Overview

Dataset statistics

Number of variables7
Number of observations430
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory24.5 KiB
Average record size in memory58.3 B

Variable types

Categorical2
Text3
Numeric2

Dataset

Description연명의료중단등결정 및 이행을 위한 의료기관윤리위원회가 설치된 의료기관의 정보 (시도, 종별, 기관명, 전화번호, 주소, 위도, 경도)
Author보건복지부
URLhttps://www.data.go.kr/data/15075103/fileData.do

Alerts

기관명 has unique valuesUnique

Reproduction

Analysis started2024-03-14 21:15:33.766447
Analysis finished2024-03-14 21:15:36.074313
Duration2.31 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도
Categorical

Distinct17
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Memory size3.5 KiB
경기도
91 
서울특별시
70 
부산광역시
32 
인천광역시
29 
전라북도
27 
Other values (12)
181 

Length

Max length7
Median length5
Mean length4.4348837
Min length3

Unique

Unique1 ?
Unique (%)0.2%

Sample

1st row서울특별시
2nd row서울특별시
3rd row강원특별자치도
4th row대구광역시
5th row충청남도

Common Values

ValueCountFrequency (%)
경기도 91
21.2%
서울특별시 70
16.3%
부산광역시 32
 
7.4%
인천광역시 29
 
6.7%
전라북도 27
 
6.3%
대구광역시 24
 
5.6%
광주광역시 21
 
4.9%
충청북도 19
 
4.4%
경상북도 19
 
4.4%
대전광역시 18
 
4.2%
Other values (7) 80
18.6%

Length

2024-03-15T06:15:36.206715image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
경기도 91
21.2%
서울특별시 70
16.3%
부산광역시 32
 
7.4%
인천광역시 29
 
6.7%
전라북도 27
 
6.3%
대구광역시 24
 
5.6%
광주광역시 21
 
4.9%
경상북도 19
 
4.4%
충청북도 19
 
4.4%
대전광역시 18
 
4.2%
Other values (7) 80
18.6%

종별
Categorical

Distinct5
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size3.5 KiB
종합병원
204 
요양병원
136 
상급종합병원
45 
병원
37 
의원
 
8

Length

Max length6
Median length4
Mean length4
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row종합병원
2nd row종합병원
3rd row종합병원
4th row상급종합병원
5th row상급종합병원

Common Values

ValueCountFrequency (%)
종합병원 204
47.4%
요양병원 136
31.6%
상급종합병원 45
 
10.5%
병원 37
 
8.6%
의원 8
 
1.9%

Length

2024-03-15T06:15:36.547895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T06:15:36.923558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
종합병원 204
47.4%
요양병원 136
31.6%
상급종합병원 45
 
10.5%
병원 37
 
8.6%
의원 8
 
1.9%

기관명
Text

UNIQUE 

Distinct430
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size3.5 KiB
2024-03-15T06:15:37.705385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length21
Mean length10.067442
Min length3

Characters and Unicode

Total characters4329
Distinct characters294
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique430 ?
Unique (%)100.0%

Sample

1st row서울적십자병원
2nd row가톨릭대학교 은평성모병원
3rd row강원대학교병원
4th row경북대학교병원
5th row단국대의과대학부속병원
ValueCountFrequency (%)
의료법인 34
 
5.9%
서울특별시 5
 
0.9%
근로복지공단 5
 
0.9%
가톨릭대학교 3
 
0.5%
재단법인 3
 
0.5%
경기도의료원 3
 
0.5%
요양병원 2
 
0.3%
명지병원 2
 
0.3%
센트럴요양병원 2
 
0.3%
학교법인 2
 
0.3%
Other values (503) 512
89.4%
2024-03-15T06:15:38.775639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
원 480
 
11.1%
병 393
 
9.1%
의 231
 
5.3%
료 192
 
4.4%
145
 
3.3%
양 131
 
3.0%
인 128
 
3.0%
요 119
 
2.7%
대 114
 
2.6%
단 108
 
2.5%
Other values (284) 2288
52.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4120
95.2%
Space Separator 145
 
