Overview

Dataset statistics

Number of variables38
Number of observations571
Missing cells3463
Missing cells (%)16.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory184.7 KiB
Average record size in memory331.2 B

Variable types

Numeric15
Categorical13
Text5
Unsupported4
DateTime1

Dataset

Description6270000_대구광역시_09_30_11_P_소독업_8월
Author대구광역시
URLhttp://data.daegu.go.kr/open/data/dataView.do?dataSetId=DMI_0000085943&dataSetDetailId=DDI_0000085977&provdMethod=FILE

Alerts

개방서비스명 has constant value ""Constant
개방서비스ID has constant value ""Constant
영업상태구분코드 is highly imbalanced (50.4%)Imbalance
영업상태명 is highly imbalanced (50.4%)Imbalance
상세영업상태코드 is highly imbalanced (50.4%)Imbalance
상세영업상태명 is highly imbalanced (50.4%)Imbalance
휴업시작일자 is highly imbalanced (98.1%)Imbalance
휴업종료일자 is highly imbalanced (98.1%)Imbalance
초미립자살포기수 is highly imbalanced (79.4%)Imbalance
휴대용소독기수 is highly imbalanced (89.2%)Imbalance
동력분무기수 is highly imbalanced (53.5%)Imbalance
진공청소기수 is highly imbalanced (75.2%)Imbalance
인허가취소일자 has 571 (100.0%) missing valuesMissing
폐업일자 has 382 (66.9%) missing valuesMissing
재개업일자 has 571 (100.0%) missing valuesMissing
소재지전화 has 165 (28.9%) missing valuesMissing
소재지면적 has 571 (100.0%) missing valuesMissing
소재지우편번호 has 330 (57.8%) missing valuesMissing
소재지전체주소 has 58 (10.2%) missing valuesMissing
도로명우편번호 has 51 (8.9%) missing valuesMissing
업태구분명 has 571 (100.0%) missing valuesMissing
사무실면적 has 86 (15.1%) missing valuesMissing
소독차량차고면적 has 101 (17.7%) missing valuesMissing
사무실면적 is highly skewed (γ1 = 20.24242281)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 started2024-04-20 17:43:33.972140
Analysis finished2024-04-20 17:43:35.107750
Duration1.14 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct571
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean286
Minimum1
Maximum571
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.1 KiB
2024-04-21T02:43:35.284250image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile29.5
Q1143.5
median286
Q3428.5
95-th percentile542.5
Maximum571
Range570
Interquartile range (IQR)285

Descriptive statistics

Standard deviation164.97778
Coefficient of variation (CV)0.57684537
Kurtosis-1.2
Mean286
Median Absolute Deviation (MAD)143
Skewness0
Sum163306
Variance27217.667
MonotonicityStrictly increasing
2024-04-21T02:43:35.698145image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.2%
385 1
 
0.2%
379 1
 
0.2%
380 1
 
0.2%
381 1
 
0.2%
382 1
 
0.2%
383 1
 
0.2%
384 1
 
0.2%
386 1
 
0.2%
377 1
 
0.2%
Other values (561) 561
98.2%
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 (%)
571 1
0.2%
570 1
0.2%
569 1
0.2%
568 1
0.2%
567 1
0.2%
566 1
0.2%
565 1
0.2%
564 1
0.2%
563 1
0.2%
562 1
0.2%

개방서비스명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.6 KiB
소독업
571 

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 571
100.0%

Length

2024-04-21T02:43:36.102700image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T02:43:36.384633image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
소독업 571
100.0%

개방서비스ID
Categorical

CONSTANT 

Distinct1
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size4.6 KiB
09_30_11_P
571 

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 571
100.0%

Length

2024-04-21T02:43:36.592050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T02:43:36.771538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
09_30_11_p 571
100.0%

개방자치단체코드
Real number (ℝ)

Distinct8
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3446077.1
Minimum3410000
Maximum3480000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.1 KiB
2024-04-21T02:43:36.913343image/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 deviation21505.308
Coefficient of variation (CV)0.0062405185
Kurtosis-1.3126273
Mean3446077.1
Median Absolute Deviation (MAD)20000
Skewness-0.22571575
Sum1.96771 × 109
Variance4.6247826 × 108
MonotonicityIncreasing
2024-04-21T02:43:37.109011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
3470000 123
21.5%
3420000 106
18.6%
3460000 96
16.8%
3450000 80
14.0%
3440000 49
 
8.6%
3430000 47
 
8.2%
3410000 45
 
7.9%
3480000 25
 
4.4%
ValueCountFrequency (%)
3410000 45
 
7.9%
3420000 106
18.6%
3430000 47
 
8.2%
3440000 49
 
8.6%
3450000 80
14.0%
3460000 96
16.8%
3470000 123
21.5%
3480000 25
 
4.4%
ValueCountFrequency (%)
3480000 25
 
4.4%
3470000 123
21.5%
3460000 96
16.8%
3450000 80
14.0%
3440000 49
 
8.6%
3430000 47
 
8.2%
3420000 106
18.6%
3410000 45
 
7.9%

관리번호
Text

UNIQUE 

Distinct571
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size4.6 KiB
2024-04-21T02:43:37.747107image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length25
Median length25
Mean length25
Min length25

Characters and Unicode

Total characters14275
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

Unique571 ?
Unique (%)100.0%

Sample

1st rowPHMB520173410023042500003
2nd rowPHMB520193410023042500004
3rd rowPHMB520053410023042500002
4th rowPHMB519993410023042500003
5th rowPHMB520093410023042500002
ValueCountFrequency (%)
phmb520173410023042500003 1
 
0.2%
phmb520173460023042500005 1
 
0.2%
phmb520183460023042500001 1
 
0.2%
phmb520203460023042500016 1
 
0.2%
phmb520203460023042500012 1
 
0.2%
phmb520183460023042500002 1
 
0.2%
phmb520193460023042500002 1
 
0.2%
phmb520193460023042500001 1
 
0.2%
phmb520203460023042500018 1
 
0.2%
phmb520203460023042500013 1
 
0.2%
Other values (561) 561
98.2%
2024-04-21T02:43:38.600672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 4766
33.4%
2 2189
15.3%
4 1348
 
