Overview

Dataset statistics

Number of variables38
Number of observations580
Missing cells3531
Missing cells (%)16.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory187.6 KiB
Average record size in memory331.2 B

Variable types

Numeric15
Categorical13
Text5
Unsupported4
DateTime1

Dataset

Description6270000_대구광역시_09_30_11_P_소독업_9월
Author대구광역시
URLhttp://data.daegu.go.kr/open/data/dataView.do?dataSetId=DMI_0000086183&dataSetDetailId=DDI_0000086217&provdMethod=FILE

Alerts

개방서비스명 has constant value ""Constant
개방서비스ID has constant value ""Constant
영업상태구분코드 is highly imbalanced (50.6%)Imbalance
영업상태명 is highly imbalanced (50.6%)Imbalance
상세영업상태코드 is highly imbalanced (50.6%)Imbalance
상세영업상태명 is highly imbalanced (50.6%)Imbalance
휴업시작일자 is highly imbalanced (98.2%)Imbalance
휴업종료일자 is highly imbalanced (98.2%)Imbalance
초미립자살포기수 is highly imbalanced (78.7%)Imbalance
휴대용소독기수 is highly imbalanced (89.3%)Imbalance
동력분무기수 is highly imbalanced (53.4%)Imbalance
진공청소기수 is highly imbalanced (74.9%)Imbalance
인허가취소일자 has 580 (100.0%) missing valuesMissing
폐업일자 has 390 (67.2%) missing valuesMissing
재개업일자 has 580 (100.0%) missing valuesMissing
소재지전화 has 171 (29.5%) missing valuesMissing
소재지면적 has 580 (100.0%) missing valuesMissing
소재지우편번호 has 339 (58.4%) missing valuesMissing
소재지전체주소 has 61 (10.5%) missing valuesMissing
도로명우편번호 has 51 (8.8%) missing valuesMissing
업태구분명 has 580 (100.0%) missing valuesMissing
사무실면적 has 89 (15.3%) missing valuesMissing
소독차량차고면적 has 104 (17.9%) missing valuesMissing
사무실면적 is highly skewed (γ1 = 20.35689329)Skewed
번호 has unique valuesUnique
관리번호 has unique valuesUnique
최종수정시점 has unique valuesUnique
인허가취소일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
재개업일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
소재지면적 is an unsupported type, check if it needs cleaning or further analysisUnsupported
업태구분명 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-04-18 07:40:25.438182
Analysis finished2024-04-18 07:40:26.127237
Duration0.69 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct580
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean290.5
Minimum1
Maximum580
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.2 KiB
2024-04-18T16:40:26.449795image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile29.95
Q1145.75
median290.5
Q3435.25
95-th percentile551.05
Maximum580
Range579
Interquartile range (IQR)289.5

Descriptive statistics

Standard deviation167.57585
Coefficient of variation (CV)0.5768532
Kurtosis-1.2
Mean290.5
Median Absolute Deviation (MAD)145
Skewness0
Sum168490
Variance28081.667
MonotonicityStrictly increasing
2024-04-18T16:40:26.577761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.2%
365 1
 
0.2%
385 1
 
0.2%
386 1
 
0.2%
387 1
 
0.2%
388 1
 
0.2%
389 1
 
0.2%
390 1
 
0.2%
391 1
 
0.2%
392 1
 
0.2%
Other values (570) 570
98.3%
ValueCountFrequency (%)
1 1
0.2%
2 1
0.2%
3 1
0.2%
4 1
0.2%
5 1
0.2%
6 1
0.2%
7 1
0.2%
8 1
0.2%
9 1
0.2%
10 1
0.2%
ValueCountFrequency (%)
580 1
0.2%
579 1
0.2%
578 1
0.2%
577 1
0.2%
576 1
0.2%
575 1
0.2%
574 1
0.2%
573 1
0.2%
572 1
0.2%
571 1
0.2%

개방서비스명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.7 KiB
소독업
580 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
소독업 580
100.0%

Length

2024-04-18T16:40:26.697060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T16:40:26.784729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
소독업 580
100.0%

개방서비스ID
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.7 KiB
09_30_11_P
580 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row09_30_11_P
2nd row09_30_11_P
3rd row09_30_11_P
4th row09_30_11_P
5th row09_30_11_P

Common Values

ValueCountFrequency (%)
09_30_11_P 580
100.0%

Length

2024-04-18T16:40:26.885370image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T16:40:26.990006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
09_30_11_p 580
100.0%

개방자치단체코드
Real number (ℝ)

Distinct8
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3446069
Minimum3410000
Maximum3480000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.2 KiB
2024-04-18T16:40:27.068749image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3410000
5-th percentile3410000
Q13420000
median3450000
Q33470000
95-th percentile3470000
Maximum3480000
Range70000
Interquartile range (IQR)50000

Descriptive statistics

Standard deviation21571.956
Coefficient of variation (CV)0.0062598736
Kurtosis-1.319841
Mean3446069
Median Absolute Deviation (MAD)20000
Skewness-0.22016776
Sum1.99872 × 109
Variance4.6534929 × 108
MonotonicityIncreasing
2024-04-18T16:40:27.172225image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
3470000 126
21.7%
3420000 108
18.6%
3460000 96
16.6%
3450000 80
13.8%
3440000 50
 
8.6%
3430000 48
 
8.3%
3410000 46
 
7.9%
3480000 26
 
4.5%
ValueCountFrequency (%)
3410000 46
 
7.9%
3420000 108
18.6%
3430000 48
 
8.3%
3440000 50
 
8.6%
3450000 80
13.8%
3460000 96
16.6%
3470000 126
21.7%
3480000 26
 
4.5%
ValueCountFrequency (%)
3480000 26
 
4.5%
3470000 126
21.7%
3460000 96
16.6%
3450000 80
13.8%
3440000 50
 
8.6%
3430000 48
 
8.3%
3420000 108
18.6%
3410000 46
 
7.9%

관리번호
Text

UNIQUE 

Distinct580
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size4.7 KiB
2024-04-18T16:40:27.384457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length25
Mean length25
Min length25

Characters and Unicode

Total characters14500
Distinct characters14
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

Unique580 ?
Unique (%)100.0%

Sample

1st rowPHMB520173410023042500003
2nd rowPHMB520193410023042500001
3rd rowPHMB520053410023042500002
4th rowPHMB519993410023042500003
5th rowPHMB520093410023042500002
ValueCountFrequency (%)
phmb520173410023042500003 1
 
0.2%
phmb520143460023042500003 1
 
0.2%
phmb520033460023042500001 1
 
0.2%
phmb520103460023042500001 1
 
0.2%
phmb520093460023042500002 1
 
0.2%
phmb520093460023042500001 1
 
0.2%
phmb519953460023042500001 1
 
0.2%
phmb519943460023042500002 1
 
0.2%
phmb520053460023042500001 1
 
0.2%
phmb520193460023042500005 1
 
0.2%
Other values (570) 570
98.3%
2024-04-18T16:40:27.712048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 4843
33.4%
2 2231
15.4%
4 1368
 
9.4%
5 1340
 
9.2%
3 993
 
6.8%
1 710
 
4.9%
P 580
 
4.0%
H 580
 
4.0%
M 580
 
4.0%
B 580
 
4.0%
Other values (4) 695
 
4.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 12180
84.0%
Uppercase Letter 2320
 
16.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4843
39.8%
2 2231
18.3%
4 1368
 