3.3%
Close Punctuation 27
 
0.6%
Open Punctuation 25
 
0.6%
Decimal Number 10
 
0.2%
Uppercase Letter 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
원 480
 
11.7%
병 393
 
9.5%
의 231
 
5.6%
료 192
 
4.7%
양 131
 
3.2%
인 128
 
3.1%
요 119
 
2.9%
대 114
 
2.8%
단 108
 
2.6%
재 105
 
2.5%
Other values (274) 2119
51.4%
Decimal Number
ValueCountFrequency (%)
1 3
30.0%
2 2
20.0%
0 2
20.0%
4 2
20.0%
3 1
 
10.0%
Uppercase Letter
ValueCountFrequency (%)
S 1
50.0%
K 1
50.0%
Space Separator
ValueCountFrequency (%)
145
100.0%
Close Punctuation
ValueCountFrequency (%)
) 27
100.0%
Open Punctuation
ValueCountFrequency (%)
( 25
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4120
95.2%
Common 207
 
4.8%
Latin 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
원 480
 
11.7%
병 393
 
9.5%
의 231
 
5.6%
료 192
 
4.7%
양 131
 
3.2%
인 128
 
3.1%
요 119
 
2.9%
대 114
 
2.8%
단 108
 
2.6%
재 105
 
2.5%
Other values (274) 2119
51.4%
Common
ValueCountFrequency (%)
145
70.0%
) 27
 
13.0%
( 25
 
12.1%
1 3
 
1.4%
2 2
 
1.0%
0 2
 
1.0%
4 2
 
1.0%
3 1
 
0.5%
Latin
ValueCountFrequency (%)
S 1
50.0%
K 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4120
95.2%
ASCII 209
 
4.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
원 480
 
11.7%
병 393
 
9.5%
의 231
 
5.6%
료 192
 
4.7%
양 131
 
3.2%
인 128
 
3.1%
요 119
 
2.9%
대 114
 
2.8%
단 108
 
2.6%
재 105
 
2.5%
Other values (274) 2119
51.4%
ASCII
ValueCountFrequency (%)
145
69.4%
) 27
 
12.9%
( 25
 
12.0%
1 3
 
1.4%
2 2
 
1.0%
0 2
 
1.0%
4 2
 
1.0%
3 1
 
0.5%
S 1
 
0.5%
K 1
 
0.5%

전화번호
Text

Distinct428
Distinct (%)99.5%
Missing0
Missing (%)0.0%
Memory size3.5 KiB
2024-03-15T06:15:39.822290image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length11.981395
Min length9

Characters and Unicode

Total characters5152
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

Unique426 ?
Unique (%)99.1%

Sample

1st row02-2002-8860
2nd row02-2030-4291
3rd row033-258-9217
4th row053-200-4501
5th row041-550-6891
ValueCountFrequency (%)
051-757-5119 2
 
0.5%
033-732-0270 2
 
0.5%
031-8041-3537 1
 
0.2%
063-547-5000 1
 
0.2%
051-610-9770 1
 
0.2%
031-949-4188 1
 
0.2%
042-220-8017 1
 
0.2%
042-609-1952 1
 
0.2%
042-670-5410 1
 
0.2%
031-799-8009 1
 
0.2%
Other values (418) 418
97.2%
2024-03-15T06:15:41.345779image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 991
19.2%
- 857
16.6%
2 523
10.2%
3 469
9.1%
1 431
8.4%
5 415
8.1%
6 321
 
6.2%
4 309
 
6.0%
9 287
 
5.6%
8 283
 
5.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 4295
83.4%
Dash Punctuation 857
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 991
23.1%
2 523
12.2%
3 469
10.9%
1 431
10.0%
5 415
9.7%
6 321
 
7.5%
4 309
 
7.2%
9 287
 
6.7%
8 283
 
6.6%
7 266
 
6.2%
Dash Punctuation
ValueCountFrequency (%)
- 857
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 5152
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 991
19.2%
- 857
16.6%
2 523
10.2%
3 469
9.1%
1 431
8.4%
5 415
8.1%
6 321
 