9.4%
5 1320
 
9.2%
3 980
 
6.9%
1 703
 
4.9%
P 571
 
4.0%
H 571
 
4.0%
M 571
 
4.0%
B 571
 
4.0%
Other values (4) 685
 
4.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 11991
84.0%
Uppercase Letter 2284
 
16.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 4766
39.7%
2 2189
18.3%
4 1348
 
11.2%
5 1320
 
11.0%
3 980
 
8.2%
1 703
 
5.9%
7 199
 
1.7%
6 198
 
1.7%
9 185
 
1.5%
8 103
 
0.9%
Uppercase Letter
ValueCountFrequency (%)
P 571
25.0%
H 571
25.0%
M 571
25.0%
B 571
25.0%

Most occurring scripts

ValueCountFrequency (%)
Common 11991
84.0%
Latin 2284
 
16.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 4766
39.7%
2 2189
18.3%
4 1348
 
11.2%
5 1320
 
11.0%
3 980
 
8.2%
1 703
 
5.9%
7 199
 
1.7%
6 198
 
1.7%
9 185
 
1.5%
8 103
 
0.9%
Latin
ValueCountFrequency (%)
P 571
25.0%
H 571
25.0%
M 571
25.0%
B 571
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 14275
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 4766
33.4%
2 2189
15.3%
4 1348
 
9.4%
5 1320
 
9.2%
3 980
 
6.9%
1 703
 
4.9%
P 571
 
4.0%
H 571
 
4.0%
M 571
 
4.0%
B 571
 
4.0%
Other values (4) 685
 
4.8%

인허가일자
Real number (ℝ)

Distinct516
Distinct (%)90.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20123795
Minimum19841217
Maximum20200828
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.1 KiB
2024-04-21T02:43:38.850246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19841217
5-th percentile20000118
Q120090470
median20130809
Q320180470
95-th percentile20200521
Maximum20200828
Range359611
Interquartile range (IQR)90000

Descriptive statistics

Standard deviation67375.748
Coefficient of variation (CV)0.0033480637
Kurtosis1.8274854
Mean20123795
Median Absolute Deviation (MAD)49302
Skewness-1.1804278
Sum1.1490687 × 1010
Variance4.5394914 × 109
MonotonicityNot monotonic
2024-04-21T02:43:39.108876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20200421 5
 
0.9%
20200828 3
 
0.5%
20090521 3
 
0.5%
20100118 3
 
0.5%
20200310 3
 
0.5%
20200102 2
 
0.4%
20200528 2
 
0.4%
20200506 2
 
0.4%
20200408 2
 
0.4%
20080218 2
 
0.4%
Other values (506) 544
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 (%)
20200828 3
0.5%
20200827 1
 
0.2%
20200826 1
 
0.2%
20200824 2
0.4%
20200821 1
 
0.2%
20200813 1
 
0.2%
20200803 1
 
0.2%
20200731 1
 
0.2%
20200722 1
 
0.2%
20200720 1
 
0.2%

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing571
Missing (%)100.0%
Memory size5.1 KiB

영업상태구분코드
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size4.6 KiB
1
381 
3
184 
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 (%)
1 381
66.7%
3 184
32.2%
4 5
 
0.9%
2 1
 
0.2%

Length

2024-04-21T02:43:39.352684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T02:43:39.723063image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 381
66.7%
3 184
32.2%
4 5
 
0.9%
2 1
 
0.2%

영업상태명
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size4.6 KiB
영업/정상
381 
폐업
184 
취소/말소/만료/정지/중지
 
5
휴업
 
1

Length

Max length14
Median length5
Mean length4.1068301
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 381
66.7%
폐업 184
32.2%
취소/말소/만료/정지/중지 5
 
0.9%
휴업 1
 
0.2%

Length

2024-04-21T02:43:39.914354image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T02:43:40.122581image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 381
66.7%
폐업 184
32.2%
취소/말소/만료/정지/중지 5
 
0.9%
휴업 1
 
0.2%

상세영업상태코드
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size4.6 KiB
13
381 
3
184 
24
 
5
2
 
1

Length

Max length2
Median length2
Mean length1.676007
Min length1

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
13 381
66.7%
3 184
32.2%
24 5
 
0.9%
2 1
 
0.2%

Length

2024-04-21T02:43:40.360076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T02:43:40.603098image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
13 381
66.7%
3 184
32.2%
24 5
 
0.9%
2 1
 
0.2%

상세영업상태명
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size4.6 KiB
영업중
381 
폐업
184 
직권폐업
 
5
휴업
 
1

Length

Max length4
Median length3
Mean length2.6847636
Min length2

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
영업중 381
66.7%
폐업 184
32.2%
직권폐업 5
 
0.9%
휴업 1
 
0.2%

Length

2024-04-21T02:43:40.858955image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T02:43:41.111480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업중 381
66.7%
폐업 184
32.2%
직권폐업 5
 
0.9%
휴업 1
 
0.2%

폐업일자
Real number (ℝ)

MISSING 

Distinct182
Distinct (%)96.3%
Missing382
Missing (%)66.9%
Infinite0
Infinite (%)0.0%
Mean20146911
Minimum20081010
Maximum20200729
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.1 KiB
2024-04-21T02:43:41.430823image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20081010
5-th percentile20100205
Q120120702
median20150514
Q320171128
95-th percentile20200115
Maximum20200729
Range119719
Interquartile range (IQR)50426

Descriptive statistics

Standard deviation32169.178
Coefficient of variation (CV)0.00159673
Kurtosis-1.1144275
Mean20146911
Median Absolute Deviation (MAD)29597
Skewness-0.034800387
Sum3.8077663 × 109
Variance1.034856 × 109
MonotonicityNot monotonic
2024-04-21T02:43:41.883658image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20121231 3
 
