Overview

Dataset statistics

Number of variables16
Number of observations100
Missing cells87
Missing cells (%)5.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory13.2 KiB
Average record size in memory135.3 B

Variable types

Categorical4
Text4
DateTime2
Numeric6

Dataset

Description정신병원 현황(병원급)
Author행정안전부
URLhttps://data.gg.go.kr/portal/data/service/selectServicePage.do?&infId=DCXQ785CN7PVG6KKGY232146022&infSeq=1

Alerts

의료기관종별명 has constant value ""Constant
병상수(개) is highly overall correlated with 의료인수(명) and 3 other fieldsHigh correlation
의료인수(명) is highly overall correlated with 병상수(개) and 2 other fieldsHigh correlation
입원실수(개) is highly overall correlated with 병상수(개) and 3 other fieldsHigh correlation
연면적(㎡) is highly overall correlated with 병상수(개) and 2 other fieldsHigh correlation
WGS84위도 is highly overall correlated with 시군명 and 1 other fieldsHigh correlation
WGS84경도 is highly overall correlated with 시군명High correlation
시군명 is highly overall correlated with 병상수(개) and 3 other fieldsHigh correlation
진료과목내용 is highly overall correlated with WGS84위도High correlation
폐업일자 has 87 (87.0%) missing valuesMissing

Reproduction

Analysis started2024-05-10 21:19:18.447198
Analysis finished2024-05-10 21:19:32.701478
Duration14.25 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군명
Categorical

HIGH CORRELATION 

Distinct24
Distinct (%)24.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
부천시
13 
고양시
11 
용인시
10 
의정부시
7 
수원시
6 
Other values (19)
53 

Length

Max length4
Median length3
Mean length3.11
Min length3

Unique

Unique2 ?
Unique (%)2.0%

Sample

1st row가평군
2nd row가평군
3rd row고양시
4th row고양시
5th row고양시

Common Values

ValueCountFrequency (%)
부천시 13
13.0%
고양시 11
 
11.0%
용인시 10
 
10.0%
의정부시 7
 
7.0%
수원시 6
 
6.0%
화성시 5
 
5.0%
김포시 5
 
5.0%
남양주 4
 
4.0%
안산시 4
 
4.0%
의왕시 4
 
4.0%
Other values (14) 31
31.0%

Length

2024-05-10T21:19:32.905143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
부천시 13
13.0%
고양시 11
 
11.0%
용인시 10
 
10.0%
의정부시 7
 
7.0%
수원시 6
 
6.0%
화성시 5
 
5.0%
김포시 5
 
5.0%
남양주 4
 
4.0%
안산시 4
 
4.0%
의왕시 4
 
4.0%
Other values (14) 31
31.0%

사업장명
Text

Distinct63
Distinct (%)63.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2024-05-10T21:19:33.351010image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length18
Mean length7.21
Min length3

Characters and Unicode

Total characters721
Distinct characters123
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

Unique28 ?
Unique (%)28.0%

Sample

1st row청평우리병원
2nd row청평우리병원
3rd row늘푸른병원
4th row의료법인상록의료재단화정병원
5th row카프성모병원
ValueCountFrequency (%)
의료법인 7
 
6.0%
부천한병원 3
 
2.6%
연세서울병원 3
 
2.6%
아주편한병원 2
 
1.7%
성남사랑의병원 2
 
1.7%
여주순영병원 2
 
1.7%
청평우리병원 2
 
1.7%
루카스병원 2
 
1.7%
이룸병원 2
 
1.7%
의정부힐링스병원 2
 
1.7%
Other values (60) 89
76.7%
2024-05-10T21:19:34.250397image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
원 103
 
14.3%
병 100
 
13.9%
의 22
 
3.1%
정 21
 
2.9%
료 18
 
2.5%
신 17
 
2.4%
16
 
2.2%
인 15
 
2.1%
성 14
 
1.9%
세 11
 
1.5%
Other values (113) 384
53.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 701
97.2%
Space Separator 16
 
2.2%
Close Punctuation 2
 
0.3%
Open Punctuation 2
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
원 103
 
14.7%
병 100
 
14.3%
의 22
 
3.1%
정 21
 
3.0%
료 18
 
2.6%
신 17
 
2.4%
인 15
 
2.1%
성 14
 
2.0%
세 11
 
1.6%
단 11
 
1.6%
Other values (110) 369
52.6%
Space Separator
ValueCountFrequency (%)
16
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 701
97.2%
Common 20
 
2.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
원 103
 
14.7%
병 100
 
14.3%
의 22
 
3.1%
정 21
 
3.0%
료 18
 
2.6%
신 17
 
2.4%
인 15
 
2.1%
성 14
 
2.0%
세 11
 
1.6%
단 11
 
1.6%
Other values (110) 369
52.6%
Common
ValueCountFrequency (%)
16
80.0%
) 2
 
10.0%
( 2
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 701
97.2%
ASCII 20
 
