Overview

Dataset statistics

Number of variables6
Number of observations324
Missing cells111
Missing cells (%)5.7%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory15.6 KiB
Average record size in memory49.4 B

Variable types

Numeric1
Text4
DateTime1

Dataset

Description청주시 건물위생관리업소 현황에 대한 데이터로 청주시 4개구(상당구, 서원구, 흥덕구, 청원구)의 업소명, 도로명주소, 지번주소, 소재지전화를 제공합니다.
URLhttps://www.data.go.kr/data/15066828/fileData.do

Alerts

데이터기준일 has constant value ""Constant
소재지전화 has 110 (34.0%) missing valuesMissing
연번 has unique valuesUnique
업소명 has unique valuesUnique

Reproduction

Analysis started2023-12-12 17:14:16.811693
Analysis finished2023-12-12 17:14:17.610427
Duration0.8 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

연번
Real number (ℝ)

UNIQUE 

Distinct324
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean162.5
Minimum1
Maximum324
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.0 KiB
2023-12-13T02:14:17.707893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile17.15
Q181.75
median162.5
Q3243.25
95-th percentile307.85
Maximum324
Range323
Interquartile range (IQR)161.5

Descriptive statistics

Standard deviation93.67497
Coefficient of variation (CV)0.57646135
Kurtosis-1.2
Mean162.5
Median Absolute Deviation (MAD)81
Skewness0
Sum52650
Variance8775
MonotonicityStrictly increasing
2023-12-13T02:14:17.895586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.3%
205 1
 
0.3%
223 1
 
0.3%
222 1
 
0.3%
221 1
 
0.3%
220 1
 
0.3%
219 1
 
0.3%
218 1
 
0.3%
217 1
 
0.3%
216 1
 
0.3%
Other values (314) 314
96.9%
ValueCountFrequency (%)
1 1
0.3%
2 1
0.3%
3 1
0.3%
4 1
0.3%
5 1
0.3%
6 1
0.3%
7 1
0.3%
8 1
0.3%
9 1
0.3%
10 1
0.3%
ValueCountFrequency (%)
324 1
0.3%
323 1
0.3%
322 1
0.3%
321 1
0.3%
320 1
0.3%
319 1
0.3%
318 1
0.3%
317 1
0.3%
316 1
0.3%
315 1
0.3%

업소명
Text

UNIQUE 

Distinct324
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size2.7 KiB
2023-12-13T02:14:18.150590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length21
Median length15
Mean length7.058642
Min length2

Characters and Unicode

Total characters2287
Distinct characters297
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique324 ?
Unique (%)100.0%

Sample

1st row(주)영창
2nd row안전용역
3rd row(주)경보
4th row(주)영우아웃소싱
5th row부건피앤피(주)
ValueCountFrequency (%)
주식회사 26
 
7.0%
환경 2
 
0.5%
주)케이에스지 2
 
0.5%
청주 2
 
0.5%
주)영창 1
 
0.3%
씨엔씨크린 1
 
0.3%
씨제이(cj)종합관리 1
 
0.3%
나린클린 1
 
0.3%
시니어푸르미(청주흥덕시니어클럽 1
 
0.3%
두꺼비산업개발 1
 
0.3%
Other values (335) 335
89.8%
2023-12-13T02:14:18.517362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 187
 
8.2%
) 136
 
5.9%
( 134
 
5.9%
사 64
 
2.8%
린 54
 
2.4%
이 53
 
2.3%
회 50
 
2.2%
49
 
2.1%
스 48
 
2.1%
식 45
 
2.0%
Other values (287) 1467
64.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1932
84.5%
Close Punctuation 136
 
5.9%
Open Punctuation 134
 
5.9%
Space Separator 49
 
2.1%
Uppercase Letter 26
 
1.1%
Other Punctuation 9
 
0.4%
Decimal Number 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 187
 
9.7%
사 64
 
3.3%
린 54
 
2.8%
이 53
 
2.7%
회 50
 
2.6%
스 48
 
2.5%
식 45
 
2.3%
청 40
 
2.1%
리 40
 
2.1%
크 39
 
2.0%
Other values (266) 1312
67.9%
Uppercase Letter
ValueCountFrequency (%)
S 4
15.4%
C 4
15.4%
D 3
11.5%
J 3
11.5%
K 2
7.7%
M 2
7.7%
W 1
 
3.8%
B 1
 
3.8%
A 1
 
3.8%
Y 1
 
3.8%
Other values (4) 4
15.4%
Other Punctuation
ValueCountFrequency (%)
, 5
55.6%
& 3
33.3%
. 1
 