11.2%
5 1340
 
11.0%
3 993
 
8.2%
1 710
 
5.8%
7 203
 
1.7%
6 200
 
1.6%
9 188
 
1.5%
8 104
 
0.9%
Uppercase Letter
ValueCountFrequency (%)
P 580
25.0%
H 580
25.0%
M 580
25.0%
B 580
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 12180
84.0%
Latin 2320
 
16.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4843
39.8%
2 2231
18.3%
4 1368
 
11.2%
5 1340
 
11.0%
3 993
 
8.2%
1 710
 
5.8%
7 203
 
1.7%
6 200
 
1.6%
9 188
 
1.5%
8 104
 
0.9%
Latin
ValueCountFrequency (%)
P 580
25.0%
H 580
25.0%
M 580
25.0%
B 580
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 14500
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4843
33.4%
2 2231
15.4%
4 1368
 
9.4%
5 1340
 
9.2%
3 993
 
6.8%
1 710
 
4.9%
P 580
 
4.0%
H 580
 
4.0%
M 580
 
4.0%
B 580
 
4.0%
Other values (4) 695
 
4.8%

인허가일자
Real number (ℝ)

Distinct524
Distinct (%)90.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20124992
Minimum19841217
Maximum20200924
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.2 KiB
2024-04-18T16:40:27.863740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19841217
5-th percentile20000123
Q120090521
median20131119
Q320180604
95-th percentile20200625
Maximum20200924
Range359707
Interquartile range (IQR)90083.25

Descriptive statistics

Standard deviation67527.362
Coefficient of variation (CV)0.0033553983
Kurtosis1.8183478
Mean20124992
Median Absolute Deviation (MAD)49250.5
Skewness-1.1843263
Sum1.1672495 × 1010
Variance4.5599447 × 109
MonotonicityNot monotonic
2024-04-18T16:40:28.009783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20200421 5
 
0.9%
20100118 3
 
0.5%
20200828 3
 
0.5%
20090521 3
 
0.5%
20200310 3
 
0.5%
20200717 2
 
0.3%
20030710 2
 
0.3%
20190911 2
 
0.3%
20111213 2
 
0.3%
20190327 2
 
0.3%
Other values (514) 553
95.3%
ValueCountFrequency (%)
19841217 1
0.2%
19850104 1
0.2%
19850622 1
0.2%
19870302 1
0.2%
19880520 1
0.2%
19891106 1
0.2%
19900223 1
0.2%
19900314 1
0.2%
19920224 1
0.2%
19920723 1
0.2%
ValueCountFrequency (%)
20200924 1
 
0.2%
20200923 1
 
0.2%
20200922 1
 
0.2%
20200921 1
 
0.2%
20200917 1
 
0.2%
20200910 2
0.3%
20200908 1
 
0.2%
20200907 1
 
0.2%
20200828 3
0.5%
20200827 1
 
0.2%

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing580
Missing (%)100.0%
Memory size5.2 KiB

영업상태구분코드
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size4.7 KiB
1
389 
3
185 
4
 
5
2
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)0.2%

Sample

1st row4
2nd row1
3rd row3
4th row3
5th row3

Common Values

ValueCountFrequency (%)
1 389
67.1%
3 185
31.9%
4 5
 
0.9%
2 1
 
0.2%

Length

2024-04-18T16:40:28.140865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T16:40:28.238925image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 389
67.1%
3 185
31.9%
4 5
 
0.9%
2 1
 
0.2%

영업상태명
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size4.7 KiB
영업/정상
389 
폐업
185 
취소/말소/만료/정지/중지
 
5
휴업
 
1

Length

Max length14
Median length5
Mean length4.1155172
Min length2

Unique

Unique1 ?
Unique (%)0.2%

Sample

1st row취소/말소/만료/정지/중지
2nd row영업/정상
3rd row폐업
4th row폐업
5th row폐업

Common Values

ValueCountFrequency (%)
영업/정상 389
67.1%
폐업 185
31.9%
취소/말소/만료/정지/중지 5
 
0.9%
휴업 1
 
0.2%

Length

2024-04-18T16:40:28.356811image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T16:40:28.555534image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 389
67.1%
폐업 185
31.9%
취소/말소/만료/정지/중지 5
 
0.9%
휴업 1
 
0.2%

상세영업상태코드
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size4.7 KiB
13
389 
3
185 
24
 
5
2
 
1

Length

Max length2
Median length2
Mean length1.6793103
Min length1

Unique

Unique1 ?
Unique (%)0.2%

Sample

1st row24
2nd row13
3rd row3
4th row3
5th row3

Common Values

ValueCountFrequency (%)
13 389
67.1%
3 185
31.9%
24 5
 
0.9%
2 1
 
0.2%

Length

2024-04-18T16:40:28.706801image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T16:40:28.801545image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
13 389
67.1%
3 185
31.9%
24 5
 
0.9%
2 1
 
0.2%

상세영업상태명
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size4.7 KiB
영업중
389 
폐업
185 
직권폐업
 
5
휴업
 
1

Length

Max length4
Median length3
Mean length2.687931
Min length2

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
영업중 389
67.1%
폐업 185
31.9%
직권폐업 5
 
0.9%
휴업 1
 
0.2%

Length

2024-04-18T16:40:28.941291image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T16:40:29.054822image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업중 389
67.1%
폐업 185
31.9%
직권폐업 5
 
0.9%
휴업 1
 
0.2%

폐업일자
Real number (ℝ)

MISSING 

Distinct183
Distinct (%)96.3%
Missing390
Missing (%)67.2%
Infinite0
Infinite (%)0.0%
Mean20147196
Minimum20081010
Maximum20200908
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.2 KiB
2024-04-18T16:40:29.178556image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20081010
5-th percentile20100205
Q120120704
median20150518
Q320171202
95-th percentile20200175
Maximum20200908
Range119898
Interquartile range (IQR)50497

Descriptive statistics

Standard deviation32322.222
Coefficient of variation (CV)0.0016043038
Kurtosis-1.1175502
Mean20147196
Median Absolute Deviation (MAD)29598.5
Skewness-0.035853301
Sum3.8279672 × 109
Variance1.044726 × 109
MonotonicityNot monotonic
2024-04-18T16:40:29.320938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20121231 3
 
0.5%
20130222 2
 
0.3%
20140109 2
 
0.3%
20130809 2
 
0.3%
20150526 2
 
0.3%
20100525 2
 
0.3%
20160127 1
 
0.2%
20081010 1
 
0.2%
20110722 1
 
0.2%
20151222 1
 
0.2%
Other values (173) 173
29.8%
(Missing) 390
67.2%
ValueCountFrequency (%)
20081010 1
0.2%
20090212 1
0.2%
20090213 1
0.2%
20090324 1
0.2%
20090504 1
0.2%
20091221 1
0.2%
20091222 1
0.2%
20091229 1
0.2%
20100129 1
0.2%
20100203 1
0.2%
ValueCountFrequency (%)
20200908 1
0.2%
20200729 1
0.2%
20200724 1
0.2%
20200710 1
0.2%
20200625 1
0.2%
20200604 1
0.2%
20200508 1
0.2%
20200318 1
0.2%
20200303 1
0.2%
20200217 1
0.2%

휴업시작일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size4.7 KiB
<NA>
579 
20170311
 
1

Length

Max length8
Median length4
Mean length4.0068966
Min length4

Unique

Unique1 ?
Unique (%)0.2%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 579
99.8%
20170311 1
 
0.2%

Length

2024-04-18T16:40:29.480754image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T16:40:29.579847image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 579
99.8%
20170311 1
 
0.2%

휴업종료일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size4.7 KiB
<NA>
579 
20200310
 
1

Length

Max length8
Median length4
Mean length4.0068966
Min length4

Unique

Unique1 ?
Unique (%)0.2%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 579
99.8%
20200310 1
 