2.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
원 103
 
14.7%
병 100
 
14.3%
의 22
 
3.1%
정 21
 
3.0%
료 18
 
2.6%
신 17
 
2.4%
인 15
 
2.1%
성 14
 
2.0%
세 11
 
1.6%
단 11
 
1.6%
Other values (110) 369
52.6%
ASCII
ValueCountFrequency (%)
16
80.0%
) 2
 
10.0%
( 2
 
10.0%

인허가일자
Date

Distinct65
Distinct (%)65.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
Minimum1976-05-25 00:00:00
Maximum2020-03-11 00:00:00
2024-05-10T21:19:34.639973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:19:35.083017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

영업상태명
Categorical

Distinct5
Distinct (%)5.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
영업/정상
49 
영업중
36 
폐업
12 
휴업
 
2
취소/말소/만료/정지/중지
 
1

Length

Max length14
Median length5
Mean length3.95
Min length2

Unique

Unique1 ?
Unique (%)1.0%

Sample

1st row영업/정상
2nd row영업중
3rd row영업/정상
4th row영업/정상
5th row영업/정상

Common Values

ValueCountFrequency (%)
영업/정상 49
49.0%
영업중 36
36.0%
폐업 12
 
12.0%
휴업 2
 
2.0%
취소/말소/만료/정지/중지 1
 
1.0%

Length

2024-05-10T21:19:35.530080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T21:19:35.878071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 49
49.0%
영업중 36
36.0%
폐업 12
 
12.0%
휴업 2
 
2.0%
취소/말소/만료/정지/중지 1
 
1.0%

폐업일자
Date

MISSING 

Distinct13
Distinct (%)100.0%
Missing87
Missing (%)87.0%
Memory size932.0 B
Minimum2012-06-01 00:00:00
Maximum2022-12-30 00:00:00
2024-05-10T21:19:36.161830image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:19:36.528156image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=13)

병상수(개)
Real number (ℝ)

HIGH CORRELATION 

Distinct53
Distinct (%)53.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean226.32
Minimum50
Maximum800
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-05-10T21:19:36.919206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum50
5-th percentile95.6
Q1153.75
median213
Q3253.75
95-th percentile307.25
Maximum800
Range750
Interquartile range (IQR)100

Descriptive statistics

Standard deviation132.68934
Coefficient of variation (CV)0.58629085
Kurtosis10.266398
Mean226.32
Median Absolute Deviation (MAD)53
Skewness2.8695057
Sum22632
Variance17606.462
MonotonicityNot monotonic
2024-05-10T21:19:37.389503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
238 6
 
6.0%
299 5
 
5.0%
240 4
 
4.0%
195 3
 
3.0%
242 3
 
3.0%
121 3
 
3.0%
213 3
 
3.0%
236 3
 
3.0%
149 3
 
3.0%
212 3
 
3.0%
Other values (43) 64
64.0%
ValueCountFrequency (%)
50 2
2.0%
58 1
 
1.0%
88 2
2.0%
96 1
 
1.0%
103 1
 
1.0%
106 1
 
1.0%
116 2
2.0%
117 1
 
1.0%
120 2
2.0%
121 3
3.0%
ValueCountFrequency (%)
800 2
 
2.0%
758 2
 
2.0%
464 1
 
1.0%
299 5
5.0%
294 1
 
1.0%
293 1
 
1.0%
290 2
 
2.0%
289 2
 
2.0%
283 1
 
1.0%
282 1
 
1.0%

의료기관종별명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
정신병원
100 

Length

Max length4
Median length4
Mean length4
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
정신병원 100
100.0%

Length

2024-05-10T21:19:37.810442image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-10T21:19:38.169163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
정신병원 100
100.0%

의료인수(명)
Real number (ℝ)

HIGH CORRELATION 

Distinct31
Distinct (%)31.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean18.69
Minimum0
Maximum76
Zeros1
Zeros (%)1.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-05-10T21:19:38.412439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile7
Q110.75
median18
Q322
95-th percentile29.2
Maximum76
Range76
Interquartile range (IQR)11.25

Descriptive statistics

Standard deviation11.988795
Coefficient of variation (CV)0.64145507
Kurtosis10.311248
Mean18.69
Median Absolute Deviation (MAD)5
Skewness2.689494
Sum1869
Variance143.73121
MonotonicityNot monotonic
2024-05-10T21:19:38.732403image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=31)
ValueCountFrequency (%)
21 10
 
10.0%
8 7
 
7.0%
9 6
 
6.0%
22 6
 
6.0%
10 6
 
6.0%
15 6
 
6.0%
17 6
 
6.0%
19 5
 
5.0%
18 5
 
5.0%
29 4
 
4.0%
Other values (21) 39
39.0%
ValueCountFrequency (%)
0 1
 
1.0%
1 1
 
1.0%
5 2
 
2.0%
7 2
 
2.0%
8 7
7.0%
9 6
6.0%
10 6
6.0%
11 2
 
2.0%
12 2
 
2.0%
13 2
 
2.0%
ValueCountFrequency (%)
76 1
 
1.0%
75 1
 
1.0%
58 1
 
1.0%
56 1
 
1.0%
33 1
 
1.0%
29 4
4.0%
28 1
 
1.0%
27 1
 
1.0%
26 2
2.0%
25 2
2.0%

입원실수(개)
Real number (ℝ)

