Overview

Dataset statistics

Number of variables14
Number of observations1225
Missing cells837
Missing cells (%)4.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory141.3 KiB
Average record size in memory118.1 B

Variable types

Categorical2
Text5
DateTime1
Numeric6

Alerts

병상수(개) is highly overall correlated with 입원실수(개)High correlation
입원실수(개) is highly overall correlated with 병상수(개)High correlation
WGS84위도 is highly overall correlated with 시군명High correlation
WGS84경도 is highly overall correlated with 시군명High correlation
시군명 is highly overall correlated with WGS84위도 and 1 other fieldsHigh correlation
영업상태명 is highly imbalanced (50.0%)Imbalance
폐업일자 has 743 (60.7%) missing valuesMissing
소재지도로명주소 has 26 (2.1%) missing valuesMissing
소재지우편번호 has 13 (1.1%) missing valuesMissing
WGS84위도 has 26 (2.1%) missing valuesMissing
WGS84경도 has 26 (2.1%) missing valuesMissing
병상수(개) has 889 (72.6%) zerosZeros
의료인수(명) has 14 (1.1%) zerosZeros
입원실수(개) has 922 (75.3%) zerosZeros
연면적(㎡) has 24 (2.0%) zerosZeros

Reproduction

Analysis started2024-03-16 04:49:22.431425
Analysis finished2024-03-16 04:49:38.361181
Duration15.93 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군명
Categorical

HIGH CORRELATION 

Distinct32
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size9.7 KiB
고양시
148 
용인시
106 
화성시
96 
부천시
86 
안산시
 
71
Other values (27)
718 

Length

Max length4
Median length3
Mean length3.0408163
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
고양시 148
 
12.1%
용인시 106
 
8.7%
화성시 96
 
7.8%
부천시 86
 
7.0%
안산시 71
 
5.8%
안양시 69
 
5.6%
성남시 66
 
5.4%
시흥시 56
 
4.6%
수원시 52
 
4.2%
남양주 48
 
3.9%
Other values (22) 427
34.9%

Length

2024-03-16T04:49:38.605473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
고양시 148
 
12.1%
용인시 106
 
8.7%
화성시 96
 
7.8%
부천시 86
 
7.0%
안산시 71
 
5.8%
안양시 69
 
5.6%
성남시 66
 
5.4%
시흥시 56
 
4.6%
수원시 52
 
4.2%
남양주 48
 
3.9%
Other values (22) 427
34.9%

사업장명
Text

Distinct1065
Distinct (%)86.9%
Missing0
Missing (%)0.0%
Memory size9.7 KiB
2024-03-16T04:49:39.084081image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length22
Mean length8.1126531
Min length3

Characters and Unicode

Total characters9938
Distinct characters391
Distinct categories8 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique955 ?
Unique (%)78.0%

Sample

1st row최피부과의원
2nd row금빛여성의원
3rd row강현철의원
4th row늘푸른의원
5th row현리중앙의원
ValueCountFrequency (%)
서울산부인과의원 9
 
0.7%
애플산부인과의원 8
 
0.6%
로앤산부인과의원 7
 
0.6%
성모의원 6
 
0.5%
중앙산부인과의원 6
 
0.5%
하나산부인과의원 5
 
0.4%
제일산부인과의원 5
 
0.4%
의원 4
 
0.3%
여성의원 3
 
0.2%
행복한산부인과의원 3
 
0.2%
Other values (1085) 1213
95.6%
2024-03-16T04:49:40.026972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
의 1320
 
13.3%
원 1239
 
12.5%
과 794
 
8.0%
인 601
 
6.0%
산 577
 
5.8%
부 563
 
5.7%
성 214
 
2.2%
이 125
 
1.3%
정 118
 
1.2%
미 109
 
1.1%
Other values (381) 4278
43.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 9795
98.6%
Decimal Number 52
 
0.5%
Space Separator 44
 
0.4%
Uppercase Letter 27
 
0.3%
Close Punctuation 8
 
0.1%
Open Punctuation 7
 
0.1%
Other Punctuation 4
 
< 0.1%
Lowercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
의 1320
 
13.5%
원 1239
 
12.6%
과 794
 
8.1%
인 601
 
6.1%
산 577
 
5.9%
부 563
 
5.7%
성 214
 
2.2%
이 125
 
1.3%
정 118
 
1.2%
미 109
 
1.1%
Other values (355) 4135
42.2%
Uppercase Letter
ValueCountFrequency (%)
C 5
18.5%
S 5
18.5%
B 3
11.1%
L 2
 
7.4%
H 2
 
7.4%
K 2
 
7.4%
J 2
 
7.4%
O 2
 
7.4%
P 1
 
3.7%
M 1
 
3.7%
Other values (2) 2
 
7.4%
Decimal Number
ValueCountFrequency (%)
5 11
21.2%
6 11
21.2%
3 11
21.2%
2 9
17.3%
1 8
15.4%
7 1
 
1.9%
4 1
 
1.9%
Other Punctuation
ValueCountFrequency (%)
. 2
50.0%
, 1
25.0%
& 1
25.0%
Space Separator
ValueCountFrequency (%)
44
100.0%
Close Punctuation
ValueCountFrequency (%)
) 8
100.0%
Open Punctuation
ValueCountFrequency (%)
( 7
100.0%
Lowercase Letter
ValueCountFrequency (%)
s 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 9794
98.6%
Common 115
 