6.2%
4 309
 
6.0%
9 287
 
5.6%
8 283
 
5.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5152
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 991
19.2%
- 857
16.6%
2 523
10.2%
3 469
9.1%
1 431
8.4%
5 415
8.1%
6 321
 
6.2%
4 309
 
6.0%
9 287
 
5.6%
8 283
 
5.5%

주소
Text

Distinct427
Distinct (%)99.3%
Missing0
Missing (%)0.0%
Memory size3.5 KiB
2024-03-15T06:15:42.706760image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length82
Median length57
Mean length21.727907
Min length14

Characters and Unicode

Total characters9343
Distinct characters326
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique424 ?
Unique (%)98.6%

Sample

1st row서울특별시 종로구 새문안로 9
2nd row서울특별시 은평구 통일로 1021
3rd row강원특별자치도 춘천시 백령로 156
4th row대구광역시 중구 동덕로 130
5th row충청남도 천안시 동남구 망향로 201
ValueCountFrequency (%)
경기도 91
 
4.4%
서울특별시 70
 
3.4%
부산광역시 32
 
1.6%
인천광역시 29
 
1.4%
전라북도 27
 
1.3%
대구광역시 24
 
1.2%
광주광역시 21
 
1.0%
경상북도 19
 
0.9%
충청북도 19
 
0.9%
서구 18
 
0.9%
Other values (1036) 1695
82.9%
2024-03-15T06:15:44.766956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1634
 
17.5%
시 429
 
4.6%
로 405
 
4.3%
구 330
 
3.5%
1 298
 
3.2%
도 239
 
2.6%
2 220
 
2.4%
동 191
 
2.0%
광 172
 
1.8%
3 170
 
1.8%
Other values (316) 5255
56.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5821
62.3%
Space Separator 1634
 
17.5%
Decimal Number 1494
 
16.0%
Close Punctuation 113
 
1.2%
Open Punctuation 113
 
1.2%
Other Punctuation 98
 
1.0%
Dash Punctuation 48
 
0.5%
Math Symbol 19
 
0.2%
Uppercase Letter 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 429
 
7.4%
로 405
 
7.0%
구 330
 
5.7%
도 239
 
4.1%
동 191
 
3.3%
광 172
 
3.0%
대 152
 
2.6%
경 147
 
2.5%
서 141
 
2.4%
역 136
 
2.3%
Other values (295) 3479
59.8%
Decimal Number
ValueCountFrequency (%)
1 298
19.9%
2 220
14.7%
3 170
11.4%
5 152
10.2%
0 123
8.2%
7 119
 
8.0%
6 115
 
7.7%
4 107
 
7.2%
9 101
 
6.8%
8 89
 
6.0%
Uppercase Letter
ValueCountFrequency (%)
M 1
33.3%
B 1
33.3%
D 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 97
99.0%
/ 1
 
1.0%
Math Symbol
ValueCountFrequency (%)
~ 18
94.7%
～ 1
 
5.3%
Space Separator
ValueCountFrequency (%)
1634
100.0%
Close Punctuation
ValueCountFrequency (%)
) 113
100.0%
Open Punctuation
ValueCountFrequency (%)
( 113
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 48
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5821
62.3%
Common 3519
37.7%
Latin 3
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 429
 
7.4%
로 405
 
7.0%
구 330
 
5.7%
도 239
 
4.1%
동 191
 
3.3%
광 172
 
3.0%
대 152
 
2.6%
경 147
 
2.5%
서 141
 
2.4%
역 136
 
2.3%
Other values (295) 3479
59.8%
Common
ValueCountFrequency (%)
1634
46.4%
1 298
 
8.5%
2 220
 
6.3%
3 170
 
4.8%
5 152
 
4.3%
0 123
 
3.5%
7 119
 
3.4%
6 115
 
3.3%
) 113
 
3.2%
( 113
 
3.2%
Other values (8) 462
 
13.1%
Latin
ValueCountFrequency (%)
M 1
33.3%
B 1
33.3%
D 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5821
62.3%
ASCII 3521
37.7%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1634
46.4%
1 298
 
