Overview

Dataset statistics

Number of variables9
Number of observations100
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory7.3 KiB
Average record size in memory74.3 B

Variable types

Categorical5
Numeric1
Text3

Dataset

Description샘플 데이터
Author지디에스컨설팅그룹
URLhttps://www.bigdata-environment.kr/user/data_market/detail.do?id=69270d70-fe2a-11ea-9d31-b9e02b707df2

Alerts

시설코드 has constant value ""Constant
시설명 has constant value ""Constant
상가,사업체 구분 has constant value ""Constant
업종코드명 is highly overall correlated with 업종코드High correlation
업종코드 is highly overall correlated with 업종코드명High correlation
사업체고유번호 has unique valuesUnique
사업체명 has unique valuesUnique

Reproduction

Analysis started2023-12-10 13:31:29.147643
Analysis finished2023-12-10 13:31:30.362287
Duration1.21 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시설코드
Categorical

CONSTANT 

Distinct1
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
A0001
100 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowA0001
2nd rowA0001
3rd rowA0001
4th rowA0001
5th rowA0001

Common Values

ValueCountFrequency (%)
A0001 100
100.0%

Length

2023-12-10T22:31:30.483184image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:31:30.633971image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
a0001 100
100.0%

시설명
Categorical

CONSTANT 

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

Length

Max length12
Median length12
Mean length12
Min length12

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
서울꽃동네신내노인요양원 100
100.0%

Length

2023-12-10T22:31:30.770380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:31:30.898825image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
서울꽃동네신내노인요양원 100
100.0%

상가,사업체 구분
Categorical

CONSTANT 

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

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
S 100
100.0%

Length

2023-12-10T22:31:31.027303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-10T22:31:31.239267image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
s 100
100.0%

사업체고유번호
Real number (ℝ)

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean11986526
Minimum10456702
Maximum12589970
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.0 KiB
2023-12-10T22:31:31.401044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum10456702
5-th percentile10551078
Q111871146
median12050456
Q312586635
95-th percentile12589731
Maximum12589970
Range2133268
Interquartile range (IQR)715488.5

Descriptive statistics

Standard deviation572893.62
Coefficient of variation (CV)0.047794802
Kurtosis1.2251892
Mean11986526
Median Absolute Deviation (MAD)226858.5
Skewness-1.2333271
Sum1.1986526 × 109
Variance3.282071 × 1011
MonotonicityStrictly increasing
2023-12-10T22:31:31.732342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10456702 1
 
1.0%
12052103 1
 
1.0%
12586544 1
 
1.0%
12585612 1
 
1.0%
12525217 1
 
1.0%
12480925 1
 
1.0%
12299434 1
 
1.0%
12256518 1
 
1.0%
12114237 1
 
1.0%
12106502 1
 
1.0%
Other values (90) 90
90.0%
ValueCountFrequency (%)
10456702 1
1.0%
10460246 1
1.0%
10460482 1
1.0%
10468325 1
1.0%
10476871 1
1.0%
10554984 1
1.0%
10706854 1
1.0%
10882452 1
1.0%
10910607 1
1.0%
11017872 1
1.0%
ValueCountFrequency (%)
12589970 1
1.0%
12589942 1
1.0%
12589920 1
1.0%
12589840 1
1.0%
12589796 1
1.0%
12589728 1
1.0%
12589507 1
1.0%
12589324 1
1.0%
12589058 1
1.0%
12588940 1
1.0%

사업체명
Text

UNIQUE 

Distinct100
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T22:31:32.062841image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length6.85
Min length3

Characters and Unicode

Total characters685
Distinct characters186
Distinct categories5 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique100 ?
Unique (%)100.0%

Sample

1st row복음약국
2nd row서상원한의원
3rd row호21C치과의원
4th row서울메디칼약국
5th row다담한의원
ValueCountFrequency (%)
복음약국 1
 
1.0%
성북메디의원 1
 
1.0%
중앙드림치과의원 1
 
1.0%
태릉밝은안과 1
 
1.0%
감초당약국 1
 
1.0%
봉은한의원 1
 
1.0%
새우림약국 1
 
1.0%
구리소아청소년과 1
 
1.0%
자연휴한의원 1
 
1.0%
더조은요양병원장례식장 1
 
1.0%
Other values (90) 90
90.0%
2023-12-10T22:31:32.575341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
원 69
 