HIGH CORRELATION 

Distinct43
Distinct (%)43.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean48.37
Minimum10
Maximum208
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-05-10T21:19:39.103078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10
5-th percentile17
Q128
median44
Q353.25
95-th percentile74
Maximum208
Range198
Interquartile range (IQR)25.25

Descriptive statistics

Standard deviation35.59215
Coefficient of variation (CV)0.73583108
Kurtosis12.629588
Mean48.37
Median Absolute Deviation (MAD)13
Skewness3.3260217
Sum4837
Variance1266.8011
MonotonicityNot monotonic
2024-05-10T21:19:39.580009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
49 9
 
9.0%
28 8
 
8.0%
44 6
 
6.0%
42 4
 
4.0%
66 4
 
4.0%
54 4
 
4.0%
50 3
 
3.0%
29 3
 
3.0%
25 3
 
3.0%
51 3
 
3.0%
Other values (33) 53
53.0%
ValueCountFrequency (%)
10 2
2.0%
12 1
 
1.0%
15 1
 
1.0%
17 2
2.0%
18 1
 
1.0%
19 1
 
1.0%
20 1
 
1.0%
21 2
2.0%
24 2
2.0%
25 3
3.0%
ValueCountFrequency (%)
208 2
2.0%
199 2
2.0%
93 1
 
1.0%
73 2
2.0%
69 1
 
1.0%
66 4
4.0%
65 2
2.0%
64 2
2.0%
63 1
 
1.0%
59 2
2.0%

진료과목내용
Categorical

HIGH CORRELATION 

Distinct28
Distinct (%)28.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
정신건강의학과
30 
신경과, 정신건강의학과
10 
내과, 정신건강의학과, 가정의학과
9 
내과, 신경과, 정신건강의학과, 가정의학과
7 
내과, 정신건강의학과
5 
Other values (23)
39 

Length

Max length58
Median length53
Mean length19.16
Min length7

Unique

Unique8 ?
Unique (%)8.0%

Sample

1st row정신건강의학과
2nd row정신건강의학과
3rd row내과, 신경과, 정신건강의학과
4th row내과, 신경과, 정신건강의학과, 소아청소년과, 가정의학과, 침구과
5th row정신건강의학과, 가정의학과

Common Values

ValueCountFrequency (%)
정신건강의학과 30
30.0%
신경과, 정신건강의학과 10
 
10.0%
내과, 정신건강의학과, 가정의학과 9
 
9.0%
내과, 신경과, 정신건강의학과, 가정의학과 7
 
7.0%
내과, 정신건강의학과 5
 
5.0%
내과, 신경과, 정신건강의학과 3
 
3.0%
내과, 정신건강의학과, 정형외과, 가정의학과 2
 
2.0%
내과, 신경과, 정신건강의학과, 산부인과, 소아청소년과, 이비인후과, 피부과, 비뇨의학과, 가정의학과 2
 
2.0%
내과, 신경과, 정신건강의학과, 소아청소년과, 가정의학과, 침구과 2
 
2.0%
정신건강의학과, 가정의학과 2
 
2.0%
Other values (18) 28
28.0%

Length

2024-05-10T21:19:40.110633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
정신건강의학과 100
31.9%
내과 52
16.6%
가정의학과 44
14.1%
신경과 41
13.1%
소아청소년과 16
 
5.1%
재활의학과 8
 
2.6%
피부과 8
 
2.6%
비뇨의학과 7
 
2.2%
외과 6
 
1.9%
산부인과 6
 
1.9%
Other values (10) 25
 
8.0%

연면적(㎡)
Real number (ℝ)

HIGH CORRELATION 

Distinct67
Distinct (%)67.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4289.4719
Minimum783.34
Maximum21889.07
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-05-10T21:19:40.539181image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum783.34
5-th percentile1579.805
Q12602
median3654.065
Q34713.56
95-th percentile8209.003
Maximum21889.07
Range21105.73
Interquartile range (IQR)2111.56

Descriptive statistics

Standard deviation3429.1462
Coefficient of variation (CV)0.79943318
Kurtosis14.249936
Mean4289.4719
Median Absolute Deviation (MAD)1055.78
Skewness3.44611
Sum428947.19
Variance11759043
MonotonicityNot monotonic
2024-05-10T21:19:40.962707image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
3928.48 2
 
2.0%
2336.46 2
 
2.0%
4713.56 2
 
2.0%
4602.66 2
 
2.0%
2782.9 2
 
2.0%
4716.0 2
 
2.0%
2654.88 2
 
2.0%
4089.75 2
 
2.0%
8120.0 2
 
2.0%
2602.0 2
 
2.0%
Other values (57) 80
80.0%
ValueCountFrequency (%)
783.34 1
1.0%
1127.67 1
1.0%
1440.34 1
1.0%
1451.08 1
1.0%
1498.2 1
1.0%
1584.1 1
1.0%
1606.9 1
1.0%
1641.98 1
1.0%
1736.74 2
2.0%
1790.12 1
1.0%
ValueCountFrequency (%)
21889.07 2
2.0%
15243.52 2
2.0%
9900.06 1
1.0%
8120.0 2
2.0%
7404.71 1
1.0%
7062.6 2
2.0%
6102.0 2
2.0%
6060.08 1
1.0%
5765.38 1
1.0%
5730.35 1
1.0%

