Overview

Dataset statistics

Number of variables50
Number of observations1706
Missing cells17971
Missing cells (%)21.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory721.5 KiB
Average record size in memory433.1 B

Variable types

Numeric16
Categorical19
Text6
Unsupported6
DateTime1
Boolean2

Dataset

Description6270000_대구광역시_09_30_04_P_건물위생관리업_8월
Author대구광역시
URLhttp://data.daegu.go.kr/open/data/dataView.do?dataSetId=DMI_0000085943&dataSetDetailId=DDI_0000085974&provdMethod=FILE

Alerts

개방서비스명 has constant value ""Constant
개방서비스ID has constant value ""Constant
발한실여부 has constant value ""Constant
조건부허가신고사유 has constant value ""Constant
업태구분명 is highly imbalanced (94.0%)Imbalance
위생업태명 is highly imbalanced (94.0%)Imbalance
의자수 is highly imbalanced (54.0%)Imbalance
다중이용업소여부 is highly imbalanced (97.1%)Imbalance
인허가취소일자 has 1706 (100.0%) missing valuesMissing
폐업일자 has 539 (31.6%) missing valuesMissing
휴업시작일자 has 1706 (100.0%) missing valuesMissing
휴업종료일자 has 1706 (100.0%) missing valuesMissing
재개업일자 has 1706 (100.0%) missing valuesMissing
소재지전화 has 417 (24.4%) missing valuesMissing
도로명전체주소 has 595 (34.9%) missing valuesMissing
도로명우편번호 has 603 (35.3%) missing valuesMissing
좌표정보(X) has 26 (1.5%) missing valuesMissing
좌표정보(Y) has 26 (1.5%) missing valuesMissing
건물지상층수 has 175 (10.3%) missing valuesMissing
건물지하층수 has 348 (20.4%) missing valuesMissing
사용시작지상층 has 261 (15.3%) missing valuesMissing
사용끝지상층 has 396 (23.2%) missing valuesMissing
발한실여부 has 46 (2.7%) missing valuesMissing
조건부허가신고사유 has 1705 (99.9%) missing valuesMissing
조건부허가시작일자 has 1706 (100.0%) missing valuesMissing
조건부허가종료일자 has 1706 (100.0%) missing valuesMissing
여성종사자수 has 1383 (81.1%) missing valuesMissing
남성종사자수 has 1201 (70.4%) missing valuesMissing
번호 has unique valuesUnique
관리번호 has unique valuesUnique
인허가취소일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업시작일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업종료일자 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
조건부허가시작일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
조건부허가종료일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
소재지면적 has 160 (9.4%) zerosZeros
건물지상층수 has 283 (16.6%) zerosZeros
건물지하층수 has 716 (42.0%) zerosZeros
사용시작지상층 has 164 (9.6%) zerosZeros
사용끝지상층 has 102 (6.0%) zerosZeros
여성종사자수 has 196 (11.5%) zerosZeros
남성종사자수 has 123 (7.2%) zerosZeros

Reproduction

Analysis started2024-04-18 00:18:17.916570
Analysis finished2024-04-18 00:18:18.906015
Duration0.99 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct1706
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean853.5
Minimum1
Maximum1706
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size15.1 KiB
2024-04-18T09:18:18.967347image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile86.25
Q1427.25
median853.5
Q31279.75
95-th percentile1620.75
Maximum1706
Range1705
Interquartile range (IQR)852.5

Descriptive statistics

Standard deviation492.6241
Coefficient of variation (CV)0.57718113
Kurtosis-1.2
Mean853.5
Median Absolute Deviation (MAD)426.5
Skewness0
Sum1456071
Variance242678.5
MonotonicityStrictly increasing
2024-04-18T09:18:19.093456image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.1%
1147 1
 