0.5%
20140109 2
 
0.4%
20130809 2
 
0.4%
20150526 2
 
0.4%
20100525 2
 
0.4%
20130222 2
 
0.4%
20100218 1
 
0.2%
20130708 1
 
0.2%
20081010 1
 
0.2%
20161024 1
 
0.2%
Other values (172) 172
30.1%
(Missing) 382
66.9%
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 (%)
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%
20200123 1
0.2%

휴업시작일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.6 KiB
<NA>
570 
20170311
 
1

Length

Max length8
Median length4
Mean length4.0070053
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> 570
99.8%
20170311 1
 
0.2%

Length

2024-04-21T02:43:42.331084image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T02:43:42.660570image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 570
99.8%
20170311 1
 
0.2%

휴업종료일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.6 KiB
<NA>
570 
20200310
 
1

Length

Max length8
Median length4
Mean length4.0070053
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> 570
99.8%
20200310 1
 
0.2%

Length

2024-04-21T02:43:43.014861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T02:43:43.347463image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 570
99.8%
20200310 1
 
0.2%

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing571
Missing (%)100.0%
Memory size5.1 KiB

소재지전화
Text

MISSING 

Distinct388
Distinct (%)95.6%
Missing165
Missing (%)28.9%
Memory size4.6 KiB
2024-04-21T02:43:44.286190image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length12
Mean length10.596059
Min length7

Characters and Unicode

Total characters4302
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

Unique370 ?
Unique (%)91.1%

Sample

1st row053-719-0599
2nd row053792-5369
3rd row053-473-0005
4th row053-421-0421
5th row053-421-6866
ValueCountFrequency (%)
753-6306 2
 
0.5%
053-638-8004 2
 
0.5%
053-584-2520 2
 
0.5%
053-631-3225 2
 
0.5%
742-3344 2
 
0.5%
053-961-0376 2
 
0.5%
744-3910 2
 
0.5%
053-767-0408 2
 
0.5%
784-6080 2
 
0.5%
741-5110 2
 
0.5%
Other values (380) 388
95.1%
2024-04-21T02:43:45.673864image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 634
14.7%
- 631
14.7%
3 507
11.8%
0 500
11.6%
2 355
8.3%
6 330
7.7%
7 308
7.2%
1 302
7.0%
4 270
6.3%
8 232
 
5.4%
Other values (7) 233
 
5.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3657
85.0%
Dash Punctuation 631
 
14.7%
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 (%)
5 634
17.3%
3 507
13.9%
0 500
13.7%
2 355
9.7%
6 330
9.0%
7 308
8.4%
1 302
8.3%
4 270
7.4%
8 232
 
6.3%
9 219
 
6.0%
Other Punctuation
ValueCountFrequency (%)
. 2
66.7%
/ 1
33.3%
Dash Punctuation
ValueCountFrequency (%)
- 631
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 4302
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 634
14.7%
- 631
14.7%
3 507
11.8%
0 500
11.6%
2 355
8.3%
6 330
7.7%
7 308
7.2%
1 302
7.0%
4 270
6.3%
8 232
 
5.4%
Other values (7) 233
 
5.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 4302
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 634
14.7%
- 631
14.7%
3 507
11.8%
0 500
11.6%
2 355
8.3%
6 330
7.7%
7 308
7.2%
1 302
7.0%
4 270
6.3%
8 232
 
5.4%
Other values (7) 233
 
5.4%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing571
Missing (%)100.0%
Memory size5.1 KiB

소재지우편번호
Real number (ℝ)

MISSING 

Distinct176
Distinct (%)73.0%
Missing330
Missing (%)57.8%
Infinite0
Infinite (%)0.0%
Mean695689.46
Minimum41230
Maximum711844
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.1 KiB
2024-04-21T02:43:46.071035image/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
2024-04-21T02:43:46.487634image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
706010 5
 
0.9%
702072 4
 
0.7%
701848 3
 
0.5%
701846 3
 
0.5%
701811 3
 
0.5%
701829 3
 
0.5%
706032 3
 
0.5%
701849 3
 
0.5%
706040 3
 
0.5%
701810 3
 
0.5%
Other values (166) 208
36.4%
(Missing) 330
57.8%
ValueCountFrequency (%)
41230 1
0.2%
41946 1
0.2%
42696 1
0.2%
700082 1
0.2%
700230 2
0.4%
700380 1
0.2%
700400 1
0.2%
700421 1
0.2%
700423 2
0.4%
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
0.4%
706913 1
0.2%
706852 2
0.4%
706844 1
0.2%
706839 1
0.2%

소재지전체주소
Text

MISSING 

Distinct494
Distinct (%)96.3%
Missing58
Missing (%)10.2%
Memory size4.6 KiB
2024-04-21T02:43:47.597097image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length50
Median length43
Mean length23.697856
Min length12

Characters and Unicode

Total characters12157
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

Unique475 ?
Unique (%)92.6%

Sample

1st row대구광역시 중구 대봉동 20번지 1호
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 513
 
19.0%
달서구 122
 
4.5%
동구 88
 
3.3%
수성구 82
 
3.0%
북구 79
 
2.9%
1호 64
 
2.4%
서구 46
 
1.7%
남구 42
 
1.6%
2호 39
 
1.4%
중구 38
 
1.4%
Other values (733) 1580
58.7%
2024-04-21T02:43:49.177143image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2189
18.0%
구 1023
 
8.4%
동 617
 
5.1%
1 588
 
4.8%
대 556
 
4.6%
지 528
 
4.3%
시 521
 
4.3%
광 516
 
4.2%
역 514
 
4.2%
번 491
 
4.0%
Other values (184) 4614
38.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7352
60.5%
Decimal Number 2565
 
21.1%
Space Separator 2189
 
18.0%
Dash Punctuation 19
 
0.2%
Open Punctuation 13
 
0.1%
Close Punctuation 13
 
0.1%
Other Punctuation 5
 
< 0.1%
Uppercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 1023
13.9%
동 617
 