11.1%
Close Punctuation
ValueCountFrequency (%)
) 136
100.0%
Open Punctuation
ValueCountFrequency (%)
( 134
100.0%
Space Separator
ValueCountFrequency (%)
49
100.0%
Decimal Number
ValueCountFrequency (%)
3 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1932
84.5%
Common 329
 
14.4%
Latin 26
 
1.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 187
 
9.7%
사 64
 
3.3%
린 54
 
2.8%
이 53
 
2.7%
회 50
 
2.6%
스 48
 
2.5%
식 45
 
2.3%
청 40
 
2.1%
리 40
 
2.1%
크 39
 
2.0%
Other values (266) 1312
67.9%
Latin
ValueCountFrequency (%)
S 4
15.4%
C 4
15.4%
D 3
11.5%
J 3
11.5%
K 2
7.7%
M 2
7.7%
W 1
 
3.8%
B 1
 
3.8%
A 1
 
3.8%
Y 1
 
3.8%
Other values (4) 4
15.4%
Common
ValueCountFrequency (%)
) 136
41.3%
( 134
40.7%
49
 
14.9%
, 5
 
1.5%
& 3
 
0.9%
. 1
 
0.3%
3 1
 
0.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1932
84.5%
ASCII 355
 
15.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 187
 
9.7%
사 64
 
3.3%
린 54
 
2.8%
이 53
 
2.7%
회 50
 
2.6%
스 48
 
2.5%
식 45
 
2.3%
청 40
 
2.1%
리 40
 
2.1%
크 39
 
2.0%
Other values (266) 1312
67.9%
ASCII
ValueCountFrequency (%)
) 136
38.3%
( 134
37.7%
49
 
13.8%
, 5
 
1.4%
S 4
 
1.1%
C 4
 
1.1%
& 3
 
0.8%
D 3
 
0.8%
J 3
 
0.8%
K 2
 
0.6%
Other values (11) 12
 
3.4%

영업소 주소(도로명)
Text

Distinct316
Distinct (%)97.8%
Missing1
Missing (%)0.3%
Memory size2.7 KiB
2023-12-13T02:14:18.759201image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length55
Median length48
Mean length34.910217
Min length24

Characters and Unicode

Total characters11276
Distinct characters235
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique309 ?
Unique (%)95.7%

Sample

1st row충청북도 청주시 상당구 교서로 80-1 (영동, 3층)
2nd row충청북도 청주시 상당구 원봉로93번길 13 (용암동)
3rd row충청북도 청주시 상당구 용정로38번길 27-1, 1층 (용정동)
4th row충청북도 청주시 상당구 교동로3번길 60, 2층 (수동)
5th row충청북도 청주시 상당구 용암북로160번길 20, 대화프라자 201호 (용암동)
ValueCountFrequency (%)
청주시 324
 
13.6%
충청북도 323
 
13.5%
1층 139
 
5.8%
흥덕구 112
 
4.7%
청원구 79
 
3.3%
상당구 72
 
3.0%
서원구 60
 
2.5%
2층 55
 
2.3%
봉명동 29
 
1.2%
일부호 26
 
1.1%
Other values (619) 1166
48.9%
2023-12-13T02:14:19.113686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2062
 
18.3%
청 753
 
6.7%
1 509
 
4.5%
충 347
 
3.1%
북 346
 
3.1%
주 343
 
3.0%
구 338
 
3.0%
시 328
 
2.9%
도 326
 
2.9%
동 316
 
2.8%
Other values (225) 5608
49.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6442
57.1%
Space Separator 2062
 
18.3%
Decimal Number 1747
 
15.5%
Other Punctuation 317
 
2.8%
Open Punctuation 298
 
2.6%
Close Punctuation 298
 
2.6%
Dash Punctuation 100
 
0.9%
Uppercase Letter 8
 
0.1%
Math Symbol 2
 
< 0.1%
Lowercase Letter 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
청 753
 
11.7%
충 347
 
5.4%
북 346
 
5.4%
주 343
 
5.3%
구 338
 
5.2%
시 328
 
5.1%
도 326
 
5.1%
동 316
 
4.9%
로 313
 
4.9%
층 275
 
4.3%
Other values (202) 2757
42.8%
Decimal Number
ValueCountFrequency (%)
1 509
29.1%
2 280
16.0%
3 199
 