0.2%

Length

2024-04-18T16:40:29.689046image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T16:40:29.789340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 579
99.8%
20200310 1
 
0.2%

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing580
Missing (%)100.0%
Memory size5.2 KiB

소재지전화
Text

MISSING 

Distinct391
Distinct (%)95.6%
Missing171
Missing (%)29.5%
Memory size4.7 KiB
2024-04-18T16:40:30.029840image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length12
Mean length10.594132
Min length7

Characters and Unicode

Total characters4333
Distinct characters17
Distinct categories7 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique373 ?
Unique (%)91.2%

Sample

1st row053-954-0170
2nd row053792-5369
3rd row053-473-0005
4th row053-421-0421
5th row053-421-6866
ValueCountFrequency (%)
257-8119 2
 
0.5%
742-3344 2
 
0.5%
753-6306 2
 
0.5%
784-6080 2
 
0.5%
053-961-0376 2
 
0.5%
741-5110 2
 
0.5%
053-471-7751 2
 
0.5%
053-326-9398 2
 
0.5%
053-767-0408 2
 
0.5%
255-9942 2
 
0.5%
Other values (383) 391
95.1%
2024-04-18T16:40:30.421055image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 639
14.7%
- 634
14.6%
3 511
11.8%
0 502
11.6%
2 356
8.2%
6 331
7.6%
7 309
7.1%
1 305
7.0%
4 278
6.4%
8 234
 
5.4%
Other values (7) 234
 
5.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3685
85.0%
Dash Punctuation 634
 
14.6%
Close Punctuation 5
 
0.1%
Math Symbol 3
 
0.1%
Other Punctuation 3
 
0.1%
Space Separator 2
 
< 0.1%
Open Punctuation 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 639
17.3%
3 511
13.9%
0 502
13.6%
2 356
9.7%
6 331
9.0%
7 309
8.4%
1 305
8.3%
4 278
7.5%
8 234
 
6.4%
9 220
 
6.0%
Other Punctuation
ValueCountFrequency (%)
. 2
66.7%
/ 1
33.3%
Dash Punctuation
ValueCountFrequency (%)
- 634
100.0%
Close Punctuation
ValueCountFrequency (%)
) 5
100.0%
Math Symbol
ValueCountFrequency (%)
~ 3
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 4333
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 639
14.7%
- 634
14.6%
3 511
11.8%
0 502
11.6%
2 356
8.2%
6 331
7.6%
7 309
7.1%
1 305
7.0%
4 278
6.4%
8 234
 
5.4%
Other values (7) 234
 
5.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4333
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 639
14.7%
- 634
14.6%
3 511
11.8%
0 502
11.6%
2 356
8.2%
6 331
7.6%
7 309
7.1%
1 305
7.0%
4 278
6.4%
8 234
 
5.4%
Other values (7) 234
 
5.4%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing580
Missing (%)100.0%
Memory size5.2 KiB

소재지우편번호
Real number (ℝ)

MISSING 

Distinct176
Distinct (%)73.0%
Missing339
Missing (%)58.4%
Infinite0
Infinite (%)0.0%
Mean695689.46
Minimum41230
Maximum711844
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.2 KiB
2024-04-18T16:40:30.573051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum41230
5-th percentile700431
Q1701846
median703806
Q3705829
95-th percentile706838
Maximum711844
Range670614
Interquartile range (IQR)3983

Descriptive statistics

Standard deviation73586.757
Coefficient of variation (CV)0.10577529
Kurtosis76.793178
Mean695689.46
Median Absolute Deviation (MAD)1962
Skewness-8.8357427
Sum1.6766116 × 108
Variance5.4150108 × 109
MonotonicityNot monotonic
2024-04-18T16:40:30.702428image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
706010 5
 
0.9%
702072 4
 
0.7%
703064 3
 
0.5%
702808 3
 
0.5%
701810 3
 
0.5%
701848 3
 
0.5%
701829 3
 
0.5%
706040 3
 
0.5%
701811 3
 
0.5%
706032 3
 
0.5%
Other values (166) 208
35.9%
(Missing) 339
58.4%
ValueCountFrequency (%)
41230 1
0.2%
41946 1
0.2%
42696 1
0.2%
700082 1
0.2%
700230 2
0.3%
700380 1
0.2%
700400 1
0.2%
700421 1
0.2%
700423 2
0.3%
700424 1
0.2%
ValueCountFrequency (%)
711844 1
0.2%
711838 1
0.2%
711834 1
0.2%
711833 1
0.2%
711812 1
0.2%
711702 2
0.3%
706913 1
0.2%
706852 2
0.3%
706844 1
0.2%
706839 1
0.2%

소재지전체주소
Text

MISSING 

Distinct501
Distinct (%)96.5%
Missing61
Missing (%)10.5%
Memory size4.7 KiB
2024-04-18T16:40:30.992087image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length50
Median length43
Mean length23.680154
Min length12

Characters and Unicode

Total characters12290
Distinct characters194
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique483 ?
Unique (%)93.1%

Sample

1st row대구광역시 중구 대봉동 44번지 30호 선모빌딩
2nd row대구광역시 중구 남산동 615번지 4호
3rd row대구광역시 중구 대봉동 60번지 10호
4th row대구광역시 중구 남산4동 2482번지 458호 까치아파트 상가104 지하1층
5th row대구광역시 중구 동인동3가 271번지 190호
ValueCountFrequency (%)
대구광역시 519
 
19.1%
달서구 124
 
4.6%
동구 89
 
3.3%
수성구 82
 
3.0%
북구 79
 
2.9%
1호 64
 
2.4%
서구 47
 
1.7%
남구 43
 
1.6%
중구 39
 
1.4%
2호 38
 
1.4%
Other values (743) 1597
58.7%
2024-04-18T16:40:31.434567image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2211
18.0%
구 1035
 
8.4%
동 625
 
5.1%
1 593
 
4.8%
대 564
 
4.6%
지 527
 
4.3%
시 527
 
4.3%
광 522
 
4.2%
역 520
 
4.2%
번 490
 
4.0%
Other values (184) 4676
38.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7420
60.4%
Decimal Number 2600
 
21.2%
Space Separator 2211
 
18.0%
Dash Punctuation 26
 
0.2%
Open Punctuation 13
 
0.1%
Close Punctuation 13
 
0.1%
Other Punctuation 6
 
< 0.1%
Uppercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 1035
13.9%
동 625
 
8.4%
대 564
 
7.6%
지 527
 
7.1%
시 527
 
7.1%
광 522
 
7.0%
역 520
 
7.0%
번 490
 
6.6%
호 477
 
6.4%
서 183
 
2.5%
Other values (167) 1950
26.3%
Decimal Number
ValueCountFrequency (%)
1 593
22.8%
2 373
14.3%
4 270
10.4%
3 260
10.0%
0 223
 
8.6%
5 195
 
7.5%
8 182
 
7.0%
6 179
 
6.9%
7 169
 
6.5%
9 156
 
6.0%
Other Punctuation
ValueCountFrequency (%)
, 5
83.3%
. 1
 
16.7%
Space Separator
ValueCountFrequency (%)
2211
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 26
100.0%
Open Punctuation
ValueCountFrequency (%)
( 13
100.0%
Close Punctuation
ValueCountFrequency (%)
) 13
100.0%
Uppercase Letter
ValueCountFrequency (%)
B 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 7420
60.4%
Common 4869
39.6%
Latin 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 1035
13.9%
동 625
 