8.4%
대 556
 
7.6%
지 528
 
7.2%
시 521
 
7.1%
광 516
 
7.0%
역 514
 
7.0%
번 491
 
6.7%
호 476
 
6.5%
서 180
 
2.4%
Other values (167) 1930
26.3%
Decimal Number
ValueCountFrequency (%)
1 588
22.9%
2 366
14.3%
4 267
10.4%
3 256
10.0%
0 221
 
8.6%
5 192
 
7.5%
8 179
 
7.0%
6 177
 
6.9%
7 167
 
6.5%
9 152
 
5.9%
Other Punctuation
ValueCountFrequency (%)
, 4
80.0%
. 1
 
20.0%
Space Separator
ValueCountFrequency (%)
2189
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 19
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 7352
60.5%
Common 4804
39.5%
Latin 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 1023
13.9%
동 617
 
8.4%
대 556
 
7.6%
지 528
 
7.2%
시 521
 
7.1%
광 516
 
7.0%
역 514
 
7.0%
번 491
 
6.7%
호 476
 
6.5%
서 180
 
2.4%
Other values (167) 1930
26.3%
Common
ValueCountFrequency (%)
2189
45.6%
1 588
 
12.2%
2 366
 
7.6%
4 267
 
5.6%
3 256
 
5.3%
0 221
 
4.6%
5 192
 
4.0%
8 179
 
3.7%
6 177
 
3.7%
7 167
 
3.5%
Other values (6) 202
 
4.2%
Latin
ValueCountFrequency (%)
B 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 7352
60.5%
ASCII 4805
39.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2189
45.6%
1 588
 
12.2%
2 366
 
7.6%
4 267
 
5.6%
3 256
 
5.3%
0 221
 
4.6%
5 192
 
4.0%
8 179
 
3.7%
6 177
 
3.7%
7 167
 
3.5%
Other values (7) 203
 
4.2%
Hangul
ValueCountFrequency (%)
구 1023
13.9%
동 617
 
8.4%
대 556
 
7.6%
지 528
 
7.2%
시 521
 
7.1%
광 516
 
7.0%
역 514
 
7.0%
번 491
 
6.7%
호 476
 
6.5%
서 180
 
2.4%
Other values (167) 1930
26.3%

도로명전체주소
Text

Distinct549
Distinct (%)96.5%
Missing2
Missing (%)0.4%
Memory size4.6 KiB
2024-04-21T02:43:50.479783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length56
Median length48
Mean length27.920914
Min length20

Characters and Unicode

Total characters15887
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

Unique529 ?
Unique (%)93.0%

Sample

1st row대구광역시 중구 중앙대로 269 (남산동)
2nd row대구광역시 중구 달구벌대로 2200, 3층 (대봉동)
3rd row대구광역시 중구 관덕정길 73 (남산동)
4th row대구광역시 중구 대봉로 260 (대봉동)
5th row대구광역시 중구 남산로7길 75 (남산동,까치아파트 상가104 지하1층)
ValueCountFrequency (%)
대구광역시 569
 
17.3%
달서구 123
 
3.7%
동구 105
 
3.2%
수성구 95
 
2.9%
1층 86
 
2.6%
북구 80
 
2.4%
2층 69
 
2.1%
남구 48
 
1.5%
서구 47
 
1.4%
중구 45
 
1.4%
Other values (932) 2024
61.5%
2024-04-21T02:43:52.034985image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2748
 
17.3%
구 1177
 
7.4%
동 766
 
4.8%
대 694
 
4.4%
시 581
 
3.7%
광 571
 
3.6%
역 570
 
3.6%
1 562
 
3.5%
) 550
 
3.5%
( 550
 
3.5%
Other values (241) 7118
44.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 9099
57.3%
Space Separator 2748
 
17.3%
Decimal Number 2488
 
15.7%
Close Punctuation 550
 
3.5%
Open Punctuation 550
 
3.5%
Other Punctuation 339
 
2.1%
Dash Punctuation 109
 
0.7%
Uppercase Letter 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 1177
 
12.9%
동 766
 
8.4%
대 694
 
7.6%
시 581
 
6.4%
광 571
 
6.3%
역 570
 
6.3%
로 541
 
5.9%
길 322
 
3.5%
층 260
 
2.9%
서 218
 
2.4%
Other values (221) 3399
37.4%
Decimal Number
ValueCountFrequency (%)
1 562
22.6%
2 422
17.0%
3 285
11.5%
4 251
10.1%
0 210
 
8.4%
5 201
 
8.1%
6 169
 
6.8%
7 146
 
5.9%
8 126
 
5.1%
9 116
 
4.7%
Uppercase Letter
ValueCountFrequency (%)
B 1
25.0%
A 1
25.0%
H 1
25.0%
C 1
25.0%
Other Punctuation
ValueCountFrequency (%)
, 338
99.7%
. 1
 
0.3%
Space Separator
ValueCountFrequency (%)
2748
100.0%
Close Punctuation
ValueCountFrequency (%)
) 550
100.0%
Open Punctuation
ValueCountFrequency (%)
( 550
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 109
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 9099
57.3%
Common 6784
42.7%
Latin 4
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 1177
 
12.9%
동 766
 
8.4%
대 694
 
7.6%
시 581
 
6.4%
광 571
 
6.3%
역 570
 
6.3%
로 541
 
5.9%
길 322
 
3.5%
층 260
 
2.9%
서 218
 
2.4%
Other values (221) 3399
37.4%
Common
ValueCountFrequency (%)
2748
40.5%
1 562
 
8.3%
) 550
 
8.1%
( 550
 
8.1%
2 422
 
6.2%
, 338
 
5.0%
3 285
 
4.2%
4 251
 
3.7%
0 210
 
3.1%
5 201
 
3.0%
Other values (6) 667
 
9.8%
Latin
ValueCountFrequency (%)
B 1
25.0%
A 1
25.0%
H 1
25.0%
C 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 9099
57.3%
ASCII 6788
42.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2748
40.5%
1 562
 
