Overview

Dataset statistics

Number of variables14
Number of observations3029
Missing cells5844
Missing cells (%)13.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory349.2 KiB
Average record size in memory118.0 B

Variable types

Categorical2
Text4
DateTime2
Unsupported1
Numeric5

Dataset

Description치과병원 현황(병원급)
Author행정안전부
URLhttps://data.gg.go.kr/portal/data/service/selectServicePage.do?&infId=35UIB8G2423NNDNAW1332073152&infSeq=1

Alerts

소재지우편번호 is highly overall correlated with WGS84위도 and 1 other fieldsHigh correlation
WGS84위도 is highly overall correlated with 소재지우편번호 and 1 other fieldsHigh correlation
WGS84경도 is highly overall correlated with 시군명High correlation
시군명 is highly overall correlated with 소재지우편번호 and 2 other fieldsHigh correlation
영업상태명 is highly imbalanced (77.6%)Imbalance
폐업일자 has 2734 (90.3%) missing valuesMissing
의료기관종별명 has 3029 (100.0%) missing valuesMissing
연면적(㎡) is highly skewed (γ1 = 54.26318408)Skewed
의료기관종별명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
연면적(㎡) has 31 (1.0%) zerosZeros

Reproduction

Analysis started2024-05-03 19:20:45.808230
Analysis finished2024-05-03 19:21:01.613037
Duration15.8 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군명
Categorical

HIGH CORRELATION 

Distinct31
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size23.8 KiB
부천시
397 
성남시
282 
수원시
264 
용인시
230 
고양시
181 
Other values (26)
1675 

Length

Max length4
Median length3
Mean length3.0732915
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
부천시 397
 
13.1%
성남시 282
 
9.3%
수원시 264
 
8.7%
용인시 230
 
7.6%
고양시 181
 
6.0%
화성시 160
 
5.3%
시흥시 154
 
5.1%
안양시 136
 
4.5%
남양주시 114
 
3.8%
안산시 105
 
3.5%
Other values (21) 1006
33.2%

Length

2024-05-03T19:21:01.838447image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
부천시 397
 
13.1%
성남시 282
 
9.3%
수원시 264
 
8.7%
용인시 230
 
7.6%
고양시 181
 
6.0%
화성시 160
 
5.3%
시흥시 154
 
5.1%
안양시 136
 
4.5%
남양주시 114
 
3.8%
안산시 105
 
3.5%
Other values (21) 1006
33.2%

사업장명
Text

Distinct2355
Distinct (%)77.7%
Missing0
Missing (%)0.0%
Memory size23.8 KiB
2024-05-03T19:21:02.451234image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length21
Mean length7.9745791
Min length4

Characters and Unicode

Total characters24155
Distinct characters529
Distinct categories10 ?
Distinct scripts4 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2029 ?
Unique (%)67.0%

Sample

1st row연세세브란스치과의원
2nd row서울우리치과의원
3rd row서울정성치과의원
4th row서울마음치과의원
5th row서울연합치과의원
ValueCountFrequency (%)
치과의원 45
 
1.4%
유디치과의원 15
 
0.5%
굿모닝치과의원 12
 
0.4%
서울치과의원 12
 
0.4%
우리치과의원 10
 
0.3%
현대치과의원 9
 
0.3%
서울삼성치과의원 9
 
0.3%
보스톤치과의원 8
 
0.3%
이편한치과의원 8
 
0.3%
하나치과의원 8
 
0.3%
Other values (2373) 3002
95.7%
2024-05-03T19:21:03.686176image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
과 3259
 
13.5%
치 3148
 
13.0%
원 3092
 
12.8%
의 2984
 
12.4%
이 466
 
1.9%
서 417
 
1.7%
울 408
 
1.7%
스 332
 
1.4%
세 323
 
1.3%
연 293
 
1.2%
Other values (519) 9433
39.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 23677
98.0%
Decimal Number 140
 
0.6%
Space Separator 109
 
0.5%
Uppercase Letter 93
 
0.4%
Lowercase Letter 54
 
0.2%
Open Punctuation 29
 
0.1%
Close Punctuation 29
 
0.1%
Dash Punctuation 18
 
0.1%
Other Punctuation 5
 
< 0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
과 3259
 
13.8%
치 3148
 
13.3%
원 3092
 
13.1%
의 2984
 
12.6%
이 466
 
2.0%
서 417
 
1.8%
울 408
 
1.7%
스 332
 
1.4%
세 323
 
1.4%
연 293
 
1.2%
Other values (472) 8955
37.8%
Uppercase Letter
ValueCountFrequency (%)
S 19
20.4%
T 11
11.8%
C 7
 
7.5%
U 7
 
7.5%
D 7
 
7.5%
M 6
 
6.5%
K 5
 
5.4%
E 4
 
4.3%
N 4
 
4.3%
L 4
 
4.3%
Other values (9) 19
20.4%
Lowercase Letter
ValueCountFrequency (%)
e 38
70.4%
h 5
 
9.3%
i 2
 
3.7%
r 2
 
3.7%
u 2
 
3.7%
a 1
 
1.9%
y 1
 
1.9%
l 1
 
1.9%
o 1
 
1.9%
n 1
 
1.9%
Decimal Number
ValueCountFrequency (%)
3 31
22.1%
5 29
20.7%
6 24
17.1%
1 17
12.1%
2 15
10.7%
0 12
 
