Overview

Dataset statistics

Number of variables16
Number of observations94
Missing cells4
Missing cells (%)0.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory12.4 KiB
Average record size in memory135.4 B

Variable types

Text5
DateTime1
Categorical4
Numeric6

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

상세영업상태명 has constant value ""Constant
데이터기준일자 has constant value ""Constant
업태구분명 is highly overall correlated with 의료기관종별명High correlation
의료기관종별명 is highly overall correlated with 업태구분명High correlation
의료인수 is highly overall correlated with 입원실수 and 1 other fieldsHigh correlation
입원실수 is highly overall correlated with 의료인수 and 2 other fieldsHigh correlation
병상수 is highly overall correlated with 입원실수 and 1 other fieldsHigh correlation
총면적 is highly overall correlated with 의료인수 and 2 other fieldsHigh correlation
총면적 has 1 (1.1%) missing valuesMissing
진료과목내용명 has 3 (3.2%) missing valuesMissing
사업장명 has unique valuesUnique
인허가일자 has unique valuesUnique
의료인수 has 6 (6.4%) zerosZeros
입원실수 has 2 (2.1%) zerosZeros
병상수 has 2 (2.1%) zerosZeros

Reproduction

Analysis started2024-03-14 02:31:36.010123
Analysis finished2024-03-14 02:31:40.304792
Duration4.29 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

사업장명
Text

UNIQUE 

Distinct94
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size884.0 B
2024-03-14T11:31:40.571917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length21
Mean length8.0319149
Min length3

Characters and Unicode

Total characters755
Distinct characters156
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 row가람한방병원
2nd row나은요양병원
3rd row누가한방병원
4th row다사랑병원
5th row다생한방병원
ValueCountFrequency (%)
의료법인 4
 
3.6%
한빛의료소비자생활협동조합 2
 
1.8%
전주다솔아동병원 1
 
0.9%
전주우석병원 1
 
0.9%
전주우리병원 1
 
0.9%
전주우리들병원 1
 
0.9%
전주열린병원 1
 
0.9%
전주신세계정형외과병원 1
 
0.9%
전주시립요양병원 1
 
0.9%
전주수한방병원 1
 
0.9%
Other values (96) 96
87.3%
2024-03-14T11:31:40.932015image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
원 96
 
12.7%
병 95
 
12.6%
양 35
 
4.6%
요 34
 
4.5%
한 30
 
4.0%
전 27
 
3.6%
주 24
 
3.2%
의 22
 
2.9%
방 21
 
2.8%
료 18
 
2.4%
Other values (146) 353
46.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 737
97.6%
Space Separator 16
 
2.1%
Decimal Number 2
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
원 96
 
13.0%
병 95
 
12.9%
양 35
 
4.7%
요 34
 
4.6%
한 30
 
4.1%
전 27
 
3.7%
주 24
 
3.3%
의 22
 
3.0%
방 21
 
2.8%
료 18
 
2.4%
Other values (143) 335
45.5%
Decimal Number
ValueCountFrequency (%)
1 1
50.0%
2 1
50.0%
Space Separator
ValueCountFrequency (%)
16
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 737
97.6%
Common 18
 
2.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
원 96
 
13.0%
병 95
 
12.9%
양 35
 
4.7%
요 34
 
4.6%
한 30
 
4.1%
전 27
 
3.7%
주 24
 
3.3%
의 22
 
3.0%
방 21
 
2.8%
료 18
 
2.4%
Other values (143) 335
45.5%
Common
ValueCountFrequency (%)
16
88.9%
1 1
 
5.6%
2 1
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 737
97.6%
ASCII 18
 
2.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
원 96
 
13.0%
병 95
 
12.9%
양 35
 
4.7%
요 34
 
4.6%
한 30
 
4.1%
전 27
 
3.7%
주 24
 
3.3%
의 22
 
3.0%
방 21
 
2.8%
료 18
 
2.4%
Other values (143) 335
45.5%
ASCII
ValueCountFrequency (%)
16
88.9%
1 1
 
5.6%
2 1
 
5.6%

인허가일자
Date

UNIQUE 

Distinct94
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size884.0 B
Minimum1974-05-09 00:00:00
Maximum2022-02-25 00:00:00
2024-03-14T11:31:41.047466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T11:31:41.151208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

상세영업상태명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size884.0 B
영업중
94 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업중 94
100.0%

Length

2024-03-14T11:31:41.260823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T11:31:41.330236image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업중 94
100.0%

소재지전화
Text

Distinct93
Distinct (%)98.9%
Missing0
Missing (%)0.0%
Memory size884.0 B
2024-03-14T11:31:41.500566image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters1128
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 row063-270-8600
2nd row063-715-2300
3rd row063-252-9111
4th row063-228-5540
5th row063-714-2000
ValueCountFrequency (%)
063-220-8300 2
 
2.1%
063-220-0600 1
 
1.1%
063-278-8008 1
 
1.1%
063-714-4001 1
 
1.1%
063-228-6002 1
 
1.1%
063-710-3130 1
 
1.1%
063-715-3700 1
 
1.1%
063-286-2233 1
 
1.1%
063-270-1900 1
 
1.1%
063-220-9700 1
 
1.1%
Other values (83) 83
88.3%
2024-03-14T11:31:41.778683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 260
23.0%
- 188
16.7%
2 145
12.9%
3 135
12.0%
6 112
9.9%
1 78
 