8.4%
대 564
 
7.6%
지 527
 
7.1%
시 527
 
7.1%
광 522
 
7.0%
역 520
 
7.0%
번 490
 
6.6%
호 477
 
6.4%
서 183
 
2.5%
Other values (167) 1950
26.3%
Common
ValueCountFrequency (%)
2211
45.4%
1 593
 
12.2%
2 373
 
7.7%
4 270
 
5.5%
3 260
 
5.3%
0 223
 
4.6%
5 195
 
4.0%
8 182
 
3.7%
6 179
 
3.7%
7 169
 
3.5%
Other values (6) 214
 
4.4%
Latin
ValueCountFrequency (%)
B 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 7420
60.4%
ASCII 4870
39.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2211
45.4%
1 593
 
12.2%
2 373
 
7.7%
4 270
 
5.5%
3 260
 
5.3%
0 223
 
4.6%
5 195
 
4.0%
8 182
 
3.7%
6 179
 
3.7%
7 169
 
3.5%
Other values (7) 215
 
4.4%
Hangul
ValueCountFrequency (%)
구 1035
13.9%
동 625
 
8.4%
대 564
 
7.6%
지 527
 
7.1%
시 527
 
7.1%
광 522
 
7.0%
역 520
 
7.0%
번 490
 
6.6%
호 477
 
6.4%
서 183
 
2.5%
Other values (167) 1950
26.3%

도로명전체주소
Text

Distinct557
Distinct (%)96.4%
Missing2
Missing (%)0.3%
Memory size4.7 KiB
2024-04-18T16:40:31.803852image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length56
Median length47
Mean length27.948097
Min length20

Characters and Unicode

Total characters16154
Distinct characters251
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique536 ?
Unique (%)92.7%

Sample

1st row대구광역시 중구 중앙대로 269 (남산동)
2nd row대구광역시 중구 동덕로 61, 선모빌딩 4층 (대봉동)
3rd row대구광역시 중구 관덕정길 73 (남산동)
4th row대구광역시 중구 대봉로 260 (대봉동)
5th row대구광역시 중구 남산로7길 75 (남산동,까치아파트 상가104 지하1층)
ValueCountFrequency (%)
대구광역시 578
 
17.3%
달서구 126
 
3.8%
동구 107
 
3.2%
수성구 95
 
2.8%
1층 88
 
2.6%
북구 80
 
2.4%
2층 71
 
2.1%
남구 49
 
1.5%
서구 48
 
1.4%
중구 46
 
1.4%
Other values (947) 2060
61.5%
2024-04-18T16:40:32.280466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2796
 
17.3%
구 1194
 
7.4%
동 777
 
4.8%
대 705
 
4.4%
시 590
 
3.7%
광 580
 
3.6%
역 579
 
3.6%
1 571
 
3.5%
( 558
 
3.5%
) 558
 
3.5%
Other values (241) 7246
44.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 9246
57.2%
Space Separator 2796
 
17.3%
Decimal Number 2535
 
15.7%
Open Punctuation 558
 
3.5%
Close Punctuation 558
 
3.5%
Other Punctuation 347
 
2.1%
Dash Punctuation 110
 
0.7%
Uppercase Letter 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 1194
 
12.9%
동 777
 
8.4%
대 705
 
7.6%
시 590
 
6.4%
광 580
 
6.3%
역 579
 
6.3%
로 549
 
5.9%
길 326
 
3.5%
층 266
 
2.9%
서 222
 
2.4%
Other values (221) 3458
37.4%
Decimal Number
ValueCountFrequency (%)
1 571
22.5%
2 436
17.2%
3 285
11.2%
4 255
10.1%
0 217
 
8.6%
5 201
 
7.9%
6 172
 
6.8%
7 148
 
5.8%
8 130
 
5.1%
9 120
 
4.7%
Uppercase Letter
ValueCountFrequency (%)
B 1
25.0%
H 1
25.0%
A 1
25.0%
C 1
25.0%
Other Punctuation
ValueCountFrequency (%)
, 346
99.7%
. 1
 
0.3%
Space Separator
ValueCountFrequency (%)
2796
100.0%
Open Punctuation
ValueCountFrequency (%)
( 558
100.0%
Close Punctuation
ValueCountFrequency (%)
) 558
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 110
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 9246
57.2%
Common 6904
42.7%
Latin 4
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 1194
 
12.9%
동 777
 
8.4%
대 705
 
7.6%
시 590
 
6.4%
광 580
 
6.3%
역 579
 
6.3%
로 549
 
5.9%
길 326
 
3.5%
층 266
 
2.9%
서 222
 
2.4%
Other values (221) 3458
37.4%
Common
ValueCountFrequency (%)
2796
40.5%
1 571
 
8.3%
( 558
 
8.1%
) 558
 
8.1%
2 436
 
6.3%
, 346
 
5.0%
3 285
 
4.1%
4 255
 
3.7%
0 217
 
3.1%
5 201
 
2.9%
Other values (6) 681
 
9.9%
Latin
ValueCountFrequency (%)
B 1
25.0%
H 1
25.0%
A 1
25.0%
C 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 9246
57.2%
ASCII 6908
42.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2796
40.5%
1 571
 
8.3%
( 558
 
8.1%
) 558
 
8.1%
2 436
 
6.3%
, 346
 
5.0%
3 285
 
4.1%
4 255
 
3.7%
0 217
 
3.1%
5 201
 
2.9%
Other values (10) 685
 
9.9%
Hangul
ValueCountFrequency (%)
구 1194
 
12.9%
동 777
 
8.4%
대 705
 
7.6%
시 590
 
6.4%
광 580
 
6.3%
역 579
 
6.3%
로 549
 
5.9%
길 326
 
3.5%
층 266
 
2.9%
서 222
 
2.4%
Other values (221) 3458
37.4%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct386
Distinct (%)73.0%
Missing51
Missing (%)8.8%
Infinite0
Infinite (%)0.0%
Mean117148.45
Minimum41007
Maximum711702
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.2 KiB
2024-04-18T16:40:32.411755image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum41007
5-th percentile41120
Q141537
median42165
Q342733
95-th percentile704386
Maximum711702
Range670695
Interquartile range (IQR)1196

Descriptive statistics

Standard deviation210235.24
Coefficient of variation (CV)1.7946054
Kurtosis3.9939557
Mean117148.45
Median Absolute Deviation (MAD)598
Skewness2.4451277
Sum61971532
Variance4.4198857 × 1010
MonotonicityNot monotonic
2024-04-18T16:40:32.550163image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
41196 4
 
0.7%
42679 4
 
0.7%
42733 4
 
0.7%
42471 4
 
0.7%
41078 4
 
0.7%
41465 3
 
0.5%
42665 3
 
0.5%
42135 3
 
0.5%
42187 3
 
0.5%
42819 3
 
0.5%
Other values (376) 494
85.2%
(Missing) 51
 
8.8%
ValueCountFrequency (%)
41007 1
0.2%
41017 1
0.2%
41029 1
0.2%
41033 1
0.2%
41035 1
0.2%
41042 1
0.2%
41048 2
0.3%
41057 1
0.2%
41067 1
0.2%
41068 2
0.3%
ValueCountFrequency (%)
711702 2
0.3%
706853 1
0.2%
706852 2
0.3%
706838 2
0.3%
706833 1
0.2%
706824 1
0.2%
706818 1
0.2%
706813 2
0.3%
706810 1
0.2%
706808 2
0.3%

사업장명
Text

Distinct542
Distinct (%)93.4%
Missing0
Missing (%)0.0%
Memory size4.7 KiB
2024-04-18T16:40:32.769482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length33
Median length22
Mean length7.4103448
Min length2