소재지도로명주소
Text

Distinct64
Distinct (%)64.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2024-05-10T21:19:41.494894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length79
Median length55.5
Mean length34.14
Min length20

Characters and Unicode

Total characters3414
Distinct characters189
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

Unique31 ?
Unique (%)31.0%

Sample

1st row경기도 가평군 청평면 경춘로 791-11
2nd row경기도 가평군 청평면 경춘로 791-11
3rd row경기도 고양시 덕양구 원당로 139 (주교동)
4th row경기도 고양시 일산동구 중산로157번길 49, 대산타운 110,201~205,301,401,501,601호 (중산동)
5th row경기도 고양시 일산동구 일산로 86 (백석동, 한국음주문화센터)
ValueCountFrequency (%)
경기도 100
 
15.3%
부천시 13
 
2.0%
고양시 11
 
1.7%
용인시 10
 
1.5%
원미구 9
 
1.4%
중부대로 8
 
1.2%
의정부시 7
 
1.1%
기흥구 7
 
1.1%
일산동구 6
 
0.9%
평화로 6
 
0.9%
Other values (259) 477
72.9%
2024-05-10T21:19:42.494678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
556
 
16.3%
1 154
 
4.5%
, 150
 
4.4%
경 116
 
3.4%
기 111
 
3.3%
도 107
 
3.1%
2 104
 
3.0%
로 101
 
3.0%
시 98
 
2.9%
동 93
 
2.7%
Other values (179) 1824
53.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1829
53.6%
Decimal Number 681
 
19.9%
Space Separator 556
 
16.3%
Other Punctuation 150
 
4.4%
Close Punctuation 77
 
2.3%
Open Punctuation 77
 
2.3%
Dash Punctuation 20
 
0.6%
Math Symbol 20
 
0.6%
Uppercase Letter 4
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
경 116
 
6.3%
기 111
 
6.1%
도 107
 
5.9%
로 101
 
5.5%
시 98
 
5.4%
동 93
 
5.1%
층 54
 
3.0%
구 51
 
2.8%
원 43
 
2.4%
부 41
 
2.2%
Other values (159) 1014
55.4%
Decimal Number
ValueCountFrequency (%)
1 154
22.6%
2 104
15.3%
0 90
13.2%
4 61
 
9.0%
7 61
 
9.0%
5 54
 
7.9%
3 50
 
7.3%
9 41
 
6.0%
6 34
 
5.0%
8 32
 
4.7%
Uppercase Letter
ValueCountFrequency (%)
B 2
50.0%
V 1
25.0%
M 1
25.0%
Math Symbol
ValueCountFrequency (%)
~ 19
95.0%
∼ 1
 
5.0%
Space Separator
ValueCountFrequency (%)
556
100.0%
Other Punctuation
ValueCountFrequency (%)
, 150
100.0%
Close Punctuation
ValueCountFrequency (%)
) 77
100.0%
Open Punctuation
ValueCountFrequency (%)
( 77
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 20
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1829
53.6%
Common 1581
46.3%
Latin 4
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
경 116
 
6.3%
기 111
 
6.1%
도 107
 
5.9%
로 101
 
5.5%
시 98
 
5.4%
동 93
 
5.1%
층 54
 
3.0%
구 51
 
2.8%
원 43
 
2.4%
부 41
 
2.2%
Other values (159) 1014
55.4%
Common
ValueCountFrequency (%)
556
35.2%
1 154
 
9.7%
, 150
 
9.5%
2 104
 
6.6%
0 90
 
5.7%
) 77
 
4.9%
( 77
 
4.9%
4 61
 
3.9%
7 61
 
3.9%
5 54
 
3.4%
Other values (7) 197
 
12.5%
Latin
ValueCountFrequency (%)
B 2
50.0%
V 1
25.0%
M 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1829
53.6%
ASCII 1584
46.4%
Math Operators 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
556
35.1%
1 154
 
9.7%
, 150
 
9.5%
2 104
 
6.6%
0 90
 
5.7%
) 77
 
4.9%
( 77
 
4.9%
4 61
 
3.9%
7 61
 
3.9%
5 54
 
3.4%
Other values (9) 200
 
12.6%
Hangul
ValueCountFrequency (%)
경 116
 
6.3%
기 111
 
6.1%
도 107
 
5.9%
로 101
 
5.5%
시 98
 
5.4%
동 93
 
5.1%
층 54
 
3.0%
구 51
 
2.8%
원 43
 
2.4%
부 41
 
2.2%
Other values (159) 1014
55.4%
Math Operators
ValueCountFrequency (%)
∼ 1
100.0%

소재지지번주소
Text

Distinct64
Distinct (%)64.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2024-05-10T21:19:43.008405image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length57
Median length39
Mean length27.2
Min length17

Characters and Unicode

Total characters2720
Distinct characters170
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