6.9%
7 64
 
5.7%
8 48
 
4.3%
5 42
 
3.7%
4 36
 
3.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 940
83.3%
Dash Punctuation 188
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 260
27.7%
2 145
15.4%
3 135
14.4%
6 112
11.9%
1 78
 
8.3%
7 64
 
6.8%
8 48
 
5.1%
5 42
 
4.5%
4 36
 
3.8%
9 20
 
2.1%
Dash Punctuation
ValueCountFrequency (%)
- 188
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1128
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 260
23.0%
- 188
16.7%
2 145
12.9%
3 135
12.0%
6 112
9.9%
1 78
 
6.9%
7 64
 
5.7%
8 48
 
4.3%
5 42
 
3.7%
4 36
 
3.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1128
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 260
23.0%
- 188
16.7%
2 145
12.9%
3 135
12.0%
6 112
9.9%
1 78
 
6.9%
7 64
 
5.7%
8 48
 
4.3%
5 42
 
3.7%
4 36
 
3.2%

도로명주소
Text

Distinct93
Distinct (%)98.9%
Missing0
Missing (%)0.0%
Memory size884.0 B
2024-03-14T11:31:42.125734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length53
Median length39
Mean length30.180851
Min length25

Characters and Unicode

Total characters2837
Distinct characters158
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 송천중앙로 60, 3~6층 (송천동1가)
2nd row전라북도 전주시 덕진구 기린대로 951 (여의동)
3rd row전라북도 전주시 덕진구 안덕원로 218 (인후동1가)
4th row전라북도 전주시 완산구 백제대로 74 (삼천동1가)
5th row전라북도 전주시 덕진구 벚꽃로 48, 0동 (진북동,참조은병원)
ValueCountFrequency (%)
전라북도 94
 
16.1%
전주시 94
 
16.1%
완산구 58
 
9.9%
덕진구 36
 
6.2%
백제대로 13
 
2.2%
중화산동2가 9
 
1.5%
금암동 8
 
1.4%
효자동2가 7
 
1.2%
평화동1가 6
 
1.0%
장승배기로 5
 
0.9%
Other values (182) 255
43.6%
2024-03-14T11:31:42.555192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
491
 
17.3%
전 199
 
7.0%
동 102
 
3.6%
주 101
 
3.6%
북 97
 
3.4%
구 97
 
3.4%
라 95
 
3.3%
) 95
 
3.3%
( 95
 
3.3%
도 94
 
3.3%
Other values (148) 1371
48.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1763
62.1%
Space Separator 491
 
17.3%
Decimal Number 357
 
12.6%
Close Punctuation 95
 
3.3%
Open Punctuation 95
 
3.3%
Other Punctuation 26
 
0.9%
Dash Punctuation 8
 
0.3%
Math Symbol 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
전 199
 
11.3%
동 102
 
5.8%
주 101
 
5.7%
북 97
 
5.5%
구 97
 
5.5%
라 95
 
5.4%
도 94
 
5.3%
시 94
 
5.3%
산 79
 
4.5%
로 77
 
4.4%
Other values (132) 728
41.3%
Decimal Number
ValueCountFrequency (%)
1 79
22.1%
2 69
19.3%
3 46
12.9%
0 30
 
8.4%
7 27
 
7.6%
4 25
 
7.0%
6 24
 
6.7%
5 24
 
6.7%
8 21
 
5.9%
9 12
 
3.4%
Space Separator
ValueCountFrequency (%)
491
100.0%
Close Punctuation
ValueCountFrequency (%)
) 95
100.0%
Open Punctuation
ValueCountFrequency (%)
( 95
100.0%
Other Punctuation
ValueCountFrequency (%)
, 26
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 8
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1763
62.1%
Common 1074
37.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
전 199
 
11.3%
동 102
 
5.8%
주 101
 
5.7%
북 97
 
5.5%
구 97
 
5.5%
라 95
 
5.4%
도 94
 
5.3%
시 94
 
5.3%
산 79
 
4.5%
로 77
 
4.4%
Other values (132) 728
41.3%
Common
ValueCountFrequency (%)
491
45.7%
) 95
 
8.8%
( 95
 
8.8%
1 79
 
7.4%
2 69
 
6.4%
3 46
 
4.3%
0 30
 
2.8%
7 27
 
2.5%
, 26
 
2.4%
4 25
 
2.3%
Other values (6) 91
 
8.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1763
62.1%
ASCII 1074
37.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
491
45.7%
) 95
 
8.8%
( 95
 
8.8%
1 79
 
7.4%
2 69
 
6.4%
3 46
 
4.3%
0 30
 
2.8%
7 27
 
2.5%
, 26
 
2.4%
4 25
 
2.3%
Other values (6) 91
 
8.5%
Hangul
ValueCountFrequency (%)
전 199
 
11.3%
동 102
 
5.8%
주 101
 
5.7%
북 97
 
5.5%
구 97
 
5.5%
라 95
 
5.4%
도 94
 
5.3%
시 94
 
5.3%
산 79
 
4.5%
로 77
 
4.4%
Other values (132) 728
41.3%

지번주소
Text

Distinct92
Distinct (%)97.9%
Missing0
Missing (%)0.0%
Memory size884.0 B
2024-03-14T11:31:43.129121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length26
Median length25
Mean length23.723404
Min length20