1.2%
Latin 28
 
0.3%
Han 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
의 1320
 
13.5%
원 1239
 
12.7%
과 794
 
8.1%
인 601
 
6.1%
산 577
 
5.9%
부 563
 
5.7%
성 214
 
2.2%
이 125
 
1.3%
정 118
 
1.2%
미 109
 
1.1%
Other values (354) 4134
42.2%
Common
ValueCountFrequency (%)
44
38.3%
5 11
 
9.6%
6 11
 
9.6%
3 11
 
9.6%
2 9
 
7.8%
) 8
 
7.0%
1 8
 
7.0%
( 7
 
6.1%
. 2
 
1.7%
, 1
 
0.9%
Other values (3) 3
 
2.6%
Latin
ValueCountFrequency (%)
C 5
17.9%
S 5
17.9%
B 3
10.7%
L 2
 
7.1%
H 2
 
7.1%
K 2
 
7.1%
J 2
 
7.1%
O 2
 
7.1%
P 1
 
3.6%
M 1
 
3.6%
Other values (3) 3
10.7%
Han
ValueCountFrequency (%)
愛 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 9794
98.6%
ASCII 143
 
1.4%
CJK 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
의 1320
 
13.5%
원 1239
 
12.7%
과 794
 
8.1%
인 601
 
6.1%
산 577
 
5.9%
부 563
 
5.7%
성 214
 
2.2%
이 125
 
1.3%
정 118
 
1.2%
미 109
 
1.1%
Other values (354) 4134
42.2%
ASCII
ValueCountFrequency (%)
44
30.8%
5 11
 
7.7%
6 11
 
7.7%
3 11
 
7.7%
2 9
 
6.3%
) 8
 
5.6%
1 8
 
5.6%
( 7
 
4.9%
C 5
 
3.5%
S 5
 
3.5%
Other values (16) 24
16.8%
CJK
ValueCountFrequency (%)
愛 1
100.0%

인허가일자
Date

Distinct1102
Distinct (%)90.0%
Missing0
Missing (%)0.0%
Memory size9.7 KiB
Minimum1959-12-01 00:00:00
Maximum2024-02-27 00:00:00
2024-03-16T04:49:40.440867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T04:49:40.986032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

영업상태명
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size9.7 KiB
영업/정상
713 
폐업
478 
영업중
 
24
휴업
 
5
취소/말소/만료/정지/중지
 
5

Length

Max length14
Median length5
Mean length3.8146939
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업/정상 713
58.2%
폐업 478
39.0%
영업중 24
 
2.0%
휴업 5
 
0.4%
취소/말소/만료/정지/중지 5
 
0.4%

Length

2024-03-16T04:49:41.679325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-16T04:49:42.177306image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 713
58.2%
폐업 478
39.0%
영업중 24
 
2.0%
휴업 5
 
0.4%
취소/말소/만료/정지/중지 5
 
0.4%

폐업일자
Text

MISSING 

Distinct455
Distinct (%)94.4%
Missing743
Missing (%)60.7%
Memory size9.7 KiB
2024-03-16T04:49:43.102696image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length10
Median length10
Mean length9.7614108
Min length5

Characters and Unicode

Total characters4705
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

Unique429 ?
Unique (%)89.0%

Sample

1st row2008-12-22
2nd row2002-12-23
3rd row1992-12-21
4th row2015-12-01
5th row2005-01-15
ValueCountFrequency (%)
2015-01-30 3
 
0.6%
2012-10-11 2
 
0.4%
2010-12-31 2
 
0.4%
2009-08-31 2
 
0.4%
2009-09-30 2
 
0.4%
2010-02-01 2
 
0.4%
2011-12-30 2
 
0.4%
2015-12-31 2
 
0.4%
2016-02-29 2
 
0.4%
2012-12-31 2
 
0.4%
Other values (445) 461
95.6%
2024-03-16T04:49:44.480586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1202
25.5%
- 918
19.5%
2 857
18.2%
1 749
15.9%
3 209
 
4.4%
9 177
 
3.8%
4 138
 
2.9%
5 119
 
2.5%
8 114
 
2.4%
6 113
 
2.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3787
80.5%
Dash Punctuation 918
 
19.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1202
31.7%
2 857
22.6%
1 749
19.8%
3 209
 
5.5%
9 177
 
4.7%
4 138
 
3.6%
5 119
 
3.1%
8 114
 
3.0%
6 113
 
3.0%
7 109
 
2.9%
Dash Punctuation
ValueCountFrequency (%)
- 918
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4705
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1202
25.5%
- 918
19.5%
2 857
18.2%
1 749
15.9%
3 209
 
4.4%
9 177
 
3.8%
4 138
 
2.9%
5 119
 
2.5%
8 114
 
2.4%
6 113
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4705
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1202
25.5%
- 918
19.5%
2 857
18.2%
1 749
15.9%
3 209
 
4.4%
9 177
 
3.8%
4 138
 
2.9%
5 119
 
2.5%
8 114
 
2.4%
6 113
 
2.4%

병상수(개)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct30
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.8538776
Minimum0
Maximum29
Zeros889
Zeros (%)72.6%
Negative0
Negative (%)0.0%
Memory size10.9 KiB
2024-03-16T04:49:45.163575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile22
Maximum29
Range29
Interquartile range (IQR)1