0.1%
1145 1
 
0.1%
1144 1
 
0.1%
1143 1
 
0.1%
1142 1
 
0.1%
1141 1
 
0.1%
1140 1
 
0.1%
1139 1
 
0.1%
1138 1
 
0.1%
Other values (1696) 1696
99.4%
ValueCountFrequency (%)
1 1
0.1%
2 1
0.1%
3 1
0.1%
4 1
0.1%
5 1
0.1%
6 1
0.1%
7 1
0.1%
8 1
0.1%
9 1
0.1%
10 1
0.1%
ValueCountFrequency (%)
1706 1
0.1%
1705 1
0.1%
1704 1
0.1%
1703 1
0.1%
1702 1
0.1%
1701 1
0.1%
1700 1
0.1%
1699 1
0.1%
1698 1
0.1%
1697 1
0.1%

개방서비스명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size13.5 KiB
건물위생관리업
1706 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
건물위생관리업 1706
100.0%

Length

2024-04-18T09:18:19.214898image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T09:18:19.302085image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
건물위생관리업 1706
100.0%

개방서비스ID
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size13.5 KiB
09_30_04_P
1706 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row09_30_04_P
2nd row09_30_04_P
3rd row09_30_04_P
4th row09_30_04_P
5th row09_30_04_P

Common Values

ValueCountFrequency (%)
09_30_04_P 1706
100.0%

Length

2024-04-18T09:18:19.398538image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T09:18:19.490228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
09_30_04_p 1706
100.0%

개방자치단체코드
Real number (ℝ)

Distinct8
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3445603.8
Minimum3410000
Maximum3480000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size15.1 KiB
2024-04-18T09:18:19.570270image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3410000
5-th percentile3410000
Q13420000
median3450000
Q33460000
95-th percentile3470000
Maximum3480000
Range70000
Interquartile range (IQR)40000

Descriptive statistics

Standard deviation21553.019
Coefficient of variation (CV)0.0062552228
Kurtosis-1.3330505
Mean3445603.8
Median Absolute Deviation (MAD)20000
Skewness-0.19279045
Sum5.8782 × 109
Variance4.6453263 × 108
MonotonicityIncreasing
2024-04-18T09:18:19.677718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
3470000 341
20.0%
3460000 331
19.4%
3420000 307
18.0%
3450000 178
10.4%
3440000 169
9.9%
3430000 161
9.4%
3410000 144
8.4%
3480000 75
 
4.4%
ValueCountFrequency (%)
3410000 144
8.4%
3420000 307
18.0%
3430000 161
9.4%
3440000 169
9.9%
3450000 178
10.4%
3460000 331
19.4%
3470000 341
20.0%
3480000 75
 
4.4%
ValueCountFrequency (%)
3480000 75
 
4.4%
3470000 341
20.0%
3460000 331
19.4%
3450000 178
10.4%
3440000 169
9.9%
3430000 161
9.4%
3420000 307
18.0%
3410000 144
8.4%

관리번호
Text

UNIQUE 

Distinct1706
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size13.5 KiB
2024-04-18T09:18:19.870632image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length22
Mean length22
Min length22

Characters and Unicode

Total characters37532
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1706 ?
Unique (%)100.0%

Sample

1st row3410000-206-1998-00004
2nd row3410000-206-2012-00005
3rd row3410000-206-2003-00006
4th row3410000-206-2004-00009
5th row3410000-206-2014-00004
ValueCountFrequency (%)
3410000-206-1998-00004 1
 
0.1%
3460000-206-2006-00003 1
 
0.1%
3460000-206-2004-00021 1
 
0.1%
3460000-206-2007-00002 1
 
0.1%
3460000-206-2007-00004 1
 
0.1%
3460000-206-2015-00003 1
 
0.1%
3460000-206-2017-00008 1
 
0.1%
3460000-206-2010-00018 1
 
0.1%
3460000-206-2018-00001 1
 
0.1%
3460000-206-2008-00001 1
 
0.1%
Other values (1696) 1696
99.4%
2024-04-18T09:18:20.189868image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 17559
46.8%
- 5118
 
13.6%
2 4041
 
10.8%
6 2349
 
6.3%
3 2258
 
6.0%
4 2245
 
6.0%
1 1861
 
5.0%
7 646
 
1.7%
9 582
 
1.6%
5 487
 
1.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 32414
86.4%
Dash Punctuation 5118
 