Characters and Unicode

Total characters2230
Distinct characters55
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique90 ?
Unique (%)95.7%

Sample

1st row전라북도 전주시 덕진구 송천동1가 270-1
2nd row전라북도 전주시 덕진구 여의동 558-4
3rd row전라북도 전주시 덕진구 인후동1가 594-14
4th row전라북도 전주시 완산구 삼천동1가 732-3
5th row전라북도 전주시 덕진구 진북동 1021-2
ValueCountFrequency (%)
전라북도 94
19.9%
전주시 94
19.9%
완산구 58
 
12.3%
덕진구 36
 
7.6%
중화산동2가 9
 
1.9%
효자동2가 7
 
1.5%
평화동1가 6
 
1.3%
금암동 6
 
1.3%
삼천동1가 5
 
1.1%
효자동1가 5
 
1.1%
Other values (120) 152
32.2%
2024-03-14T11:31:43.498919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
378
17.0%
전 188
 
8.4%
1 106
 
4.8%
북 96
 
4.3%
라 94
 
4.2%
동 94
 
4.2%
구 94
 
4.2%
시 94
 
4.2%
주 94
 
4.2%
도 94
 
4.2%
Other values (45) 898
40.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1316
59.0%
Decimal Number 458
 
20.5%
Space Separator 378
 
17.0%
Dash Punctuation 78
 
3.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
전 188
14.3%
북 96
 
7.3%
라 94
 
7.1%
동 94
 
7.1%
구 94
 
7.1%
시 94
 
7.1%
주 94
 
7.1%
도 94
 
7.1%
산 77
 
5.9%
가 72
 
5.5%
Other values (33) 319
24.2%
Decimal Number
ValueCountFrequency (%)
1 106
23.1%
2 83
18.1%
5 45
9.8%
3 41
 
9.0%
4 39
 
8.5%
8 35
 
7.6%
7 33
 
7.2%
9 32
 
7.0%
6 25
 
5.5%
0 19
 
4.1%
Space Separator
ValueCountFrequency (%)
378
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 78
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1316
59.0%
Common 914
41.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
전 188
14.3%
북 96
 
7.3%
라 94
 
7.1%
동 94
 
7.1%
구 94
 
7.1%
시 94
 
7.1%
주 94
 
7.1%
도 94
 
7.1%
산 77
 
5.9%
가 72
 
5.5%
Other values (33) 319
24.2%
Common
ValueCountFrequency (%)
378
41.4%
1 106
 
11.6%
2 83
 
9.1%
- 78
 
8.5%
5 45
 
4.9%
3 41
 
4.5%
4 39
 
4.3%
8 35
 
3.8%
7 33
 
3.6%
9 32
 
3.5%
Other values (2) 44
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1315
59.0%
ASCII 914
41.0%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
378
41.4%
1 106
 
11.6%
2 83
 
9.1%
- 78
 
8.5%
5 45
 
4.9%
3 41
 
4.5%
4 39
 
4.3%
8 35
 
3.8%
7 33
 
3.6%
9 32
 
3.5%
Other values (2) 44
 
4.8%
Hangul
ValueCountFrequency (%)
전 188
14.3%
북 96
 
7.3%
라 94
 
7.1%
동 94
 
7.1%
구 94
 
7.1%
시 94
 
7.1%
주 94
 
7.1%
도 94
 
7.1%
산 77
 
5.9%
가 72
 
5.5%
Other values (32) 318
24.2%
Compat Jamo
ValueCountFrequency (%)
ㅂ 1
100.0%

위도
Real number (ℝ)

Distinct92
Distinct (%)97.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.823826
Minimum35.767077
Maximum35.873456
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size978.0 B
2024-03-14T11:31:43.617501image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.767077
5-th percentile35.793092
Q135.805536
median35.819066
Q335.839898
95-th percentile35.865805
Maximum35.873456
Range0.10637892
Interquartile range (IQR)0.034362655

Descriptive statistics

Standard deviation0.023033312
Coefficient of variation (CV)0.0006429607
Kurtosis-0.45782191
Mean35.823826
Median Absolute Deviation (MAD)0.016289325
Skewness0.33492355
Sum3367.4397
Variance0.00053053347
MonotonicityNot monotonic
2024-03-14T11:31:43.732601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35.84788528 2
 
2.1%
35.81741014 2
 
2.1%
35.83930266 1
 
1.1%
35.81243343 1
 
1.1%
35.79602215 1
 
1.1%
35.79907862 1
 
1.1%
35.80543226 1
 
1.1%
35.80314477 1
 
1.1%
35.8266425 1
 
1.1%
35.85822916 1
 
1.1%
Other values (82) 82
87.2%
ValueCountFrequency (%)
35.76707707 1
1.1%
35.78686647 1
1.1%
35.79056737 1
1.1%
35.79189899 1
1.1%
35.79204365 1
1.1%
35.79365647 1
1.1%
35.79459473 1
1.1%
35.79490906 1
1.1%
35.79599558 1
1.1%
35.79602215 1
1.1%
ValueCountFrequency (%)
35.87345599 1
1.1%
35.87257595 1
1.1%
35.87124647 1
1.1%
35.87001072 1
1.1%
35.86644046 1
1.1%
35.86546346 1
1.1%
35.86442664 1
1.1%
35.86333293 1
1.1%
35.86169453 1
1.1%
35.85913066 1
1.1%

