Overview

Dataset statistics

Number of variables15
Number of observations65
Missing cells9
Missing cells (%)0.9%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory8.1 KiB
Average record size in memory128.0 B

Variable types

Text5
Categorical3
Numeric6
DateTime1

Dataset

Description대전광역시 서구 관내에서 운영중인 치과기공소 현황 정보(업소명칭, 지번주소, 도로명주소, 전화번호 등)를 제공합니다.
Author대전광역시 서구
URLhttps://www.data.go.kr/data/15124340/fileData.do

Alerts

종별명 has constant value ""Constant
데이터기준일자 has constant value ""Constant
법정동명 is highly overall correlated with 행정동코드 and 6 other fieldsHigh correlation
행정동명 is highly overall correlated with 행정동코드 and 6 other fieldsHigh correlation
행정동코드 is highly overall correlated with 법정동코드 and 2 other fieldsHigh correlation
법정동코드 is highly overall correlated with 행정동코드 and 2 other fieldsHigh correlation
지번주소_X is highly overall correlated with 도로명주소_X and 2 other fieldsHigh correlation
지번주소_Y is highly overall correlated with 도로명주소_Y and 2 other fieldsHigh correlation
도로명주소_X is highly overall correlated with 지번주소_X and 2 other fieldsHigh correlation
도로명주소_Y is highly overall correlated with 지번주소_Y and 2 other fieldsHigh correlation
전화번호 has 9 (13.8%) missing valuesMissing
의료업소명칭 has unique valuesUnique

Reproduction

Analysis started2023-12-12 06:11:13.683596
Analysis finished2023-12-12 06:11:19.347574
Duration5.66 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

의료업소명칭
Text

UNIQUE 

Distinct65
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size652.0 B
2023-12-12T15:11:19.527759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length7
Mean length7.7846154
Min length2

Characters and Unicode

Total characters506
Distinct characters127
Distinct categories4 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique65 ?
Unique (%)100.0%

Sample

1st row도담치과기공소
2nd rowPDL(피디엘)치과기공소
3rd row나로치과기공소
4th row유니플란트치과기공소
5th row디지털시너지기공소
ValueCountFrequency (%)
도담치과기공소 1
 
1.5%
수미치과기공소 1
 
1.5%
수치과기공소 1
 
1.5%
이에스치과기공소 1
 
1.5%
혜성치과기공소 1
 
1.5%
한빛치과기공소 1
 
1.5%
해정치과기공소 1
 
1.5%
formtion(펌션)치과기공소 1
 
1.5%
새롬치과기공소 1
 
1.5%
건치과기공소 1
 
1.5%
Other values (55) 55
84.6%
2023-12-12T15:11:20.038309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
기 62
 
12.3%
공 62
 
12.3%
소 62
 
12.3%
치 61
 
12.1%
과 60
 
11.9%
이 9
 
1.8%
스 8
 
1.6%
트 6
 
1.2%
지 4
 
0.8%
( 4
 
0.8%
Other values (117) 168
33.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 481
95.1%
Uppercase Letter 17
 
3.4%
Open Punctuation 4
 
0.8%
Close Punctuation 4
 
0.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
기 62
12.9%
공 62
12.9%
소 62
12.9%
치 61
12.7%
과 60
12.5%
이 9
 
1.9%
스 8
 
1.7%
트 6
 
1.2%
지 4
 
0.8%
다 3
 
0.6%
Other values (101) 144
29.9%
Uppercase Letter
ValueCountFrequency (%)
O 2
11.8%
P 2
11.8%
K 2
11.8%
I 1
 
5.9%
T 1
 
5.9%
M 1
 
5.9%
R 1
 
5.9%
N 1
 
5.9%
F 1
 
5.9%
Y 1
 
5.9%
Other values (4) 4
23.5%
Open Punctuation
ValueCountFrequency (%)
( 4
100.0%
Close Punctuation
ValueCountFrequency (%)
) 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 481
95.1%
Latin 17
 
3.4%
Common 8
 
1.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
기 62
12.9%
공 62
12.9%
소 62
12.9%
치 61
12.7%
과 60
12.5%
이 9
 
1.9%
스 8
 
1.7%
트 6
 
1.2%
지 4
 
0.8%
다 3
 
0.6%
Other values (101) 144
29.9%
Latin
ValueCountFrequency (%)
O 2
11.8%
P 2
11.8%
K 2
11.8%
I 1
 
5.9%
T 1
 
5.9%
M 1
 
5.9%
R 1
 
5.9%
N 1
 
5.9%
F 1
 
5.9%
Y 1
 
5.9%
Other values (4) 4
23.5%
Common
ValueCountFrequency (%)
( 4
50.0%
) 4
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 481
95.1%
ASCII 25
 
4.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
기 62
12.9%
공 62
12.9%
소 62
12.9%
치 61
12.7%
과 60
12.5%
이 9
 
1.9%
스 8
 
1.7%
트 6
 
1.2%
지 4
 
0.8%
다 3
 
0.6%
Other values (101) 144
29.9%
ASCII
ValueCountFrequency (%)
( 4
16.0%
) 4
16.0%
O 2
 
8.0%
P 2
 
8.0%
K 2
 
8.0%
I 1
 
4.0%
T 1
 
4.0%
M 1
 
4.0%
R 1
 
4.0%
N 1
 
4.0%
Other values (6) 6
24.0%

종별명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size652.0 B
치과기공소
65 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
치과기공소 65
100.0%