Descriptive statistics

Standard deviation6.6950892
Coefficient of variation (CV)2.3459623
Kurtosis6.7779376
Mean2.8538776
Median Absolute Deviation (MAD)0
Skewness2.7456457
Sum3496
Variance44.824219
MonotonicityNot monotonic
2024-03-16T04:49:45.672086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=30)
ValueCountFrequency (%)
0 889
72.6%
2 35
 
2.9%
1 35
 
2.9%
3 32
 
2.6%
29 25
 
2.0%
10 25
 
2.0%
9 24
 
2.0%
4 22
 
1.8%
6 19
 
1.6%
5 15
 
1.2%
Other values (20) 104
 
8.5%
ValueCountFrequency (%)
0 889
72.6%
1 35
 
2.9%
2 35
 
2.9%
3 32
 
2.6%
4 22
 
1.8%
5 15
 
1.2%
6 19
 
1.6%
7 12
 
1.0%
8 12
 
1.0%
9 24
 
2.0%
ValueCountFrequency (%)
29 25
2.0%
28 10
 
0.8%
27 4
 
0.3%
26 4
 
0.3%
25 4
 
0.3%
24 8
 
0.7%
23 4
 
0.3%
22 6
 
0.5%
21 3
 
0.2%
20 4
 
0.3%

의료인수(명)
Real number (ℝ)

ZEROS 

Distinct34
Distinct (%)2.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.717551
Minimum0
Maximum90
Zeros14
Zeros (%)1.1%
Negative0
Negative (%)0.0%
Memory size10.9 KiB
2024-03-16T04:49:46.078578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q11
median1
Q32
95-th percentile9
Maximum90
Range90
Interquartile range (IQR)1

Descriptive statistics

Standard deviation5.8543231
Coefficient of variation (CV)2.1542643
Kurtosis80.895423
Mean2.717551
Median Absolute Deviation (MAD)0
Skewness7.8379056
Sum3329
Variance34.273099
MonotonicityNot monotonic
2024-03-16T04:49:46.480118image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=34)
ValueCountFrequency (%)
1 768
62.7%
2 203
 
16.6%
3 71
 
5.8%
4 32
 
2.6%
5 27
 
2.2%
6 18
 
1.5%
0 14
 
1.1%
8 13
 
1.1%
9 12
 
1.0%
7 11
 
0.9%
Other values (24) 56
 
4.6%
ValueCountFrequency (%)
0 14
 
1.1%
1 768
62.7%
2 203
 
16.6%
3 71
 
5.8%
4 32
 
2.6%
5 27
 
2.2%
6 18
 
1.5%
7 11
 
0.9%
8 13
 
1.1%
9 12
 
1.0%
ValueCountFrequency (%)
90 1
 
0.1%
65 1
 
0.1%
63 1
 
0.1%
61 1
 
0.1%
52 1
 
0.1%
47 3
0.2%
34 1
 
0.1%
32 2
0.2%
26 2
0.2%
25 1
 
0.1%

입원실수(개)
Real number (ℝ)

HIGH CORRELATION  ZEROS 

Distinct22
Distinct (%)1.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1.6359184
Minimum0
Maximum26
Zeros922
Zeros (%)75.3%
Negative0
Negative (%)0.0%
Memory size10.9 KiB
2024-03-16T04:49:46.914280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile10
Maximum26
Range26
Interquartile range (IQR)0

Descriptive statistics

Standard deviation3.8792665
Coefficient of variation (CV)2.3713081
Kurtosis8.5997875
Mean1.6359184
Median Absolute Deviation (MAD)0
Skewness2.8807086
Sum2004
Variance15.048709
MonotonicityNot monotonic
2024-03-16T04:49:47.298916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=22)
ValueCountFrequency (%)
0 922
75.3%
1 53
 
4.3%
2 32
 
2.6%
3 28
 
2.3%
4 23
 
1.9%
9 22
 
1.8%
8 21
 
1.7%
5 20
 
1.6%
7 20
 
1.6%
10 19
 
1.6%
Other values (12) 65
 
5.3%
ValueCountFrequency (%)
0 922
75.3%
1 53
 
4.3%
2 32
 
2.6%
3 28
 
2.3%
4 23
 
1.9%
5 20
 
1.6%
6 12
 
1.0%
7 20
 
1.6%
8 21
 
1.7%
9 22
 
1.8%
ValueCountFrequency (%)
26 2
 
0.2%
20 3
 
0.2%
19 1
 
0.1%
18 9
0.7%
17 10
0.8%
16 5
0.4%
15 5
0.4%
14 5
0.4%
13 3
 
0.2%
12 6
0.5%

연면적(㎡)
Real number (ℝ)

ZEROS 

Distinct1094
Distinct (%)89.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean411.14962
Minimum0
Maximum7995.88
Zeros24
Zeros (%)2.0%
Negative0
Negative (%)0.0%
Memory size10.9 KiB
2024-03-16T04:49:47.714995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile72.298
Q1133.01
median205.34
Q3404.7
95-th percentile1430.222
Maximum7995.88
Range7995.88
Interquartile range (IQR)271.69

Descriptive statistics

Standard deviation679.54096
Coefficient of variation (CV)1.6527827
Kurtosis47.537447
Mean411.14962
Median Absolute Deviation (MAD)93.3
Skewness5.8198355
Sum503658.28
Variance461775.91
MonotonicityNot monotonic
2024-03-16T04:49:48.292892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 24
 