경도
Real number (ℝ)

Distinct92
Distinct (%)97.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.12589
Minimum127.05808
Maximum127.17342
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size978.0 B
2024-03-14T11:31:43.837245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum127.05808
5-th percentile127.07989
Q1127.11621
median127.12798
Q3127.1401
95-th percentile127.15852
Maximum127.17342
Range0.1153361
Interquartile range (IQR)0.023885175

Descriptive statistics

Standard deviation0.021888911
Coefficient of variation (CV)0.00017218295
Kurtosis0.75820138
Mean127.12589
Median Absolute Deviation (MAD)0.0120265
Skewness-0.65560514
Sum11949.834
Variance0.00047912444
MonotonicityNot monotonic
2024-03-14T11:31:43.951022image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.1411043 2
 
2.1%
127.1285633 2
 
2.1%
127.1681718 1
 
1.1%
127.1299118 1
 
1.1%
127.1347789 1
 
1.1%
127.1296839 1
 
1.1%
127.1238722 1
 
1.1%
127.1081728 1
 
1.1%
127.1453841 1
 
1.1%
127.1205777 1
 
1.1%
Other values (82) 82
87.2%
ValueCountFrequency (%)
127.0580791 1
1.1%
127.0731777 1
1.1%
127.0752271 1
1.1%
127.0767305 1
1.1%
127.0784751 1
1.1%
127.0806498 1
1.1%
127.0857351 1
1.1%
127.0887394 1
1.1%
127.0946211 1
1.1%
127.1013386 1
1.1%
ValueCountFrequency (%)
127.1734152 1
1.1%
127.1681718 1
1.1%
127.1673162 1
1.1%
127.159232 1
1.1%
127.1587682 1
1.1%
127.1583892 1
1.1%
127.154112 1
1.1%
127.1533161 1
1.1%
127.1509241 1
1.1%
127.1500603 1
1.1%

업태구분명
Categorical

HIGH CORRELATION 

Distinct6
Distinct (%)6.4%
Missing0
Missing (%)0.0%
Memory size884.0 B
요양병원(일반요양병원)
34 
병원
30 
한방병원
21 
종합병원
6 
치과병원
 
2

Length

Max length12
Median length10
Mean length6.3191489
Min length2

Unique

Unique1 ?
Unique (%)1.1%

Sample

1st row한방병원
2nd row요양병원(일반요양병원)
3rd row한방병원
4th row병원
5th row한방병원

Common Values

ValueCountFrequency (%)
요양병원(일반요양병원) 34
36.2%
병원 30
31.9%
한방병원 21
22.3%
종합병원 6
 
6.4%
치과병원 2
 
2.1%
요양병원(노인병원) 1
 
1.1%

Length

2024-03-14T11:31:44.056081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T11:31:44.163464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
요양병원(일반요양병원 34
36.2%
병원 30
31.9%
한방병원 21
22.3%
종합병원 6
 
6.4%
치과병원 2
 
2.1%
요양병원(노인병원 1
 
1.1%

의료기관종별명
Categorical

HIGH CORRELATION 

Distinct6
Distinct (%)6.4%
Missing0
Missing (%)0.0%
Memory size884.0 B
요양병원(일반요양병원)
34 
병원
30 
한방병원
21 
종합병원
6 
치과병원
 
2

Length

Max length12
Median length10
Mean length6.3191489
Min length2

Unique

Unique1 ?
Unique (%)1.1%

Sample

1st row한방병원
2nd row요양병원(일반요양병원)
3rd row한방병원
4th row병원
5th row한방병원

Common Values

ValueCountFrequency (%)
요양병원(일반요양병원) 34
36.2%
병원 30
31.9%
한방병원 21
22.3%
종합병원 6
 
6.4%
치과병원 2
 
2.1%
요양병원(노인병원) 1
 
1.1%

Length

2024-03-14T11:31:44.295968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T11:31:44.400541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
요양병원(일반요양병원 34
36.2%
병원 30
31.9%
한방병원 21
22.3%
종합병원 6
 
6.4%
치과병원 2
 
2.1%
요양병원(노인병원 1
 
1.1%

의료인수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct39
Distinct (%)41.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean42.861702
Minimum0
Maximum1505
Zeros6
Zeros (%)6.4%
Negative0
Negative (%)0.0%
Memory size978.0 B
2024-03-14T11:31:44.517114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q17
median14
Q323
95-th percentile67.5
Maximum1505
Range1505
Interquartile range (IQR)16

Descriptive statistics

Standard deviation173.85982
Coefficient of variation (CV)4.0562977
Kurtosis58.295396
Mean42.861702
Median Absolute Deviation (MAD)9
Skewness7.4247161
Sum4029
Variance30227.239
MonotonicityNot monotonic
2024-03-14T11:31:44.621653image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=39)
ValueCountFrequency (%)
14 8
 