13.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 17559
54.2%
2 4041
 
12.5%
6 2349
 
7.2%
3 2258
 
7.0%
4 2245
 
6.9%
1 1861
 
5.7%
7 646
 
2.0%
9 582
 
1.8%
5 487
 
1.5%
8 386
 
1.2%
Dash Punctuation
ValueCountFrequency (%)
- 5118
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 37532
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 17559
46.8%
- 5118
 
13.6%
2 4041
 
10.8%
6 2349
 
6.3%
3 2258
 
6.0%
4 2245
 
6.0%
1 1861
 
5.0%
7 646
 
1.7%
9 582
 
1.6%
5 487
 
1.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 37532
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 17559
46.8%
- 5118
 
13.6%
2 4041
 
10.8%
6 2349
 
6.3%
3 2258
 
6.0%
4 2245
 
6.0%
1 1861
 
5.0%
7 646
 
1.7%
9 582
 
1.6%
5 487
 
1.3%

인허가일자
Real number (ℝ)

Distinct1316
Distinct (%)77.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20084116
Minimum19821207
Maximum20200827
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size15.1 KiB
2024-04-18T09:18:20.323071image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19821207
5-th percentile19980613
Q120031042
median20081204
Q320131189
95-th percentile20190311
Maximum20200827
Range379620
Interquartile range (IQR)100146.75

Descriptive statistics

Standard deviation64709.574
Coefficient of variation (CV)0.0032219279
Kurtosis-0.56138619
Mean20084116
Median Absolute Deviation (MAD)50079
Skewness-0.15746922
Sum3.4263502 × 1010
Variance4.187329 × 109
MonotonicityNot monotonic
2024-04-18T09:18:20.456294image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20030718 12
 
0.7%
20101013 11
 
0.6%
20121012 7
 
0.4%
20040414 5
 
0.3%
20070323 5
 
0.3%
20110414 5
 
0.3%
20110630 4
 
0.2%
20110609 4
 
0.2%
20081215 4
 
0.2%
20070312 4
 
0.2%
Other values (1306) 1645
96.4%
ValueCountFrequency (%)
19821207 1
0.1%
19871113 1
0.1%
19880114 1
0.1%
19880130 1
0.1%
19900707 1
0.1%
19901024 1
0.1%
19911211 1
0.1%
19920220 1
0.1%
19920611 1
0.1%
19921229 1
0.1%
ValueCountFrequency (%)
20200827 1
0.1%
20200824 1
0.1%
20200819 1
0.1%
20200804 1
0.1%
20200722 1
0.1%
20200721 1
0.1%
20200715 1
0.1%
20200709 1
0.1%
20200623 1
0.1%
20200615 1
0.1%

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1706
Missing (%)100.0%
Memory size15.1 KiB
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size13.5 KiB
3
1168 
1
538 

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 (%)
3 1168
68.5%
1 538
31.5%

Length

2024-04-18T09:18:20.579924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T09:18:20.668666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 1168
68.5%
1 538
31.5%

영업상태명
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size13.5 KiB
폐업
1168 
영업/정상
538 

Length

Max length5
Median length2
Mean length2.9460727
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row영업/정상
2nd row영업/정상
3rd row영업/정상
4th row영업/정상
5th row영업/정상

Common Values

ValueCountFrequency (%)
폐업 1168
68.5%
영업/정상 538
31.5%

Length

2024-04-18T09:18:20.767303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T09:18:20.861293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 1168
68.5%
영업/정상 538
31.5%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size13.5 KiB
2
1168 
1
538 

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 (%)
2 1168
68.5%
1 538
31.5%

Length

2024-04-18T09:18:20.956311image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T09:18:21.046943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 1168
68.5%
1 538
31.5%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size13.5 KiB
폐업
1168 
영업
538 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 1168
68.5%
영업 538
31.5%

Length

2024-04-18T09:18:21.158130image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T09:18:21.262455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 1168
68.5%
영업 538
31.5%

폐업일자
Real number (ℝ)

MISSING 

Distinct873
Distinct (%)74.8%
Missing539
Missing (%)31.6%
Infinite0
Infinite (%)0.0%
Mean20113910
Minimum20000720
Maximum20200827
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size15.1 KiB
2024-04-18T09:18:21.371944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20000720
5-th percentile20031009
Q120060566
median20111213
Q320161227
95-th percentile20191220
Maximum20200827
Range200107
Interquartile range (IQR)100660.5