8.5%
2 220
 
6.2%
3 170
 
4.8%
5 152
 
4.3%
0 123
 
3.5%
7 119
 
3.4%
6 115
 
3.3%
) 113
 
3.2%
( 113
 
3.2%
Other values (10) 464
 
13.2%
Hangul
ValueCountFrequency (%)
시 429
 
7.4%
로 405
 
7.0%
구 330
 
5.7%
도 239
 
4.1%
동 191
 
3.3%
광 172
 
3.0%
대 152
 
2.6%
경 147
 
2.5%
서 141
 
2.4%
역 136
 
2.3%
Other values (295) 3479
59.8%
None
ValueCountFrequency (%)
～ 1
100.0%

위도
Real number (ℝ)

Distinct427
Distinct (%)99.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.26458
Minimum37.410465
Maximum129.4288
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.9 KiB
2024-03-15T06:15:45.362292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.410465
5-th percentile126.64753
Q1126.88668
median127.10826
Q3127.98576
95-th percentile129.0881
Maximum129.4288
Range92.01834
Interquartile range (IQR)1.0990856

Descriptive statistics

Standard deviation4.4215162
Coefficient of variation (CV)0.034742708
Kurtosis400.14966
Mean127.26458
Median Absolute Deviation (MAD)0.319952
Skewness-19.643152
Sum54723.77
Variance19.549806
MonotonicityNot monotonic
2024-03-15T06:15:46.029447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
129.0498794 2
 
0.5%
127.1467189 2
 
0.5%
129.0700475 2
 
0.5%
127.0506957 1
 
0.2%
128.707849 1
 
0.2%
129.1106007 1
 
0.2%
126.7602246 1
 
0.2%
127.4104197 1
 
0.2%
127.3249905 1
 
0.2%
127.4281175 1
 
0.2%
Other values (417) 417
97.0%
ValueCountFrequency (%)
37.41046494 1
0.2%
126.4162705 1
0.2%
126.4202278 1
0.2%
126.4658947 1
0.2%
126.4848019 1
0.2%
126.4857297 1
0.2%
126.5170824 1
0.2%
126.5366645 1
0.2%
126.5452008 1
0.2%
126.5468743 1
0.2%
ValueCountFrequency (%)
129.4288047 1
0.2%
129.3615706 1
0.2%
129.3399072 1
0.2%
129.3314003 1
0.2%
129.3232393 1
0.2%
129.3020903 1
0.2%
129.2976075 1
0.2%
129.2698249 1
0.2%
129.2443303 1
0.2%
129.2239829 1
0.2%

경도
Real number (ℝ)

Distinct427
Distinct (%)99.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean36.752321
Minimum33.256067
Maximum127.12584
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.9 KiB
2024-03-15T06:15:46.441799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum33.256067
5-th percentile35.054568
Q135.799717
median36.800163
Q337.495653
95-th percentile37.703074
Maximum127.12584
Range93.869769
Interquartile range (IQR)1.6959359

Descriptive statistics

Standard deviation4.4965345
Coefficient of variation (CV)0.12234695
Kurtosis382.70692
Mean36.752321
Median Absolute Deviation (MAD)0.77451662
Skewness18.996839
Sum15803.498
Variance20.218823
MonotonicityNot monotonic
2024-03-15T06:15:46.939180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35.15785018 2
 
0.5%
37.5282209 2
 
0.5%
35.1497852 2
 
0.5%
37.75182904 1
 
0.2%
35.19926241 1
 
0.2%
35.15017251 1
 
0.2%
37.71616646 1
 
0.2%
36.33593926 1
 
0.2%
36.37513316 1
 
0.2%
36.36926654 1
 
0.2%
Other values (417) 417
97.0%
ValueCountFrequency (%)
33.25606706 1
0.2%
33.4457194 1
0.2%
33.45652881 1
0.2%
33.46720843 1
0.2%
33.46876945 1
0.2%
33.49049469 1
0.2%
33.50026993 1
0.2%
33.51864224 1
0.2%
34.58438004 1
0.2%
34.63749893 1
0.2%
ValueCountFrequency (%)
127.1258362 1
0.2%
38.21591429 1
0.2%
37.90330308 1
0.2%
37.8992117 1
0.2%
37.88376398 1
0.2%
37.8803661 1
0.2%
37.87470196 1
0.2%
37.8565902 1
0.2%
37.84667953 1
0.2%
37.84449802 1
0.2%