Unique31 ?
Unique (%)31.0%

Sample

1st row경기도 가평군 청평면 441번지 43호
2nd row경기도 가평군 청평면 441번지 43호
3rd row경기도 고양시 덕양구 주교동 554번지 3호 (지하1층,1~5층)
4th row경기도 고양시 일산동구 중산동 1666-4 대산타운 110,201~205,301,401,501,601호
5th row경기도 고양시 일산동구 백석동 1241번지 한국음주문화센터
ValueCountFrequency (%)
경기도 100
 
17.2%
부천시 13
 
2.2%
고양시 11
 
1.9%
용인시 10
 
1.7%
원미구 9
 
1.5%
1호 7
 
1.2%
기흥구 7
 
1.2%
의정부시 7
 
1.2%
남양주시 6
 
1.0%
일산동구 6
 
1.0%
Other values (221) 406
69.8%
2024-05-10T21:19:44.003206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
482
 
17.7%
1 109
 
4.0%
기 109
 
4.0%
도 103
 
3.8%
경 102
 
3.8%
시 98
 
3.6%
동 90
 
3.3%
지 87
 
3.2%
번 79
 
2.9%
4 65
 
2.4%
Other values (160) 1396
51.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1612
59.3%
Decimal Number 514
 
18.9%
Space Separator 482
 
17.7%
Other Punctuation 47
 
1.7%
Dash Punctuation 43
 
1.6%
Math Symbol 12
 
0.4%
Close Punctuation 4
 
0.1%
Open Punctuation 4
 
0.1%
Uppercase Letter 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 109
 
6.8%
도 103
 
6.4%
경 102
 
6.3%
시 98
 
6.1%
동 90
 
5.6%
지 87
 
5.4%
번 79
 
4.9%
구 50
 
3.1%
호 39
 
2.4%
층 38
 
2.4%
Other values (142) 817
50.7%
Decimal Number
ValueCountFrequency (%)
1 109
21.2%
4 65
12.6%
2 62
12.1%
5 50
9.7%
6 47
9.1%
0 42
 
8.2%
7 41
 
8.0%
3 41
 
8.0%
9 29
 
5.6%
8 28
 
5.4%
Uppercase Letter
ValueCountFrequency (%)
V 1
50.0%
M 1
50.0%
Space Separator
ValueCountFrequency (%)
482
100.0%
Other Punctuation
ValueCountFrequency (%)
, 47
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 43
100.0%
Math Symbol
ValueCountFrequency (%)
~ 12
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1612
59.3%
Common 1106
40.7%
Latin 2
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 109
 
6.8%
도 103
 
6.4%
경 102
 
6.3%
시 98
 
6.1%
동 90
 
5.6%
지 87
 
5.4%
번 79
 
4.9%
구 50
 
3.1%
호 39
 
2.4%
층 38
 
2.4%
Other values (142) 817
50.7%
Common
ValueCountFrequency (%)
482
43.6%
1 109
 
9.9%
4 65
 
5.9%
2 62
 
5.6%
5 50
 
4.5%
6 47
 
4.2%
, 47
 
4.2%
- 43
 
3.9%
0 42
 
3.8%
7 41
 
3.7%
Other values (6) 118
 
10.7%
Latin
ValueCountFrequency (%)
V 1
50.0%
M 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1612
59.3%
ASCII 1108
40.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
482
43.5%
1 109
 
9.8%
4 65
 
5.9%
2 62
 
5.6%
5 50
 
4.5%
6 47
 
4.2%
, 47
 
4.2%
- 43
 
3.9%
0 42
 
3.8%
7 41
 
3.7%
Other values (8) 120
 
10.8%
Hangul
ValueCountFrequency (%)
기 109
 
6.8%
도 103
 
6.4%
경 102
 
6.3%
시 98
 
6.1%
동 90
 
5.6%
지 87
 
5.4%
번 79
 
4.9%
구 50
 
3.1%
호 39
 
2.4%
층 38
 
2.4%
Other values (142) 817
50.7%

소재지우편번호
Text

Distinct58
Distinct (%)58.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2024-05-10T21:19:44.479727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length5.06
Min length5

Characters and Unicode

Total characters506
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

Unique25 ?
Unique (%)25.0%

Sample

1st row12451
2nd row12451
3rd row10298
4th row10338
5th row10450
ValueCountFrequency (%)
17089 6
 
6.0%
12663 4
 
4.0%
11927 3
 
3.0%
12223 3
 
3.0%
12025 3
 
3.0%
17182 2
 
2.0%
15457 2
 
2.0%
11757 2
 
2.0%
14491 2
 
2.0%
17392 2
 
2.0%
Other values (48) 71
71.0%
2024-05-10T21:19:45.364858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 133
26.3%
2 52
 
10.3%
0 51
 
10.1%
4 48
 
9.5%
3 41
 
8.1%
7 39
 
7.7%
8 39
 
7.7%
6 39
 
7.7%
5 39
 
7.7%
9 22
 
4.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 503
99.4%
Dash Punctuation 3
 
0.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 133
26.4%
2 52
 
10.3%
0 51
 
10.1%
4 48
 
9.5%
3 41
 
8.2%
7 39
 
7.8%
8 39
 
7.8%
6 39
 
7.8%
5 39
 
7.8%
9 22
 
4.4%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 506
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 133
26.3%
2 52
 
