Overview

Dataset statistics

Number of variables11
Number of observations513
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory45.7 KiB
Average record size in memory91.3 B

Variable types

Numeric2
Categorical6
Text3

Alerts

자료출처 has constant value ""Constant
공개여부 has constant value ""Constant
작성일 has constant value ""Constant
갱신주기 has constant value ""Constant
순번 is highly overall correlated with 시군명 and 1 other fieldsHigh correlation
우편번호 is highly overall correlated with 시군명High correlation
시군명 is highly overall correlated with 순번 and 1 other fieldsHigh correlation
병원구분 is highly overall correlated with 순번High correlation
병원구분 is highly imbalanced (71.9%)Imbalance
순번 has unique valuesUnique

Reproduction

Analysis started2024-03-14 01:18:59.469232
Analysis finished2024-03-14 01:19:00.397495
Duration0.93 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

순번
Real number (ℝ)

HIGH CORRELATION  UNIQUE 

Distinct513
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean257
Minimum1
Maximum513
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.6 KiB
2024-03-14T10:19:00.461253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile26.6
Q1129
median257
Q3385
95-th percentile487.4
Maximum513
Range512
Interquartile range (IQR)256

Descriptive statistics

Standard deviation148.23461
Coefficient of variation (CV)0.57678837
Kurtosis-1.2
Mean257
Median Absolute Deviation (MAD)128
Skewness0
Sum131841
Variance21973.5
MonotonicityStrictly increasing
2024-03-14T10:19:00.604720image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.2%
386 1
 
0.2%
352 1
 
0.2%
351 1
 
0.2%
350 1
 
0.2%
349 1
 
0.2%
348 1
 
0.2%
347 1
 
0.2%
346 1
 
0.2%
345 1
 
0.2%
Other values (503) 503
98.1%
ValueCountFrequency (%)
1 1
0.2%
2 1
0.2%
3 1
0.2%
4 1
0.2%
5 1
0.2%
6 1
0.2%
7 1
0.2%
8 1
0.2%
9 1
0.2%
10 1
0.2%
ValueCountFrequency (%)
513 1
0.2%
512 1
0.2%
511 1
0.2%
510 1
0.2%
509 1
0.2%
508 1
0.2%
507 1
0.2%
506 1
0.2%
505 1
0.2%
504 1
0.2%

시군명
Categorical

HIGH CORRELATION 

Distinct14
Distinct (%)2.7%
Missing0
Missing (%)0.0%
Memory size4.1 KiB
전주시
204 
익산시
82 
군산시
78 
정읍시
29 
김제시
23 
Other values (9)
97 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
전주시 204
39.8%
익산시 82
16.0%
군산시 78
 
15.2%
정읍시 29
 
5.7%
김제시 23
 
4.5%
남원시 20
 
3.9%
부안군 18
 
3.5%
완주군 16
 
3.1%
임실군 12
 
2.3%
고창군 10
 
1.9%
Other values (4) 21
 
4.1%

Length

2024-03-14T10:19:00.707440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
전주시 204
39.8%
익산시 82
16.0%
군산시 78
 
15.2%
정읍시 29
 
5.7%
김제시 23
 
4.5%
남원시 20
 
3.9%
부안군 18
 
3.5%
완주군 16
 
3.1%
임실군 12
 
2.3%
고창군 10
 
1.9%
Other values (4) 21
 
4.1%

병원명
Text

Distinct422
Distinct (%)82.3%
Missing0
Missing (%)0.0%
Memory size4.1 KiB
2024-03-14T10:19:00.893743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length5
Mean length5.8460039
Min length4

Characters and Unicode

Total characters2999
Distinct characters251
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

Unique364 ?
Unique (%)71.0%

Sample

1st row소망한의원
2nd row이재성한의원
3rd row다래한의원
4th row호랑이한의원
5th row서동한의원
ValueCountFrequency (%)
원광한의원 11
 
2.1%
경희한의원 7
 
1.4%
약손한의원 5
 
1.0%
제일한의원 5
 
1.0%
현대한의원 4
 
0.8%
신농씨한의원 4
 
0.8%
으뜸한의원 4
 
0.8%
중앙한의원 4
 
0.8%
우리한의원 3
 
0.6%
삼성한의원 3
 
0.6%
Other values (412) 463
90.3%
2024-03-14T10:19:01.227783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
원 548
18.3%
한 523
17.4%
의 503
16.8%
당 42
 
1.4%
산 30
 
1.0%
성 30
 
1.0%
인 29
 
1.0%
부 28
 
0.9%
방 27
 
0.9%
병 26
 
0.9%
Other values (241) 1213
40.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2994
99.8%
Decimal Number 3
 
0.1%
Open Punctuation 1
 
< 0.1%
Close Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
원 548
18.3%
한 523
17.5%
의 503
16.8%
당 42
 