10.1%
의 65
 
9.5%
과 47
 
6.9%
국 24
 
3.5%
약 23
 
3.4%
치 19
 
2.8%
리 15
 
2.2%
한 13
 
1.9%
이 11
 
1.6%
서 9
 
1.3%
Other values (176) 390
56.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 677
98.8%
Decimal Number 5
 
0.7%
Open Punctuation 1
 
0.1%
Uppercase Letter 1
 
0.1%
Close Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
원 69
 
10.2%
의 65
 
9.6%
과 47
 
6.9%
국 24
 
3.5%
약 23
 
3.4%
치 19
 
2.8%
리 15
 
2.2%
한 13
 
1.9%
이 11
 
1.6%
서 9
 
1.3%
Other values (168) 382
56.4%
Decimal Number
ValueCountFrequency (%)
5 1
20.0%
6 1
20.0%
3 1
20.0%
1 1
20.0%
2 1
20.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Uppercase Letter
ValueCountFrequency (%)
C 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 677
98.8%
Common 7
 
1.0%
Latin 1
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
원 69
 
10.2%
의 65
 
9.6%
과 47
 
6.9%
국 24
 
3.5%
약 23
 
3.4%
치 19
 
2.8%
리 15
 
2.2%
한 13
 
1.9%
이 11
 
1.6%
서 9
 
1.3%
Other values (168) 382
56.4%
Common
ValueCountFrequency (%)
5 1
14.3%
6 1
14.3%
3 1
14.3%
( 1
14.3%
1 1
14.3%
2 1
14.3%
) 1
14.3%
Latin
ValueCountFrequency (%)
C 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 677
98.8%
ASCII 8
 
1.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
원 69
 
10.2%
의 65
 
9.6%
과 47
 
6.9%
국 24
 
3.5%
약 23
 
3.4%
치 19
 
2.8%
리 15
 
2.2%
한 13
 
1.9%
이 11
 
1.6%
서 9
 
1.3%
Other values (168) 382
56.4%
ASCII
ValueCountFrequency (%)
5 1
12.5%
6 1
12.5%
3 1
12.5%
( 1
12.5%
C 1
12.5%
1 1
12.5%
2 1
12.5%
) 1
12.5%

업종코드
Categorical

HIGH CORRELATION 

Distinct17
Distinct (%)17.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
S02A01
22 
S01B99
20 
S01B04
19 
S01B06
10 
S01B07
7 
Other values (12)
22 

Length

Max length6
Median length6
Mean length6
Min length6

Unique

Unique6 ?
Unique (%)6.0%

Sample

1st rowS02A01
2nd rowS01B06
3rd rowS01B04
4th rowS02A01
5th rowS01B06

Common Values

ValueCountFrequency (%)
S02A01 22
22.0%
S01B99 20
20.0%
S01B04 19
19.0%
S01B06 10
10.0%
S01B07 7
 
7.0%
S04A02 5
 
5.0%
S01B02 3
 
3.0%
S01B14 2
 
2.0%
S01B16 2
 
2.0%
S01B11 2
 
2.0%
Other values (7) 8
 
8.0%

Length

2023-12-10T22:31:32.810182image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
s02a01 22
22.0%
s01b99 20
20.0%
s01b04 19
19.0%
s01b06 10
10.0%
s01b07 7
 
7.0%
s04a02 5
 
5.0%
s01b02 3
 
3.0%
s01b11 2
 
2.0%
s01b12 2
 
2.0%
s01b16 2
 
2.0%
Other values (7) 8
 
8.0%

업종코드명
Categorical

HIGH CORRELATION 

Distinct17
Distinct (%)17.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
약국
22 
기타병원
20 
치과의원
19 
한의원
10 
내과/외과
7 
Other values (12)
22 

Length

Max length7
Median length4
Mean length3.58
Min length2

Unique

Unique6 ?
Unique (%)6.0%

Sample

1st row약국
2nd row한의원
3rd row치과의원
4th row약국
5th row한의원

Common Values

ValueCountFrequency (%)
약국 22
22.0%
기타병원 20
20.0%
치과의원 19
19.0%
한의원 10
10.0%
내과/외과 7
 