8.6%
8 4
 
2.9%
7 4
 
2.9%
4 3
 
2.1%
9 1
 
0.7%
Other Punctuation
ValueCountFrequency (%)
. 3
60.0%
, 1
 
20.0%
& 1
 
20.0%
Space Separator
ValueCountFrequency (%)
109
100.0%
Open Punctuation
ValueCountFrequency (%)
( 29
100.0%
Close Punctuation
ValueCountFrequency (%)
) 29
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 18
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 23675
98.0%
Common 331
 
1.4%
Latin 147
 
0.6%
Han 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
과 3259
 
13.8%
치 3148
 
13.3%
원 3092
 
13.1%
의 2984
 
12.6%
이 466
 
2.0%
서 417
 
1.8%
울 408
 
1.7%
스 332
 
1.4%
세 323
 
1.4%
연 293
 
1.2%
Other values (470) 8953
37.8%
Latin
ValueCountFrequency (%)
e 38
25.9%
S 19
12.9%
T 11
 
7.5%
C 7
 
4.8%
U 7
 
4.8%
D 7
 
4.8%
M 6
 
4.1%
h 5
 
3.4%
K 5
 
3.4%
E 4
 
2.7%
Other values (19) 38
25.9%
Common
ValueCountFrequency (%)
109
32.9%
3 31
 
9.4%
( 29
 
8.8%
) 29
 
8.8%
5 29
 
8.8%
6 24
 
7.3%
- 18
 
5.4%
1 17
 
5.1%
2 15
 
4.5%
0 12
 
3.6%
Other values (8) 18
 
5.4%
Han
ValueCountFrequency (%)
林 1
50.0%
然 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 23675
98.0%
ASCII 478
 
2.0%
CJK 2
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
과 3259
 
13.8%
치 3148
 
13.3%
원 3092
 
13.1%
의 2984
 
12.6%
이 466
 
2.0%
서 417
 
1.8%
울 408
 
1.7%
스 332
 
1.4%
세 323
 
1.4%
연 293
 
1.2%
Other values (470) 8953
37.8%
ASCII
ValueCountFrequency (%)
109
22.8%
e 38
 
7.9%
3 31
 
6.5%
( 29
 
6.1%
) 29
 
6.1%
5 29
 
6.1%
6 24
 
5.0%
S 19
 
4.0%
- 18
 
3.8%
1 17
 
3.6%
Other values (37) 135
28.2%
CJK
ValueCountFrequency (%)
林 1
50.0%
然 1
50.0%

인허가일자
Date

Distinct2445
Distinct (%)80.7%
Missing0
Missing (%)0.0%
Memory size23.8 KiB
Minimum1978-05-04 00:00:00
Maximum2024-04-09 00:00:00
2024-05-03T19:21:04.076916image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:21:04.523965image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

영업상태명
Categorical

IMBALANCE 

Distinct8
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size23.8 KiB
영업중
2674 
폐업
272 
운영중
 
36
폐업 등
 
18
전출
 
11
Other values (3)
 
18

Length

Max length4
Median length3
Mean length2.9105315
Min length2

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

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

Common Values

ValueCountFrequency (%)
영업중 2674
88.3%
폐업 272
 
9.0%
운영중 36
 
1.2%
폐업 등 18
 
0.6%
전출 11
 
0.4%
휴업 11
 
0.4%
직권폐업 6
 
0.2%
삭제 1
 
< 0.1%

Length

2024-05-03T19:21:05.113051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-03T19:21:05.499201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업중 2674
87.8%
폐업 290
 
9.5%
운영중 36
 
1.2%
등 18
 
0.6%
전출 11
 
0.4%
휴업 11
 
0.4%
직권폐업 6
 
0.2%
삭제 1
 
< 0.1%

폐업일자
Date

MISSING 

Distinct264
Distinct (%)89.5%
Missing2734
Missing (%)90.3%
Memory size23.8 KiB
Minimum2005-12-23 00:00:00
Maximum2024-04-30 00:00:00
2024-05-03T19:21:05.898875image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:21:06.291491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

의료기관종별명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3029
Missing (%)100.0%
Memory size26.8 KiB

의료인수(명)
Real number (ℝ)

Distinct16
Distinct (%)0.5%
Missing17
Missing (%)0.6%
Infinite0
Infinite (%)0.0%
Mean1.562085
Minimum0
Maximum34
Zeros1
Zeros (%)< 0.1%
Negative0
Negative (%)0.0%
Memory size26.8 KiB
2024-05-03T19:21:06.630900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile1
Q11
median1
Q32
95-th percentile3
Maximum34
Range34
Interquartile range (IQR)1

Descriptive statistics

Standard deviation1.4211701
Coefficient of variation (CV)0.90979049
Kurtosis137.34196
Mean1.562085
Median Absolute Deviation (MAD)0
Skewness8.721057
Sum4705
Variance2.0197244
MonotonicityNot monotonic
2024-05-03T19:21:07.001813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
1 2095
69.2%
2 563
 