8.5%
0 6
 
6.4%
4 5
 
5.3%
9 5
 
5.3%
13 5
 
5.3%
19 5
 
5.3%
10 5
 
5.3%
3 4
 
4.3%
26 4
 
4.3%
5 4
 
4.3%
Other values (29) 43
45.7%
ValueCountFrequency (%)
0 6
6.4%
1 1
 
1.1%
2 2
 
2.1%
3 4
4.3%
4 5
5.3%
5 4
4.3%
6 1
 
1.1%
7 3
3.2%
8 2
 
2.1%
9 5
5.3%
ValueCountFrequency (%)
1505 1
1.1%
795 1
1.1%
177 1
1.1%
123 1
1.1%
87 1
1.1%
57 1
1.1%
55 1
1.1%
48 1
1.1%
41 1
1.1%
38 1
1.1%

입원실수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct48
Distinct (%)51.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean42.106383
Minimum0
Maximum297
Zeros2
Zeros (%)2.1%
Negative0
Negative (%)0.0%
Memory size978.0 B
2024-03-14T11:31:44.765728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile11.3
Q124
median32
Q345.75
95-th percentile84.2
Maximum297
Range297
Interquartile range (IQR)21.75

Descriptive statistics

Standard deviation42.162376
Coefficient of variation (CV)1.0013298
Kurtosis19.485391
Mean42.106383
Median Absolute Deviation (MAD)11
Skewness4.0356093
Sum3958
Variance1777.666
MonotonicityNot monotonic
2024-03-14T11:31:44.963370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=48)
ValueCountFrequency (%)
37 7
 
7.4%
24 6
 
6.4%
29 4
 
4.3%
18 4
 
4.3%
28 4
 
4.3%
45 4
 
4.3%
53 3
 
3.2%
25 3
 
3.2%
34 3
 
3.2%
30 2
 
2.1%
Other values (38) 54
57.4%
ValueCountFrequency (%)
0 2
2.1%
6 1
 
1.1%
10 2
2.1%
12 2
2.1%
15 2
2.1%
16 1
 
1.1%
18 4
4.3%
19 1
 
1.1%
20 2
2.1%
21 2
2.1%
ValueCountFrequency (%)
297 1
1.1%
241 1
1.1%
164 1
1.1%
159 1
1.1%
92 1
1.1%
80 1
1.1%
78 1
1.1%
68 1
1.1%
66 1
1.1%
63 1
1.1%

병상수
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct79
Distinct (%)84.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean167.02128
Minimum0
Maximum1199
Zeros2
Zeros (%)2.1%
Negative0
Negative (%)0.0%
Memory size978.0 B
2024-03-14T11:31:45.102711image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile36.85
Q172
median120.5
Q3206.75
95-th percentile353.55
Maximum1199
Range1199
Interquartile range (IQR)134.75

Descriptive statistics

Standard deviation173.25778
Coefficient of variation (CV)1.0373396
Kurtosis15.878532
Mean167.02128
Median Absolute Deviation (MAD)60
Skewness3.4904889
Sum15700
Variance30018.258
MonotonicityNot monotonic
2024-03-14T11:31:45.219202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
72 3
 
3.2%
56 2
 
2.1%
178 2
 
2.1%
75 2
 
2.1%
0 2
 
2.1%
30 2
 
2.1%
57 2
 
2.1%
188 2
 
2.1%
124 2
 
2.1%
61 2
 
2.1%
Other values (69) 73
77.7%
ValueCountFrequency (%)
0 2
2.1%
30 2
2.1%
31 1
1.1%
40 1
1.1%
43 1
1.1%
48 1
1.1%
49 1
1.1%
50 1
1.1%
51 1
1.1%
56 2
2.1%
ValueCountFrequency (%)
1199 1
1.1%
803 1
1.1%
793 1
1.1%
568 1
1.1%
427 1
1.1%
314 1
1.1%
311 1
1.1%
298 1
1.1%
289 1
1.1%
288 1
1.1%

총면적
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct93
Distinct (%)100.0%
Missing1
Missing (%)1.1%
Infinite0
Infinite (%)0.0%
Mean24197.12
Minimum844.9
Maximum1651865
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size978.0 B
2024-03-14T11:31:45.332110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum844.9
5-th percentile1321.012
Q11993.55
median3328.31
Q35244.56
95-th percentile15153.216
Maximum1651865
Range1651020.1
Interquartile range (IQR)3251.01

Descriptive statistics

Standard deviation171657.26
Coefficient of variation (CV)7.0941197
Kurtosis90.696791
Mean24197.12
Median Absolute Deviation (MAD)1563.95
Skewness9.4767045
Sum2250332.1
Variance2.9466216 × 1010
MonotonicityNot monotonic
2024-03-14T11:31:45.448862image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1530.26 1
 