7.0%
동물병원 5
 
5.0%
일반병원 3
 
3.0%
이비인후과의원 2
 
2.0%
피부과 2
 
2.0%
소아과 2
 
2.0%
Other values (7) 8
 
8.0%

Length

2023-12-10T22:31:32.987808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
약국 22
22.0%
기타병원 20
20.0%
치과의원 19
19.0%
한의원 10
10.0%
내과/외과 7
 
7.0%
동물병원 5
 
5.0%
일반병원 3
 
3.0%
소아과 2
 
2.0%
비뇨기과 2
 
2.0%
피부과 2
 
2.0%
Other values (7) 8
 
8.0%

주소
Text

Distinct50
Distinct (%)50.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T22:31:33.269593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length15
Mean length13.83
Min length11

Characters and Unicode

Total characters1383
Distinct characters85
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique25 ?
Unique (%)25.0%

Sample

1st row서울특별시 노원구 마들로1가길
2nd row경기도 구리시 검배로6번길
3rd row서울특별시 노원구 덕릉로
4th row경기도 구리시 건원대로76번길
5th row서울특별시 노원구 덕릉로
ValueCountFrequency (%)
서울특별시 56
18.7%
경기도 44
14.7%
구리시 36
12.0%
노원구 26
 
8.7%
중랑구 19
 
6.3%
동대문구 9
 
3.0%
남양주시 8
 
2.7%
경춘로 7
 
2.3%
동일로 6
 
2.0%
망우로 6
 
2.0%
Other values (46) 83
27.7%
2023-12-10T22:31:33.898418image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
200
 
14.5%
시 100
 
7.2%
로 100
 
7.2%
구 95
 
6.9%
별 62
 
4.5%
서 56
 
4.0%
울 56
 
4.0%
특 56
 
4.0%
경 52
 
3.8%
기 44
 
3.2%
Other values (75) 562
40.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1117
80.8%
Space Separator 200
 
14.5%
Decimal Number 66
 
4.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 100
 
9.0%
로 100
 
9.0%
구 95
 
8.5%
별 62
 
5.6%
서 56
 
5.0%
울 56
 
5.0%
특 56
 
5.0%
경 52
 
4.7%
기 44
 
3.9%
도 44
 
3.9%
Other values (64) 452
40.5%
Decimal Number
ValueCountFrequency (%)
2 13
19.7%
1 11
16.7%
3 9
13.6%
7 7
10.6%
5 7
10.6%
6 7
10.6%
0 6
9.1%
8 3
 
4.5%
9 2
 
3.0%
4 1
 
1.5%
Space Separator
ValueCountFrequency (%)
200
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1117
80.8%
Common 266
 
19.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 100
 
9.0%
로 100
 
9.0%
구 95
 
8.5%
별 62
 
5.6%
서 56
 
5.0%
울 56
 
5.0%
특 56
 
5.0%
경 52
 
4.7%
기 44
 
3.9%
도 44
 
3.9%
Other values (64) 452
40.5%
Common
ValueCountFrequency (%)
200
75.2%
2 13
 
4.9%
1 11
 
4.1%
3 9
 
3.4%
7 7
 
2.6%
5 7
 
2.6%
6 7
 
2.6%
0 6
 
2.3%
8 3
 
1.1%
9 2
 
0.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1117
80.8%
ASCII 266
 
19.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
200
75.2%
2 13
 
4.9%
1 11
 
4.1%
3 9
 
3.4%
7 7
 
2.6%
5 7
 
2.6%
6 7
 
2.6%
0 6
 
2.3%
8 3
 
1.1%
9 2
 
0.8%
Hangul
ValueCountFrequency (%)
시 100
 
9.0%
로 100
 
9.0%
구 95
 
8.5%
별 62
 
5.6%
서 56
 
5.0%
울 56
 
5.0%
특 56
 
5.0%
경 52
 
4.7%
기 44
 
3.9%
도 44
 
3.9%
Other values (64) 452
40.5%

공간정보
Text

Distinct79
Distinct (%)79.0%
Missing0
Missing (%)0.0%
Memory size932.0 B
2023-12-10T22:31:34.332595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length50
Median length50
Mean length50
Min length50

Characters and Unicode

Total characters5000
Distinct characters16
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique61 ?
Unique (%)61.0%