Interactions

2024-03-15T06:15:34.956932image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T06:15:34.423621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T06:15:35.206246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T06:15:34.704044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-15T06:15:47.123256image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시도종별위도경도
시도1.0000.0730.0000.000
종별0.0731.0000.0000.000
위도0.0000.0001.0000.704
경도0.0000.0000.7041.000
2024-03-15T06:15:47.375237image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
종별시도
종별1.0000.035
시도0.0351.000
2024-03-15T06:15:47.581252image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도시도종별
위도1.000-0.3780.0000.000
경도-0.3781.0000.0000.000
시도0.0000.0001.0000.035
종별0.0000.0000.0351.000

Missing values

2024-03-15T06:15:35.492185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-15T06:15:35.950341image/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

시도종별기관명전화번호주소위도경도
0서울특별시종합병원서울적십자병원02-2002-8860서울특별시 종로구 새문안로 9126.96720237.566762
1서울특별시종합병원가톨릭대학교 은평성모병원02-2030-4291서울특별시 은평구 통일로 1021126.91615137.633608
2강원특별자치도종합병원강원대학교병원033-258-9217강원특별자치도 춘천시 백령로 156127.744837.874702
3대구광역시상급종합병원경북대학교병원053-200-4501대구광역시 중구 동덕로 130128.60431535.866236
4충청남도상급종합병원단국대의과대학부속병원041-550-6891충청남도 천안시 동남구 망향로 201127.17327536.842952
5부산광역시병원동래성모병원051-559-8833부산광역시 동래구 충렬대로 188129.08017735.203264
6서울특별시병원서울특별시 북부병원02-2036-0459서울특별시 중랑구 양원역로 38127.1076837.604393
7전라남도종합병원성가롤로병원061-720-2483전라남도 순천시 순광로 221127.5417734.964473
8서울특별시종합병원성애병원02-840-7342서울특별시 영등포구 여의대방로53길 22126.92236737.51205
9경기도상급종합병원아주대학교병원031-219-4106경기도 수원시 영통구 월드컵로 164127.04752137.279448
시도종별기관명전화번호주소위도경도
420부산광역시요양병원성산현대요양병원051-555-6533부산광역시 동래구 시실로 12, (명륜동)129.08536635.217402
421경기도병원의료법인상록의료재단로하스일산병원031-972-2200경기도 고양시 일산서구 일중로 59126.77519537.684993
422경기도요양병원더원요양병원031-282-8123경기도 용인시 기흥구 용구대로 2252, 더원병원 (신갈동)127.10884337.287541
423전라남도종합병원의료법인한마음의료재단 여수제일병원061-689-8129전라남도 여수시 쌍봉로 70, (학동)127.66349434.766101
424경기도요양병원수동연세요양병원031-594-8007경기도 남양주시 수동면 비룡로 801-88, (수동면)127.31987837.709991
425경기도요양병원로젠요양병원070-4673-8417경기도 동두천시 삼육사로 1012, (생연동)127.06272937.899212
426부산광역시요양병원부산노인전문제3병원051-780-5559부산광역시 해운대구 해운대로469번가길 77, (우동)129.14736935.168254
427경기도요양병원의료법인더존의료재단 경희요양병원031-362-2947경기도 안산시 단원구 광덕대로 162, 광덕대로 154 (고잔동)126.83095537.310811
428경기도종합병원의료법인인봉의료재단 뉴고려병원031-980-9114경기도 김포시 김포한강3로 283, 뉴고려병원 (장기동)126.66021437.640959
429충청북도요양병원청풍호노인사랑병원043-646-0808충청북도 제천시 금성면 청풍호로 1147128.17544437.058821