2.0%
135.0 6
 
0.5%
162.0 4
 
0.3%
221.0 4
 
0.3%
165.0 4
 
0.3%
1.0 3
 
0.2%
100.0 3
 
0.2%
171.0 3
 
0.2%
50.0 3
 
0.2%
83.0 3
 
0.2%
Other values (1084) 1168
95.3%
ValueCountFrequency (%)
0.0 24
2.0%
1.0 3
 
0.2%
10.03 1
 
0.1%
24.58 1
 
0.1%
34.89 1
 
0.1%
36.0 1
 
0.1%
41.4 1
 
0.1%
42.4 1
 
0.1%
47.25 1
 
0.1%
48.08 1
 
0.1%
ValueCountFrequency (%)
7995.88 2
0.2%
6819.96 2
0.2%
6206.99 1
0.1%
5762.0 1
0.1%
4243.48 1
0.1%
3501.1 1
0.1%
3375.9 1
0.1%
3098.57 1
0.1%
2980.52 1
0.1%
2957.88 1
0.1%

소재지도로명주소
Text

MISSING 

Distinct1152
Distinct (%)96.1%
Missing26
Missing (%)2.1%
Memory size9.7 KiB
2024-03-16T04:49:49.067202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length76
Median length54
Mean length33.428691
Min length14

Characters and Unicode

Total characters40081
Distinct characters461
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1107 ?
Unique (%)92.3%

Sample

1st row경기도 성남시 수정구 위례광장로 322, 아이플렉스 3층 306호 (창곡동)
2nd row경기도 성남시 수정구 수정로171번길 7-1, 우일프라자 2층일부, 3~6층, 8층, 9층일부 (태평동)
3rd row경기도 가평군 청평면 청평중앙로 51
4th row경기도 가평군 설악면 신천중앙로 118, 2층
5th row경기도 가평군 조종면 현창로38번길 3 (현리중앙의원)
ValueCountFrequency (%)
경기도 1199
 
14.4%
성남시 134
 
1.6%
2층 130
 
1.6%
고양시 129
 
1.5%
수원시 116
 
1.4%
3층 92
 
1.1%
용인시 85
 
1.0%
분당구 83
 
1.0%
덕양구 82
 
1.0%
부천시 80
 
1.0%
Other values (2376) 6219
74.5%
2024-03-16T04:49:50.302638image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7163
 
17.9%
, 1429
 
3.6%
시 1281
 
3.2%
동 1277
 
3.2%
경 1270
 
3.2%
기 1252
 
3.1%
도 1225
 
3.1%
로 1187
 
3.0%
1 1168
 
2.9%
2 1103
 
2.8%
Other values (451) 21726
54.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 21954
54.8%
Space Separator 7163
 
17.9%
Decimal Number 6958
 
17.4%
Other Punctuation 1437
 
3.6%
Close Punctuation 1057
 
2.6%
Open Punctuation 1057
 
2.6%
Dash Punctuation 158
 
0.4%
Math Symbol 140
 
0.3%
Uppercase Letter 137
 
0.3%
Lowercase Letter 16
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 1281
 
5.8%
동 1277
 
5.8%
경 1270
 
5.8%
기 1252
 
5.7%
도 1225
 
5.6%
로 1187
 
5.4%
구 733
 
3.3%
호 616
 
2.8%
층 523
 
2.4%
양 437
 
2.0%
Other values (396) 12153
55.4%
Uppercase Letter
ValueCountFrequency (%)
B 24
17.5%
A 22
16.1%
M 11
 
8.0%
S 11
 
8.0%
C 8
 
5.8%
I 5
 
3.6%
L 5
 
3.6%
H 5
 
3.6%
E 5
 
3.6%
O 4
 
2.9%
Other values (14) 37
27.0%
Decimal Number
ValueCountFrequency (%)
1 1168
16.8%
2 1103
15.9%
0 1042
15.0%
3 978
14.1%
4 655
9.4%
5 566
8.1%
6 432
 
6.2%
7 374
 
5.4%
8 336
 
4.8%
9 304
 
4.4%
Lowercase Letter
ValueCountFrequency (%)
e 4
25.0%
a 2
12.5%
i 2
12.5%
r 2
12.5%
d 2
12.5%
m 1
 
6.2%
o 1
 
6.2%
w 1
 
6.2%
k 1
 
6.2%
Other Punctuation
ValueCountFrequency (%)
, 1429
99.4%
. 6
 
0.4%
@ 1
 
0.1%
/ 1
 
0.1%
Math Symbol
ValueCountFrequency (%)
~ 139
99.3%
∼ 1
 
0.7%
Letter Number
ValueCountFrequency (%)
Ⅲ 3
75.0%
Ⅰ 1
 
25.0%
Space Separator
ValueCountFrequency (%)
7163
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1057
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1057
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 158
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 21954
54.8%
Common 17970
44.8%
Latin 157
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 1281
 
5.8%
동 1277
 
5.8%
경 1270
 
5.8%
기 1252
 
5.7%
도 1225
 
5.6%
로 1187
 
5.4%
구 733
 
3.3%
호 616
 
2.8%
층 523
 
2.4%
양 437
 
2.0%
Other values (396) 12153
55.4%
Latin
ValueCountFrequency (%)
B 24
15.3%
A 22
 