Characters and Unicode

Total characters4298
Distinct characters386
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique513 ?
Unique (%)88.4%

Sample

1st row설악경호
2nd row대구광역시지체장애인협회
3rd row한울종합방제
4th row그린종합관리
5th row대구중구지역자활썬터(말끄미소독방역)
ValueCountFrequency (%)
주식회사 32
 
4.7%
한국방제공사 4
 
0.6%
청쿰방역공사 4
 
0.6%
세기위생방역 4
 
0.6%
종합관리 4
 
0.6%
대신종합관리 3
 
0.4%
더홈케어 3
 
0.4%
한일종합방역공사 3
 
0.4%
그린방역 3
 
0.4%
대구경북지사 3
 
0.4%
Other values (578) 617
90.7%
2024-04-18T16:40:33.130936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 244
 
5.7%
) 213
 
5.0%
( 211
 
4.9%
스 124
 
2.9%
사 112
 
2.6%
100
 
2.3%
역 95
 
2.2%
대 92
 
2.1%
방 89
 
2.1%
리 85
 
2.0%
Other values (376) 2933
68.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3639
84.7%
Close Punctuation 213
 
5.0%
Open Punctuation 211
 
4.9%
Space Separator 100
 
2.3%
Uppercase Letter 89
 
2.1%
Lowercase Letter 24
 
0.6%
Decimal Number 14
 
0.3%
Other Punctuation 8
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 244
 
6.7%
스 124
 
3.4%
사 112
 
3.1%
역 95
 
2.6%
대 92
 
2.5%
방 89
 
2.4%
리 85
 
2.3%
경 78
 
2.1%
합 77
 
2.1%
린 70
 
1.9%
Other values (329) 2573
70.7%
Uppercase Letter
ValueCountFrequency (%)
S 15
16.9%
E 14
15.7%
C 9
10.1%
N 9
10.1%
O 6
 
6.7%
K 6
 
6.7%
Z 5
 
5.6%
G 5
 
5.6%
M 3
 
3.4%
T 2
 
2.2%
Other values (13) 15
16.9%
Lowercase Letter
ValueCountFrequency (%)
e 6
25.0%
o 3
12.5%
n 3
12.5%
c 2
 
8.3%
r 2
 
8.3%
a 2
 
8.3%
i 1
 
4.2%
b 1
 
4.2%
l 1
 
4.2%
t 1
 
4.2%
Other values (2) 2
 
8.3%
Decimal Number
ValueCountFrequency (%)
1 6
42.9%
9 3
21.4%
3 2
 
14.3%
0 1
 
7.1%
5 1
 
7.1%
6 1
 
7.1%
Other Punctuation
ValueCountFrequency (%)
& 4
50.0%
, 3
37.5%
. 1
 
12.5%
Close Punctuation
ValueCountFrequency (%)
) 213
100.0%
Open Punctuation
ValueCountFrequency (%)
( 211
100.0%
Space Separator
ValueCountFrequency (%)
100
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3639
84.7%
Common 546
 
12.7%
Latin 113
 
2.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 244
 
6.7%
스 124
 
3.4%
사 112
 
3.1%
역 95
 
2.6%
대 92
 
2.5%
방 89
 
2.4%
리 85
 
2.3%
경 78
 
2.1%
합 77
 
2.1%
린 70
 
1.9%
Other values (329) 2573
70.7%
Latin
ValueCountFrequency (%)
S 15
13.3%
E 14
 
12.4%
C 9
 
8.0%
N 9
 
8.0%
e 6
 
5.3%
O 6
 
5.3%
K 6
 
5.3%
Z 5
 
4.4%
G 5
 
4.4%
o 3
 
2.7%
Other values (25) 35
31.0%
Common
ValueCountFrequency (%)
) 213
39.0%
( 211
38.6%
100
18.3%
1 6
 
1.1%
& 4
 
0.7%
, 3
 
0.5%
9 3
 
0.5%
3 2
 
0.4%
. 1
 
0.2%
0 1
 
0.2%
Other values (2) 2
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3639
84.7%
ASCII 659
 
15.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 244
 
6.7%
스 124
 
3.4%
사 112
 
3.1%
역 95
 
2.6%
대 92
 
2.5%
방 89
 
2.4%
리 85
 
2.3%
경 78
 
2.1%
합 77
 
2.1%
린 70
 
1.9%
Other values (329) 2573
70.7%
ASCII
ValueCountFrequency (%)
) 213
32.3%
( 211
32.0%
100
15.2%
S 15
 
2.3%
E 14
 
2.1%
C 9
 
1.4%
N 9
 
1.4%
e 6
 
0.9%
1 6
 
0.9%
O 6
 
0.9%
Other values (37) 70
 
10.6%

최종수정시점
Real number (ℝ)

UNIQUE 

Distinct580
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0171676 × 1013
Minimum2.0081203 × 1013
Maximum2.0200929 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.2 KiB
2024-04-18T16:40:33.295541image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.0081203 × 1013
5-th percentile2.0111124 × 1013
Q12.015122 × 1013
median2.018103 × 1013
Q32.0200113 × 1013
95-th percentile2.0200812 × 1013
Maximum2.0200929 × 1013
Range1.1972599 × 1011
Interquartile range (IQR)4.8892693 × 1010

Descriptive statistics

Standard deviation2.9947376 × 1010
Coefficient of variation (CV)0.0014846251
Kurtosis-0.15916061
Mean2.0171676 × 1013
Median Absolute Deviation (MAD)1.9434945 × 1010
Skewness-0.96099042
Sum1.1699572 × 1016
Variance8.9684534 × 1020
MonotonicityNot monotonic
2024-04-18T16:40:33.432677image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20190222170714 1
 
0.2%
20150909100008 1
 
0.2%
20150310111056 1
 
0.2%
20160127173533 1
 
0.2%
20100129155507 1
 
0.2%
20130611180242 1
 
0.2%
20100720142518 1
 
0.2%
20150526113203 1
 
0.2%
20191226140832 1
 
0.2%
20150722195619 1
 
0.2%
Other values (570) 570
98.3%
ValueCountFrequency (%)
20081203173913 1
0.2%
20090212100046 1
0.2%
20090327174321 1
0.2%
20090504153223 1
0.2%
20091221164820 1
0.2%
20091222160829 1
0.2%
20091229172305 1
0.2%
20100129155507 1
0.2%
20100208174220 1
0.2%
20100419110525 1
0.2%
ValueCountFrequency (%)
20200929165604 1
0.2%
20200924175614 1
0.2%
20200924110259 1
0.2%
20200922201523 1
0.2%
20200922111654 1
0.2%
20200922111338 1
0.2%
20200921194233 1
0.2%
20200921174505 1
0.2%
20200917192350 1
0.2%
20200917102535 1
0.2%

데이터갱신구분
Categorical

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size4.7 KiB
I
389 
U
191 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowU
2nd rowU
3rd rowI
4th rowI
5th rowI

Common Values

ValueCountFrequency (%)
I 389
67.1%
U 191
32.9%

Length

2024-04-18T16:40:33.549468image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T16:40:33.642304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 389
67.1%
u 191
32.9%

데이터갱신일자
Date

Distinct215
Distinct (%)37.1%
Missing0
Missing (%)0.0%
Memory size4.7 KiB
Minimum2018-08-31 23:59:59
Maximum2020-10-01 02:40:00
2024-04-18T16:40:33.740241image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T16:40:33.859265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing580
Missing (%)100.0%
Memory size5.2 KiB

좌표정보(X)
Real number (ℝ)