10.3%
0 51
 
10.1%
4 48
 
9.5%
3 41
 
8.1%
7 39
 
7.7%
8 39
 
7.7%
6 39
 
7.7%
5 39
 
7.7%
9 22
 
4.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 506
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 133
26.3%
2 52
 
10.3%
0 51
 
10.1%
4 48
 
9.5%
3 41
 
8.1%
7 39
 
7.7%
8 39
 
7.7%
6 39
 
7.7%
5 39
 
7.7%
9 22
 
4.3%

WGS84위도
Real number (ℝ)

HIGH CORRELATION 

Distinct60
Distinct (%)60.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean37.480024
Minimum37.056433
Maximum37.900051
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-05-10T21:19:45.778905image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum37.056433
5-th percentile37.122127
Q137.267785
median37.499402
Q337.684077
95-th percentile37.772405
Maximum37.900051
Range0.84361844
Interquartile range (IQR)0.41629122

Descriptive statistics

Standard deviation0.22804758
Coefficient of variation (CV)0.0060845099
Kurtosis-1.2919858
Mean37.480024
Median Absolute Deviation (MAD)0.211506
Skewness-0.093276593
Sum3748.0024
Variance0.052005697
MonotonicityNot monotonic
2024-05-10T21:19:46.195740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.250729009 6
 
6.0%
37.178461361 4
 
4.0%
37.7386114815 3
 
3.0%
37.3104770943 2
 
2.0%
37.4994017401 2
 
2.0%
37.5157868164 2
 
2.0%
37.7318847522 2
 
2.0%
37.7530805063 2
 
2.0%
37.4432907619 2
 
2.0%
37.7546998778 2
 
2.0%
Other values (50) 73
73.0%
ValueCountFrequency (%)
37.0564329129 2
2.0%
37.0897441362 2
2.0%
37.1221270912 2
2.0%
37.1649545092 1
 
1.0%
37.178461361 4
4.0%
37.1931473609 1
 
1.0%
37.2044835228 1
 
1.0%
37.2087499974 1
 
1.0%
37.2172663677 1
 
1.0%
37.2415456323 1
 
1.0%
ValueCountFrequency (%)
37.9000513558 2
2.0%
37.8444924497 1
 
1.0%
37.789003963 2
2.0%
37.7715317017 2
2.0%
37.7546998778 2
2.0%
37.7530805063 2
2.0%
37.7497190283 1
 
1.0%
37.7413021036 2
2.0%
37.7386114815 3
3.0%
37.7374181944 2
2.0%

WGS84경도
Real number (ℝ)

HIGH CORRELATION 

Distinct60
Distinct (%)60.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.02277
Minimum126.56868
Maximum127.56614
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2024-05-10T21:19:46.798043image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.56868
5-th percentile126.71184
Q1126.79015
median126.99316
Q3127.15465
95-th percentile127.47348
Maximum127.56614
Range0.99746211
Interquartile range (IQR)0.36449219

Descriptive statistics

Standard deviation0.2371156
Coefficient of variation (CV)0.0018667174
Kurtosis-0.41656781
Mean127.02277
Median Absolute Deviation (MAD)0.16381055
Skewness0.54623186
Sum12702.277
Variance0.056223809
MonotonicityNot monotonic
2024-05-10T21:19:47.322066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.1546471639 6
 
6.0%
127.5661389553 4
 
4.0%
127.3102217551 3
 
3.0%
126.9908552497 2
 
2.0%
126.7865141395 2
 
2.0%
126.775913835 2
 
2.0%
127.0477224771 2
 
2.0%
127.0709328423 2
 
2.0%
127.1275141356 2
 
2.0%
127.0437352748 2
 
2.0%
Other values (50) 73
73.0%
ValueCountFrequency (%)
126.5686768408 1
1.0%
126.6994788321 1
1.0%
126.7092233886 1
1.0%
126.7097694598 2
2.0%
126.7119521932 2
2.0%
126.7606583714 1
1.0%
126.7649138628 2
2.0%
126.775913835 2
2.0%
126.7759797566 2
2.0%
126.7772058298 2
2.0%
ValueCountFrequency (%)
127.5661389553 4
4.0%
127.4734789087 2
2.0%
127.421670646 2
2.0%
127.4157412051 2
2.0%
127.3881478567 1
 