Length

2023-12-12T15:11:20.224114image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T15:11:20.372988image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
치과기공소 65
100.0%

행정동코드
Real number (ℝ)

HIGH CORRELATION 

Distinct19
Distinct (%)29.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.0170571 × 109
Minimum3.017052 × 109
Maximum3.017066 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size717.0 B
2023-12-12T15:11:20.491503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.017052 × 109
5-th percentile3.017052 × 109
Q13.0170555 × 109
median3.0170575 × 109
Q33.0170586 × 109
95-th percentile3.017064 × 109
Maximum3.017066 × 109
Range14000
Interquartile range (IQR)3100

Descriptive statistics

Standard deviation3446.8178
Coefficient of variation (CV)1.1424437 × 10-6
Kurtosis0.54713569
Mean3.0170571 × 109
Median Absolute Deviation (MAD)2000
Skewness0.72240713
Sum1.9610871 × 1011
Variance11880553
MonotonicityNot monotonic
2023-12-12T15:11:20.643189image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=19)
ValueCountFrequency (%)
3017055500 11
16.9%
3017058100 8
12.3%
3017052000 7
10.8%
3017058200 5
7.7%
3017054000 5
7.7%
3017059000 5
7.7%
3017058600 3
 
4.6%
3017057500 3
 
4.6%
3017056000 3
 
4.6%
3017064000 3
 
4.6%
Other values (9) 12
18.5%
ValueCountFrequency (%)
3017052000 7
10.8%
3017053000 1
 
1.5%
3017053500 2
 
3.1%
3017054000 5
7.7%
3017055000 1
 
1.5%
3017055500 11
16.9%
3017056000 3
 
4.6%
3017057000 1
 
1.5%
3017057500 3
 
4.6%
3017058100 8
12.3%
ValueCountFrequency (%)
3017066000 2
 
3.1%
3017065000 1
 
1.5%
3017064000 3
 
4.6%
3017063000 1
 
1.5%
3017060000 1
 
1.5%
3017059000 5
7.7%
3017058700 2
 
3.1%
3017058600 3
 
4.6%
3017058200 5
7.7%
3017058100 8
12.3%

행정동명
Categorical

HIGH CORRELATION 

Distinct20
Distinct (%)30.8%
Missing0
Missing (%)0.0%
Memory size652.0 B
탄방동
11 
갈마1동
8 
도마1동
7 
갈마2동
5 
변동
5 
Other values (15)
29 

Length

Max length4
Median length4
Mean length3.4153846
Min length2

Unique

Unique6 ?
Unique (%)9.2%

Sample

1st row탄방동
2nd row갈마2동
3rd row내동
4th row가수원동
5th row갈마1동

Common Values

ValueCountFrequency (%)
탄방동 11
16.9%
갈마1동 8
12.3%
도마1동 7
10.8%
갈마2동 5
 
7.7%
변동 5
 
7.7%
가수원동 3
 
4.6%
월평1동 3
 
4.6%
내동 3
 
4.6%
괴정동 3
 
4.6%
둔산2동 3
 
4.6%
Other values (10) 14
21.5%

Length

2023-12-12T15:11:20.795265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
탄방동 11
16.9%
갈마1동 8
12.3%
도마1동 7
10.8%
갈마2동 5
 
7.7%
변동 5
 
7.7%
가수원동 3
 
4.6%
월평1동 3
 
4.6%
내동 3
 
4.6%
괴정동 3
 
4.6%
둔산2동 3
 
4.6%
Other values (10) 14
21.5%

법정동코드
Real number (ℝ)

HIGH CORRELATION 

Distinct15
Distinct (%)23.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.0170109 × 109
Minimum3.0170102 × 109
Maximum3.0170128 × 109
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size717.0 B
2023-12-12T15:11:20.969331image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.0170102 × 109
5-th percentile3.0170102 × 109
Q13.0170106 × 109
median3.017011 × 109
Q33.0170112 × 109
95-th percentile3.0170115 × 109
Maximum3.0170128 × 109
Range2600
Interquartile range (IQR)600

Descriptive statistics

Standard deviation477.5891
Coefficient of variation (CV)1.5829877 × 10-7
Kurtosis2.4422305
Mean3.0170109 × 109
Median Absolute Deviation (MAD)400
Skewness0.81673759
Sum1.9610571 × 1011
Variance228091.35
MonotonicityNot monotonic
2023-12-12T15:11:21.129522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
3017011100 13
20.0%
3017010600 11
16.9%
3017010300 8
12.3%
3017011200 6
9.2%
3017011300 5
 
7.7%
3017010200 5
 
7.7%
3017011000 3
 
4.6%
3017011400 3
 
4.6%
3017010800 3
 
4.6%
3017010400 2
 
3.1%
Other values (5) 6
9.2%
ValueCountFrequency (%)
3017010200 5
 
7.7%
3017010300 8
12.3%
3017010400 2
 
3.1%
3017010500 1
 
1.5%
3017010600 11
16.9%
3017010800 3
 
4.6%
3017010900 1
 
1.5%
3017011000 3
 
4.6%
3017011100 13
20.0%
3017011200 6
9.2%
ValueCountFrequency (%)
3017012800 1
 
1.5%
3017011700 1
 
1.5%
3017011500 2
 
3.1%
3017011400 3
 
4.6%
3017011300 5
 
7.7%
3017011200 6
9.2%
3017011100 13
20.0%
3017011000 3
 
4.6%
3017010900 1
 
1.5%
3017010800 3
 
4.6%

법정동명
Categorical

HIGH CORRELATION 

Distinct15
Distinct (%)23.1%
Missing0
Missing (%)0.0%
Memory size652.0 B
갈마동
13 
탄방동
11 
도마동
8 
둔산동
6 
월평동
5 
Other values (10)
22 