Descriptive statistics

Standard deviation55795.846
Coefficient of variation (CV)0.002773993
Kurtosis-1.3455995
Mean20113910
Median Absolute Deviation (MAD)50499
Skewness-0.053206279
Sum2.3472933 × 1010
Variance3.1131764 × 109
MonotonicityNot monotonic
2024-04-18T09:18:21.515643image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20031231 12
 
0.7%
20031128 11
 
0.6%
20031230 10
 
0.6%
20030929 8
 
0.5%
20040417 8
 
0.5%
20180625 8
 
0.5%
20050114 7
 
0.4%
20090108 7
 
0.4%
20030930 7
 
0.4%
20031229 6
 
0.4%
Other values (863) 1083
63.5%
(Missing) 539
31.6%
ValueCountFrequency (%)
20000720 1
0.1%
20020121 2
0.1%
20020430 1
0.1%
20020810 1
0.1%
20020819 1
0.1%
20020823 1
0.1%
20020826 1
0.1%
20020828 1
0.1%
20020924 1
0.1%
20021019 1
0.1%
ValueCountFrequency (%)
20200827 1
0.1%
20200820 1
0.1%
20200818 1
0.1%
20200812 1
0.1%
20200810 1
0.1%
20200731 2
0.1%
20200730 2
0.1%
20200729 2
0.1%
20200714 1
0.1%
20200622 2
0.1%

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1706
Missing (%)100.0%
Memory size15.1 KiB

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1706
Missing (%)100.0%
Memory size15.1 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1706
Missing (%)100.0%
Memory size15.1 KiB

소재지전화
Text

MISSING 

Distinct1108
Distinct (%)86.0%
Missing417
Missing (%)24.4%
Memory size13.5 KiB
2024-04-18T09:18:21.804692image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length11.183088
Min length3

Characters and Unicode

Total characters14415
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique966 ?
Unique (%)74.9%

Sample

1st row053 4296199
2nd row053 2524452
3rd row053 5596661
4th row053 2563083
5th row053 2533504
ValueCountFrequency (%)
053 1147
38.4%
744 16
 
0.5%
742 16
 
0.5%
070 13
 
0.4%
745 12
 
0.4%
653 11
 
0.4%
767 10
 
0.3%
746 10
 
0.3%
766 10
 
0.3%
782 9
 
0.3%
Other values (1260) 1733
58.0%
2024-04-18T09:18:22.210086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 2403
16.7%
0 2092
14.5%
3 1960
13.6%
1722
11.9%
6 1090
7.6%
7 1021
7.1%
2 995
6.9%
4 921
 
6.4%
1 824
 
5.7%
8 748
 
5.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 12693
88.1%
Space Separator 1722
 
11.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 2403
18.9%
0 2092
16.5%
3 1960
15.4%
6 1090
8.6%
7 1021
8.0%
2 995
7.8%
4 921
 
7.3%
1 824
 
6.5%
8 748
 
5.9%
9 639
 
5.0%
Space Separator
ValueCountFrequency (%)
1722
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 14415
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 2403
16.7%
0 2092
14.5%
3 1960
13.6%
1722
11.9%
6 1090
7.6%
7 1021
7.1%
2 995
6.9%
4 921
 
6.4%
1 824
 
5.7%
8 748
 
5.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 14415
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 2403
16.7%
0 2092
14.5%
3 1960
13.6%
1722
11.9%
6 1090
7.6%
7 1021
7.1%
2 995
6.9%
4 921
 
6.4%
1 824
 
5.7%
8 748
 
5.2%

소재지면적
Real number (ℝ)

ZEROS 

Distinct1080
Distinct (%)63.5%
Missing5
Missing (%)0.3%
Infinite0
Infinite (%)0.0%
Mean60.88341
Minimum0
Maximum667.39
Zeros160
Zeros (%)9.4%
Negative0
Negative (%)0.0%
Memory size15.1 KiB
2024-04-18T09:18:22.345020image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q125.8
median48.18
Q384.13
95-th percentile160
Maximum667.39
Range667.39
Interquartile range (IQR)58.33