14.0%
M 11
 
7.0%
S 11
 
7.0%
C 8
 
5.1%
I 5
 
3.2%
L 5
 
3.2%
H 5
 
3.2%
E 5
 
3.2%
e 4
 
2.5%
Other values (25) 57
36.3%
Common
ValueCountFrequency (%)
7163
39.9%
, 1429
 
8.0%
1 1168
 
6.5%
2 1103
 
6.1%
) 1057
 
5.9%
( 1057
 
5.9%
0 1042
 
5.8%
3 978
 
5.4%
4 655
 
3.6%
5 566
 
3.1%
Other values (10) 1752
 
9.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 21954
54.8%
ASCII 18122
45.2%
Number Forms 4
 
< 0.1%
Math Operators 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
7163
39.5%
, 1429
 
7.9%
1 1168
 
6.4%
2 1103
 
6.1%
) 1057
 
5.8%
( 1057
 
5.8%
0 1042
 
5.7%
3 978
 
5.4%
4 655
 
3.6%
5 566
 
3.1%
Other values (42) 1904
 
10.5%
Hangul
ValueCountFrequency (%)
시 1281
 
5.8%
동 1277
 
5.8%
경 1270
 
5.8%
기 1252
 
5.7%
도 1225
 
5.6%
로 1187
 
5.4%
구 733
 
3.3%
호 616
 
2.8%
층 523
 
2.4%
양 437
 
2.0%
Other values (396) 12153
55.4%
Number Forms
ValueCountFrequency (%)
Ⅲ 3
75.0%
Ⅰ 1
 
25.0%
Math Operators
ValueCountFrequency (%)
∼ 1
100.0%

소재지지번주소
Text

Distinct1171
Distinct (%)95.8%
Missing3
Missing (%)0.2%
Memory size9.7 KiB
2024-03-16T04:49:50.975049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length70
Median length50
Mean length27.10802
Min length3

Characters and Unicode

Total characters33126
Distinct characters425
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1122 ?
Unique (%)91.8%

Sample

1st row경기도 성남시 수정구 창곡동 508번지 아이플렉스
2nd row경기도 성남시 수정구 태평동 3406 우일프라자
3rd row경기도 가평군 청평면 청평리 465번지 8호
4th row경기도 가평군 설악면 신천리 435번지 14호
5th row경기도 가평군 조종면 현리 265번지 12호
ValueCountFrequency (%)
경기도 1200
 
16.6%
수원시 117
 
1.6%
성남시 114
 
1.6%
고양시 101
 
1.4%
용인시 93
 
1.3%
1호 90
 
1.2%
부천시 80
 
1.1%
2층 80
 
1.1%
화성시 79
 
1.1%
안산시 70
 
1.0%
Other values (2235) 5223
72.1%
2024-03-16T04:49:52.347375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6064
 
18.3%
시 1272
 
3.8%
동 1263
 
3.8%
기 1250
 
3.8%
1 1224
 
3.7%
도 1217
 
3.7%
경 1214
 
3.7%
2 938
 
2.8%
3 883
 
2.7%
지 867
 
2.6%
Other values (415) 16934
51.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 19171
57.9%
Decimal Number 6878
 
20.8%
Space Separator 6064
 
18.3%
Dash Punctuation 499
 
1.5%
Other Punctuation 249
 
0.8%
Uppercase Letter 109
 
0.3%
Math Symbol 56
 
0.2%
Open Punctuation 40
 
0.1%
Close Punctuation 40
 
0.1%
Lowercase Letter 16
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 1272
 
6.6%
동 1263
 
6.6%
기 1250
 
6.5%
도 1217
 
6.3%
경 1214
 
6.3%
지 867
 
4.5%
호 819
 
4.3%
번 754
 
3.9%
구 725
 
3.8%
양 434
 
2.3%
Other values (358) 9356
48.8%
Uppercase Letter
ValueCountFrequency (%)
A 15
13.8%
S 11
 
10.1%
B 9
 
8.3%
M 8
 
7.3%
I 6
 
5.5%
C 6
 
5.5%
H 5
 
4.6%
E 5
 
4.6%
L 4
 
3.7%
O 4
 
3.7%
Other values (15) 36
33.0%
Decimal Number
ValueCountFrequency (%)
1 1224
17.8%
2 938
13.6%
3 883
12.8%
0 778
11.3%
4 683
9.9%
5 560
8.1%
6 501
7.3%
7 481
 
7.0%
8 429
 
6.2%
9 401
 
5.8%
Lowercase Letter
ValueCountFrequency (%)
e 4
25.0%
d 2
12.5%
a 2
12.5%
r 2
12.5%
i 2
12.5%
w 1
 
6.2%
m 1
 
6.2%
o 1
 
6.2%
k 1
 
6.2%
Other Punctuation
ValueCountFrequency (%)
, 212
85.1%
. 35
 
14.1%
/ 1
 
0.4%
@ 1
 
0.4%
Math Symbol
ValueCountFrequency (%)
~ 54
96.4%
∼ 1
 
1.8%
+ 1
 
1.8%
Letter Number
ValueCountFrequency (%)
Ⅲ 3
75.0%
Ⅰ 1
 
25.0%
Space Separator
ValueCountFrequency (%)
6064
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 499
100.0%
Open Punctuation
ValueCountFrequency (%)
( 40
100.0%
Close Punctuation
ValueCountFrequency (%)
) 40
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 19171
57.9%
Common 13826
41.7%
Latin 129
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 1272
 