18.6%
3 203
 
6.7%
4 68
 
2.2%
5 36
 
1.2%
6 14
 
0.5%
7 13
 
0.4%
8 6
 
0.2%
9 4
 
0.1%
11 3
 
0.1%
Other values (6) 7
 
0.2%
(Missing) 17
 
0.6%
ValueCountFrequency (%)
0 1
 
< 0.1%
1 2095
69.2%
2 563
 
18.6%
3 203
 
6.7%
4 68
 
2.2%
5 36
 
1.2%
6 14
 
0.5%
7 13
 
0.4%
8 6
 
0.2%
9 4
 
0.1%
ValueCountFrequency (%)
34 1
 
< 0.1%
22 1
 
< 0.1%
20 2
 
0.1%
19 1
 
< 0.1%
16 1
 
< 0.1%
11 3
 
0.1%
9 4
 
0.1%
8 6
0.2%
7 13
0.4%
6 14
0.5%

진료과목내용
Text

Distinct422
Distinct (%)14.0%
Missing17
Missing (%)0.6%
Memory size23.8 KiB
2024-05-03T19:21:07.413635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length83
Median length70
Mean length23.773572
Min length2

Characters and Unicode

Total characters71606
Distinct characters43
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

Unique297 ?
Unique (%)9.9%

Sample

1st row412 411 410 409 408 407 406 405 404 403 402
2nd row407 410 402 406 404 405 409 408 403 411
3rd row412 411 410 409 408 407 406 405 404 403 402
4th row412 411 410 409 408 407 406 405 404 403 402
5th row401
ValueCountFrequency (%)
403 1681
9.1%
406 1659
9.0%
407 1649
8.9%
405 1594
8.6%
402 1578
8.5%
404 1508
8.1%
411 1496
8.1%
408 1494
8.1%
409 1358
7.3%
401 1238
 
6.7%
Other values (30) 3271
17.7%
2024-05-03T19:21:08.412424image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4 18909
26.4%
0 15826
22.1%
15514
21.7%
1 6507
 
9.1%
2 3698
 
5.2%
3 1778
 
2.5%
6 1775
 
2.5%
7 1765
 
2.5%
5 1707
 
2.4%
8 1570
 
2.2%
Other values (33) 2557
 
3.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 54951
76.7%
Space Separator 15514
 
21.7%
Other Letter 969
 
1.4%
Other Punctuation 172
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
과 291
30.0%
치 162
16.7%
보 54
 
5.6%
구 46
 
4.7%
강 46
 
4.7%
정 28
 
2.9%
교 28
 
2.9%
존 27
 
2.8%
철 27
 
2.8%
면 24
 
2.5%
Other values (21) 236
24.4%
Decimal Number
ValueCountFrequency (%)
4 18909
34.4%
0 15826
28.8%
1 6507
 
11.8%
2 3698
 
6.7%
3 1778
 
3.2%
6 1775
 
3.2%
7 1765
 
3.2%
5 1707
 
3.1%
8 1570
 
2.9%
9 1416
 
2.6%
Space Separator
ValueCountFrequency (%)
15514
100.0%
Other Punctuation
ValueCountFrequency (%)
, 172
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 70637
98.6%
Hangul 969
 
1.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
과 291
30.0%
치 162
16.7%
보 54
 
5.6%
구 46
 
4.7%
강 46
 
4.7%
정 28
 
2.9%
교 28
 
2.9%
존 27
 
2.8%
철 27
 
2.8%
면 24
 
2.5%
Other values (21) 236
24.4%
Common
ValueCountFrequency (%)
4 18909
26.8%
0 15826
22.4%
15514
22.0%
1 6507
 
9.2%
2 3698
 
5.2%
3 1778
 
2.5%
6 1775
 
2.5%
7 1765
 
2.5%
5 1707
 
2.4%
8 1570
 
2.2%
Other values (2) 1588
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 70637
98.6%
Hangul 969
 
1.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4 18909
26.8%
0 15826
22.4%
15514
22.0%
1 6507
 
9.2%
2 3698
 
5.2%
3 1778
 
2.5%
6 1775
 
2.5%
7 1765
 
2.5%
5 1707
 
2.4%
8 1570
 
2.2%
Other values (2) 1588
 
2.2%
Hangul
ValueCountFrequency (%)
과 291
30.0%
치 162
16.7%
보 54
 
5.6%
구 46
 
4.7%
강 46
 
4.7%
정 28
 
2.9%
교 28
 
2.9%
존 27
 
2.8%
철 27
 
2.8%
면 24
 
2.5%
Other values (21) 236
24.4%

연면적(㎡)
Real number (ℝ)

SKEWED  ZEROS 

Distinct2514
Distinct (%)83.5%
Missing17
Missing (%)0.6%
Infinite0
Infinite (%)0.0%
Mean247.7319
Minimum0
Maximum120985
Zeros31
Zeros (%)1.0%
Negative0
Negative (%)0.0%
Memory size26.8 KiB
2024-05-03T19:21:08.879853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile69.199
Q1118.7225
median166.6
Q3242.725
95-th percentile452.9665
Maximum120985
Range120985
Interquartile range (IQR)124.0025

Descriptive statistics

Standard deviation2209.0964
Coefficient of variation (CV)8.9172868
Kurtosis2966.3569
Mean247.7319
Median Absolute Deviation (MAD)57.665
Skewness54.263184
Sum746168.47
Variance4880106.7
MonotonicityNot monotonic
2024-05-03T19:21:09.352697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 31
 