8.3%
) 550
 
8.1%
( 550
 
8.1%
2 422
 
6.2%
, 338
 
5.0%
3 285
 
4.2%
4 251
 
3.7%
0 210
 
3.1%
5 201
 
3.0%
Other values (10) 671
 
9.9%
Hangul
ValueCountFrequency (%)
구 1177
 
12.9%
동 766
 
8.4%
대 694
 
7.6%
시 581
 
6.4%
광 571
 
6.3%
역 570
 
6.3%
로 541
 
5.9%
길 322
 
3.5%
층 260
 
2.9%
서 218
 
2.4%
Other values (221) 3399
37.4%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct383
Distinct (%)73.7%
Missing51
Missing (%)8.9%
Infinite0
Infinite (%)0.0%
Mean118446.36
Minimum41017
Maximum711702
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.1 KiB
2024-04-21T02:43:52.269935image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum41017
5-th percentile41122.9
Q141537
median42163.5
Q342730
95-th percentile704410
Maximum711702
Range670685
Interquartile range (IQR)1193

Descriptive statistics

Standard deviation211816.19
Coefficient of variation (CV)1.7882879
Kurtosis3.8458809
Mean118446.36
Median Absolute Deviation (MAD)596.5
Skewness2.4147232
Sum61592105
Variance4.4866098 × 1010
MonotonicityNot monotonic
2024-04-21T02:43:52.508325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
42733 4
 
0.7%
41078 4
 
0.7%
42471 4
 
0.7%
42679 4
 
0.7%
41196 4
 
0.7%
42743 3
 
0.5%
41472 3
 
0.5%
42819 3
 
0.5%
41843 3
 
0.5%
42467 3
 
0.5%
Other values (373) 485
84.9%
(Missing) 51
 
8.9%
ValueCountFrequency (%)
41017 1
 
0.2%
41029 1
 
0.2%
41033 1
 
0.2%
41035 1
 
0.2%
41042 1
 
0.2%
41048 2
0.4%
41067 1
 
0.2%
41068 2
0.4%
41075 1
 
0.2%
41078 4
0.7%
ValueCountFrequency (%)
711702 2
0.4%
706853 1
0.2%
706852 2
0.4%
706838 2
0.4%
706833 1
0.2%
706824 1
0.2%
706818 1
0.2%
706813 2
0.4%
706810 1
0.2%
706808 2
0.4%

사업장명
Text

Distinct533
Distinct (%)93.3%
Missing0
Missing (%)0.0%
Memory size4.6 KiB
2024-04-21T02:43:53.343979image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length33
Median length22
Mean length7.4028021
Min length2

Characters and Unicode

Total characters4227
Distinct characters384
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

Unique504 ?
Unique (%)88.3%

Sample

1st row설악경호
2nd row터미닉스코리아 대구지사
3rd row한울종합방제
4th row그린종합관리
5th row대구중구지역자활썬터(말끄미소독방역)
ValueCountFrequency (%)
주식회사 30
 
4.5%
청쿰방역공사 4
 
0.6%
세기위생방역 4
 
0.6%
종합관리 4
 
0.6%
한국방제공사 4
 
0.6%
솔루션 3
 
0.4%
대구지사 3
 
0.4%
주 3
 
0.4%
더홈케어 3
 
0.4%
대신종합관리 3
 
0.4%
Other values (569) 606
90.9%
2024-04-21T02:43:54.640024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 239
 
5.7%
) 211
 
5.0%
( 209
 
4.9%
스 123
 
2.9%
사 107
 
2.5%
96
 
2.3%
역 92
 
2.2%
대 90
 
2.1%
방 86
 
2.0%
리 85
 
2.0%
Other values (374) 2889
68.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3576
84.6%
Close Punctuation 211
 
5.0%
Open Punctuation 209
 
4.9%
Space Separator 96
 
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 239
 
6.7%
스 123
 
3.4%
사 107
 
3.0%
역 92
 
2.6%
대 90
 
2.5%
방 86
 
2.4%
리 85
 
2.4%
합 77
 
2.2%
경 77
 
2.2%
종 69
 
1.9%
Other values (327) 2531
70.8%
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%
L 2
 
2.2%
Other values (13) 15
16.9%
Lowercase Letter
ValueCountFrequency (%)
e 6
25.0%
o 3
12.5%
n 3
12.5%
a 2
 
8.3%
r 2
 
8.3%
c 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%
5 1
 
7.1%
0 1
 
7.1%
6 1
 
7.1%
Other Punctuation
ValueCountFrequency (%)
& 4
50.0%
, 3
37.5%
. 1
 
12.5%
Close Punctuation
ValueCountFrequency (%)
) 211
100.0%
Open Punctuation
ValueCountFrequency (%)
( 209
100.0%
Space Separator
ValueCountFrequency (%)
96
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3576
84.6%
Common 538
 
12.7%
Latin 113
 
2.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 239
 
6.7%
스 123
 
3.4%
사 107
 
3.0%
역 92
 
2.6%
대 90
 
2.5%
방 86
 
2.4%
리 85
 
2.4%
합 77
 
2.2%
경 77
 
2.2%
종 69
 
1.9%
Other values (327) 2531
70.8%
Latin
ValueCountFrequency (%)
S 15
13.3%
E 14
 
12.4%
C 9
 
8.0%
N 9
 
8.0%
O 6
 
5.3%
e 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 (%)
) 211
39.2%
( 209
38.8%
96
17.8%
1 6
 
1.1%
& 4
 
0.7%
, 3
 
0.6%
9 3
 
0.6%
3 2
 
0.4%
5 1
 
0.2%
. 1
 
0.2%
Other values (2) 2
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3576
84.6%
ASCII 651
 
15.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 239
 
6.7%
스 123
 
3.4%
사 107
 
3.0%
역 92
 
2.6%
대 90
 
2.5%
방 86
 
2.4%
리 85
 
2.4%
합 77
 
2.2%
경 77
 
2.2%
종 69
 
1.9%
Other values (327) 2531
70.8%
ASCII
ValueCountFrequency (%)
) 211
32.4%
( 209
32.1%
96
14.7%
S 15
 