1.0%
127.3648146702 2
2.0%
127.3102217551 3
3.0%
127.2356433043 1
 
1.0%
127.2348242997 2
2.0%
127.1837318408 1
 
1.0%

Interactions

2024-05-10T21:19:29.958146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:19:21.806603image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:19:23.348035image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:19:24.856003image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:19:26.446170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:19:28.092491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:19:30.248514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:19:22.072000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:19:23.612227image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:19:25.133367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:19:26.714658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:19:28.376573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:19:30.530912image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:19:22.343157image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:19:23.872507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:19:25.408750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:19:27.064417image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:19:28.667984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:19:30.802257image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:19:22.612185image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:19:24.139292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:19:25.673935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:19:27.309426image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:19:28.944990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:19:31.051359image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:19:22.856681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:19:24.353340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:19:25.921595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:19:27.534470image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:19:29.419921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:19:31.310780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:19:23.093485image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:19:24.594551image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:19:26.176213image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:19:27.803430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-10T21:19:29.684927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-10T21:19:47.641075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군명사업장명인허가일자영업상태명폐업일자병상수(개)의료인수(명)입원실수(개)진료과목내용연면적(㎡)소재지도로명주소소재지지번주소소재지우편번호WGS84위도WGS84경도
시군명1.0000.9980.9980.2491.0000.8720.6870.8730.8660.8100.9990.9990.9980.9710.948
사업장명0.9981.0001.0000.8801.0001.0001.0000.9980.9980.9991.0001.0000.9990.9991.000
인허가일자0.9981.0001.0000.9031.0001.0000.9980.9990.9991.0001.0001.0001.0001.0001.000
영업상태명0.2490.8800.9031.0001.0000.4820.2780.4530.0000.1940.9000.8850.8750.0000.248
폐업일자1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
병상수(개)0.8721.0001.0000.4821.0001.0000.7150.9770.6760.7430.9960.9900.9690.4700.294
의료인수(명)0.6871.0000.9980.2781.0000.7151.0000.7320.5710.9710.9980.9870.9690.3960.393
입원실수(개)0.8730.9980.9990.4531.0000.9770.7321.0000.0000.7320.9970.9900.9800.3190.236
진료과목내용0.8660.9980.9990.0001.0000.6760.5710.0001.0000.7830.9970.9970.9930.8850.745
연면적(㎡)0.8100.9991.0000.1941.0000.7430.9710.7320.7831.0001.0000.9960.9700.4880.514
소재지도로명주소0.9991.0001.0000.9001.0000.9960.9980.9970.9971.0001.0001.0001.0001.0001.000
소재지지번주소0.9991.0001.0000.8851.0000.9900.9870.9900.9970.9961.0001.0001.0001.0001.000
소재지우편번호0.9980.9991.0000.8751.0000.9690.9690.9800.9930.9701.0001.0001.0001.0001.000
WGS84위도0.9710.9991.0000.0001.0000.4700.3960.3190.8850.4881.0001.0001.0001.0000.837
WGS84경도0.9481.0001.0000.2481.0000.2940.3930.2360.7450.5141.0001.0001.0000.8371.000
2024-05-10T21:19:48.018594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군명진료과목내용영업상태명
시군명1.0000.3880.098
진료과목내용0.3881.0000.000
영업상태명0.0980.0001.000
2024-05-10T21:19:48.295136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
병상수(개)의료인수(명)입원실수(개)연면적(㎡)WGS84위도WGS84경도시군명영업상태명진료과목내용
병상수(개)1.0000.7630.9250.768-0.0980.0750.5020.3500.329
의료인수(명)0.7631.0000.7630.751-0.1580.0710.3390.1780.216
입원실수(개)0.9250.7631.0000.711-0.009-0.0440.5050.3260.000
연면적(㎡)0.7680.7510.7111.000-0.1240.1960.4640.1230.375
WGS84위도-0.098-0.158-0.009-0.1241.000-0.2430.7700.0000.513
WGS84경도0.0750.071-0.0440.196-0.2431.0000.6870.0980.334
시군명0.5020.3390.5050.4640.7700.6871.0000.0980.388
영업상태명0.3500.1780.3260.1230.0000.0980.0981.0000.000
진료과목내용0.3290.2160.0000.3750.5130.3340.3880.0001.000

Missing values

2024-05-10T21:19:31.768243image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-10T21:19:32.426203image/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