1.0%
165.0 11
 
0.4%
180.0 11
 
0.4%
175.0 9
 
0.3%
120.0 7
 
0.2%
1.0 7
 
0.2%
160.0 7
 
0.2%
142.0 6
 
0.2%
132.0 6
 
0.2%
147.0 6
 
0.2%
Other values (2504) 2911
96.1%
(Missing) 17
 
0.6%
ValueCountFrequency (%)
0.0 31
1.0%
1.0 7
 
0.2%
7.92 1
 
< 0.1%
15.03 1
 
< 0.1%
16.38 1
 
< 0.1%
22.9 1
 
< 0.1%
25.2 1
 
< 0.1%
30.0 1
 
< 0.1%
31.28 1
 
< 0.1%
33.44 1
 
< 0.1%
ValueCountFrequency (%)
120985.0 1
< 0.1%
4990.79 1
< 0.1%
3291.74 1
< 0.1%
3058.42 1
< 0.1%
2220.5 1
< 0.1%
1924.78 1
< 0.1%
1673.66 1
< 0.1%
1573.17 1
< 0.1%
1553.82 1
< 0.1%
1550.28 1
< 0.1%

소재지도로명주소
Text

Distinct2991
Distinct (%)98.7%
Missing0
Missing (%)0.0%
Memory size23.8 KiB
2024-05-03T19:21:10.427840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length73
Median length59
Mean length35.343348
Min length17

Characters and Unicode

Total characters107055
Distinct characters567
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks5 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2953 ?
Unique (%)97.5%

Sample

1st row경기도 가평군 조종면 조종희망로 7, 3층
2nd row경기도 가평군 설악면 신천중앙로 146, 1층, 2층
3rd row경기도 가평군 청평면 청평중앙로 52, 2층
4th row경기도 가평군 가평읍 장터3길 10, 2층
5th row경기도 가평군 청평면 청평중앙로 48, 2층
ValueCountFrequency (%)
경기도 3029
 
13.6%
2층 470
 
2.1%
3층 436
 
2.0%
부천시 398
 
1.8%
성남시 282
 
1.3%
수원시 264
 
1.2%
원미구 236
 
1.1%
용인시 230
 
1.0%
4층 223
 
1.0%
고양시 180
 
0.8%
Other values (4746) 16580
74.3%
2024-05-03T19:21:11.987582image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
19310
 
18.0%
, 4248
 
4.0%
동 3461
 
3.2%
시 3301
 
3.1%
2 3230
 
3.0%
경 3195
 
3.0%
기 3190
 
3.0%
도 3130
 
2.9%
0 3015
 
2.8%
로 2978
 
2.8%
Other values (557) 57997
54.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 57979
54.2%
Space Separator 19310
 
18.0%
Decimal Number 18811
 
17.6%
Other Punctuation 4274
 
4.0%
Open Punctuation 2840
 
2.7%
Close Punctuation 2840
 
2.7%
Dash Punctuation 334
 
0.3%
Uppercase Letter 334
 
0.3%
Math Symbol 270
 
0.3%
Lowercase Letter 50
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 3461
 
6.0%
시 3301
 
5.7%
경 3195
 
5.5%
기 3190
 
5.5%
도 3130
 
5.4%
로 2978
 
5.1%
호 2003
 
3.5%
구 1737
 
3.0%
층 1531
 
2.6%
원 918
 
1.6%
Other values (489) 32535
56.1%
Uppercase Letter
ValueCountFrequency (%)
B 52
15.6%
A 44
13.2%
C 30
 
9.0%
I 26
 
7.8%
S 26
 
7.8%
T 18
 
5.4%
K 18
 
5.4%
M 15
 
4.5%
E 12
 
3.6%
R 12
 
3.6%
Other values (14) 81
24.3%
Lowercase Letter
ValueCountFrequency (%)
e 16
32.0%
a 4
 
8.0%
l 4
 
8.0%
m 3
 
6.0%
r 3
 
6.0%
t 3
 
6.0%
k 2
 
4.0%
p 2
 
4.0%
n 2
 
4.0%
i 2
 
4.0%
Other values (7) 9
18.0%
Decimal Number
ValueCountFrequency (%)
2 3230
17.2%
0 3015
16.0%
1 2977
15.8%
3 2888
15.4%
4 1877
10.0%
5 1390
7.4%
6 1066
 
5.7%
7 858
 
4.6%
8 823
 
4.4%
9 687
 
3.7%
Other Punctuation
ValueCountFrequency (%)
, 4248
99.4%
. 16
 
0.4%
@ 4
 
0.1%
/ 2
 
< 0.1%
· 2
 
< 0.1%
& 2
 
< 0.1%
Letter Number
ValueCountFrequency (%)
Ⅱ 6
46.2%
Ⅲ 4
30.8%
Ⅳ 2
 
15.4%
Ⅰ 1
 
7.7%
Math Symbol
ValueCountFrequency (%)
~ 267
98.9%
∼ 2
 
0.7%
+ 1
 
0.4%
Space Separator
ValueCountFrequency (%)
19310
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2840
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2840
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 334
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 57979
54.2%
Common 48679
45.5%
Latin 397
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 3461
 
6.0%
시 3301
 
5.7%
경 3195
 
5.5%
기 3190
 
5.5%
도 3130
 
5.4%
로 2978
 
5.1%
호 2003
 
3.5%
구 1737
 
3.0%
층 1531
 
2.6%
원 918
 
1.6%
Other values (489) 32535
56.1%
Latin
ValueCountFrequency (%)
B 52
 
13.1%
A 44
 
11.1%
C 30
 
7.6%
I 26
 
6.5%
S 26
 
6.5%
T 18
 
4.5%
K 18
 
4.5%
e 16
 
4.0%
M 15
 
3.8%
E 12
 
3.0%
Other values (35) 140
35.3%
Common
ValueCountFrequency (%)
19310
39.7%
, 4248
 