Distinct528
Distinct (%)91.3%
Missing2
Missing (%)0.3%
Infinite0
Infinite (%)0.0%
Mean343433.92
Minimum327191.86
Maximum356430.94
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.2 KiB
2024-04-18T16:40:33.974702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum327191.86
5-th percentile336240.38
Q1340015.8
median343372.29
Q3346640.81
95-th percentile352820.75
Maximum356430.94
Range29239.08
Interquartile range (IQR)6625.0067

Descriptive statistics

Standard deviation4799.361
Coefficient of variation (CV)0.013974627
Kurtosis0.41991311
Mean343433.92
Median Absolute Deviation (MAD)3293.2976
Skewness0.11703271
Sum1.985048 × 108
Variance23033866
MonotonicityNot monotonic
2024-04-18T16:40:34.426687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
343199.085449 4
 
0.7%
342420.478177 3
 
0.5%
341508.517038 2
 
0.3%
343995.225894 2
 
0.3%
348516.86977 2
 
0.3%
347474.164613 2
 
0.3%
340631.442113 2
 
0.3%
339726.534362 2
 
0.3%
337714.029318 2
 
0.3%
341761.961791 2
 
0.3%
Other values (518) 555
95.7%
ValueCountFrequency (%)
327191.856602 1
0.2%
329454.216845 1
0.2%
330387.847151 1
0.2%
330459.024991 1
0.2%
330567.11783 1
0.2%
330750.666655 1
0.2%
331517.0 1
0.2%
331926.347477 1
0.2%
332220.064187 1
0.2%
332260.469104 1
0.2%
ValueCountFrequency (%)
356430.936586 1
0.2%
356354.352971 1
0.2%
355875.122869 1
0.2%
355857.357218 1
0.2%
355720.0 1
0.2%
355706.163421 1
0.2%
355597.073543 2
0.3%
355595.530398 1
0.2%
354843.399478 1
0.2%
354818.553042 1
0.2%

좌표정보(Y)
Real number (ℝ)

Distinct527
Distinct (%)91.2%
Missing2
Missing (%)0.3%
Infinite0
Infinite (%)0.0%
Mean263279.89
Minimum240800.46
Maximum277860.93
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.2 KiB
2024-04-18T16:40:34.547478image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum240800.46
5-th percentile257531.9
Q1261125.1
median263386.3
Q3265333.65
95-th percentile270254.95
Maximum277860.93
Range37060.467
Interquartile range (IQR)4208.5499

Descriptive statistics

Standard deviation3967.9334
Coefficient of variation (CV)0.01507116
Kurtosis4.5664528
Mean263279.89
Median Absolute Deviation (MAD)2131.2504
Skewness-0.64056408
Sum1.5217577 × 108
Variance15744495
MonotonicityNot monotonic
2024-04-18T16:40:34.685214image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
263950.695637 4
 
0.7%
261583.685645 3
 
0.5%
264280.169629 2
 
0.3%
264196.310678 2
 
0.3%
261668.530778 2
 
0.3%
262561.778893 2
 
0.3%
265215.39989 2
 
0.3%
262518.530341 2
 
0.3%
257953.713823 2
 
0.3%
262769.73809 2
 
0.3%
Other values (517) 555
95.7%
ValueCountFrequency (%)
240800.459747 1
0.2%
244510.0 1
0.2%
245096.11462 1
0.2%
245194.809411 1
0.2%
245436.0 1
0.2%
250585.802562 1
0.2%
252984.61594 1
0.2%
253850.09474 1
0.2%
254464.570032 1
0.2%
255815.905387 1
0.2%
ValueCountFrequency (%)
277860.926384 1
0.2%
274231.062512 1
0.2%
273560.875554 1
0.2%
273502.153909 1
0.2%
273085.642493 1
0.2%
273035.671294 1
0.2%
272948.795549 1
0.2%
272889.980552 1
0.2%
272812.307211 1
0.2%
272627.220724 2
0.3%

사무실면적
Real number (ℝ)

MISSING  SKEWED 

Distinct379
Distinct (%)77.2%
Missing89
Missing (%)15.3%
Infinite0
Infinite (%)0.0%
Mean57.804338
Minimum2.6
Maximum4284
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.2 KiB
2024-04-18T16:40:34.817817image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.6
5-th percentile9.81
Q119.435
median35
Q360.33
95-th percentile138.27
Maximum4284
Range4281.4
Interquartile range (IQR)40.895

Descriptive statistics

Standard deviation196.70359
Coefficient of variation (CV)3.402921
Kurtosis437.2608
Mean57.804338
Median Absolute Deviation (MAD)18
Skewness20.356893
Sum28381.93
Variance38692.304
MonotonicityNot monotonic
2024-04-18T16:40:34.935759image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
30.0 9
 
1.6%
10.0 7
 
1.2%
35.0 6
 
1.0%
33.0 6
 
1.0%
36.0 5
 
0.9%
15.6 4
 
0.7%
23.1 4
 
0.7%
16.5 3
 
0.5%
86.0 3
 
0.5%
21.6 3
 
0.5%
Other values (369) 441
76.0%
(Missing) 89
 
15.3%
ValueCountFrequency (%)
2.6 1
0.2%
3.3 1
0.2%
4.62 1
0.2%
5.0 1
0.2%
6.0 1
0.2%
6.05 1
0.2%
6.2 1
0.2%
6.27 1
0.2%
6.5 1
0.2%
7.7 1
0.2%
ValueCountFrequency (%)
4284.0 1
0.2%
471.41 1
0.2%
327.0 1
0.2%
264.0 1
0.2%
230.0 1
0.2%
221.5 1
0.2%
218.3 1
0.2%
198.0 1
0.2%
190.0 1
0.2%
179.0 1
0.2%

소독차량차고면적
Real number (ℝ)

MISSING 

Distinct271
Distinct (%)56.9%
Missing104
Missing (%)17.9%
Infinite0
Infinite (%)0.0%
Mean22.700735
Minimum0.9
Maximum1776
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.2 KiB
2024-04-18T16:40:35.063722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.9
5-th percentile3.4575
Q17.475
median12.5
Q322.035
95-th percentile50.05
Maximum1776
Range1775.1
Interquartile range (IQR)14.56

Descriptive statistics

Standard deviation83.772015
Coefficient of variation (CV)3.6902776
Kurtosis406.25026
Mean22.700735
Median Absolute Deviation (MAD)5.9
Skewness19.471766
Sum10805.55
Variance7017.7504
MonotonicityNot monotonic
2024-04-18T16:40:35.188100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10.0 22
 
3.8%
16.5 13
 
2.2%
7.0 10
 
1.7%
5.0 10
 
1.7%
9.9 10
 
1.7%
6.0 8
 
1.4%
6.6 8
 
1.4%
15.0 7
 
1.2%
20.0 7
 
1.2%
16.0 6
 
1.0%
Other values (261) 375
64.7%
(Missing) 104
 
17.9%
ValueCountFrequency (%)
0.9 1
0.2%
1.1 1
0.2%
1.56 1
0.2%
1.8 1
0.2%
1.82 1
0.2%
1.95 1
0.2%
2.0 2
0.3%
2.2 2
0.3%
2.3 2
0.3%
3.0 2
0.3%
ValueCountFrequency (%)
1776.0 1
0.2%
216.0 1
0.2%
207.0 1
0.2%
181.02 1
0.2%
175.0 1
0.2%
135.5 1
0.2%
110.8 1
0.2%
98.0 1
0.2%
90.0 1
0.2%
82.6 1
0.2%

초미립자살포기수
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size4.7 KiB
1
535 
2
 