Length

Max length4
Median length3
Mean length2.9230769
Min length2

Unique

Unique4 ?
Unique (%)6.2%

Sample

1st row탄방동
2nd row갈마동
3rd row내동
4th row가수원동
5th row갈마동

Common Values

ValueCountFrequency (%)
갈마동 13
20.0%
탄방동 11
16.9%
도마동 8
12.3%
둔산동 6
9.2%
월평동 5
 
7.7%
변동 5
 
7.7%
내동 3
 
4.6%
가수원동 3
 
4.6%
괴정동 3
 
4.6%
정림동 2
 
3.1%
Other values (5) 6
9.2%

Length

2023-12-12T15:11:21.302041image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
갈마동 13
20.0%
탄방동 11
16.9%
도마동 8
12.3%
둔산동 6
9.2%
월평동 5
 
7.7%
변동 5
 
7.7%
내동 3
 
4.6%
가수원동 3
 
4.6%
괴정동 3
 
4.6%
정림동 2
 
3.1%
Other values (5) 6
9.2%

지번주소
Text

Distinct61
Distinct (%)93.8%
Missing0
Missing (%)0.0%
Memory size652.0 B
2023-12-12T15:11:21.604645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length23
Mean length18.230769
Min length16

Characters and Unicode

Total characters1185
Distinct characters71
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

Unique57 ?
Unique (%)87.7%

Sample

1st row대전광역시 서구 탄방동 642
2nd row대전광역시 서구 갈마동 1374
3rd row대전광역시 서구 내동 36-3
4th row대전광역시 서구 가수원동 774-15
5th row대전광역시 서구 갈마동 363-11
ValueCountFrequency (%)
대전광역시 65
24.2%
서구 65
24.2%
갈마동 13
 
4.8%
탄방동 11
 
4.1%
도마동 8
 
3.0%
둔산동 6
 
2.2%
변동 5
 
1.9%
월평동 5
 
1.9%
내동 3
 
1.1%
가수원동 3
 
1.1%
Other values (77) 85
31.6%
2023-12-12T15:11:22.066571image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
204
17.2%
대 65
 
5.5%
전 65
 
5.5%
구 65
 
5.5%
서 65
 
5.5%
동 65
 
5.5%
시 65
 
5.5%
역 65
 
5.5%
광 65
 
5.5%
1 56
 
4.7%
Other values (61) 405
34.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 687
58.0%
Decimal Number 256
 
21.6%
Space Separator 204
 
17.2%
Dash Punctuation 38
 
3.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
대 65
9.5%
전 65
9.5%
구 65
9.5%
서 65
9.5%
동 65
9.5%
시 65
9.5%
역 65
9.5%
광 65
9.5%
마 21
 
3.1%
갈 13
 
1.9%
Other values (49) 133
19.4%
Decimal Number
ValueCountFrequency (%)
1 56
21.9%
3 34
13.3%
2 30
11.7%
9 27
10.5%
7 21
 
8.2%
6 19
 
7.4%
0 18
 
7.0%
5 18
 
7.0%
4 18
 
7.0%
8 15
 
5.9%
Space Separator
ValueCountFrequency (%)
204
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 38
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 687
58.0%
Common 498
42.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
대 65
9.5%
전 65
9.5%
구 65
9.5%
서 65
9.5%
동 65
9.5%
시 65
9.5%
역 65
9.5%
광 65
9.5%
마 21
 
3.1%
갈 13
 
1.9%
Other values (49) 133
19.4%
Common
ValueCountFrequency (%)
204
41.0%
1 56
 
11.2%
- 38
 
7.6%
3 34
 
6.8%
2 30
 
6.0%
9 27
 
5.4%
7 21
 
4.2%
6 19
 
3.8%
0 18
 
3.6%
5 18
 
3.6%
Other values (2) 33
 
6.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 687
58.0%
ASCII 498
42.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
204
41.0%
1 56
 
11.2%
- 38
 
7.6%
3 34
 
6.8%
2 30
 
6.0%
9 27
 
5.4%
7 21
 
4.2%
6 19
 
3.8%
0 18
 
3.6%
5 18
 
3.6%
Other values (2) 33
 
6.6%
Hangul
ValueCountFrequency (%)
대 65
9.5%
전 65
9.5%
구 65
9.5%
서 65
9.5%
동 65
9.5%
시 65
9.5%
역 65
9.5%
광 65
9.5%
마 21
 
3.1%
갈 13
 
1.9%
Other values (49) 133
19.4%

도로명주소
Text

Distinct61
Distinct (%)93.8%
Missing0
Missing (%)0.0%
Memory size652.0 B
2023-12-12T15:11:22.376111image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length32
Median length28
Mean length23.138462
Min length19

Characters and Unicode

Total characters1504
Distinct characters81
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique57 ?
Unique (%)87.7%

Sample

1st row대전광역시 서구 문정로48번길 70(탄방동)
2nd row대전광역시 서구 갈마로147번길 62(갈마동)
3rd row대전광역시 서구 갈마로 204(내동)
4th row대전광역시 서구 가수원로 64(가수원동)
5th row대전광역시 서구 갈마로 44(갈마동)
ValueCountFrequency (%)
대전광역시 65
24.8%
서구 65
24.8%
갈마로 5
 