8.7%
2 3230
 
6.6%
0 3015
 
6.2%
1 2977
 
6.1%
3 2888
 
5.9%
( 2840
 
5.8%
) 2840
 
5.8%
4 1877
 
3.9%
5 1390
 
2.9%
Other values (13) 4064
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 57979
54.2%
ASCII 49059
45.8%
Number Forms 13
 
< 0.1%
Math Operators 2
 
< 0.1%
None 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
19310
39.4%
, 4248
 
8.7%
2 3230
 
6.6%
0 3015
 
6.1%
1 2977
 
6.1%
3 2888
 
5.9%
( 2840
 
5.8%
) 2840
 
5.8%
4 1877
 
3.8%
5 1390
 
2.8%
Other values (52) 4444
 
9.1%
Hangul
ValueCountFrequency (%)
동 3461
 
6.0%
시 3301
 
5.7%
경 3195
 
5.5%
기 3190
 
5.5%
도 3130
 
5.4%
로 2978
 
5.1%
호 2003
 
3.5%
구 1737
 
3.0%
층 1531
 
2.6%
원 918
 
1.6%
Other values (489) 32535
56.1%
Number Forms
ValueCountFrequency (%)
Ⅱ 6
46.2%
Ⅲ 4
30.8%
Ⅳ 2
 
15.4%
Ⅰ 1
 
7.7%
Math Operators
ValueCountFrequency (%)
∼ 2
100.0%
None
ValueCountFrequency (%)
· 2
100.0%

소재지지번주소
Text

Distinct2944
Distinct (%)97.3%
Missing4
Missing (%)0.1%
Memory size23.8 KiB
2024-05-03T19:21:12.864402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length62
Median length49
Mean length27.444628
Min length2

Characters and Unicode

Total characters83020
Distinct characters535
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2873 ?
Unique (%)95.0%

Sample

1st row경기도 가평군 조종면 현리 412-2
2nd row경기도 가평군 설악면 신천리 578-1
3rd row경기도 가평군 청평면 청평리 432-10
4th row경기도 가평군 가평읍 읍내리 407-4
5th row경기도 가평군 청평면 청평리 432번지 11호 외 1
ValueCountFrequency (%)
경기도 3001
 
16.4%
부천시 395
 
2.2%
수원시 262
 
1.4%
성남시 250
 
1.4%
용인시 230
 
1.3%
2층 214
 
1.2%
원미구 205
 
1.1%
3층 202
 
1.1%
1호 185
 
1.0%
고양시 178
 
1.0%
Other values (4820) 13188
72.0%
2024-05-03T19:21:14.504473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
15383
 
18.5%
시 3210
 
3.9%
동 3165
 
3.8%
기 3125
 
3.8%
1 3080
 
3.7%
도 3065
 
3.7%
경 3032
 
3.7%
2 2308
 
2.8%
3 2237
 
2.7%
지 2107
 
2.5%
Other values (525) 42308
51.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 48384
58.3%
Decimal Number 16970
 
20.4%
Space Separator 15383
 
18.5%
Dash Punctuation 1338
 
1.6%
Other Punctuation 426
 
0.5%
Uppercase Letter 245
 
0.3%
Math Symbol 85
 
0.1%
Close Punctuation 63
 
0.1%
Open Punctuation 63
 
0.1%
Lowercase Letter 52
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 3210
 
6.6%
동 3165
 
6.5%
기 3125
 
6.5%
도 3065
 
6.3%
경 3032
 
6.3%
지 2107
 
4.4%
호 1986
 
4.1%
번 1865
 
3.9%
구 1626
 
3.4%
원 792
 
1.6%
Other values (459) 24411
50.5%
Uppercase Letter
ValueCountFrequency (%)
A 26
 
10.6%
C 25
 
10.2%
B 24
 
9.8%
S 20
 
8.2%
I 20
 
8.2%
K 15
 
6.1%
M 14
 
5.7%
T 12
 
4.9%
G 11
 
4.5%
R 10
 
4.1%
Other values (15) 68
27.8%
Lowercase Letter
ValueCountFrequency (%)
e 14
26.9%
l 5
 
9.6%
a 5
 
9.6%
t 4
 
7.7%
m 3
 
5.8%
r 3
 
5.8%
p 3
 
5.8%
k 2
 
3.8%
w 2
 
3.8%
i 2
 
3.8%
Other values (7) 9
17.3%
Decimal Number
ValueCountFrequency (%)
1 3080
18.1%
2 2308
13.6%
3 2237
13.2%
0 2087
12.3%
4 1774
10.5%
5 1393
8.2%
6 1199
 
7.1%
7 1063
 
6.3%
8 957
 
5.6%
9 872
 
5.1%
Other Punctuation
ValueCountFrequency (%)
, 370
86.9%
. 48
 
11.3%
/ 3
 
0.7%
@ 3
 
0.7%
& 2
 
0.5%
Letter Number
ValueCountFrequency (%)
Ⅱ 8
72.7%
Ⅲ 2
 
18.2%
Ⅰ 1
 
9.1%
Math Symbol
ValueCountFrequency (%)
~ 84
98.8%
+ 1
 
1.2%
Space Separator
ValueCountFrequency (%)
15383
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1338
100.0%
Close Punctuation
ValueCountFrequency (%)
) 63
100.0%
Open Punctuation
ValueCountFrequency (%)
( 63
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 48384
58.3%
Common 34328
41.3%
Latin 308
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 3210
 