1.1%
5723.54 1
 
1.1%
1352.96 1
 
1.1%
1353.0 1
 
1.1%
849.62 1
 
1.1%
1764.36 1
 
1.1%
4172.79 1
 
1.1%
8366.93 1
 
1.1%
1629.34 1
 
1.1%
5244.56 1
 
1.1%
Other values (83) 83
88.3%
ValueCountFrequency (%)
844.9 1
1.1%
849.62 1
1.1%
962.96 1
1.1%
1149.16 1
1.1%
1289.56 1
1.1%
1341.98 1
1.1%
1352.96 1
1.1%
1353.0 1
1.1%
1419.17 1
1.1%
1428.4 1
1.1%
ValueCountFrequency (%)
1651865.0 1
1.1%
178570.86 1
1.1%
45884.0 1
1.1%
23025.6 1
1.1%
20505.6 1
1.1%
11584.96 1
1.1%
10707.53 1
1.1%
9836.74 1
1.1%
9776.95 1
1.1%
8366.93 1
1.1%

진료과목내용명
Text

MISSING 

Distinct79
Distinct (%)86.8%
Missing3
Missing (%)3.2%
Memory size884.0 B
2024-03-14T11:31:45.645564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length191
Median length63
Mean length43.714286
Min length2

Characters and Unicode

Total characters3978
Distinct characters67
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

Unique74 ?
Unique (%)81.3%

Sample

1st row가정의학과+한방내과+한방부인과+한방소아과+한방안·이비인후·피부과+한방신경정신과+한방재활의학과+사상체질과+침구과
2nd row내과+외과+가정의학과+한방내과+침구과
3rd row마취통증의학과+한방내과+한방부인과+한방소아과+한방안·이비인후·피부과+한방신경정신과+한방재활의학과+사상체질과+침구과
4th row내과+외과+정형외과+소아청소년과+응급의학과
5th row가정의학과+한방내과+한방부인과+한방소아과+한방안·이비인후·피부과+한방신경정신과+한방재활의학과+사상체질과+침구과
ValueCountFrequency (%)
가정의학과+한방내과+한방부인과+한방소아과+한방안·이비인후·피부과+한방신경정신과+한방재활의학과+사상체질과+침구과 9
 
9.9%
내과+외과+정형외과+피부과+가정의학과+한방내과 2
 
2.2%
한방내과+한방부인과+한방소아과+한방안·이비인후·피부과+한방신경정신과+한방재활의학과+사상체질과+침구과 2
 
2.2%
내과+마취통증의학과+재활의학과+가정의학과 2
 
2.2%
내과+정형외과+마취통증의학과+영상의학과 2
 
2.2%
내과+정형외과+신경외과+마취통증의학과+영상치의학과 1
 
1.1%
내과+정형외과+신경외과+마취통증의학과+영상의학과 1
 
1.1%
정신건강의학과+재활의학과+가정의학과+한방내과 1
 
1.1%
외과 1
 
1.1%
내과+신경과+외과+소아청소년과+영상의학과+재활의학과+가정의학과 1
 
1.1%
Other values (69) 69
75.8%
2024-03-14T11:31:45.999498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
과 728
18.3%
+ 626
15.7%
학 208
 
5.2%
의 205
 
5.2%
방 195
 
4.9%
한 192
 
4.8%
정 133
 
3.3%
내 117
 
2.9%
외 115
 
2.9%
신 110
 
2.8%
Other values (57) 1349
33.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3302
83.0%
Math Symbol 626
 
15.7%
Other Punctuation 50
 
1.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
과 728
22.0%
학 208
 
6.3%
의 205
 
6.2%
방 195
 
5.9%
한 192
 
5.8%
정 133
 
4.0%
내 117
 
3.5%
외 115
 
3.5%
신 110
 
3.3%
부 89
 
2.7%
Other values (55) 1210
36.6%
Math Symbol
ValueCountFrequency (%)
+ 626
100.0%
Other Punctuation
ValueCountFrequency (%)
· 50
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3302
83.0%
Common 676
 
17.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
과 728
22.0%
학 208
 
6.3%
의 205
 
6.2%
방 195
 
5.9%
한 192
 
5.8%
정 133
 
4.0%
내 117
 
3.5%
외 115
 
3.5%
신 110
 
3.3%
부 89
 
2.7%
Other values (55) 1210
36.6%
Common
ValueCountFrequency (%)
+ 626
92.6%
· 50
 
7.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3302
83.0%
ASCII 626
 
15.7%
None 50
 
1.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
과 728
22.0%
학 208
 
6.3%
의 205
 
6.2%
방 195
 
5.9%
한 192
 
5.8%
정 133
 
4.0%
내 117
 
3.5%
외 115
 
3.5%
신 110
 
3.3%
부 89
 
2.7%
Other values (55) 1210
36.6%
ASCII
ValueCountFrequency (%)
+ 626
100.0%
None
ValueCountFrequency (%)
· 50
100.0%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size884.0 B
2022-06-30
94 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2022-06-30
2nd row2022-06-30
3rd row2022-06-30
4th row2022-06-30
5th row2022-06-30

Common Values

ValueCountFrequency (%)
2022-06-30 94
100.0%

Length

2024-03-14T11:31:46.089097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-14T11:31:46.152338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022-06-30 94
100.0%