1.9%
갈마로147번길 4
 
1.5%
신갈마로 3
 
1.1%
괴정로 2
 
0.8%
둔산남로9번길 2
 
0.8%
월평중로3번길 2
 
0.8%
도산로 2
 
0.8%
탄방로7번길 2
 
0.8%
Other values (104) 110
42.0%
2023-12-12T15:11:22.886558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
197
 
13.1%
동 70
 
4.7%
대 68
 
4.5%
서 67
 
4.5%
구 65
 
4.3%
) 65
 
4.3%
( 65
 
4.3%
전 65
 
4.3%
시 65
 
4.3%
역 65
 
4.3%
Other values (71) 712
47.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 938
62.4%
Decimal Number 232
 
15.4%
Space Separator 197
 
13.1%
Close Punctuation 65
 
4.3%
Open Punctuation 65
 
4.3%
Dash Punctuation 5
 
0.3%
Other Punctuation 2
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 70
 
7.5%
대 68
 
7.2%
서 67
 
7.1%
구 65
 
6.9%
전 65
 
6.9%
시 65
 
6.9%
역 65
 
6.9%
광 65
 
6.9%
로 59
 
6.3%
마 37
 
3.9%
Other values (56) 312
33.3%
Decimal Number
ValueCountFrequency (%)
1 50
21.6%
3 26
11.2%
6 25
10.8%
7 25
10.8%
4 23
9.9%
2 21
9.1%
0 18
 
7.8%
5 18
 
7.8%
8 13
 
5.6%
9 13
 
5.6%
Space Separator
ValueCountFrequency (%)
197
100.0%
Close Punctuation
ValueCountFrequency (%)
) 65
100.0%
Open Punctuation
ValueCountFrequency (%)
( 65
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%
Other Punctuation
ValueCountFrequency (%)
, 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 938
62.4%
Common 566
37.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 70
 
7.5%
대 68
 
7.2%
서 67
 
7.1%
구 65
 
6.9%
전 65
 
6.9%
시 65
 
6.9%
역 65
 
6.9%
광 65
 
6.9%
로 59
 
6.3%
마 37
 
3.9%
Other values (56) 312
33.3%
Common
ValueCountFrequency (%)
197
34.8%
) 65
 
11.5%
( 65
 
11.5%
1 50
 
8.8%
3 26
 
4.6%
6 25
 
4.4%
7 25
 
4.4%
4 23
 
4.1%
2 21
 
3.7%
0 18
 
3.2%
Other values (5) 51
 
9.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 938
62.4%
ASCII 566
37.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
197
34.8%
) 65
 
11.5%
( 65
 
11.5%
1 50
 
8.8%
3 26
 
4.6%
6 25
 
4.4%
7 25
 
4.4%
4 23
 
4.1%
2 21
 
3.7%
0 18
 
3.2%
Other values (5) 51
 
9.0%
Hangul
ValueCountFrequency (%)
동 70
 
7.5%
대 68
 
7.2%
서 67
 
7.1%
구 65
 
6.9%
전 65
 
6.9%
시 65
 
6.9%
역 65
 
6.9%
광 65
 
6.9%
로 59
 
6.3%
마 37
 
3.9%
Other values (56) 312
33.3%

상세주소
Text

Distinct63
Distinct (%)96.9%
Missing0
Missing (%)0.0%
Memory size652.0 B
2023-12-12T15:11:23.237727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length41
Median length34
Mean length28.769231
Min length22

Characters and Unicode

Total characters1870
Distinct characters102
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique61 ?
Unique (%)93.8%

Sample

1st row대전광역시 서구 문정로48번길 70, 202(일부)호 (탄방동)
2nd row대전광역시 서구 갈마로147번길 62, 2층 (갈마동)
3rd row대전광역시 서구 갈마로 204, 3층 (내동)
4th row대전광역시 서구 가수원로 64 (가수원동)
5th row대전광역시 서구 갈마로 44, 4층 (갈마동)
ValueCountFrequency (%)
대전광역시 65
 
16.6%
서구 65
 
16.6%
2층 20
 
5.1%
갈마동 13
 
3.3%
3층 13
 
3.3%
탄방동 11
 
2.8%
도마동 8
 
2.0%
둔산동 6
 
1.5%
갈마로 5
 
1.3%
변동 5
 
1.3%
Other values (136) 181
46.2%
2023-12-12T15:11:23.745151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
327
 
17.5%
동 70
 
3.7%
대 68
 
3.6%
서 67
 
3.6%
) 66
 
3.5%
( 66
 
3.5%
시 65
 
3.5%
역 65
 
3.5%
전 65
 
3.5%
구 65
 
3.5%
Other values (92) 946
50.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1027
54.9%
Space Separator 327
 
17.5%
Decimal Number 320
 
17.1%
Close Punctuation 66
 
3.5%
Open Punctuation 66
 
3.5%
Other Punctuation 59
 
3.2%
Dash Punctuation 5
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 70
 
6.8%
대 68
 
6.6%
서 67
 
6.5%
시 65
 
6.3%
역 65
 
6.3%
전 65
 
6.3%
구 65
 
6.3%
광 65
 
6.3%
로 60
 
5.8%
층 45
 
4.4%
Other values (76) 392
38.2%
Decimal Number
ValueCountFrequency (%)
1 63
19.7%
2 51
15.9%
3 45
14.1%
0 31
9.7%
4 30
9.4%
6 26
8.1%
7 25
 