6.6%
동 3165
 
6.5%
기 3125
 
6.5%
도 3065
 
6.3%
경 3032
 
6.3%
지 2107
 
4.4%
호 1986
 
4.1%
번 1865
 
3.9%
구 1626
 
3.4%
원 792
 
1.6%
Other values (459) 24411
50.5%
Latin
ValueCountFrequency (%)
A 26
 
8.4%
C 25
 
8.1%
B 24
 
7.8%
S 20
 
6.5%
I 20
 
6.5%
K 15
 
4.9%
M 14
 
4.5%
e 14
 
4.5%
T 12
 
3.9%
G 11
 
3.6%
Other values (35) 127
41.2%
Common
ValueCountFrequency (%)
15383
44.8%
1 3080
 
9.0%
2 2308
 
6.7%
3 2237
 
6.5%
0 2087
 
6.1%
4 1774
 
5.2%
5 1393
 
4.1%
- 1338
 
3.9%
6 1199
 
3.5%
7 1063
 
3.1%
Other values (11) 2466
 
7.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 48384
58.3%
ASCII 34625
41.7%
Number Forms 11
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
15383
44.4%
1 3080
 
8.9%
2 2308
 
6.7%
3 2237
 
6.5%
0 2087
 
6.0%
4 1774
 
5.1%
5 1393
 
4.0%
- 1338
 
3.9%
6 1199
 
3.5%
7 1063
 
3.1%
Other values (53) 2763
 
8.0%
Hangul
ValueCountFrequency (%)
시 3210
 
6.6%
동 3165
 
6.5%
기 3125
 
6.5%
도 3065
 
6.3%
경 3032
 
6.3%
지 2107
 
4.4%
호 1986
 
4.1%
번 1865
 
3.9%
구 1626
 
3.4%
원 792
 
1.6%
Other values (459) 24411
50.5%
Number Forms
ValueCountFrequency (%)
Ⅱ 8
72.7%
Ⅲ 2
 
18.2%
Ⅰ 1
 
9.1%

소재지우편번호
Real number (ℝ)

HIGH CORRELATION 

Distinct1342
Distinct (%)44.4%
Missing8
Missing (%)0.3%
Infinite0
Infinite (%)0.0%
Mean14472.857
Minimum10018
Maximum18611
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size26.8 KiB
2024-05-03T19:21:15.060133image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10018
5-th percentile10387
Q112788
median14547
Q316490
95-th percentile18266
Maximum18611
Range8593
Interquartile range (IQR)3702

Descriptive statistics

Standard deviation2354.0272
Coefficient of variation (CV)0.16265117
Kurtosis-0.89599349
Mean14472.857
Median Absolute Deviation (MAD)1888
Skewness-0.1522658
Sum43722502
Variance5541444
MonotonicityNot monotonic
2024-05-03T19:21:15.658939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
15865 30
 
1.0%
14072 19
 
0.6%
18478 15
 
0.5%
15066 15
 
0.5%
14548 15
 
0.5%
13837 14
 
0.5%
14545 14
 
0.5%
13591 14
 
0.5%
10071 13
 
0.4%
14538 12
 
0.4%
Other values (1332) 2860
94.4%
ValueCountFrequency (%)
10018 4
0.1%
10024 1
 
< 0.1%
10031 3
0.1%
10039 2
0.1%
10040 1
 
< 0.1%
10059 1
 
< 0.1%
10062 1
 
< 0.1%
10063 1
 
< 0.1%
10066 4
0.1%
10068 2
0.1%
ValueCountFrequency (%)
18611 4
0.1%
18606 2
0.1%
18603 1
 
< 0.1%
18598 1
 
< 0.1%
18594 1
 
< 0.1%
18593 2
0.1%
18592 3
0.1%
18568 1
 
< 0.1%
18567 2
0.1%
18555 1
 
< 0.1%

WGS84위도
Real number (ℝ)

HIGH CORRELATION 

Distinct2715
Distinct (%)89.9%
Missing9
Missing (%)0.3%
Infinite0
Infinite (%)0.0%
Mean37.426316
Minimum36.960384
Maximum38.125979
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size26.8 KiB
2024-05-03T19:21:16.124274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.960384
5-th percentile37.136954
Q137.295961
median37.400651
Q337.526646
95-th percentile37.740061
Maximum38.125979
Range1.1655943
Interquartile range (IQR)0.23068492

Descriptive statistics

Standard deviation0.18900524
Coefficient of variation (CV)0.0050500627
Kurtosis-0.050422313
Mean37.426316
Median Absolute Deviation (MAD)0.11360424
Skewness0.18437604
Sum113027.47
Variance0.03572298
MonotonicityNot monotonic
2024-05-03T19:21:16.659142image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.2022258061 6
 