1.4%
산 30
 
1.0%
성 30
 
1.0%
인 29
 
1.0%
부 28
 
0.9%
방 27
 
0.9%
병 26
 
0.9%
Other values (236) 1208
40.3%
Decimal Number
ValueCountFrequency (%)
8 1
33.3%
1 1
33.3%
2 1
33.3%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2994
99.8%
Common 5
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
원 548
18.3%
한 523
17.5%
의 503
16.8%
당 42
 
1.4%
산 30
 
1.0%
성 30
 
1.0%
인 29
 
1.0%
부 28
 
0.9%
방 27
 
0.9%
병 26
 
0.9%
Other values (236) 1208
40.3%
Common
ValueCountFrequency (%)
8 1
20.0%
1 1
20.0%
2 1
20.0%
( 1
20.0%
) 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2994
99.8%
ASCII 5
 
0.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
원 548
18.3%
한 523
17.5%
의 503
16.8%
당 42
 
1.4%
산 30
 
1.0%
성 30
 
1.0%
인 29
 
1.0%
부 28
 
0.9%
방 27
 
0.9%
병 26
 
0.9%
Other values (236) 1208
40.3%
ASCII
ValueCountFrequency (%)
8 1
20.0%
1 1
20.0%
2 1
20.0%
( 1
20.0%
) 1
20.0%

병원구분
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.1 KiB
한의원
488 
한방병원
 
25

Length

Max length4
Median length3
Mean length3.0487329
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
한의원 488
95.1%
한방병원 25
 
4.9%

Length

2024-03-14T10:19:01.335102image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T10:19:01.405216image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
한의원 488
95.1%
한방병원 25
 
4.9%

도로명주소
Text

Distinct510
Distinct (%)99.4%
Missing0
Missing (%)0.0%
Memory size4.1 KiB
2024-03-14T10:19:01.724083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length30
Median length24
Mean length18.814815
Min length10

Characters and Unicode

Total characters9652
Distinct characters220
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique507 ?
Unique (%)98.8%

Sample

1st row익산시 동천로7길 51
2nd row익산시 고현로 101 (모현동1가)
3rd row익산시 고현로 93
4th row익산시 마한로5길 33
5th row익산시 무왕로 1103
ValueCountFrequency (%)
전주시 204
 
9.1%
완산구 127
 
5.7%
익산시 82
 
3.7%
군산시 78
 
3.5%
덕진구 77
 
3.4%
정읍시 29
 
1.3%
김제시 23
 
1.0%
부안읍 22
 
1.0%
나운동 21
 
0.9%
중앙로 21
 
0.9%
Other values (700) 1559
69.5%
2024-03-14T10:19:02.309479image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1730
 
17.9%
로 445
 
4.6%
시 444
 
4.6%
( 384
 
4.0%
) 384
 
4.0%
1 362
 
3.8%
산 359
 
3.7%
동 332
 
3.4%
2 244
 
2.5%
주 240
 
2.5%
Other values (210) 4728
49.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5531
57.3%
Space Separator 1730
 
17.9%
Decimal Number 1554
 
16.1%
Open Punctuation 384
 
4.0%
Close Punctuation 384
 
4.0%
Dash Punctuation 61
 
0.6%
Other Punctuation 8
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
로 445
 
8.0%
시 444
 
8.0%
산 359
 
6.5%
동 332
 
6.0%
주 240
 
4.3%
전 222
 
4.0%
구 221
 
4.0%
군 158
 
2.9%
완 144
 
2.6%
읍 139
 
2.5%
Other values (194) 2827
51.1%
Decimal Number
ValueCountFrequency (%)
1 362
23.3%
2 244
15.7%
3 158
10.2%
4 144
 
9.3%
5 126
 
8.1%
6 122
 
7.9%
8 108
 
6.9%
0 104
 
6.7%
7 100
 
6.4%
9 86
 
5.5%
Other Punctuation
ValueCountFrequency (%)
. 4
50.0%
, 4
50.0%
Space Separator
ValueCountFrequency (%)
1730
100.0%
Open Punctuation
ValueCountFrequency (%)
( 384
100.0%
Close Punctuation
ValueCountFrequency (%)
) 384
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 61
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5531
57.3%
Common 4121
42.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
로 445
 
8.0%
시 444
 
8.0%
산 359
 
6.5%
동 332
 
6.0%
주 240
 
4.3%
전 222
 
4.0%
구 221
 
4.0%
군 158
 
2.9%
완 144
 
2.6%
읍 139
 
2.5%
Other values (194) 2827
51.1%
Common
ValueCountFrequency (%)
1730
42.0%
( 384
 