7.8%
5 23
 
7.2%
9 13
 
4.1%
8 13
 
4.1%
Other Punctuation
ValueCountFrequency (%)
, 58
98.3%
@ 1
 
1.7%
Space Separator
ValueCountFrequency (%)
327
100.0%
Close Punctuation
ValueCountFrequency (%)
) 66
100.0%
Open Punctuation
ValueCountFrequency (%)
( 66
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1027
54.9%
Common 843
45.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 70
 
6.8%
대 68
 
6.6%
서 67
 
6.5%
시 65
 
6.3%
역 65
 
6.3%
전 65
 
6.3%
구 65
 
6.3%
광 65
 
6.3%
로 60
 
5.8%
층 45
 
4.4%
Other values (76) 392
38.2%
Common
ValueCountFrequency (%)
327
38.8%
) 66
 
7.8%
( 66
 
7.8%
1 63
 
7.5%
, 58
 
6.9%
2 51
 
6.0%
3 45
 
5.3%
0 31
 
3.7%
4 30
 
3.6%
6 26
 
3.1%
Other values (6) 80
 
9.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1027
54.9%
ASCII 843
45.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
327
38.8%
) 66
 
7.8%
( 66
 
7.8%
1 63
 
7.5%
, 58
 
6.9%
2 51
 
6.0%
3 45
 
5.3%
0 31
 
3.7%
4 30
 
3.6%
6 26
 
3.1%
Other values (6) 80
 
9.5%
Hangul
ValueCountFrequency (%)
동 70
 
6.8%
대 68
 
6.6%
서 67
 
6.5%
시 65
 
6.3%
역 65
 
6.3%
전 65
 
6.3%
구 65
 
6.3%
광 65
 
6.3%
로 60
 
5.8%
층 45
 
4.4%
Other values (76) 392
38.2%

전화번호
Text

MISSING 

Distinct55
Distinct (%)98.2%
Missing9
Missing (%)13.8%
Memory size652.0 B
2023-12-12T15:11:24.337631image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length12.071429
Min length12

Characters and Unicode

Total characters676
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

Unique54 ?
Unique (%)96.4%

Sample

1st row042-583-2511
2nd row042-632-2239
3rd row042-254-9609
4th row070-8221-2804
5th row042-472-7204
ValueCountFrequency (%)
042-632-2239 2
 
3.6%
042-483-9773 1
 
1.8%
042-585-2822 1
 
1.8%
042-532-8395 1
 
1.8%
070-8812-6909 1
 
1.8%
042-522-6148 1
 
1.8%
042-521-2804 1
 
1.8%
042-531-1804 1
 
1.8%
042-534-2879 1
 
1.8%
042-482-2876 1
 
1.8%
Other values (45) 45
80.4%
2023-12-12T15:11:24.699027image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2 145
21.4%
- 112
16.6%
4 107
15.8%
0 87
12.9%
8 56
 
8.3%
5 48
 
7.1%
3 40
 
5.9%
7 29
 
4.3%
6 18
 
2.7%
9 17
 
2.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 564
83.4%
Dash Punctuation 112
 
16.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
2 145
25.7%
4 107
19.0%
0 87
15.4%
8 56
 
9.9%
5 48
 
8.5%
3 40
 
7.1%
7 29
 
5.1%
6 18
 
3.2%
9 17
 
3.0%
1 17
 
3.0%
Dash Punctuation
ValueCountFrequency (%)
- 112
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 676
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
2 145
21.4%
- 112
16.6%
4 107
15.8%
0 87
12.9%
8 56
 
8.3%
5 48
 
7.1%
3 40
 
5.9%
7 29
 
4.3%
6 18
 
2.7%
9 17
 
2.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 676
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2 145
21.4%
- 112
16.6%
4 107
15.8%
0 87
12.9%
8 56
 
8.3%
5 48
 
7.1%
3 40
 
5.9%
7 29
 
4.3%
6 18
 
2.7%
9 17
 
2.5%

데이터기준일자
Date

CONSTANT 

Distinct1
Distinct (%)1.5%
Missing0
Missing (%)0.0%
Memory size652.0 B
Minimum2022-09-13 00:00:00
Maximum2022-09-13 00:00:00
2023-12-12T15:11:24.799529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:11:24.877344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

지번주소_X
Real number (ℝ)

HIGH CORRELATION 

Distinct60
Distinct (%)92.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.37666
Minimum127.34149
Maximum127.39912
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size717.0 B
2023-12-12T15:11:24.978796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum127.34149
5-th percentile127.35178
Q1127.36907
median127.37762
Q3127.38525
95-th percentile127.39589
Maximum127.39912
Range0.057634
Interquartile range (IQR)0.016184

Descriptive statistics

Standard deviation0.013160291
Coefficient of variation (CV)0.00010331792
Kurtosis0.30564943
Mean127.37666
Median Absolute Deviation (MAD)0.00823
Skewness-0.62767089
Sum8279.483
Variance0.00017319327
MonotonicityNot monotonic
2023-12-12T15:11:25.106709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.36829 2
 