6.6%
동 1263
 
6.6%
기 1250
 
6.5%
도 1217
 
6.3%
경 1214
 
6.3%
지 867
 
4.5%
호 819
 
4.3%
번 754
 
3.9%
구 725
 
3.8%
양 434
 
2.3%
Other values (358) 9356
48.8%
Latin
ValueCountFrequency (%)
A 15
 
11.6%
S 11
 
8.5%
B 9
 
7.0%
M 8
 
6.2%
I 6
 
4.7%
C 6
 
4.7%
H 5
 
3.9%
E 5
 
3.9%
L 4
 
3.1%
O 4
 
3.1%
Other values (26) 56
43.4%
Common
ValueCountFrequency (%)
6064
43.9%
1 1224
 
8.9%
2 938
 
6.8%
3 883
 
6.4%
0 778
 
5.6%
4 683
 
4.9%
5 560
 
4.1%
6 501
 
3.6%
- 499
 
3.6%
7 481
 
3.5%
Other values (11) 1215
 
8.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 19171
57.9%
ASCII 13950
42.1%
Number Forms 4
 
< 0.1%
Math Operators 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6064
43.5%
1 1224
 
8.8%
2 938
 
6.7%
3 883
 
6.3%
0 778
 
5.6%
4 683
 
4.9%
5 560
 
4.0%
6 501
 
3.6%
- 499
 
3.6%
7 481
 
3.4%
Other values (44) 1339
 
9.6%
Hangul
ValueCountFrequency (%)
시 1272
 
6.6%
동 1263
 
6.6%
기 1250
 
6.5%
도 1217
 
6.3%
경 1214
 
6.3%
지 867
 
4.5%
호 819
 
4.3%
번 754
 
3.9%
구 725
 
3.8%
양 434
 
2.3%
Other values (358) 9356
48.8%
Number Forms
ValueCountFrequency (%)
Ⅲ 3
75.0%
Ⅰ 1
 
25.0%
Math Operators
ValueCountFrequency (%)
∼ 1
100.0%

소재지우편번호
Text

MISSING 

Distinct769
Distinct (%)63.4%
Missing13
Missing (%)1.1%
Memory size9.7 KiB
2024-03-16T04:49:53.190125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length5.2128713
Min length5

Characters and Unicode

Total characters6318
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

Unique515 ?
Unique (%)42.5%

Sample

1st row13640
2nd row13292
3rd row12452
4th row12465
5th row12437
ValueCountFrequency (%)
11695 7
 
0.6%
10071 7
 
0.6%
15360 6
 
0.5%
10503 6
 
0.5%
13355 6
 
0.5%
18302 6
 
0.5%
463-824 6
 
0.5%
18261 6
 
0.5%
13618 6
 
0.5%
10500 6
 
0.5%
Other values (759) 1150
94.9%
2024-03-16T04:49:54.538456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 1574
24.9%
4 714
11.3%
0 591
 
9.4%
5 580
 
9.2%
3 523
 
8.3%
6 511
 
8.1%
8 478
 
7.6%
2 465
 
7.4%
9 383
 
6.1%
7 370
 
5.9%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 6189
98.0%
Dash Punctuation 129
 
2.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 1574
25.4%
4 714
11.5%
0 591
 
9.5%
5 580
 
9.4%
3 523
 
8.5%
6 511
 
8.3%
8 478
 
7.7%
2 465
 
7.5%
9 383
 
6.2%
7 370
 
6.0%
Dash Punctuation
ValueCountFrequency (%)
- 129
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 6318
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 1574
24.9%
4 714
11.3%
0 591
 
9.4%
5 580
 
9.2%
3 523
 
8.3%
6 511
 
8.1%
8 478
 
7.6%
2 465
 
7.4%
9 383
 
6.1%
7 370
 
5.9%

Most occurring blocks

ValueCountFrequency (%)
ASCII 6318
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 1574
24.9%
4 714
11.3%
0 591
 
9.4%
5 580
 
9.2%
3 523
 
8.3%
6 511
 
8.1%
8 478
 
7.6%
2 465
 
7.4%
9 383
 
6.1%
7 370
 
5.9%

WGS84위도
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct1031
Distinct (%)86.0%
Missing26
Missing (%)2.1%
Infinite0
Infinite (%)0.0%
Mean37.428845
Minimum36.97722
Maximum38.101672
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.9 KiB
2024-03-16T04:49:55.028176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.97722
5-th percentile37.144584
Q137.293769
median37.391226
Q337.601853
95-th percentile37.742388
Maximum38.101672
Range1.124452
Interquartile range (IQR)0.3080841

Descriptive statistics

Standard deviation0.19641506
Coefficient of variation (CV)0.0052476922
Kurtosis-0.16411203
Mean37.428845
Median Absolute Deviation (MAD)0.11753991
Skewness0.28222117
Sum44877.185
Variance0.038578876
MonotonicityNot monotonic
2024-03-16T04:49:55.650115image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.4331662207 5
 
0.4%
37.3642865126 4
 
0.3%
37.3438261411 4
 
0.3%
37.2652290262 3
 
0.2%
37.625990987 3
 
0.2%
37.3689045947 3
 
0.2%
37.1447106935 3
 
0.2%
37.3067600253 3
 
0.2%
37.5042650697 3
 
0.2%
37.3119260049 3
 
0.2%
Other values (1021) 1165
95.1%
(Missing) 26
 
2.1%
ValueCountFrequency (%)
36.9772202616 1
0.1%
36.9837904271 1
0.1%
36.9886033762 1
0.1%
36.989085519 1
0.1%
36.9899577762 1
0.1%
36.9900804842 1
0.1%
36.9914945843 1
0.1%
36.9917612086 1
0.1%
36.9922255991 1
0.1%
36.9924469835 1
0.1%
ValueCountFrequency (%)
38.1016722272 1
0.1%
38.0903278355 1
0.1%
38.0350477269 1
0.1%
38.0295532014 1
0.1%
38.0278475587 1
0.1%
38.0270087162 1
0.1%
37.9583733138 1
0.1%
37.9089967194 1
0.1%
37.9075050576 1
0.1%
37.9053739082 1
0.1%

