.0001.0001.0000.0000.964
팩스번호0.0000.0000.0000.000NaN0.0001.0000.000
의료기관종별1.0000.0000.4080.9640.6160.9640.0001.000
2024-03-14T11:31:52.135124image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
개설자명의료기관종별
개설자명1.0000.000
의료기관종별0.0001.000
2024-03-14T11:31:52.204942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
의료기관우편번호(도로명)병상수개설자명의료기관종별
의료기관우편번호(도로명)1.000-0.0390.1400.219
병상수-0.0391.0000.2010.424
개설자명0.1400.2011.0000.000
의료기관종별0.2190.4240.0001.000

Missing values

2024-03-14T11:31:48.549833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T11:31:48.647941image/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.
2024-03-14T11:31:48.965204image/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

의료기관명개설자명의료기관우편번호(도로명)의료기관주소(도로명)병상수전화번호팩스번호의료기관종별
0우리노인전문병원정*****54876전라북도 전주시 덕진구 정여립로 978 (만성동)166063-210-3600<NA>노인병원
1전주샘물아동병원박*****54969전라북도 전주시 완산구 세내로 285, 샘물아동병원 5층 (효자동3가)50063-230-7200063-224-3550병원
2온누리안과병원문*****54972전라북도 전주시 완산구 백제대로 325, 온누리안과 (중화산동2가)30063-277-2774<NA>병원
3박종혁믿음병원박*****54969전라북도 전주시 완산구 홍산로 250-0 (효자동3가)75063-224-5100<NA>병원
4전주문병원문*****55082전라북도 전주시 완산구 용머리로 106-0, 0동 (효자동1가,전주문병원)40063-286-0000<NA>병원
5전주다솔아동병원김*****54966전라북도 전주시 완산구 우전로 250, 2~4층 (효자동2가)72063-280-0800<NA>병원
6더세움병원양*****55019전라북도 전주시 덕진구 서가재미2길 7 (인후동1가)128063-243-9100<NA>병원
7의료법인영경의료재단호성전주병원이*****54902전라북도 전주시 덕진구 동부대로 895 (호성동1가)128063-240-8800<NA>병원
8유앤미 병원김*****54954전라북도 전주시 완산구 백제대로 361 (서신동)57063-279-1500<NA>병원
9전주신세계정형외과병원황*****54838전라북도 전주시 덕진구 송천중앙로 125 (송천동1가)51063-270-1900<NA>병원
의료기관명개설자명의료기관우편번호(도로명)의료기관주소(도로명)병상수전화번호팩스번호의료기관종별
84중경한방병원채*****55134전라북도 전주시 완산구 장승배기로 166 (평화동1가)61063-232-2626063-288-3355한방병원
85덕진한방병원양*****54835전라북도 전주시 덕진구 솔내로 131 (송천동1가)61063-225-1075<NA>한방병원
86솔한방병원이*****55102전라북도 전주시 완산구 팔달로 7 (서서학동)72063-714-2200<NA>한방병원
87가람한방병원허*****54837전라북도 전주시 덕진구 송천중앙로 60, 3~6층 (송천동1가)83063-270-8600<NA>한방병원
88명인한방병원안*****55086전라북도 전주시 완산구 용리로 42 (삼천동1가)57063-714-4848<NA>한방병원
89지리산한방병원권*****54950전라북도 전주시 완산구 서신로 62, 301호 (서신동, 지리산빌딩)79063-279-0900<NA>한방병원
90전주수한방병원임*****55015전라북도 전주시 덕진구 안덕원로 378 (산정동)115063-247-9999<NA>한방병원
91누가한방병원최*****55008전라북도 전주시 덕진구 안덕원로 218 (인후동1가)84063-252-9111<NA>한방병원
92우석대부속전주한방병원서*****54987전라북도 전주시 완산구 어은로 46 (중화산동2가)100063-220-8300<NA>한방병원
93원광대학교전주한방병원허*****54887전라북도 전주시 덕진구 가련산로 99 (덕진동2가)125063-270-1114<NA>한방병원