11.4%
0 136
 
7.8%
4 134
 
7.7%
5 128
 
7.3%
6 106
 
6.1%
9 90
 
5.2%
8 85
 
4.9%
7 80
 
4.6%
Uppercase Letter
ValueCountFrequency (%)
B 4
50.0%
S 2
25.0%
D 1
 
12.5%
A 1
 
12.5%
Other Punctuation
ValueCountFrequency (%)
, 316
99.7%
. 1
 
0.3%
Lowercase Letter
ValueCountFrequency (%)
t 1
50.0%
s 1
50.0%
Space Separator
ValueCountFrequency (%)
2062
100.0%
Open Punctuation
ValueCountFrequency (%)
( 298
100.0%
Close Punctuation
ValueCountFrequency (%)
) 298
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 100
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6442
57.1%
Common 4824
42.8%
Latin 10
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
청 753
 
11.7%
충 347
 
5.4%
북 346
 
5.4%
주 343
 
5.3%
구 338
 
5.2%
시 328
 
5.1%
도 326
 
5.1%
동 316
 
4.9%
로 313
 
4.9%
층 275
 
4.3%
Other values (202) 2757
42.8%
Common
ValueCountFrequency (%)
2062
42.7%
1 509
 
10.6%
, 316
 
6.6%
( 298
 
6.2%
) 298
 
6.2%
2 280
 
5.8%
3 199
 
4.1%
0 136
 
2.8%
4 134
 
2.8%
5 128
 
2.7%
Other values (7) 464
 
9.6%
Latin
ValueCountFrequency (%)
B 4
40.0%
S 2
20.0%
D 1
 
10.0%
t 1
 
10.0%
A 1
 
10.0%
s 1
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6442
57.1%
ASCII 4834
42.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2062
42.7%
1 509
 
10.5%
, 316
 
6.5%
( 298
 
6.2%
) 298
 
6.2%
2 280
 
5.8%
3 199
 
4.1%
0 136
 
2.8%
4 134
 
2.8%
5 128
 
2.6%
Other values (13) 474
 
9.8%
Hangul
ValueCountFrequency (%)
청 753
 
11.7%
충 347
 
5.4%
북 346
 
5.4%
주 343
 
5.3%
구 338
 
5.2%
시 328
 
5.1%
도 326
 
5.1%
동 316
 
4.9%
로 313
 
4.9%
층 275
 
4.3%
Other values (202) 2757
42.8%

영업소 주소(지번)
Text

Distinct304
Distinct (%)93.8%
Missing0
Missing (%)0.0%
Memory size2.7 KiB
2023-12-13T02:14:19.289598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length46
Median length41
Mean length26.740741
Min length9

Characters and Unicode

Total characters8664
Distinct characters214
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique289 ?
Unique (%)89.2%

Sample

1st row충청북도 청주시 상당구 영동 13-13
2nd row충청북도 청주시 상당구 용암동 2168
3rd row충청북도 청주시 상당구 용정동 1203 1층
4th row충청북도 청주시 상당구 수동 341-2 (2층)
5th row충청북도 청주시 상당구 용암동 2650 대화프라자 201호
ValueCountFrequency (%)
충청북도 323
16.8%
청주시 323
16.8%
흥덕구 112
 
5.8%
청원구 78
 
4.1%
상당구 73
 
3.8%
1층 68
 
3.5%
서원구 60
 
3.1%
2층 29
 
1.5%
봉명동 29
 
1.5%
내덕동 22
 
1.1%
Other values (480) 803
41.8%
2023-12-13T02:14:19.618433image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1893
21.8%
청 744
 
8.6%
1 371
 
4.3%
주 341
 
3.9%
충 336
 
3.9%
북 332
 
3.8%
시 328
 
3.8%
구 326
 
3.8%
도 325
 
3.8%
동 293
 
3.4%
Other values (204) 3375
39.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4915
56.7%
Space Separator 1893
 
21.8%
Decimal Number 1529
 
17.6%
Dash Punctuation 205
 
2.4%
Close Punctuation 47
 
0.5%
Open Punctuation 47
 
0.5%
Uppercase Letter 13
 
0.2%
Other Punctuation 10
 
0.1%
Math Symbol 3
 
< 0.1%
Lowercase Letter 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
청 744
15.1%
주 341
 
6.9%
충 336
 
6.8%
북 332
 
6.8%
시 328
 
6.7%
구 326
 
6.6%
도 325
 
6.6%
동 293
 
6.0%
원 143
 
2.9%
층 138
 
2.8%
Other values (175) 1609
32.7%
Decimal Number
ValueCountFrequency (%)
1 371
24.3%
2 222
14.5%
3 149
9.7%
4 147
 