31
3
 
9
4
 
3
0
 
2

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 535
92.2%
2 31
 
5.3%
3 9
 
1.6%
4 3
 
0.5%
0 2
 
0.3%

Length

2024-04-18T16:40:35.302952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T16:40:35.401365image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 535
92.2%
2 31
 
5.3%
3 9
 
1.6%
4 3
 
0.5%
0 2
 
0.3%

휴대용소독기수
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size4.7 KiB
2
564 
3
 
11
4
 
4
7
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)0.2%

Sample

1st row2
2nd row2
3rd row2
4th row2
5th row2

Common Values

ValueCountFrequency (%)
2 564
97.2%
3 11
 
1.9%
4 4
 
0.7%
7 1
 
0.2%

Length

2024-04-18T16:40:35.494219image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T16:40:35.580042image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 564
97.2%
3 11
 
1.9%
4 4
 
0.7%
7 1
 
0.2%

동력분무기수
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size4.7 KiB
1
313 
0
261 
2
 
3
3
 
2
7
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)0.2%

Sample

1st row0
2nd row0
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 313
54.0%
0 261
45.0%
2 3
 
0.5%
3 2
 
0.3%
7 1
 
0.2%

Length

2024-04-18T16:40:35.669030image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T16:40:35.768472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 313
54.0%
0 261
45.0%
2 3
 
0.5%
3 2
 
0.3%
7 1
 
0.2%

수동식분무기수
Real number (ℝ)

Distinct12
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.4189655
Minimum3
Maximum24
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.2 KiB
2024-04-18T16:40:35.858126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3
5-th percentile3
Q13
median5
Q35
95-th percentile6.05
Maximum24
Range21
Interquartile range (IQR)2

Descriptive statistics

Standard deviation1.8572508
Coefficient of variation (CV)0.42029086
Kurtosis39.969239
Mean4.4189655
Median Absolute Deviation (MAD)0.5
Skewness4.8435299
Sum2563
Variance3.4493806
MonotonicityNot monotonic
2024-04-18T16:40:35.948690image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
5 290
50.0%
3 237
40.9%
7 13
 
2.2%
6 12
 
2.1%
4 12
 
2.1%
8 5
 
0.9%
10 4
 
0.7%
9 2
 
0.3%
20 2
 
0.3%
24 1
 
0.2%
Other values (2) 2
 
0.3%
ValueCountFrequency (%)
3 237
40.9%
4 12
 
2.1%
5 290
50.0%
6 12
 
2.1%
7 13
 
2.2%
8 5
 
0.9%
9 2
 
0.3%
10 4
 
0.7%
14 1
 
0.2%
15 1
 
0.2%
ValueCountFrequency (%)
24 1
 
0.2%
20 2
 
0.3%
15 1
 
0.2%
14 1
 
0.2%
10 4
 
0.7%
9 2
 
0.3%
8 5
 
0.9%
7 13
 
2.2%
6 12
 
2.1%
5 290
50.0%

방독면수
Real number (ℝ)

Distinct6
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.1017241
Minimum5
Maximum20
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.2 KiB
2024-04-18T16:40:36.037459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5
5-th percentile5
Q15
median5
Q35
95-th percentile5
Maximum20
Range15
Interquartile range (IQR)0

Descriptive statistics

Standard deviation0.82595867
Coefficient of variation (CV)0.16189795
Kurtosis195.08673
Mean5.1017241
Median Absolute Deviation (MAD)0
Skewness12.486948
Sum2959
Variance0.68220773
MonotonicityNot monotonic
2024-04-18T16:40:36.133459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
5 564
97.2%
10 6
 
1.0%
6 5
 
0.9%
7 3
 
0.5%
8 1
 
0.2%
20 1
 
0.2%
ValueCountFrequency (%)
5 564
97.2%
6 5
 
0.9%
7 3
 
0.5%
8 1
 
0.2%
10 6
 
1.0%
20 1
 
0.2%
ValueCountFrequency (%)
20 1
 
0.2%
10 6
 
1.0%
8 1
 
0.2%
7 3
 
0.5%
6 5
 
0.9%
5 564
97.2%

보호안경수
Real number (ℝ)

Distinct6
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.1224138
Minimum5
Maximum20
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.2 KiB
2024-04-18T16:40:36.232900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5
5-th percentile5
Q15
median5
Q35
95-th percentile5
Maximum20
Range15
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.0266809
Coefficient of variation (CV)0.20042912
Kurtosis156.35184
Mean5.1224138
Median Absolute Deviation (MAD)0
Skewness11.715945
Sum2971
Variance1.0540736
MonotonicityNot monotonic
2024-04-18T16:40:36.327861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
5 564
97.2%
10 6
 
1.0%
6 6
 
1.0%
20 2
 
0.3%
8 1
 
0.2%
7 1
 
0.2%
ValueCountFrequency (%)
5 564
97.2%
6 6
 
1.0%
7 1
 
0.2%
8 1
 
0.2%
10 6
 
1.0%
20 2
 
0.3%
ValueCountFrequency (%)
20 2
 
0.3%
10 6
 
1.0%
8 1
 
0.2%
7 1
 
0.2%
6 6
 
1.0%
5 564
97.2%

보호용의복수
Real number (ℝ)

Distinct10
Distinct (%)1.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.3362069
Minimum5
Maximum30
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.2 KiB
2024-04-18T16:40:36.428168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5
5-th percentile5
Q15
median5
Q35
95-th percentile6
Maximum30
Range25
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.9988942
Coefficient of variation (CV)0.37459083
Kurtosis93.178459
Mean5.3362069
Median Absolute Deviation (MAD)0
Skewness9.0095909
Sum3095
Variance3.995578
MonotonicityNot monotonic
2024-04-18T16:40:36.534412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=10)
ValueCountFrequency (%)
5 545
94.0%
10 13
 
2.2%
6 7
 
1.2%
7 5
 
0.9%
8 4
 
0.7%
20 2
 
0.3%
9 1
 
0.2%
29 1
 
0.2%
30 1
 
0.2%
23 1
 
0.2%
ValueCountFrequency (%)
5 545
94.0%
6 7
 
1.2%
7 5
 
0.9%
8 4
 
0.7%
9 1
 
0.2%
10 13
 
2.2%
20 2
 
0.3%
23 1
 
0.2%
29 1
 
0.2%
30 1
 
0.2%
ValueCountFrequency (%)
30 1
 
0.2%
29 1
 
0.2%
23 1
 
0.2%
20 2
 
0.3%
10 13
 
2.2%
9 1
 
0.2%
8 4
 
0.7%
7 5
 
0.9%
6 7
 
1.2%
5 545
94.0%

진공청소기수
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size4.7 KiB
1
527 
2
 
32
5
 
9
3
 
9
4
 
3

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2
2nd row1
3rd row1
4th row1
5th row1

Common Values

ValueCountFrequency (%)
1 527
90.9%
2 32
 
5.5%
5 9
 
1.6%
3 9
 
1.6%
4 3
 
0.5%

Length

2024-04-18T16:40:36.639843image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T16:40:36.755596image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 527
90.9%
2 32
 