9.3%
) 384
 
9.3%
1 362
 
8.8%
2 244
 
5.9%
3 158
 
3.8%
4 144
 
3.5%
5 126
 
3.1%
6 122
 
3.0%
8 108
 
2.6%
Other values (6) 359
 
8.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5531
57.3%
ASCII 4121
42.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1730
42.0%
( 384
 
9.3%
) 384
 
9.3%
1 362
 
8.8%
2 244
 
5.9%
3 158
 
3.8%
4 144
 
3.5%
5 126
 
3.1%
6 122
 
3.0%
8 108
 
2.6%
Other values (6) 359
 
8.7%
Hangul
ValueCountFrequency (%)
로 445
 
8.0%
시 444
 
8.0%
산 359
 
6.5%
동 332
 
6.0%
주 240
 
4.3%
전 222
 
4.0%
구 221
 
4.0%
군 158
 
2.9%
완 144
 
2.6%
읍 139
 
2.5%
Other values (194) 2827
51.1%

전화번호
Text

Distinct512
Distinct (%)99.8%
Missing0
Missing (%)0.0%
Memory size4.1 KiB
2024-03-14T10:19:02.503400image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length12
Mean length12.021442
Min length12

Characters and Unicode

Total characters6167
Distinct characters14
Distinct categories5 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique511 ?
Unique (%)99.6%

Sample

1st row063-856-7975
2nd row063-858-9900
3rd row063-843-1075
4th row063-858-3700
5th row063-839-3000
ValueCountFrequency (%)
063-644-1616 2
 
0.4%
063-856-7975 1
 
0.2%
063-324-9111 1
 
0.2%
063-272-7008 1
 
0.2%
063-277-8096 1
 
0.2%
063-253-9300 1
 
0.2%
063-227-2665 1
 
0.2%
063-231-1025 1
 
0.2%
063-212-5747 1
 
0.2%
063-229-5880 1
 
0.2%
Other values (502) 502
97.9%
2024-03-14T10:19:02.818965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 1028
16.7%
0 882
14.3%
3 840
13.6%
6 793
12.9%
5 559
9.1%
2 526
8.5%
7 410
 
6.6%
1 343
 
5.6%
8 331
 
5.4%
4 318
 
5.2%
Other values (4) 137
 
2.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 5135
83.3%
Dash Punctuation 1028
 
16.7%
Other Punctuation 2
 
< 0.1%
Open Punctuation 1
 
< 0.1%
Close Punctuation 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 882
17.2%
3 840
16.4%
6 793
15.4%
5 559
10.9%
2 526
10.2%
7 410
8.0%
1 343
 
6.7%
8 331
 
6.4%
4 318
 
6.2%
9 133
 
2.6%
Dash Punctuation
ValueCountFrequency (%)
- 1028
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 6167
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 1028
16.7%
0 882
14.3%
3 840
13.6%
6 793
12.9%
5 559
9.1%
2 526
8.5%
7 410
 
6.6%
1 343
 
5.6%
8 331
 
5.4%
4 318
 
5.2%
Other values (4) 137
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6167
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 1028
16.7%
0 882
14.3%
3 840
13.6%
6 793
12.9%
5 559
9.1%
2 526
8.5%
7 410
 
6.6%
1 343
 
5.6%
8 331
 
5.4%
4 318
 
5.2%
Other values (4) 137
 
2.2%

우편번호
Real number (ℝ)

HIGH CORRELATION 

Distinct306
Distinct (%)59.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean54993.542
Minimum54010
Maximum56468
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size4.6 KiB
2024-03-14T10:19:02.935412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum54010
5-th percentile54081
Q154561
median54951
Q355134
95-th percentile56307.4
Maximum56468
Range2458
Interquartile range (IQR)573

Descriptive statistics

Standard deviation644.73749
Coefficient of variation (CV)0.011723876
Kurtosis-0.36051687
Mean54993.542
Median Absolute Deviation (MAD)375
Skewness0.55695828
Sum28211687
Variance415686.43
MonotonicityNot monotonic
2024-03-14T10:19:03.062906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
55043 7
 
1.4%
54950 6
 
1.2%
54139 6
 
1.2%
55008 6
 
1.2%
55088 6
 
1.2%
56315 6
 
1.2%
54132 5
 
1.0%
54946 5
 
1.0%
56163 5
 
1.0%
55122 5
 
1.0%
Other values (296) 456
88.9%
ValueCountFrequency (%)
54010 1
 
0.2%
54011 1
 
0.2%
54013 1
 
0.2%
54021 1
 
0.2%
54022 1
 
0.2%
54025 1
 
0.2%
54027 1
 
0.2%
54028 2
0.4%
54029 3
0.6%
54030 1
 
0.2%
ValueCountFrequency (%)
56468 1
 
0.2%
56436 2
0.4%
56432 4
0.8%
56415 1
 
0.2%
56410 1
 
0.2%
56402 1
 
0.2%
56346 1
 
0.2%
56342 1
 
0.2%
56337 1
 
0.2%
56326 2
0.4%

자료출처
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.1 KiB
보건의료과
513 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
보건의료과 513
100.0%