WGS84경도
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct1031
Distinct (%)86.0%
Missing26
Missing (%)2.1%
Infinite0
Infinite (%)0.0%
Mean126.99089
Minimum126.5871
Maximum127.63996
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size10.9 KiB
2024-03-16T04:49:56.078226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.5871
5-th percentile126.7502
Q1126.83325
median127.02073
Q3127.11209
95-th percentile127.23481
Maximum127.63996
Range1.0528565
Interquartile range (IQR)0.27884294

Descriptive statistics

Standard deviation0.17315071
Coefficient of variation (CV)0.0013634892
Kurtosis0.13151262
Mean126.99089
Median Absolute Deviation (MAD)0.12165991
Skewness0.29454409
Sum152262.08
Variance0.029981168
MonotonicityNot monotonic
2024-03-16T04:49:56.511488image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.1297006478 5
 
0.4%
126.9308538464 4
 
0.3%
126.7848840878 4
 
0.3%
127.0327990111 3
 
0.2%
126.8178749714 3
 
0.2%
126.9564103302 3
 
0.2%
127.0682792246 3
 
0.2%
127.0846083156 3
 
0.2%
126.7523564778 3
 
0.2%
126.8310374164 3
 
0.2%
Other values (1021) 1165
95.1%
(Missing) 26
 
2.1%
ValueCountFrequency (%)
126.5870994059 1
0.1%
126.5877251202 2
0.2%
126.5989605649 1
0.1%
126.6222321021 1
0.1%
126.6228753128 1
0.1%
126.6244078438 1
0.1%
126.6251141119 2
0.2%
126.6270138759 2
0.2%
126.6273248993 1
0.1%
126.6275192643 1
0.1%
ValueCountFrequency (%)
127.6399559232 1
0.1%
127.6332866478 1
0.1%
127.6298291203 1
0.1%
127.593123981 1
0.1%
127.5892647695 1
0.1%
127.4951811015 1
0.1%
127.4935296283 1
0.1%
127.4913125413 1
0.1%
127.4909276543 1
0.1%
127.4890610905 1
0.1%

Interactions

2024-03-16T04:49:34.920829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T04:49:25.199807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T04:49:26.868582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T04:49:28.963433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T04:49:30.872876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T04:49:33.001008image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T04:49:35.224110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T04:49:25.471436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T04:49:27.145299image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T04:49:29.293328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T04:49:31.316497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T04:49:33.320589image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T04:49:35.528082image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T04:49:25.717393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T04:49:27.443614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T04:49:29.565686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T04:49:31.688778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T04:49:33.605210image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T04:49:35.879296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T04:49:25.983919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T04:49:27.859083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T04:49:29.903848image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T04:49:32.058419image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T04:49:33.892652image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T04:49:36.181320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T04:49:26.267723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T04:49:28.241337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T04:49:30.267884image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T04:49:32.392270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T04:49:34.198658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T04:49:36.463295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T04:49:26.588728image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T04:49:28.626429image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T04:49:30.558917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T04:49:32.707151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-16T04:49:34.499011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-16T04:49:56.784494image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군명영업상태명병상수(개)의료인수(명)입원실수(개)연면적(㎡)WGS84위도WGS84경도
시군명1.0000.3380.3340.0000.1870.0000.9570.927
영업상태명0.3381.0000.2570.2390.1840.1820.0000.064
병상수(개)0.3340.2571.0000.2520.7940.5080.3210.135
의료인수(명)0.0000.2390.2521.0000.2820.8500.0000.000
입원실수(개)0.1870.1840.7940.2821.0000.7290.1760.000
연면적(㎡)0.0000.1820.5080.8500.7291.0000.0000.088
WGS84위도0.9570.0000.3210.0000.1760.0001.0000.697
WGS84경도0.9270.0640.1350.0000.0000.0880.6971.000
2024-03-16T04:49:57.095792image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
영업상태명시군명
영업상태명1.0000.166
시군명0.1661.000
2024-03-16T04:49:57.352774image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
병상수(개)의료인수(명)입원실수(개)연면적(㎡)WGS84위도WGS84경도시군명영업상태명
병상수(개)1.0000.2940.9230.468-0.052-0.0090.1230.109
의료인수(명)0.2941.0000.3060.483-0.0740.0820.0000.152
입원실수(개)0.9230.3061.0000.467-0.0840.0170.0750.106
연면적(㎡)0.4680.4830.4671.000-0.0800.0050.0000.106
WGS84위도-0.052-0.074-0.084-0.0801.000-0.2150.7560.000
WGS84경도-0.0090.0820.0170.005-0.2151.0000.6600.026
시군명0.1230.0000.0750.0000.7560.6601.0000.166
영업상태명0.1090.1520.1060.1060.0000.0260.1661.000