Sample

1st row01010000203B1400006BFEC85C515A2D41095FF5FB0BDF3D41
2nd row01010000203B140000DD4F5245E18C2D416386212686D73D41
3rd row01010000203B140000392A75D21B582D41B11B755669EB3D41
4th row01010000203B140000F99BD7E6148D2D41BF1B8D0296DA3D41
5th row01010000203B140000392A75D21B582D41B11B755669EB3D41
ValueCountFrequency (%)
01010000203b1400006bfec85c515a2d41095ff5fb0bdf3d41 3
 
3.0%
01010000203b140000392a75d21b582d41b11b755669eb3d41 3
 
3.0%
01010000203b140000dd4f5245e18c2d416386212686d73d41 3
 
3.0%
01010000203b140000e205fe451d812d41d93dfa4bb4eb3d41 2
 
2.0%
01010000203b14000014562f7ce55f2d418dd811069dd13d41 2
 
2.0%
01010000203b140000b801878cda6a2d41de6a3006b9d63d41 2
 
2.0%
01010000203b14000061f20330245e2d41730a2c4003cd3d41 2
 
2.0%
01010000203b1400000ce21026a57c2d41cad504d44de53d41 2
 
2.0%
01010000203b1400000c382fb9598d2d4162257f6b13d83d41 2
 
2.0%
01010000203b140000929624dd54582d415e7802dd5be73d41 2
 
2.0%
Other values (69) 77
77.0%
2023-12-10T22:31:35.042724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 1244
24.9%
1 634
12.7%
4 442
 
8.8%
D 427
 
8.5%
2 347
 
6.9%
3 311
 
6.2%
B 233
 
4.7%
5 180
 
3.6%
8 175
 
3.5%
6 174
 
3.5%
Other values (6) 833
16.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3791
75.8%
Uppercase Letter 1209
 
24.2%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 1244
32.8%
1 634
16.7%
4 442
 
11.7%
2 347
 
9.2%
3 311
 
8.2%
5 180
 
4.7%
8 175
 
4.6%
6 174
 
4.6%
9 150
 
4.0%
7 134
 
3.5%
Uppercase Letter
ValueCountFrequency (%)
D 427
35.3%
B 233
19.3%
E 151
 
12.5%
F 147
 
12.2%
C 145
 
12.0%
A 106
 
8.8%

Most occurring scripts

ValueCountFrequency (%)
Common 3791
75.8%
Latin 1209
 
24.2%

Most frequent character per script

Common
ValueCountFrequency (%)
0 1244
32.8%
1 634
16.7%
4 442
 
11.7%
2 347
 
9.2%
3 311
 
8.2%
5 180
 
4.7%
8 175
 
4.6%
6 174
 
4.6%
9 150
 
4.0%
7 134
 
3.5%
Latin
ValueCountFrequency (%)
D 427
35.3%
B 233
19.3%
E 151
 
12.5%
F 147
 
12.2%
C 145
 
12.0%
A 106
 
8.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 5000
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 1244
24.9%
1 634
12.7%
4 442
 
8.8%
D 427
 
8.5%
2 347
 
6.9%
3 311
 
6.2%
B 233
 
4.7%
5 180
 
3.6%
8 175
 
3.5%
6 174
 
3.5%
Other values (6) 833
16.7%

Interactions

2023-12-10T22:31:29.829601image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-10T22:31:35.220564image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
사업체고유번호사업체명업종코드업종코드명주소공간정보
사업체고유번호1.0001.0000.0000.0000.8450.947
사업체명1.0001.0001.0001.0001.0001.000
업종코드0.0001.0001.0001.0000.8700.831
업종코드명0.0001.0001.0001.0000.8700.831
주소0.8451.0000.8700.8701.0001.000
공간정보0.9471.0000.8310.8311.0001.000
2023-12-10T22:31:35.410616image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
업종코드명업종코드
업종코드명1.0001.000
업종코드1.0001.000
2023-12-10T22:31:35.544269image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
사업체고유번호업종코드업종코드명
사업체고유번호1.0000.0000.000
업종코드0.0001.0001.000
업종코드명0.0001.0001.000

Missing values

2023-12-10T22:31:30.030993image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-10T22:31:30.280722image/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