Length

2024-03-14T10:19:03.185466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T10:19:03.258194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
보건의료과 513
100.0%

공개여부
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.1 KiB
공개
513 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
공개 513
100.0%

Length

2024-03-14T10:19:03.329836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T10:19:03.404624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
공개 513
100.0%

작성일
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.1 KiB
2015.1
513 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2015.1
2nd row2015.1
3rd row2015.1
4th row2015.1
5th row2015.1

Common Values

ValueCountFrequency (%)
2015.1 513
100.0%

Length

2024-03-14T10:19:03.476988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T10:19:03.546093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2015.1 513
100.0%

갱신주기
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.1 KiB
1년
513 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1년
2nd row1년
3rd row1년
4th row1년
5th row1년

Common Values

ValueCountFrequency (%)
1년 513
100.0%

Length

2024-03-14T10:19:03.619513image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T10:19:03.686857image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1년 513
100.0%

Interactions

2024-03-14T10:19:00.062770image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T10:18:59.914499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T10:19:00.132115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T10:18:59.981243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-14T10:19:03.732193image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번시군명병원구분우편번호
순번1.0000.8700.8340.920
시군명0.8701.0000.0000.982
병원구분0.8340.0001.0000.100
우편번호0.9200.9820.1001.000
2024-03-14T10:19:03.812933image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군명병원구분
시군명1.0000.000
병원구분0.0001.000
2024-03-14T10:19:03.983609image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
순번우편번호시군명병원구분
순번1.0000.3000.5940.661
우편번호0.3001.0000.9180.077
시군명0.5940.9181.0000.000
병원구분0.6610.0770.0001.000

Missing values

2024-03-14T10:19:00.226929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T10:19:00.340268image/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

순번시군명병원명병원구분도로명주소전화번호우편번호자료출처공개여부작성일갱신주기
01익산시소망한의원한의원익산시 동천로7길 51063-856-797554610보건의료과공개2015.11년
12익산시이재성한의원한의원익산시 고현로 101 (모현동1가)063-858-990054659보건의료과공개2015.11년
23익산시다래한의원한의원익산시 고현로 93063-843-107554659보건의료과공개2015.11년
34익산시호랑이한의원한의원익산시 마한로5길 33063-858-370054540보건의료과공개2015.11년
45익산시서동한의원한의원익산시 무왕로 1103063-839-300054546보건의료과공개2015.11년
56익산시성원한의원한의원익산시 고봉로34길 29 (영등동)063-833-757754544보건의료과공개2015.11년
67익산시삼인당한의원한의원익산시 무왕로 1087 (영등동)063-830-000154546보건의료과공개2015.11년
78익산시재단법인원불교영등보화당한의원한의원익산시 무왕로 1058 (영등동)063-831-922854637보건의료과공개2015.11년
89익산시특별한한의원한의원익산시 무왕로 1030063-836-099054636보건의료과공개2015.11년
910익산시삼생한의원한의원익산시 고봉로24길 38 (영등동)063-854-555054643보건의료과공개2015.11년
순번시군명병원명병원구분도로명주소전화번호우편번호자료출처공개여부작성일갱신주기
503504전주시해피수한방병원한방병원전주시 덕진구 벚꽃로 48 (진북동)063-714-390054939보건의료과공개2015.11년
504505전주시덕진한방병원한방병원전주시 덕진구 와룡로 32-9 (송천동2가)063-225-107554832보건의료과공개2015.11년
505506전주시가람한방병원한방병원전주시 덕진구 송천1길 1063-286-107554838보건의료과공개2015.11년
506507전주시동의한방병원한방병원전주시 덕진구 백제대로 625 (금암동)063-231-270054899보건의료과공개2015.11년
507508전주시원광대한의대부속전주한방병원한방병원전주시 덕진구 가련산로 99 (덕진동2가)063-270-111454887보건의료과공개2015.11년
508509전주시전주수한방병원한방병원전주시 덕진구 안덕원로 378 (산정동)063-247-999955015보건의료과공개2015.11년
509510전주시누가한방병원한방병원전주시 덕진구 안덕원로 208 (인후동1가)063-252-911155008보건의료과공개2015.11년
510511전주시에덴한방병원한방병원전주시 완산구 백제대로 277 (중화산동2가)063-281-002254976보건의료과공개2015.11년
511512전주시지리산한방병원한방병원전주시 완산구 서신로 62063-279-090054950보건의료과공개2015.11년
512513전주시우석대부속전주한방병원한방병원전주시 완산구 어은로 46 (중화산동2가)063-220-830054987보건의료과공개2015.11년