2.3%
E 14
 
2.2%
C 9
 
1.4%
N 9
 
1.4%
O 6
 
0.9%
e 6
 
0.9%
K 6
 
0.9%
Other values (37) 70
 
10.8%

최종수정시점
Real number (ℝ)

UNIQUE 

Distinct571
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0171018 × 1013
Minimum2.0081203 × 1013
Maximum2.0200831 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.1 KiB
2024-04-21T02:43:55.054579image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.0081203 × 1013
5-th percentile2.0111124 × 1013
Q12.0151169 × 1013
median2.0180723 × 1013
Q32.0191224 × 1013
95-th percentile2.0200719 × 1013
Maximum2.0200831 × 1013
Range1.19628 × 1011
Interquartile range (IQR)4.0055055 × 1010

Descriptive statistics

Standard deviation2.9897782 × 1010
Coefficient of variation (CV)0.0014822148
Kurtosis-0.19940461
Mean2.0171018 × 1013
Median Absolute Deviation (MAD)1.9680909 × 1010
Skewness-0.93758152
Sum1.1517651 × 1016
Variance8.9387738 × 1020
MonotonicityNot monotonic
2024-04-21T02:43:55.516247image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20190222170714 1
 
0.2%
20180723184345 1
 
0.2%
20200701090501 1
 
0.2%
20181025135943 1
 
0.2%
20190325192748 1
 
0.2%
20200116091537 1
 
0.2%
20171129132941 1
 
0.2%
20191112092749 1
 
0.2%
20170522203631 1
 
0.2%
20200828140449 1
 
0.2%
Other values (561) 561
98.2%
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 (%)
20200831174031 1
0.2%
20200828140659 1
0.2%
20200828140449 1
0.2%
20200828101739 1
0.2%
20200828092006 1
0.2%
20200827180657 1
0.2%
20200827131556 1
0.2%
20200825203204 1
0.2%
20200824203410 1
0.2%
20200824085623 1
0.2%

데이터갱신구분
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.6 KiB
I
387 
U
184 

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 387
67.8%
U 184
32.2%

Length

2024-04-21T02:43:55.932222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T02:43:56.229729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 387
67.8%
u 184
32.2%

데이터갱신일자
Date

Distinct204
Distinct (%)35.7%
Missing0
Missing (%)0.0%
Memory size4.6 KiB
Minimum2018-08-31 23:59:59
Maximum2020-09-02 00:23:13
2024-04-21T02:43:56.552808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-21T02:43:56.993520image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing571
Missing (%)100.0%
Memory size5.1 KiB

좌표정보(X)
Real number (ℝ)

Distinct520
Distinct (%)91.4%
Missing2
Missing (%)0.4%
Infinite0
Infinite (%)0.0%
Mean343450.32
Minimum327191.86
Maximum356430.94
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.1 KiB
2024-04-21T02:43:57.391947image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum327191.86
5-th percentile336295.12
Q1340073.2
median343386.59
Q3346641.97
95-th percentile352824.63
Maximum356430.94
Range29239.08
Interquartile range (IQR)6568.7729

Descriptive statistics

Standard deviation4777.3385
Coefficient of variation (CV)0.013909839
Kurtosis0.47122136
Mean343450.32
Median Absolute Deviation (MAD)3297.2117
Skewness0.10882792
Sum1.9542323 × 108
Variance22822963
MonotonicityNot monotonic
2024-04-21T02:43:57.803183image/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%
339145.209362 2
 
0.4%
339602.802351 2
 
0.4%
340807.798244 2
 
0.4%
337714.029318 2
 
0.4%
336652.545031 2
 
0.4%
337093.983895 2
 
0.4%
345960.705739 2
 
0.4%
339893.483467 2
 
0.4%
Other values (510) 546
95.6%
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
0.4%
355595.530398 1
0.2%
354843.399478 1
0.2%
354818.553042 1
0.2%

좌표정보(Y)
Real number (ℝ)

Distinct519
Distinct (%)91.2%
Missing2
Missing (%)0.4%
Infinite0
Infinite (%)0.0%
Mean263276.16
Minimum240800.46
Maximum274231.06
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.1 KiB
2024-04-21T02:43:58.427060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum240800.46
5-th percentile257626.74
Q1261137.23
median263388.14
Q3265334.46
95-th percentile270213.86
Maximum274231.06
Range33430.603
Interquartile range (IQR)4197.2254

Descriptive statistics

Standard deviation3926.1349
Coefficient of variation (CV)0.014912611
Kurtosis4.6535281
Mean263276.16
Median Absolute Deviation (MAD)2126.9477
Skewness-0.74486521
Sum1.4980414 × 108
Variance15414535
MonotonicityNot monotonic
2024-04-21T02:43:58.866145image/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%
266273.9172 2
 
0.4%
260576.729655 2
 
0.4%
272627.220724 2
 
0.4%
265533.584398 2
 
0.4%
270254.952188 2
 
0.4%
261826.249533 2
 
0.4%
261668.530778 2
 
0.4%
261758.126509 2
 
0.4%
Other values (509) 546
95.6%
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 (%)
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
0.4%
272589.689012 1
0.2%

사무실면적
Real number (ℝ)

MISSING  SKEWED 

Distinct375
Distinct (%)77.3%
Missing86
Missing (%)15.1%
Infinite0
Infinite (%)0.0%
Mean58.025155
Minimum2.6
Maximum4284
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.1 KiB
2024-04-21T02:43:59.288533image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.6
5-th percentile9.756
Q119.47
median35
Q360.36
95-th percentile139.308
Maximum4284
Range4281.4
Interquartile range (IQR)40.89

Descriptive statistics

Standard deviation197.87717
Coefficient of variation (CV)3.4101964
Kurtosis432.21284
Mean58.025155
Median Absolute Deviation (MAD)18
Skewness20.242423
Sum28142.2
Variance39155.375
MonotonicityNot monotonic
2024-04-21T02:43:59.700533image/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%
33.0 6
 