3.1%
127.37711 2
 
3.1%
127.36907 2
 
3.1%
127.39599 2
 
3.1%
127.378334 2
 
3.1%
127.39845 1
 
1.5%
127.376396 1
 
1.5%
127.377075 1
 
1.5%
127.38806 1
 
1.5%
127.3788 1
 
1.5%
Other values (50) 50
76.9%
ValueCountFrequency (%)
127.34149 1
1.5%
127.344 1
1.5%
127.34917 1
1.5%
127.35138 1
1.5%
127.35337 1
1.5%
127.35368 1
1.5%
127.35415 1
1.5%
127.36062 1
1.5%
127.362076 1
1.5%
127.36571 1
1.5%
ValueCountFrequency (%)
127.399124 1
1.5%
127.39845 1
1.5%
127.39599 2
3.1%
127.395485 1
1.5%
127.394485 1
1.5%
127.39417 1
1.5%
127.3936 1
1.5%
127.39164 1
1.5%
127.39151 1
1.5%
127.39108 1
1.5%

지번주소_Y
Real number (ℝ)

HIGH CORRELATION 

Distinct61
Distinct (%)93.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean36.335689
Minimum36.254356
Maximum36.366047
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size717.0 B
2023-12-12T15:11:25.243139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.254356
5-th percentile36.302312
Q136.328205
median36.341084
Q336.34841
95-th percentile36.355819
Maximum36.366047
Range0.111691
Interquartile range (IQR)0.020205

Descriptive statistics

Standard deviation0.019021759
Coefficient of variation (CV)0.0005235007
Kurtosis3.9367881
Mean36.335689
Median Absolute Deviation (MAD)0.009643
Skewness-1.5518524
Sum2361.8198
Variance0.00036182731
MonotonicityNot monotonic
2023-12-12T15:11:25.360943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
36.341084 2
 
3.1%
36.34841 2
 
3.1%
36.319096 2
 
3.1%
36.344467 2
 
3.1%
36.34367 1
 
1.5%
36.348377 1
 
1.5%
36.329205 1
 
1.5%
36.33304 1
 
1.5%
36.350407 1
 
1.5%
36.34988 1
 
1.5%
Other values (51) 51
78.5%
ValueCountFrequency (%)
36.254356 1
1.5%
36.30038 1
1.5%
36.30163 1
1.5%
36.30187 1
1.5%
36.30408 1
1.5%
36.305645 1
1.5%
36.30746 1
1.5%
36.31323 1
1.5%
36.31324 1
1.5%
36.317326 1
1.5%
ValueCountFrequency (%)
36.366047 1
1.5%
36.35943 1
1.5%
36.359303 1
1.5%
36.35615 1
1.5%
36.354496 1
1.5%
36.354248 1
1.5%
36.353313 1
1.5%
36.35309 1
1.5%
36.351494 1
1.5%
36.350727 1
1.5%

도로명주소_X
Real number (ℝ)

HIGH CORRELATION 

Distinct60
Distinct (%)92.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.37666
Minimum127.3415
Maximum127.39912
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size717.0 B
2023-12-12T15:11:25.502059image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum127.3415
5-th percentile127.35178
Q1127.36912
median127.37761
Q3127.38522
95-th percentile127.39589
Maximum127.39912
Range0.057624
Interquartile range (IQR)0.016096

Descriptive statistics

Standard deviation0.013152554
Coefficient of variation (CV)0.00010325717
Kurtosis0.30896928
Mean127.37666
Median Absolute Deviation (MAD)0.00823
Skewness-0.62947218
Sum8279.4829
Variance0.00017298967
MonotonicityNot monotonic
2023-12-12T15:11:25.631585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.36832 2
 
3.1%
127.377106 2
 
3.1%
127.36912 2
 
3.1%
127.39599 2
 
3.1%
127.378334 2
 
3.1%
127.39845 1
 
1.5%
127.376396 1
 
1.5%
127.37707 1
 
1.5%
127.38805 1
 
1.5%
127.3788 1
 
1.5%
Other values (50) 50
76.9%
ValueCountFrequency (%)
127.3415 1
1.5%
127.34401 1
1.5%
127.349174 1
1.5%
127.35138 1
1.5%
127.35337 1
1.5%
127.353676 1
1.5%
127.35414 1
1.5%
127.36062 1
1.5%
127.362076 1
1.5%
127.365715 1
1.5%
ValueCountFrequency (%)
127.399124 1
1.5%
127.39845 1
1.5%
127.39599 2
3.1%
127.39549 1
1.5%
127.394485 1
1.5%
127.39418 1
1.5%
127.3936 1
1.5%
127.391655 1
1.5%
127.391106 1
1.5%
127.39105 1
1.5%

도로명주소_Y
Real number (ℝ)

HIGH CORRELATION 

Distinct61
Distinct (%)93.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean36.335683
Minimum36.25435
Maximum36.366066
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size717.0 B
2023-12-12T15:11:25.788333image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum36.25435
5-th percentile36.302329
Q136.328205
median36.34109
Q336.348415
95-th percentile36.355815
Maximum36.366066
Range0.111716
Interquartile range (IQR)0.02021

Descriptive statistics

Standard deviation0.019017258
Coefficient of variation (CV)0.00052337691
Kurtosis3.9426603
Mean36.335683
Median Absolute Deviation (MAD)0.009626
Skewness-1.5512294
Sum2361.8194
Variance0.00036165609
MonotonicityNot monotonic
2023-12-12T15:11:25.949972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
36.34109 2
 