0.2%
37.4727049587 6
 
0.2%
37.4835579233 5
 
0.2%
37.5051300224 5
 
0.2%
37.4413298775 4
 
0.1%
37.1670263464 4
 
0.1%
37.4963836443 4
 
0.1%
37.5032013091 4
 
0.1%
37.2759130636 4
 
0.1%
37.4411251667 4
 
0.1%
Other values (2705) 2974
98.2%
(Missing) 9
 
0.3%
ValueCountFrequency (%)
36.9603843188 1
< 0.1%
36.9608455198 1
< 0.1%
36.9617628515 1
< 0.1%
36.9641644629 1
< 0.1%
36.9644052069 1
< 0.1%
36.9749590885 1
< 0.1%
36.9787555958 1
< 0.1%
36.9790863294 1
< 0.1%
36.9849901158 1
< 0.1%
36.9877046831 1
< 0.1%
ValueCountFrequency (%)
38.1259785955 1
< 0.1%
38.0351559194 1
< 0.1%
38.0261744802 1
< 0.1%
38.0252478956 1
< 0.1%
38.0244186522 1
< 0.1%
38.0242658138 1
< 0.1%
38.0016929626 1
< 0.1%
38.0005930515 1
< 0.1%
37.9572546734 1
< 0.1%
37.9565510831 1
< 0.1%

WGS84경도
Real number (ℝ)

HIGH CORRELATION 

Distinct2715
Distinct (%)89.9%
Missing9
Missing (%)0.3%
Infinite0
Infinite (%)0.0%
Mean126.98615
Minimum126.55327
Maximum127.6446
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size26.8 KiB
2024-05-03T19:21:17.113163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.55327
5-th percentile126.73805
Q1126.80784
median126.99995
Q3127.11279
95-th percentile127.25939
Maximum127.6446
Range1.0913306
Interquartile range (IQR)0.30494857

Descriptive statistics

Standard deviation0.18556495
Coefficient of variation (CV)0.0014613007
Kurtosis0.15517977
Mean126.98615
Median Absolute Deviation (MAD)0.14107001
Skewness0.4348371
Sum383498.17
Variance0.034434351
MonotonicityNot monotonic
2024-05-03T19:21:17.622587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.0979268967 6
 
0.2%
127.1429411379 6
 
0.2%
126.7794033193 5
 
0.2%
126.7537281611 5
 
0.2%
127.146459042 4
 
0.1%
127.1061443849 4
 
0.1%
126.7646980209 4
 
0.1%
126.7681610448 4
 
0.1%
127.0715918075 4
 
0.1%
126.7843434953 4
 
0.1%
Other values (2705) 2974
98.2%
(Missing) 9
 
0.3%
ValueCountFrequency (%)
126.5532656671 1
< 0.1%
126.5828112985 1
< 0.1%
126.5848517955 1
< 0.1%
126.5852196596 1
< 0.1%
126.5855969115 1
< 0.1%
126.5877251202 1
< 0.1%
126.5972829105 1
< 0.1%
126.5978618162 1
< 0.1%
126.5981243903 1
< 0.1%
126.5984311406 1
< 0.1%
ValueCountFrequency (%)
127.6445962471 1
< 0.1%
127.6377097685 1
< 0.1%
127.6365235466 1
< 0.1%
127.6361725903 1
< 0.1%
127.6358356783 1
< 0.1%
127.6357230109 1
< 0.1%
127.6350809464 1
< 0.1%
127.6349578582 1
< 0.1%
127.6319470185 1
< 0.1%
127.630911545 1
< 0.1%

Interactions

2024-05-03T19:20:57.223816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:20:49.222019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:20:51.069505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:20:53.285944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:20:55.199084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:20:57.651143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:20:49.669587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:20:51.582807image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:20:53.704636image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:20:55.563907image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:20:58.065238image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:20:49.977560image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:20:52.074900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:20:54.075780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:20:56.032959image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:20:58.375514image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:20:50.260128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:20:52.487850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:20:54.435209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:20:56.513815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:20:58.719601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:20:50.656687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:20:52.897842image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:20:54.909673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-03T19:20:56.876132image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-05-03T19:21:18.017649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군명영업상태명의료인수(명)연면적(㎡)소재지우편번호WGS84위도WGS84경도
시군명1.0000.1420.0000.0000.9910.9730.946
영업상태명0.1421.0000.3620.0430.1200.0670.017
의료인수(명)0.0000.3621.0000.0000.0000.0000.000
연면적(㎡)0.0000.0430.0001.0000.0480.0140.262
소재지우편번호0.9910.1200.0000.0481.0000.9260.859
WGS84위도0.9730.0670.0000.0140.9261.0000.710
WGS84경도0.9460.0170.0000.2620.8590.7101.000
2024-05-03T19:21:18.360578image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
영업상태명시군명
영업상태명1.0000.055
시군명0.0551.000
2024-05-03T19:21:18.865999image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
의료인수(명)연면적(㎡)소재지우편번호WGS84위도WGS84경도시군명영업상태명
의료인수(명)1.0000.457-0.019-0.0090.0130.0000.128
연면적(㎡)0.4571.000-0.008-0.0200.0080.0000.032
소재지우편번호-0.019-0.0081.000-0.8960.1370.9230.057
WGS84위도-0.009-0.020-0.8961.000-0.2710.8230.032
WGS84경도0.0130.0080.137-0.2711.0000.7180.008
시군명0.0000.0000.9230.8230.7181.0000.055
영업상태명0.1280.0320.0570.0320.0080.0551.000

Missing values

2024-05-03T19:20:59.130077image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-05-03T19:21:00.094290image/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.
2024-05-03T19:21:01.249455image/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