9.6%
0 140
 
9.2%
5 119
 
7.8%
6 112
 
7.3%
7 107
 
7.0%
8 96
 
6.3%
9 66
 
4.3%
Uppercase Letter
ValueCountFrequency (%)
B 4
30.8%
S 2
15.4%
E 2
15.4%
A 1
 
7.7%
C 1
 
7.7%
L 1
 
7.7%
P 1
 
7.7%
R 1
 
7.7%
Math Symbol
ValueCountFrequency (%)
~ 1
33.3%
> 1
33.3%
< 1
33.3%
Other Punctuation
ValueCountFrequency (%)
, 9
90.0%
. 1
 
10.0%
Lowercase Letter
ValueCountFrequency (%)
t 1
50.0%
s 1
50.0%
Space Separator
ValueCountFrequency (%)
1893
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 205
100.0%
Close Punctuation
ValueCountFrequency (%)
) 47
100.0%
Open Punctuation
ValueCountFrequency (%)
( 47
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4915
56.7%
Common 3734
43.1%
Latin 15
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
청 744
15.1%
주 341
 
6.9%
충 336
 
6.8%
북 332
 
6.8%
시 328
 
6.7%
구 326
 
6.6%
도 325
 
6.6%
동 293
 
6.0%
원 143
 
2.9%
층 138
 
2.8%
Other values (175) 1609
32.7%
Common
ValueCountFrequency (%)
1893
50.7%
1 371
 
9.9%
2 222
 
5.9%
- 205
 
5.5%
3 149
 
4.0%
4 147
 
3.9%
0 140
 
3.7%
5 119
 
3.2%
6 112
 
3.0%
7 107
 
2.9%
Other values (9) 269
 
7.2%
Latin
ValueCountFrequency (%)
B 4
26.7%
S 2
13.3%
E 2
13.3%
A 1
 
6.7%
t 1
 
6.7%
s 1
 
6.7%
C 1
 
6.7%
L 1
 
6.7%
P 1
 
6.7%
R 1
 
6.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4915
56.7%
ASCII 3749
43.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1893
50.5%
1 371
 
9.9%
2 222
 
5.9%
- 205
 
5.5%
3 149
 
4.0%
4 147
 
3.9%
0 140
 
3.7%
5 119
 
3.2%
6 112
 
3.0%
7 107
 
2.9%
Other values (19) 284
 
7.6%
Hangul
ValueCountFrequency (%)
청 744
15.1%
주 341
 
6.9%
충 336
 
6.8%
북 332
 
6.8%
시 328
 
6.7%
구 326
 
6.6%
도 325
 
6.6%
동 293
 
6.0%
원 143
 
2.9%
층 138
 
2.8%
Other values (175) 1609
32.7%

소재지전화
Text

MISSING 

Distinct208
Distinct (%)97.2%
Missing110
Missing (%)34.0%
Memory size2.7 KiB
2023-12-13T02:14:20.163034image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length14
Mean length13.71028
Min length12

Characters and Unicode

Total characters2934
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique202 ?
Unique (%)94.4%

Sample

1st row043- 255-7757
2nd row043- 294-7560
3rd row043- 225-0020
4th row043- 223-2001
5th row043 -233 -8525
ValueCountFrequency (%)
043 197
34.6%
221 9
 
1.6%
070 8
 
1.4%
264 7
 
1.2%
288 6
 
1.1%
233 6
 
1.1%
223 5
 
0.9%
237 5
 
0.9%
292 5
 
0.9%
222 5
 
0.9%
Other values (254) 316
55.5%
2023-12-13T02:14:20.970567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 428
14.6%
0 374
12.7%
355
12.1%
3 350
11.9%
2 342
11.7%
4 313
10.7%
7 150
 
5.1%
8 141
 
4.8%
5 135
 
4.6%
1 131
 
4.5%
Other values (2) 215
7.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2151
73.3%
Dash Punctuation 428
 
14.6%
Space Separator 355
 
12.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 374
17.4%
3 350
16.3%
2 342
15.9%
4 313
14.6%
7 150
7.0%
8 141
 
6.6%
5 135
 
6.3%
1 131
 
6.1%
6 115
 
5.3%
9 100
 
4.6%
Dash Punctuation
ValueCountFrequency (%)
- 428
100.0%
Space Separator
ValueCountFrequency (%)
355
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2934
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 428
14.6%
0 374
12.7%
355
12.1%
3 350
11.9%
2 342
11.7%
4 313
10.7%
7 150
 
5.1%
8 141
 
4.8%
5 135
 
4.6%
1 131
 
4.5%
Other values (2) 215
7.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2934
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 428
14.6%
0 374
12.7%
355
12.1%
3 350
11.9%
2 342
11.7%
4 313
10.7%
7 150
 