시군명사업장명인허가일자영업상태명폐업일자병상수(개)의료기관종별명의료인수(명)입원실수(개)진료과목내용연면적(㎡)소재지도로명주소소재지지번주소소재지우편번호WGS84위도WGS84경도
0가평군청평우리병원2005-02-15영업/정상<NA>213정신병원1949정신건강의학과3928.48경기도 가평군 청평면 경춘로 791-11경기도 가평군 청평면 441번지 43호1245137.737418127.415741
1가평군청평우리병원2005-02-15영업중<NA>213정신병원1949정신건강의학과3928.48경기도 가평군 청평면 경춘로 791-11경기도 가평군 청평면 441번지 43호1245137.737418127.415741
2고양시늘푸른병원2004-02-19영업/정상<NA>116정신병원821내과, 신경과, 정신건강의학과1736.74경기도 고양시 덕양구 원당로 139 (주교동)경기도 고양시 덕양구 주교동 554번지 3호 (지하1층,1~5층)1029837.663622126.840116
3고양시의료법인상록의료재단화정병원2009-11-06영업/정상<NA>212정신병원2244내과, 신경과, 정신건강의학과, 소아청소년과, 가정의학과, 침구과2574.45경기도 고양시 일산동구 중산로157번길 49, 대산타운 110,201~205,301,401,501,601호 (중산동)경기도 고양시 일산동구 중산동 1666-4 대산타운 110,201~205,301,401,501,601호1033837.684077126.77918
4고양시카프성모병원2004-02-17영업/정상<NA>149정신병원1828정신건강의학과, 가정의학과2923.26경기도 고양시 일산동구 일산로 86 (백석동, 한국음주문화센터)경기도 고양시 일산동구 백석동 1241번지 한국음주문화센터1045037.645157126.791062
5고양시연세서울병원2009-12-02영업/정상<NA>236정신병원2149내과, 정신건강의학과, 가정의학과3035.97경기도 고양시 일산동구 중앙로 1200, 삼희골드프라자 5,6,7,9층 902호 (마두동)경기도 고양시 일산동구 마두동 798-1 삼희골드프라자 5,6,7,9층 902호1041437.653798126.777206
6고양시라엘마음병원2011-10-07영업/정상<NA>213정신병원1944내과, 신경과, 정신건강의학과2293.83경기도 고양시 덕양구 중앙로 628, 예일프라자 2층(202호제외),6층(607,608),7층호 (화정동)경기도 고양시 덕양구 화정동 1148-1 예일프라자1050337.627532126.82891
7고양시고양정신병원1999-03-04영업/정상<NA>274정신병원2453내과, 정신건강의학과, 가정의학과6102.0경기도 고양시 덕양구 통일로1102번길 46 (내유동)경기도 고양시 덕양구 내유동 294-2번지1026437.711499126.854566
8고양시카프성모병원2004-02-17영업중<NA>149정신병원1428정신건강의학과, 가정의학과2923.26경기도 고양시 일산동구 일산로 86 (백석동, 한국음주문화센터)경기도 고양시 일산동구 백석동 1241번지 한국음주문화센터1045037.645157126.791062
9고양시의료법인상록의료재단화정병원2009-11-06영업중<NA>212정신병원2144내과, 신경과, 정신건강의학과, 소아청소년과, 가정의학과, 침구과2748.58경기도 고양시 일산동구 중산로157번길 49, 대산타운 106~109, 110, 201~205, 301, 401, 501, 601호 (중산동)경기도 고양시 일산동구 중산동 1666-4 대산타운1033837.684077126.77918
시군명사업장명인허가일자영업상태명폐업일자병상수(개)의료기관종별명의료인수(명)입원실수(개)진료과목내용연면적(㎡)소재지도로명주소소재지지번주소소재지우편번호WGS84위도WGS84경도
90이천시성안드레아병원1990-09-03폐업2022-01-31282정신병원3366정신건강의학과9900.06경기도 이천시 마장면 서이천로320번길 109-84, 성안드레아병원경기도 이천시 마장면 표교리 586-2번지 성안드레아병원1738437.246114127.388148
91파주시민들레병원2002-10-01영업/정상<NA>240정신병원1554정신건강의학과3978.0경기도 파주시 탄현면 소리개길 74-17, 민들레병원경기도 파주시 탄현면 법흥리 376번지 4호 민들레병원1085837.789004126.709769
92파주시민들레병원2002-10-01영업중<NA>240정신병원1554정신건강의학과3978.0경기도 파주시 탄현면 소리개길 74-17, 민들레병원경기도 파주시 탄현면 법흥리 376번지 4호 민들레병원1085837.789004126.709769
93포천시인화병원2014-12-29영업/정상<NA>252정신병원1942내과, 정신건강의학과, 가정의학과5050.61경기도 포천시 소흘읍 광릉수목원로 745경기도 포천시 소흘읍 이곡리 48-6번지1118737.771532127.156531
94포천시인화병원2014-12-29영업중<NA>252정신병원1942내과, 정신건강의학과, 가정의학과5050.61경기도 포천시 소흘읍 광릉수목원로 745경기도 포천시 소흘읍 이곡리 48-6번지1118737.771532127.156531
95화성시새샘병원2012-07-05영업/정상<NA>134정신병원1025정신건강의학과1923.66경기도 화성시 떡전골로 112-13 (진안동)경기도 화성시 진안동 525번지 14호1839037.20875127.033463
96화성시의료법인 승민의료재단 화성초록병원2011-05-23영업/정상<NA>244정신병원2049정신건강의학과4177.58경기도 화성시 양감면 사격장길 133-25경기도 화성시 양감면 사창리 808번지 10호1862637.089744126.956892
97화성시메타메디병원2011-10-04영업/정상<NA>149정신병원1329내과, 신경과, 정신건강의학과, 소아청소년과, 이비인후과2662.62경기도 화성시 동탄원천로 338-7, 동탄V프라자 3~7층 (능동)경기도 화성시 능동 1066번지 4호 동탄V프라자1842337.217266127.058849
98화성시의료법인 승민의료재단 화성초록병원2011-05-23영업중<NA>244정신병원2049정신건강의학과4177.58경기도 화성시 양감면 사격장길 133-25경기도 화성시 양감면 사창리 808번지 10호1862637.089744126.956892
99화성시의료법인 정도의료재단 아미고병원2011-01-24영업중<NA>120정신병원728내과, 신경과, 정신건강의학과, 가정의학과2924.04경기도 화성시 마도면 화성로 848-16경기도 화성시 마도면 두곡리 418번지 2호1853737.204484126.782246