5.5%
5 9
 
1.6%
3 9
 
1.6%
4 3
 
0.5%

Sample

번호개방서비스명개방서비스ID개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)사무실면적소독차량차고면적초미립자살포기수휴대용소독기수동력분무기수수동식분무기수방독면수보호안경수보호용의복수진공청소기수
01소독업09_30_11_P3410000PHMB52017341002304250000320170425<NA>4취소/말소/만료/정지/중지24직권폐업20190221<NA><NA><NA><NA><NA><NA><NA>대구광역시 중구 중앙대로 269 (남산동)41968설악경호20190222170714U2019-02-24 02:40:00.0<NA>343606.417424263096.26307382.6135.512035552
12소독업09_30_11_P3410000PHMB52019341002304250000120190211<NA>1영업/정상13영업중<NA><NA><NA><NA>053-954-0170<NA><NA>대구광역시 중구 대봉동 44번지 30호 선모빌딩대구광역시 중구 동덕로 61, 선모빌딩 4층 (대봉동)41954대구광역시지체장애인협회20191105191623U2019-11-07 02:40:00.0<NA>344791.930978263429.773339221.526.412035551
23소독업09_30_11_P3410000PHMB52005341002304250000220051020<NA>3폐업3폐업20091222<NA><NA><NA>053792-5369<NA>700442대구광역시 중구 남산동 615번지 4호대구광역시 중구 관덕정길 73 (남산동)<NA>한울종합방제20091222160829I2018-08-31 23:59:59.0<NA>343651.425274263636.980396<NA><NA>12155551
34소독업09_30_11_P3410000PHMB51999341002304250000319990930<NA>3폐업3폐업20090213<NA><NA><NA>053-473-0005<NA>700755대구광역시 중구 대봉동 60번지 10호대구광역시 중구 대봉로 260 (대봉동)700755그린종합관리20131223100359I2018-08-31 23:59:59.0<NA>344584.149436263593.636812<NA><NA>12155551
45소독업09_30_11_P3410000PHMB52009341002304250000220090302<NA>3폐업3폐업20120726<NA><NA><NA><NA><NA>700753대구광역시 중구 남산4동 2482번지 458호 까치아파트 상가104 지하1층대구광역시 중구 남산로7길 75 (남산동,까치아파트 상가104 지하1층)<NA>대구중구지역자활썬터(말끄미소독방역)20120914155736I2018-08-31 23:59:59.0<NA>342565.585038263288.453034<NA><NA>12155551
56소독업09_30_11_P3410000PHMB52009341002304250000120090227<NA>3폐업3폐업20091229<NA><NA><NA>053-421-0421<NA>700423대구광역시 중구 동인동3가 271번지 190호대구광역시 중구 국채보상로143길 61 (동인동3가)<NA>(주)청담씨엔에스20091229172305I2018-08-31 23:59:59.0<NA>345189.726096264687.004871<NA><NA>12155551
67소독업09_30_11_P3410000PHMB52011341002304250000120110503<NA>3폐업3폐업20111006<NA><NA><NA><NA><NA>700440대구광역시 중구 남산동 175번지 1호대구광역시 중구 달구벌대로 2034 (남산동)<NA>세기위생방역20111007101037I2018-08-31 23:59:59.0<NA>343199.085449263950.69563731.3910.4412155551
78소독업09_30_11_P3410000PHMB52010341002304250000120100118<NA>3폐업3폐업20120914<NA><NA><NA>053-421-6866<NA>700803대구광역시 중구 남산1동 726번지 8호대구광역시 중구 명륜로22길 13 (남산동)<NA>(사)대구광역시보육시설연합회20120917100951I2018-08-31 23:59:59.0<NA>343964.972875263369.13141815.088.3812155551
89소독업09_30_11_P3410000PHMB52009341002304250000420091105<NA>3폐업3폐업20110504<NA><NA><NA><NA><NA>700442대구광역시 중구 남산2동 175번지 1호 서현빌딩 5층대구광역시 중구 달구벌대로 2034 (남산동,서현빌딩 5층)<NA>세기위생방역20110624115137I2018-08-31 23:59:59.0<NA>343199.085449263950.695637<NA><NA>12155551
910소독업09_30_11_P3410000PHMB52009341002304250000320090605<NA>3폐업3폐업20171231<NA><NA><NA>427-0990<NA>700421대구광역시 중구 동인동1가 351번지 2호대구광역시 중구 동덕로 198-14 (동인동1가)<NA>삼정종합관리(주)20180118141452I2018-08-31 23:59:59.0<NA>344913.492939264738.12848788.033.012155551
번호개방서비스명개방서비스ID개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)사무실면적소독차량차고면적초미립자살포기수휴대용소독기수동력분무기수수동식분무기수방독면수보호안경수보호용의복수진공청소기수
570571소독업09_30_11_P3480000PHMB52020348001204250000720200519<NA>1영업/정상13영업중<NA><NA><NA><NA>053-634-7871<NA><NA><NA>대구광역시 달성군 화원읍 류목정길 4842957크린톡20200520201833I2020-05-22 00:23:19.0<NA>334225.172263255815.90538782.66.612035551
571572소독업09_30_11_P3480000PHMB52020348001204250000820200604<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA><NA>대구광역시 달성군 논공읍 비슬로331길 942976주식회사 케스원20200806161717U2020-08-08 02:40:00.0<NA>327191.856602252984.6159430.013.012035551
572573소독업09_30_11_P3480000PHMB52020348001204250000620200511<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA><NA>대구광역시 달성군 화원읍 비슬로525길 7-1642953(주)강인종합관리20200914094032U2020-09-16 02:40:00.0<NA>335778.665831257265.642741<NA><NA>12035551
573574소독업09_30_11_P3480000PHMB52020348001204250000520200512<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA><NA>대구광역시 달성군 다사읍 세천로 108, 121호42930(주)콤페이20200921194233U2020-09-23 02:40:00.0<NA><NA><NA>38.5438.5412035551
574575소독업09_30_11_P3480000PHMB52020348001204250000320200409<NA>1영업/정상13영업중<NA><NA><NA><NA>053-624-1559<NA><NA><NA>대구광역시 달성군 화원읍 비슬로 240042957(주)홍당무20200410131807I2020-04-12 00:23:22.0<NA>333979.883924255971.33530951.07.812045551
575576소독업09_30_11_P3480000PHMB52020348001204250000120200303<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>대구광역시 달성군 유가읍 도의리 975번지 3호대구광역시 달성군 유가읍 도의길 86-3842993주식회사한미드론20200305190305I2020-03-07 00:23:22.0<NA>331926.347477240800.4597474284.01776.012035551
576577소독업09_30_11_P3480000PHMB52020348001204250000220200325<NA>1영업/정상13영업중<NA><NA><NA><NA>053-716-6337<NA><NA><NA>대구광역시 달성군 현풍읍 테크노상업로 30, 4층 401호43017주식회사 엠허브서비스20200330104718U2020-04-01 02:40:00.0<NA>331517.0244510.088.3122.6212035551
577578소독업09_30_11_P3480000PHMB52019348001204250000420191226<NA>1영업/정상13영업중<NA><NA><NA><NA>053-617-9220<NA><NA>대구광역시 달성군 화원읍 천내리 892번지 1호대구광역시 달성군 화원읍 비슬로512길 66, 화원전통시장건물 2층42962달성시니어홈클린20191230203421U2020-01-01 02:40:00.0<NA>335471.540882256711.03692180.033.612035551
578579소독업09_30_11_P3480000PHMB52019348001204250000320191025<NA>1영업/정상13영업중<NA><NA><NA><NA>053-584-2520<NA><NA><NA>대구광역시 달성군 다사읍 달구벌대로 861, 8층42914(주)행복한동행20191029093044I2019-10-31 00:23:03.0<NA>332260.469104263406.22948835.09.212035551
579580소독업09_30_11_P3480000PHMB52014348001204250000120141204<NA>3폐업3폐업20170626<NA><NA><NA>053-584-2520<NA>711812대구광역시 달성군 다사읍 매곡리 1546번지 7호대구광역시 달성군 다사읍 달구벌대로 86142914(주)행복한동행20170626102024I2018-08-31 23:59:59.0<NA>332220.064187263114.52719650.76.012155551