1.1%
35.0 6
 
1.1%
36.0 5
 
0.9%
15.6 4
 
0.7%
23.1 4
 
0.7%
49.5 3
 
0.5%
21.6 3
 
0.5%
86.0 3
 
0.5%
Other values (365) 435
76.2%
(Missing) 86
 
15.1%
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 

Distinct270
Distinct (%)57.4%
Missing101
Missing (%)17.7%
Infinite0
Infinite (%)0.0%
Mean22.846489
Minimum0.9
Maximum1776
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.1 KiB
2024-04-21T02:44:00.051000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0.9
5-th percentile3.3945
Q17.5
median12.5
Q322.5
95-th percentile50.11
Maximum1776
Range1775.1
Interquartile range (IQR)15

Descriptive statistics

Standard deviation84.297885
Coefficient of variation (CV)3.6897522
Kurtosis401.16946
Mean22.846489
Median Absolute Deviation (MAD)5.9
Skewness19.349973
Sum10737.85
Variance7106.1334
MonotonicityNot monotonic
2024-04-21T02:44:00.298693image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
10.0 21
 
3.7%
16.5 11
 
1.9%
9.9 10
 
1.8%
5.0 10
 
1.8%
7.0 10
 
1.8%
6.0 8
 
1.4%
6.6 7
 
1.2%
15.0 7
 
1.2%
20.0 7
 
1.2%
33.0 7
 
1.2%
Other values (260) 372
65.1%
(Missing) 101
 
17.7%
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
0.4%
2.2 2
0.4%
2.3 2
0.4%
3.0 2
0.4%
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 size4.6 KiB
1
528 
2
 
31
3
 
7
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 (%)
1 528
92.5%
2 31
 
5.4%
3 7
 
1.2%
4 3
 
0.5%
0 2
 
0.4%

Length

2024-04-21T02:44:00.530005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T02:44:00.702923image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 528
92.5%
2 31
 
5.4%
3 7
 
1.2%
4 3
 
0.5%
0 2
 
0.4%

휴대용소독기수
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size4.6 KiB
2
555 
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 (%)
2 555
97.2%
3 11
 
1.9%
4 4
 
0.7%
7 1
 
0.2%

Length

2024-04-21T02:44:00.914557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T02:44:01.234340image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 555
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 size4.6 KiB
1
313 
0
252 
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
54.8%
0 252
44.1%
2 3
 
0.5%
3 2
 
0.4%
7 1
 
0.2%

Length

2024-04-21T02:44:01.580937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T02:44:01.905521image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 313
54.8%
0 252
44.1%
2 3
 
0.5%
3 2
 
0.4%
7 1
 
0.2%

수동식분무기수
Real number (ℝ)

Distinct12
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean4.4395797
Minimum3
Maximum24
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.1 KiB
2024-04-21T02:44:02.234865image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

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

Descriptive statistics

Standard deviation1.8640954
Coefficient of variation (CV)0.41988106
Kurtosis39.795893
Mean4.4395797
Median Absolute Deviation (MAD)0
Skewness4.8392136
Sum2535
Variance3.4748518
MonotonicityNot monotonic
2024-04-21T02:44:02.582367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
5 290
50.8%
3 229
40.1%
7 13
 
2.3%
6 12
 
2.1%
4 11
 
1.9%
8 5
 
0.9%
10 4
 
0.7%
9 2
 
0.4%
20 2
 
0.4%
14 1
 
0.2%
Other values (2) 2
 
0.4%
ValueCountFrequency (%)
3 229
40.1%
4 11
 
1.9%
5 290
50.8%
6 12
 
2.1%
7 13
 
2.3%
8 5
 
0.9%
9 2
 
0.4%
10 4
 
0.7%
14 1
 
0.2%
15 1
 
0.2%
ValueCountFrequency (%)
24 1
 
0.2%
20 2
 
0.4%
15 1
 
0.2%
14 1
 
0.2%
10 4
 
0.7%
9 2
 
0.4%
8 5
 
0.9%
7 13
 
2.3%
6 12
 
2.1%
5 290
50.8%

방독면수
Real number (ℝ)

Distinct6
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.0945709
Minimum5
Maximum20
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.1 KiB
2024-04-21T02:44:02.905155image/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 deviation0.80665344
Coefficient of variation (CV)0.15833589
Kurtosis216.27927
Mean5.0945709
Median Absolute Deviation (MAD)0
Skewness13.250034
Sum2909
Variance0.65068977
MonotonicityNot monotonic
2024-04-21T02:44:03.249813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
5 556
97.4%
10 5
 
0.9%
6 5
 
0.9%
7 3
 
0.5%
8 1
 
0.2%
20 1
 
0.2%
ValueCountFrequency (%)
5 556
97.4%
6 5
 
0.9%
7 3
 
0.5%
8 1
 
0.2%
10 5
 
0.9%
20 1
 
0.2%
ValueCountFrequency (%)
20 1
 
0.2%
10 5
 
0.9%
8 1
 
0.2%
7 3
 
0.5%
6 5
 
0.9%
5 556
97.4%

보호안경수
Real number (ℝ)

Distinct6
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.0980736
Minimum5
Maximum20
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.1 KiB
2024-04-21T02:44:03.586416image/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 deviation0.82558632
Coefficient of variation (CV)0.16194084
Kurtosis198.7397
Mean5.0980736
Median Absolute Deviation (MAD)0
Skewness12.674776
Sum2911
Variance0.68159277
MonotonicityNot monotonic
2024-04-21T02:44:03.927619image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
5 556
97.4%
10 6
 
1.1%
6 6
 
1.1%
8 1
 
0.2%
7 1
 
0.2%
20 1
 
0.2%
ValueCountFrequency (%)
5 556
97.4%
6 6
 
1.1%
7 1
 
0.2%
8 1
 
0.2%
10 6
 
1.1%
20 1
 
0.2%
ValueCountFrequency (%)
20 1
 
0.2%
10 6
 
1.1%
8 1
 
0.2%
7 1
 
0.2%
6 6
 
1.1%
5 556
97.4%

보호용의복수
Real number (ℝ)