Interactions

2024-03-14T11:31:39.424917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T11:31:36.926533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T11:31:37.332223image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T11:31:37.768419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T11:31:38.395875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T11:31:38.947371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T11:31:39.504966image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T11:31:36.988637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T11:31:37.409286image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T11:31:37.846470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T11:31:38.479402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T11:31:39.024688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T11:31:39.581254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T11:31:37.055652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T11:31:37.489094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T11:31:37.932681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T11:31:38.561601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T11:31:39.099662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T11:31:39.655560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T11:31:37.123856image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T11:31:37.559028image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T11:31:38.038970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T11:31:38.649921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T11:31:39.204434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T11:31:39.725688image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T11:31:37.189055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T11:31:37.627314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T11:31:38.181442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T11:31:38.742272image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T11:31:39.280670image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T11:31:39.793246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T11:31:37.258556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T11:31:37.694772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T11:31:38.287438image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T11:31:38.837958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-14T11:31:39.349296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-14T11:31:46.209397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
사업장명인허가일자소재지전화도로명주소지번주소위도경도업태구분명의료기관종별명의료인수입원실수병상수총면적진료과목내용명
사업장명1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
인허가일자1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
소재지전화1.0001.0001.0001.0001.0001.0001.0000.9620.9621.0000.9891.0001.0000.997
도로명주소1.0001.0001.0001.0001.0001.0001.0000.9620.9621.0000.9891.0001.0000.997
지번주소1.0001.0001.0001.0001.0001.0001.0000.0000.0000.0000.0000.0000.0000.990
위도1.0001.0001.0001.0001.0001.0000.7060.2240.2240.0000.0000.2300.0000.000
경도1.0001.0001.0001.0001.0000.7061.0000.2680.2680.0000.3020.4030.0000.965
업태구분명1.0001.0000.9620.9620.0000.2240.2681.0001.0000.4910.5240.5710.4631.000
의료기관종별명1.0001.0000.9620.9620.0000.2240.2681.0001.0000.4910.5240.5710.4631.000
의료인수1.0001.0001.0001.0000.0000.0000.0000.4910.4911.0000.9270.9270.6671.000
입원실수1.0001.0000.9890.9890.0000.0000.3020.5240.5240.9271.0000.9830.7540.995
병상수1.0001.0001.0001.0000.0000.2300.4030.5710.5710.9270.9831.0000.7541.000
총면적1.0001.0001.0001.0000.0000.0000.0000.4630.4630.6670.7540.7541.0001.000
진료과목내용명1.0001.0000.9970.9970.9900.0000.9651.0001.0001.0000.9951.0001.0001.000
2024-03-14T11:31:46.371448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업태구분명의료기관종별명
업태구분명1.0001.000
의료기관종별명1.0001.000
2024-03-14T11:31:46.461480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도의료인수입원실수병상수총면적업태구분명의료기관종별명
위도1.0000.109-0.0010.0310.1010.0630.1120.112
경도0.1091.000-0.1990.0690.116-0.0060.1370.137
의료인수-0.001-0.1991.0000.5150.4910.5870.3330.333
입원실수0.0310.0690.5151.0000.8710.7500.3430.343
병상수0.1010.1160.4910.8711.0000.7230.3830.383
총면적0.063-0.0060.5870.7500.7231.0000.2130.213
업태구분명0.1120.1370.3330.3430.3830.2131.0001.000
의료기관종별명0.1120.1370.3330.3430.3830.2131.0001.000

Missing values

2024-03-14T11:31:39.923385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T11:31:40.106660image/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.
2024-03-14T11:31:40.213421image/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