Missing values

2024-03-16T04:49:36.869573image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-16T04:49:37.513406image/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.
2024-03-16T04:49:38.099161image/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

시군명사업장명인허가일자영업상태명폐업일자병상수(개)의료인수(명)입원실수(개)연면적(㎡)소재지도로명주소소재지지번주소소재지우편번호WGS84위도WGS84경도
0가평군최피부과의원2019-05-23영업/정상<NA>020131.0경기도 성남시 수정구 위례광장로 322, 아이플렉스 3층 306호 (창곡동)경기도 성남시 수정구 창곡동 508번지 아이플렉스1364037.471749127.142652
1가평군금빛여성의원2023-07-12영업/정상<NA>2613142428.33경기도 성남시 수정구 수정로171번길 7-1, 우일프라자 2층일부, 3~6층, 8층, 9층일부 (태평동)경기도 성남시 수정구 태평동 3406 우일프라자1329237.443595127.138411
2가평군강현철의원2000-03-15영업/정상<NA>010180.79경기도 가평군 청평면 청평중앙로 51경기도 가평군 청평면 청평리 465번지 8호1245237.738223127.419951
3가평군늘푸른의원2018-02-09영업/정상<NA>010246.4경기도 가평군 설악면 신천중앙로 118, 2층경기도 가평군 설악면 신천리 435번지 14호1246537.678059127.490928
4가평군현리중앙의원1998-12-26영업/정상<NA>020135.0경기도 가평군 조종면 현창로38번길 3 (현리중앙의원)경기도 가평군 조종면 현리 265번지 12호1243737.818587127.348511
5가평군청평제일산부인과의원2006-12-29폐업2008-12-22010115.0경기도 가평군 청평면 청평중앙로 59청평면 청평리 465-171245237.73862127.420756
6고양시일산윌내과의원2021-01-28영업/정상<NA>050490.91경기도 고양시 일산동구 고양대로1021번길 33, 스타타워Ⅲ 3층 302~304호 (식사동)경기도 고양시 일산동구 식사동 15871032437.673965126.807922
7고양시진세진산부인과의원2011-07-20영업/정상<NA>211167.3경기도 고양시 덕양구 화정로 47, 203,204-2호 (화정동, 동원텔)경기도 고양시 덕양구 화정동 969번지 동원텔 203, 204-2호1049737.635199126.831403
8고양시이윤정산부인과의원2021-02-25영업/정상<NA>030140.71경기도 고양시 덕양구 권율대로 685, SIB 타워 308호,309호 (원흥동)경기도 고양시 덕양구 원흥동 638 SIB 타워1056037.651197126.874053
9고양시삼성에스더산부인과의원2022-08-24영업/정상<NA>010240.2경기도 고양시 덕양구 동송로 20, 삼송농산물종합유통센터 2층 일부호 (동산동)경기도 고양시 덕양구 동산동 373 삼송농산물종합유통센터1059537.648614126.898946
시군명사업장명인허가일자영업상태명폐업일자병상수(개)의료인수(명)입원실수(개)연면적(㎡)소재지도로명주소소재지지번주소소재지우편번호WGS84위도WGS84경도
1215화성시센트럴의원2013-02-06폐업2021-03-13010133.62경기도 화성시 효행로 1069, 402호 (진안동, 우성메디피아)경기도 화성시 진안동 914번지 6호 우성메디피아 402호1839837.215244127.043657
1216화성시21세기산부인과의원2009-03-06폐업2009-10-0801051.0경기도 화성시 동탄솔빛로 48경기도 화성시 반송동 217번지 6호 거택프라자 3층1844237.193162127.073378
1217화성시태안가정의학과의원2006-09-22폐업2014-05-2101071.8경기도 화성시 효행로 990, 3층 (진안동, 비젼월드)경기도 화성시 진안동 512-1 비젼월드 3층445-39037.211213127.036367
1218화성시송명화산부인과의원1998-01-16폐업2013-04-05010167.01경기도 화성시 경기대로1010번길 6 (병점동)경기도 화성시 병점동 370번지445-36037.206177127.037017
1219화성시예닮산부인과의원2009-06-17폐업2015-03-31020643.0경기도 화성시 효행로 1035, 1~3층 (진안동, 명민빌딩)경기도 화성시 진안동 874번지 5호 명민빌딩 1,2,3층445-39037.2136127.040432
1220화성시태안의원2016-05-26폐업2019-08-01412542.69경기도 화성시 효행로 990 (진안동, 비젼월드)경기도 화성시 진안동 512번지 1호1840137.211213127.036367
1221화성시동탄제일여성의원2017-08-24폐업2021-03-08050675.23경기도 화성시 삼성1로 138, 1, 2층 (석우동)경기도 화성시 석우동 42번지 4호 1, 2층1845037.216022127.078626
1222화성시중앙메디칼의원2016-12-29폐업2017-07-06010297.0경기도 화성시 동탄순환대로 692, 402,403호 (영천동, 에이스프라자)경기도 화성시 영천동 681-6번지1846637.206778127.111415
1223화성시예사랑산부인과의원2003-10-16폐업2007-03-30414264.46<NA>경기도 화성시 우정읍 조암리 334번지 8호18568<NA><NA>
1224화성시김&리피부과의원2010-04-13폐업2019-12-29030317.0경기도 화성시 동탄반석로 134, 401호 (반송동, 에이치원메디컬센터)경기도 화성시 반송동 104번지 1호 HI메디컬빌딩 401호1845537.20106127.071362