Distinct9
Distinct (%)1.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean5.2977233
Minimum5
Maximum29
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.1 KiB
2024-04-21T02:44:04.274362image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum5
5-th percentile5
Q15
median5
Q35
95-th percentile6
Maximum29
Range24
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1.7286984
Coefficient of variation (CV)0.32630969
Kurtosis99.04108
Mean5.2977233
Median Absolute Deviation (MAD)0
Skewness9.1037922
Sum3025
Variance2.9883983
MonotonicityNot monotonic
2024-04-21T02:44:04.625587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
5 537
94.0%
10 13
 
2.3%
6 7
 
1.2%
7 5
 
0.9%
8 4
 
0.7%
20 2
 
0.4%
9 1
 
0.2%
29 1
 
0.2%
23 1
 
0.2%
ValueCountFrequency (%)
5 537
94.0%
6 7
 
1.2%
7 5
 
0.9%
8 4
 
0.7%
9 1
 
0.2%
10 13
 
2.3%
20 2
 
0.4%
23 1
 
0.2%
29 1
 
0.2%
ValueCountFrequency (%)
29 1
 
0.2%
23 1
 
0.2%
20 2
 
0.4%
10 13
 
2.3%
9 1
 
0.2%
8 4
 
0.7%
7 5
 
0.9%
6 7
 
1.2%
5 537
94.0%

진공청소기수
Categorical

IMBALANCE 

Distinct5
Distinct (%)0.9%
Missing0
Missing (%)0.0%
Memory size4.6 KiB
1
519 
2
 
32
5
 
9
3
 
9
4
 
2

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 (%)
1 519
90.9%
2 32
 
5.6%
5 9
 
1.6%
3 9
 
1.6%
4 2
 
0.4%

Length

2024-04-21T02:44:04.998440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-21T02:44:05.310194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 519
90.9%
2 32
 
5.6%
5 9
 
1.6%
3 9
 
1.6%
4 2
 
0.4%

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_P3410000PHMB52019341002304250000420150724<NA>1영업/정상13영업중<NA><NA><NA><NA>053-719-0599<NA><NA>대구광역시 중구 대봉동 20번지 1호대구광역시 중구 달구벌대로 2200, 3층 (대봉동)41951터미닉스코리아 대구지사20191101154506U2019-11-03 02:40:00.0<NA>344789.5227263686.422283198.039.012035551
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
561562소독업09_30_11_P3480000PHMB52017348001204250000120170221<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>대구광역시 달성군 화원읍 522번지 1호대구광역시 달성군 화원읍 성화로 3842946(주)청소이야기20190709175055U2019-07-11 02:40:00.0<NA>334498.15167256709.0559730.293.312035551
562563소독업09_30_11_P3480000PHMB52016348001204250000120160411<NA>1영업/정상13영업중<NA><NA><NA><NA>053-615-8961<NA><NA>대구광역시 달성군 옥포읍 교항리 2936번지대구광역시 달성군 옥포읍 돌미로 85, 4층 402호42974세스코 대구남부지사20191224173442U2019-12-26 02:40:00.0<NA>330387.847151254464.570032178.098.022055551
563564소독업09_30_11_P3480000PHMB52013348001204250000220130204<NA>1영업/정상13영업중<NA><NA><NA><NA>637-0108<NA><NA>대구광역시 달성군 논공읍 노이리 1324번지 2호대구광역시 달성군 논공읍 노이2길 5942975성강건설(주)20190115193919U2019-01-17 02:40:00.0<NA>335144.190213257035.20445560.0216.012135552
564565소독업09_30_11_P3480000PHMB52013348001204250000120130121<NA>1영업/정상13영업중<NA><NA><NA><NA>617-0420 / 635-4205<NA><NA>대구광역시 달성군 현풍면 부리 440번지 41통대구광역시 달성군 현풍면 현풍중앙로16길 1442999(주)나눔과행복20160725170123I2018-08-31 23:59:59.0<NA>330567.11783245096.1146230.012.012155551
565566소독업09_30_11_P3480000PHMB52009348001204250000120091221<NA>1영업/정상13영업중<NA><NA><NA><NA>053)639-6974<NA>711838대구광역시 달성군 화원읍 본리리 80번지 1호대구광역시 달성군 화원읍 성암로 16-1442966천내청소방역20150728110825I2018-08-31 23:59:59.0<NA>336309.096814256773.09881611.817.412155551
566567소독업09_30_11_P3480000PHMB52005348001204250000120050111<NA>1영업/정상13영업중<NA><NA><NA><NA>053-643-2377<NA>711834대구광역시 달성군 화원읍 천내리 107번지 3호대구광역시 달성군 화원읍 성천로 12242948금창환경20190723110115U2019-07-25 02:40:00.0<NA>335023.196036257280.68429829.5815.9512155551
567568소독업09_30_11_P3480000PHMB52018348001204250000120180117<NA>1영업/정상13영업중<NA><NA><NA><NA>053-765-7484<NA><NA>대구광역시 달성군 화원읍 명곡리 138번지 명곡미래빌4단지대구광역시 달성군 화원읍 화암로 88, 명곡미래빌4단지 상가동 2층 207호42959주식회사 와이엔티20180120163256I2018-08-31 23:59:59.0<NA>335371.838542256357.15297210.015.012035551
568569소독업09_30_11_P3480000PHMB52019348001204250000220190411<NA>1영업/정상13영업중<NA><NA><NA><NA><NA><NA><NA>대구광역시 달성군 유가읍 쌍계리 623번지 1호대구광역시 달성군 유가읍 현풍로47길 15-5, 1층42989방구방역 대구경북지사20190412110621I2019-04-14 02:20:20.0<NA>332374.0245436.011.34.512035551
569570소독업09_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
570571소독업09_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