시군명사업장명인허가일자영업상태명폐업일자의료기관종별명의료인수(명)진료과목내용연면적(㎡)소재지도로명주소소재지지번주소소재지우편번호WGS84위도WGS84경도
0가평군연세세브란스치과의원20220930영업중<NA><NA>1412 411 410 409 408 407 406 405 404 403 402218.79경기도 가평군 조종면 조종희망로 7, 3층경기도 가평군 조종면 현리 412-21243737.818372127.349319
1가평군서울우리치과의원2023-04-04영업중<NA><NA>1407 410 402 406 404 405 409 408 403 411143.55경기도 가평군 설악면 신천중앙로 146, 1층, 2층경기도 가평군 설악면 신천리 578-11246537.677869127.48807
2가평군서울정성치과의원2023-01-26영업중<NA><NA>1412 411 410 409 408 407 406 405 404 403 402213.64경기도 가평군 청평면 청평중앙로 52, 2층경기도 가평군 청평면 청평리 432-101245237.737917127.420315
3가평군서울마음치과의원2021-11-10영업중<NA><NA>2412 411 410 409 408 407 406 405 404 403 402248.74경기도 가평군 가평읍 장터3길 10, 2층경기도 가평군 가평읍 읍내리 407-41241937.830392127.514693
4가평군서울연합치과의원2011-04-08영업중<NA><NA>2401369.0경기도 가평군 청평면 청평중앙로 48, 2층경기도 가평군 청평면 청평리 432번지 11호 외 11245237.737728127.419929
5가평군이편한치과의원2010-03-02영업중<NA><NA>1412 411 408 407 406 405 404 403 402309.69경기도 가평군 가평읍 석봉로 192, 3층경기도 가평군 가평읍 읍내리 617번지 6호 3층1241337.832213127.510319
6가평군올바른 치과의원2018-08-13영업중<NA><NA>1411 410 409 408 407 406 405 404 403 402252.4경기도 가평군 가평읍 보납로 3, 4층경기도 가평군 가평읍 읍내리 505-21241337.831438127.510864
7가평군푸른치과의원20170214영업중<NA><NA>1411 410 409 408 407 406 405 404 403 402113.85경기도 가평군 조종면 현창로 26경기도 가평군 조종면 현리 410번지 44호1243837.817173127.349116
8가평군횃불치과의원2024-01-16영업중<NA><NA>140448.6경기도 가평군 가평읍 가화로 269경기도 가평군 가평읍 승안리 851240837.842873127.496776
9가평군에이치제이매그놀리아국제치과의원2008-10-16영업중<NA><NA>140190.0경기도 가평군 설악면 미사리로 267-177경기도 가평군 설악면 송산리 460번지1246137.691127127.521381
시군명사업장명인허가일자영업상태명폐업일자의료기관종별명의료인수(명)진료과목내용연면적(㎡)소재지도로명주소소재지지번주소소재지우편번호WGS84위도WGS84경도
3019화성시삼성드림치과의원20150608폐업20220502<NA>1407 405 403 402148.43경기도 화성시 삼성1로 160, 2층 205호 (석우동, 디지털스테이션)경기도 화성시 석우동 31번지 2호1845037.21821127.077881
3020화성시알앤디치과의원20071220폐업20220331<NA>1401180.0경기도 화성시 남양로621번길 36, 110호 (남양동, 문화관)경기도 화성시 남양동 1842(문화관 110호)1827037.197929126.823368
3021화성시웰치과의원2003-01-24폐업2022-07-19<NA>1402 403 404 405 406 407 408 409 410 411 412167.0경기도 화성시 병점서로 33, 301호 (병점동, 두산탑프라자)경기도 화성시 병점동 431-3번지 두산탑프라자 301호1841337.205539127.039906
3022화성시병점연합치과의원2005-05-27폐업2015-04-01<NA>1402149.0경기도 화성시 떡전골로 96-7, 502호 (병점동, 신성빌딩)경기도 화성시 병점동 349-4 신성빌딩 502호1841137.207494127.034516
3023화성시서울S플러스치과의원2012-10-30폐업2023-02-28<NA>1411 410 409 408 407 406 405 404 403 402226.2경기도 화성시 봉담읍 동화길 85, 406호 (이원타워)경기도 화성시 봉담읍 동화리 599번지 2호 이원타워 406호1830237.216949126.958382
3024화성시연세보스톤치과의원2016-03-02폐업2023-04-27<NA>1411 410 409 408 407 406 405 404 403 402127.92경기도 화성시 동탄순환대로 685, 501호 (영천동, 동탄메디피아)경기도 화성시 영천동 651-1465번지1847237.205965127.110923
3025화성시다인치과의원20060522폐업20170623<NA>1401264.0경기도 화성시 향남읍 발안남로55번길 27, 303호 (센트럴월드빌딩)경기도 화성시 향남읍 발안리 139번지 5호 센트럴월드빌딩 303호1859437.129995126.904964
3026화성시333치과의원20090310폐업20221120<NA>1202 205 401 206 201113.74경기도 화성시 삼성1로 150, 201호 (석우동, 파아란오피스텔)경기도 화성시 석우동 31번지 6호 파아란오피스텔 201호1845037.217364127.078359
3027화성시메디피움동탄치과의원2019-12-20폐업2023-06-01<NA>1411 410 409 408 407 406 405 404 403 402270.13경기도 화성시 동탄대로 557-9, 르보아시티 B동 301~304호 (오산동)경기도 화성시 오산동 967번지 3호1847837.203199127.097956
3028화성시서울바른치과교정과치과의원20161025폐업20210623<NA>1404199.02경기도 화성시 동탄역로 124, 301호 (오산동, 윤정프라자)경기도 화성시 오산동 968번지 6호1847837.197561127.096588