3.1%
36.348415 2
 
3.1%
36.319096 2
 
3.1%
36.344467 2
 
3.1%
36.34367 1
 
1.5%
36.34838 1
 
1.5%
36.329212 1
 
1.5%
36.333057 1
 
1.5%
36.350403 1
 
1.5%
36.349865 1
 
1.5%
Other values (51) 51
78.5%
ValueCountFrequency (%)
36.25435 1
1.5%
36.300385 1
1.5%
36.30165 1
1.5%
36.30188 1
1.5%
36.304127 1
1.5%
36.30562 1
1.5%
36.307465 1
1.5%
36.313248 1
1.5%
36.31327 1
1.5%
36.31732 1
1.5%
ValueCountFrequency (%)
36.366066 1
1.5%
36.359566 1
1.5%
36.359314 1
1.5%
36.356148 1
1.5%
36.354485 1
1.5%
36.354244 1
1.5%
36.353313 1
1.5%
36.353096 1
1.5%
36.351482 1
1.5%
36.350716 1
1.5%

Interactions

2023-12-12T15:11:18.440843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:11:14.933713image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:11:15.648443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:11:16.440069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:11:17.083723image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:11:17.786314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:11:18.547505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:11:15.080140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:11:15.752903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:11:16.540309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:11:17.203517image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:11:17.902009image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:11:18.643430image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:11:15.205058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:11:15.877725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:11:16.650464image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:11:17.332859image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:11:18.008147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:11:18.753094image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:11:15.313754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:11:16.034446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:11:16.771060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:11:17.429069image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:11:18.121678image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:11:18.837425image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:11:15.416591image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:11:16.157633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:11:16.873626image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:11:17.541316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:11:18.243222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:11:18.944897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:11:15.534499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:11:16.316276image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:11:16.982891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:11:17.683292image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T15:11:18.353866image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T15:11:26.124997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
의료업소명칭행정동코드행정동명법정동코드법정동명지번주소도로명주소상세주소전화번호지번주소_X지번주소_Y도로명주소_X도로명주소_Y
의료업소명칭1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
행정동코드1.0001.0001.0000.8690.9651.0001.0001.0001.0000.5960.8300.5960.830
행정동명1.0001.0001.0001.0001.0001.0001.0001.0001.0000.9370.9690.9370.969
법정동코드1.0000.8691.0001.0001.0001.0001.0001.0001.0000.7570.9320.7570.932
법정동명1.0000.9651.0001.0001.0001.0001.0001.0001.0000.8670.9440.8670.944
지번주소1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
도로명주소1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
상세주소1.0001.0001.0001.0001.0001.0001.0001.0000.9911.0001.0001.0001.000
전화번호1.0001.0001.0001.0001.0001.0001.0000.9911.0001.0001.0001.0001.000
지번주소_X1.0000.5960.9370.7570.8671.0001.0001.0001.0001.0000.7141.0000.714
지번주소_Y1.0000.8300.9690.9320.9441.0001.0001.0001.0000.7141.0000.7141.000
도로명주소_X1.0000.5960.9370.7570.8671.0001.0001.0001.0001.0000.7141.0000.714
도로명주소_Y1.0000.8300.9690.9320.9441.0001.0001.0001.0000.7141.0000.7141.000
2023-12-12T15:11:26.269860image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
법정동명행정동명
법정동명1.0000.949
행정동명0.9491.000
2023-12-12T15:11:26.369680image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
행정동코드법정동코드지번주소_X지번주소_Y도로명주소_X도로명주소_Y행정동명법정동명
행정동코드1.0000.953-0.3110.482-0.3110.4830.8960.799
법정동코드0.9531.000-0.4400.409-0.4400.4110.8810.928
지번주소_X-0.311-0.4401.0000.1661.0000.1620.5520.521
지번주소_Y0.4820.4090.1661.0000.1661.0000.7590.747
도로명주소_X-0.311-0.4401.0000.1661.0000.1620.5520.521
도로명주소_Y0.4830.4110.1621.0000.1621.0000.7590.747
행정동명0.8960.8810.5520.7590.5520.7591.0000.949
법정동명0.7990.9280.5210.7470.5210.7470.9491.000

Missing values

2023-12-12T15:11:19.088741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T15:11:19.278546image/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