시설코드시설명상가,사업체 구분사업체고유번호사업체명업종코드업종코드명주소공간정보
0A0001서울꽃동네신내노인요양원S10456702복음약국S02A01약국서울특별시 노원구 마들로1가길01010000203B1400006BFEC85C515A2D41095FF5FB0BDF3D41
1A0001서울꽃동네신내노인요양원S10460246서상원한의원S01B06한의원경기도 구리시 검배로6번길01010000203B140000DD4F5245E18C2D416386212686D73D41
2A0001서울꽃동네신내노인요양원S10460482호21C치과의원S01B04치과의원서울특별시 노원구 덕릉로01010000203B140000392A75D21B582D41B11B755669EB3D41
3A0001서울꽃동네신내노인요양원S10468325서울메디칼약국S02A01약국경기도 구리시 건원대로76번길01010000203B140000F99BD7E6148D2D41BF1B8D0296DA3D41
4A0001서울꽃동네신내노인요양원S10476871다담한의원S01B06한의원서울특별시 노원구 덕릉로01010000203B140000392A75D21B582D41B11B755669EB3D41
5A0001서울꽃동네신내노인요양원S10554984진서동물병원S04A02동물병원서울특별시 중랑구 신내로10길01010000203B1400001CC618C7D86D2D41951E3AD078D93D41
6A0001서울꽃동네신내노인요양원S10706854노엘치과의원S01B04치과의원경기도 구리시 이문안로01010000203B1400008F6905B2E28B2D4161DCBDC719D43D41
7A0001서울꽃동네신내노인요양원S10882452의편전한의원S01B06한의원경기도 구리시 이문안로01010000203B1400008F6905B2E28B2D4161DCBDC719D43D41
8A0001서울꽃동네신내노인요양원S10910607새하늘약국S02A01약국서울특별시 노원구 덕릉로01010000203B140000392A75D21B582D41B11B755669EB3D41
9A0001서울꽃동네신내노인요양원S11017872임명준안과의원S01B13안과의원서울특별시 노원구 공릉로59길01010000203B14000043C2E5812F5B2D41D58562D706E73D41
시설코드시설명상가,사업체 구분사업체고유번호사업체명업종코드업종코드명주소공간정보
90A0001서울꽃동네신내노인요양원S12588940서울비뇨기과의원S01B12비뇨기과경기도 구리시 건원대로01010000203B1400001F426103AC8C2D41BA3400F7FDD73D41
91A0001서울꽃동네신내노인요양원S12589058청담이라인치과의원S01B04치과의원경기도 구리시 건원대로01010000203B14000052508BD7858B2D41FD9038F94ADA3D41
92A0001서울꽃동네신내노인요양원S12589324보배의원S01B99기타병원서울특별시 중랑구 면목로01010000203B14000026BF41A591672D4182705F033BD43D41
93A0001서울꽃동네신내노인요양원S12589507연세오케이마취통증의학과의원S01B99기타병원서울특별시 중랑구 동일로01010000203B140000DCFDE1A4C1622D4126D290610FD83D41
94A0001서울꽃동네신내노인요양원S12589728서울그린정신건강의학과의원S01B99기타병원서울특별시 동대문구 망우로01010000203B140000F6F468DA91592D41921E6D80E4D33D41
95A0001서울꽃동네신내노인요양원S12589796곱디고운치과의원S01B04치과의원경기도 구리시 검배로01010000203B140000F51F79EA3E8E2D4144C97D23E0D63D41
96A0001서울꽃동네신내노인요양원S12589840늘푸른통증의학과의원S01B99기타병원서울특별시 노원구 동일로207길01010000203B140000305355A619582D4124F40D7602EA3D41
97A0001서울꽃동네신내노인요양원S12589920미유치과의원S01B04치과의원경기도 남양주시 불암로01010000203B140000063BC5A0AC782D41E90E729FC1EA3D41
98A0001서울꽃동네신내노인요양원S12589942서울굿모닝치과의원S01B04치과의원서울특별시 중랑구 면목로01010000203B1400008D96C9F00F682D411BA7CC7EA3D23D41
99A0001서울꽃동네신내노인요양원S12589970연세다나아마취통증의학과의원S01B99기타병원서울특별시 성북구 한천로76다길01010000203B14000030C8FFA1BC582D418E4C3C142BDD3D41