사업장명인허가일자상세영업상태명소재지전화도로명주소지번주소위도경도업태구분명의료기관종별명의료인수입원실수병상수총면적진료과목내용명데이터기준일자
0가람한방병원2014-04-30영업중063-270-8600전라북도 전주시 덕진구 송천중앙로 60, 3~6층 (송천동1가)전라북도 전주시 덕진구 송천동1가 270-135.852438127.120224한방병원한방병원431831530.26가정의학과+한방내과+한방부인과+한방소아과+한방안·이비인후·피부과+한방신경정신과+한방재활의학과+사상체질과+침구과2022-06-30
1나은요양병원2012-06-26영업중063-715-2300전라북도 전주시 덕진구 기린대로 951 (여의동)전라북도 전주시 덕진구 여의동 558-435.864427127.08065요양병원(일반요양병원)요양병원(일반요양병원)23372104311.4내과+외과+가정의학과+한방내과+침구과2022-06-30
2누가한방병원2009-11-04영업중063-252-9111전라북도 전주시 덕진구 안덕원로 218 (인후동1가)전라북도 전주시 덕진구 인후동1가 594-1435.835934127.150924한방병원한방병원318841476.7마취통증의학과+한방내과+한방부인과+한방소아과+한방안·이비인후·피부과+한방신경정신과+한방재활의학과+사상체질과+침구과2022-06-30
3다사랑병원2005-03-16영업중063-228-5540전라북도 전주시 완산구 백제대로 74 (삼천동1가)전라북도 전주시 완산구 삼천동1가 732-335.800878127.127854병원병원932942379.94내과+외과+정형외과+소아청소년과+응급의학과2022-06-30
4다생한방병원2018-06-25영업중063-714-2000전라북도 전주시 덕진구 벚꽃로 48, 0동 (진북동,참조은병원)전라북도 전주시 덕진구 진북동 1021-235.828807127.134791한방병원한방병원028602160.53가정의학과+한방내과+한방부인과+한방소아과+한방안·이비인후·피부과+한방신경정신과+한방재활의학과+사상체질과+침구과2022-06-30
5대자인병원2012-05-01영업중063-240-2000전라북도 전주시 덕진구 견훤로 390 (우아동3가)전라북도 전주시 덕진구 우아동3가 734-1735.845991127.153316종합병원종합병원17715956820505.6내과+신경과+정신건강의학과+외과+정형외과+신경외과+흉부외과+마취통증의학과+산부인과+소아청소년과+안과+피부과+비뇨의학과+영상의학과+병리과+진단검사의학과+재활의학과+가정의학과+핵의학과+직업환경의학과+응급의학과+한방내과+한방부인과+한방신경정신과+한방재활의학과+사상체질과+침구과+구강악안면외과+치과보철과+치과교정과+소아치과+치주과+치과보존과+구강내과2022-06-30
6더세움병원2022-02-25영업중063-243-9100전라북도 전주시 덕진구 서가재미2길 7 (인후동1가)전라북도 전주시 덕진구 인후동1가 822-435.832125127.159232병원병원1333127844.9내과+재활의학과+한방내과+한방재활의학과+사상체질과+침구과2022-06-30
7더숲요양병원2016-06-02영업중063-230-2000전라북도 전주시 완산구 흑석2길 22 (서서학동)전라북도 전주시 완산구 서서학동 1002-335.795996127.15006요양병원(일반요양병원)요양병원(일반요양병원)14682896930.96내과+신경과+외과+정형외과+신경외과+이비인후과+피부과+비뇨의학과+재활의학과+가정의학과+한방내과2022-06-30
8덕진한방병원2014-09-26영업중063-225-1075전라북도 전주시 덕진구 솔내로 131 (송천동1가)전라북도 전주시 덕진구 송천동1가 11635.861695127.126326한방병원한방병원518611419.17가정의학과+한방내과+한방부인과+한방소아과+한방안·이비인후·피부과+한방신경정신과+한방재활의학과+사상체질과+침구과2022-06-30
9동의한방병원2015-06-23영업중063-274-8575전라북도 전주시 완산구 백제대로 277, 4,5층 (중화산동2가)전라북도 전주시 완산구 중화산동2가 595-935.818073127.122501한방병원한방병원415491289.56가정의학과+한방내과+한방부인과+한방소아과+한방안·이비인후·피부과+한방신경정신과+한방재활의학과+사상체질과+침구과2022-06-30
사업장명인허가일자상세영업상태명소재지전화도로명주소지번주소위도경도업태구분명의료기관종별명의료인수입원실수병상수총면적진료과목내용명데이터기준일자
84한양병원2002-03-22영업중063-220-5000전라북도 전주시 완산구 장승배기로 204 (평화동1가)전라북도 전주시 완산구 평화동1가 711-135.796149127.135159병원병원12381233646.0내과+신경과+외과+정형외과+신경외과+마취통증의학과+소아청소년과+이비인후과+피부과+비뇨의학과+영상의학과+진단검사의학과+재활의학과+가정의학과2022-06-30
85해맑은요양병원2017-04-12영업중063-231-1100전라북도 전주시 완산구 팔달로 202-15 (경원동3가)전라북도 전주시 완산구 경원동3가 38-335.820764127.146882요양병원(일반요양병원)요양병원(일반요양병원)13371323618.93내과+방사선종양학과+한방내과2022-06-30
86해빛한방병원2020-04-06영업중063-715-5119전라북도 전주시 덕진구 사근1길 10 (송천동2가)전라북도 전주시 덕진구 송천동2가 175-5235.86644127.128103한방병원한방병원026822489.23가정의학과+한방내과+한방부인과+한방소아과+한방안·이비인후·피부과+한방신경정신과+한방재활의학과+사상체질과+침구과2022-06-30
87행복한요양병원2016-07-15영업중063-240-7000전라북도 전주시 덕진구 백제대로 700 (덕진동1가)전라북도 전주시 덕진구 인후동2가 1529-835.844096127.145958요양병원(일반요양병원)요양병원(일반요양병원)12391693531.3내과+외과+가정의학과+한방내과2022-06-30
88허병원1994-04-11영업중063-254-5599전라북도 전주시 덕진구 조경단로 103 (금암동)전라북도 전주시 덕진구 금암동 1546-935.843395127.138522병원병원1316691566.12내과+신경과+정신건강의학과2022-06-30
89효사랑가족요양병원2007-06-11영업중063-711-1111전라북도 전주시 완산구 용머리로 77 (효자동1가)전라북도 전주시 완산구 효자동1가 29235.806705127.118834요양병원(일반요양병원)요양병원(일반요양병원)5516479323025.6내과+외과+정형외과+재활의학과+가정의학과+한방내과+한방부인과+한방소아과+한방안·이비인후·피부과+한방신경정신과+한방재활의학과+사상체질과+침구과2022-06-30
90효사랑전주요양병원2006-05-26영업중063-278-8288전라북도 전주시 완산구 팔달로 272 (서노송동)전라북도 전주시 완산구 서노송동 649-535.826439127.144105요양병원(일반요양병원)요양병원(일반요양병원)41533147172.0내과+재활의학과+가정의학과+한방내과+한방부인과+한방소아과+한방안·이비인후·피부과+한방신경정신과+한방재활의학과+사상체질과+침구과2022-06-30
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