5.1%
8 141
 
4.8%
5 135
 
4.6%
1 131
 
4.5%
Other values (2) 215
7.3%

데이터기준일
Date

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size2.7 KiB
Minimum2023-08-07 00:00:00
Maximum2023-08-07 00:00:00
2023-12-13T02:14:21.100302image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-13T02:14:21.212490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

Interactions

2023-12-13T02:14:17.226166image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Missing values

2023-12-13T02:14:17.353180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-13T02:14:17.462538image/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.
2023-12-13T02:14:17.563615image/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

연번업소명영업소 주소(도로명)영업소 주소(지번)소재지전화데이터기준일
01(주)영창충청북도 청주시 상당구 교서로 80-1 (영동, 3층)충청북도 청주시 상당구 영동 13-13043- 255-77572023-08-07
12안전용역충청북도 청주시 상당구 원봉로93번길 13 (용암동)충청북도 청주시 상당구 용암동 2168043- 294-75602023-08-07
23(주)경보충청북도 청주시 상당구 용정로38번길 27-1, 1층 (용정동)충청북도 청주시 상당구 용정동 1203 1층043- 225-00202023-08-07
34(주)영우아웃소싱충청북도 청주시 상당구 교동로3번길 60, 2층 (수동)충청북도 청주시 상당구 수동 341-2 (2층)043- 223-20012023-08-07
45부건피앤피(주)충청북도 청주시 상당구 용암북로160번길 20, 대화프라자 201호 (용암동)충청북도 청주시 상당구 용암동 2650 대화프라자 201호043 -233 -85252023-08-07
56청우E&D충청북도 청주시 상당구 영운천로129번길 20 (용정동, 1층)충청북도 청주시 상당구 용정동 606 (1층)043 -257 -09322023-08-07
67삼성산업관리(주)충청북도 청주시 상당구 교서로 80-1 (영동,4층)충청북도 청주시 상당구 영동 13-13 4층043- 256-77552023-08-07
78(주)태창피엔씨충청북도 청주시 상당구 영운천로133번길 23, 1층 (용정동)충청북도 청주시 상당구 용정동 618 1층<NA>2023-08-07
89하나환경주식회사충청북도 청주시 상당구 중흥로31번길 12 (용암동, 1층)충청북도 청주시 상당구 용암동 1544 1층043 -288 -12362023-08-07
910(주)세종커뮤니티충청북도 청주시 상당구 상당로 109-1 (북문로2가, 2층)충청북도 청주시 상당구 북문로2가 116-195 2층043 -250 -91912023-08-07
연번업소명영업소 주소(도로명)영업소 주소(지번)소재지전화데이터기준일
314315주식회사 이든종합관리충청북도 청주시 청원구 오창읍 중심상업로 32-13, 엔젤프리존 7층 701-02호충청북도 청주시 청원구 오창읍 양청리 798-3 엔젤프리존 701-02호<NA>2023-08-07
315316도담하우징케어충청북도 청주시 청원구 내수읍 충청대로 889, 1,2층충청북도 청주시 청원구 내수읍 마산리 15-5 1,2층043 -224 -28012023-08-07
316317베스트테크충청북도 청주시 청원구 발산로 98-23, 1층 (사천동)충청북도 청주시 청원구 사천동 110-23 1층043 -212 -56122023-08-07
317318동보산업개발충청북도 청주시 청원구 발산로 98-17, 1층 (사천동)충청북도 청주시 청원구 사천동 110-26<NA>2023-08-07
318319홈닥터 홈케어충청북도 청주시 청원구 토성로362번길 92-2, 2층 (오동동)충청북도 청주시 청원구 오동동 26-2 2층 일부070 -8239-50072023-08-07
319320해피플러스충청북도 청주시 청원구 오창읍 두릉유리로 1130-10, B동 1층 4호충청북도 청주시 청원구 오창읍 창리 45-1 B동 4호<NA>2023-08-07
320321D&B테크충청북도 청주시 청원구 발산로 98-17, 1층 (사천동)충청북도 청주시 청원구 사천동 110-26043 -2115-5252023-08-07
321322다해드림청소충청북도 청주시 청원구 공항로 34, 1층 (내덕동)충청북도 청주시 청원구 내덕동 403-23 1층043- 296-40002023-08-07
322323신흥종합청소 상가,사무실,공장,화재청소충청북도 청주시 청원구 오창읍 양청택지로 16, 1층충청북도 청주시 청원구 오창읍 양청리 719-6 1층<NA>2023-08-07
323324(주)디자인명성충청북도 청주시 청원구 토성로214번가길 32-129, 1층 (정상동)충청북도 청주시 청원구 정상동 30-11043- 216-63882023-08-07