의료업소명칭종별명행정동코드행정동명법정동코드법정동명지번주소도로명주소상세주소전화번호데이터기준일자지번주소_X지번주소_Y도로명주소_X도로명주소_Y
0도담치과기공소치과기공소3017055500탄방동3017010600탄방동대전광역시 서구 탄방동 642대전광역시 서구 문정로48번길 70(탄방동)대전광역시 서구 문정로48번길 70, 202(일부)호 (탄방동)042-583-25112022-09-13 00:00127.38405636.34367127.3840436.34367
1PDL(피디엘)치과기공소치과기공소3017058200갈마2동3017011100갈마동대전광역시 서구 갈마동 1374대전광역시 서구 갈마로147번길 62(갈마동)대전광역시 서구 갈마로147번길 62, 2층 (갈마동)042-632-22392022-09-13 00:00127.3771136.341084127.37710636.34109
2나로치과기공소치과기공소3017057500내동3017011000내동대전광역시 서구 내동 36-3대전광역시 서구 갈마로 204(내동)대전광역시 서구 갈마로 204, 3층 (내동)<NA>2022-09-13 00:00127.37781536.336685127.37781536.336685
3유니플란트치과기공소치과기공소3017059000가수원동3017011400가수원동대전광역시 서구 가수원동 774-15대전광역시 서구 가수원로 64(가수원동)대전광역시 서구 가수원로 64 (가수원동)<NA>2022-09-13 00:00127.3513836.30038127.3513836.300385
4디지털시너지기공소치과기공소3017058100갈마1동3017011100갈마동대전광역시 서구 갈마동 363-11대전광역시 서구 갈마로 44(갈마동)대전광역시 서구 갈마로 44, 4층 (갈마동)042-254-96092022-09-13 00:00127.3690736.34841127.3691236.348415
5제이디지털랩치과기공소3017058700월평2동3017011300월평동대전광역시 서구 월평동 282-2 청사로프라자대전광역시 서구 청사로 130(월평동)대전광역시 서구 청사로 130, 청사로프라자 301호 (월평동)<NA>2022-09-13 00:00127.3783836.35943127.3784136.359566
6스마일치과기공소치과기공소3017060000기성동3017011700흑석동대전광역시 서구 흑석동 968대전광역시 서구 금평2길 25(흑석동)대전광역시 서구 금평2길 25 (흑석동)<NA>2022-09-13 00:00127.3414936.254356127.341536.25435
7램브란트치과기공소치과기공소3017063000둔산1동3017011200둔산동대전광역시 서구 둔산동 1423 크레온오피스텔대전광역시 서구 둔산남로 85(둔산동)대전광역시 서구 둔산남로 85, 크레온오피스텔 (둔산동)<NA>2022-09-13 00:00127.3870936.34932127.3870936.34932
8조아치과기공소치과기공소3017058100갈마1동3017011100갈마동대전광역시 서구 갈마동 363-11대전광역시 서구 갈마로 44(갈마동)대전광역시 서구 갈마로 44, 3층 (갈마동)<NA>2022-09-13 00:00127.3690736.34841127.3691236.348415
9금강치과기공소치과기공소3017052000도마1동3017010300도마동대전광역시 서구 도마동 89-26대전광역시 서구 도마6길 34(도마동)대전광역시 서구 도마6길 34, 2층 (도마동)070-8221-28042022-09-13 00:00127.3789236.317326127.3789236.31732
의료업소명칭종별명행정동코드행정동명법정동코드법정동명지번주소도로명주소상세주소전화번호데이터기준일자지번주소_X지번주소_Y도로명주소_X도로명주소_Y
55선사치과기공소치과기공소3017058700월평2동3017011300월평동대전광역시 서구 월평동 293대전광역시 서구 청사서로 16(월평동)대전광역시 서구 청사서로 16, 4층 (월평동)042-485-08382022-09-13 00:00127.376936.359303127.376936.359314
56신성치과기공소치과기공소3017056000괴정동3017010800괴정동대전광역시 서구 괴정동 91-22대전광역시 서구 갈마로 255(괴정동)대전광역시 서구 갈마로 255 (괴정동)042-523-85912022-09-13 00:00127.3822336.33347127.3823136.333534
57경수치과기공소치과기공소3017056000괴정동3017010800괴정동대전광역시 서구 괴정동 53-10대전광역시 서구 괴정로 107(괴정동)대전광역시 서구 괴정로 107, 302호 (괴정동)042-527-28042022-09-13 00:00127.38525436.338036127.38521636.338066
58원광치과기공소치과기공소3017054000변동3017010200변동대전광역시 서구 변동 79-23대전광역시 서구 변동중로45번길 3(변동)대전광역시 서구 변동중로45번길 3 (변동)042-523-72232022-09-13 00:00127.37427536.328598127.3742836.3286
59바른이치과기공소치과기공소3017059000도안동3017011500도안동대전광역시 서구 도안동 1197 하랑대전광역시 서구 원도안로207번길 16-35(도안동)대전광역시 서구 원도안로207번길 16-35, 1층 (도안동)042-253-02772022-09-13 00:00127.34436.323986127.3440136.32398
60부희치과기공소치과기공소3017053000도마2동3017010300도마동대전광역시 서구 도마동 99-28대전광역시 서구 도산로 117(도마동)대전광역시 서구 도산로 117 (도마동)042-532-86462022-09-13 00:00127.3775636.318813127.3775736.318813
61둔산치과기공소치과기공소3017055500탄방동3017010600탄방동대전광역시 서구 탄방동 689 산호아파트대전광역시 서구 계룡로571번길 65(탄방동, 산호아파트)대전광역시 서구 계룡로571번길 65 (탄방동, 한양산호@ 상가 305호)042-486-46342022-09-13 00:00127.3866936.34479127.3867536.34382
62세종치과기공소치과기공소3017052000도마1동3017010300도마동대전광역시 서구 도마동 83-11대전광역시 서구 도마로 116(도마동)대전광역시 서구 도마로 116, 2층 (도마동)042-525-74222022-09-13 00:00127.3828436.321285127.3828536.321304
63평화치과기공소치과기공소3017054000변동3017010200변동대전광역시 서구 변동 12-42대전광역시 서구 중반5길 8(변동)대전광역시 서구 중반5길 8, 2층 (변동)042-583-28442022-09-13 00:00127.3819736.328205127.38196636.328205
64청도치과기공소치과기공소3017057500내동3017011000내동대전광역시 서구 내동 8-19대전광역시 서구 도산로 239(내동)대전광역시 서구 도산로 239, 3층 (내동)042-531-99802022-09-13 00:00127.3816236.32928127.38164536.32926