Descriptive statistics

Standard deviation55.264885
Coefficient of variation (CV)0.90771666
Kurtosis15.261608
Mean60.88341
Median Absolute Deviation (MAD)27.66
Skewness2.6251319
Sum103562.68
Variance3054.2076
MonotonicityNot monotonic
2024-04-18T09:18:22.469152image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 160
 
9.4%
33.0 26
 
1.5%
66.0 24
 
1.4%
60.0 20
 
1.2%
30.0 17
 
1.0%
20.0 15
 
0.9%
49.5 14
 
0.8%
35.0 12
 
0.7%
99.0 11
 
0.6%
50.0 11
 
0.6%
Other values (1070) 1391
81.5%
ValueCountFrequency (%)
0.0 160
9.4%
2.64 1
 
0.1%
4.0 1
 
0.1%
5.31 1
 
0.1%
5.4 1
 
0.1%
6.0 1
 
0.1%
6.52 1
 
0.1%
6.68 1
 
0.1%
7.14 1
 
0.1%
7.2 1
 
0.1%
ValueCountFrequency (%)
667.39 1
0.1%
478.4 1
0.1%
459.68 1
0.1%
420.0 1
0.1%
409.0 1
0.1%
384.2 1
0.1%
327.25 1
0.1%
307.0 1
0.1%
300.0 1
0.1%
271.0 1
0.1%

소재지우편번호
Real number (ℝ)

Distinct427
Distinct (%)25.1%
Missing8
Missing (%)0.5%
Infinite0
Infinite (%)0.0%
Mean704315.16
Minimum700010
Maximum711891
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size15.1 KiB
2024-04-18T09:18:22.598244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum700010
5-th percentile700813.85
Q1701857
median704390
Q3705832
95-th percentile706851.15
Maximum711891
Range11881
Interquartile range (IQR)3975

Descriptive statistics

Standard deviation2525.3222
Coefficient of variation (CV)0.0035855003
Kurtosis0.9979033
Mean704315.16
Median Absolute Deviation (MAD)1820
Skewness0.75051613
Sum1.1959271 × 109
Variance6377252.3
MonotonicityNot monotonic
2024-04-18T09:18:22.723342image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
704060 30
 
1.8%
704080 22
 
1.3%
706220 19
 
1.1%
706032 18
 
1.1%
704932 16
 
0.9%
706818 15
 
0.9%
706837 14
 
0.8%
701827 14
 
0.8%
702040 14
 
0.8%
706838 13
 
0.8%
Other values (417) 1523
89.3%
ValueCountFrequency (%)
700010 4
0.2%
700020 3
0.2%
700040 2
 
0.1%
700060 2
 
0.1%
700082 6
0.4%
700092 2
 
0.1%
700111 2
 
0.1%
700112 1
 
0.1%
700113 2
 
0.1%
700150 2
 
0.1%
ValueCountFrequency (%)
711891 1
 
0.1%
711874 2
 
0.1%
711873 2
 
0.1%
711872 2
 
0.1%
711864 8
0.5%
711861 1
 
0.1%
711856 2
 
0.1%
711852 8
0.5%
711850 1
 
0.1%
711845 1
 
0.1%
Distinct1560
Distinct (%)91.5%
Missing1
Missing (%)0.1%
Memory size13.5 KiB
2024-04-18T09:18:23.018547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length51
Median length45
Mean length24.470968
Min length18

Characters and Unicode

Total characters41723
Distinct characters273
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1433 ?
Unique (%)84.0%

Sample

1st row대구광역시 중구 삼덕동2가 0210-0001번지 1503호
2nd row대구광역시 중구 남산동 2466-0092번지 지상1층
3rd row대구광역시 중구 계산동2가 0050번지 외3필지 지상9층
4th row대구광역시 중구 남산동 2482-0458번지
5th row대구광역시 중구 동인동2가 0051번지 화성파크드림시티 402호
ValueCountFrequency (%)
대구광역시 1705
22.3%
달서구 340
 
4.4%
수성구 330
 
4.3%
동구 308
 
4.0%
북구 178
 
2.3%
남구 170
 
2.2%
서구 160
 
2.1%
중구 144
 
1.9%
대명동 113
 
1.5%
달성군 75
 
1.0%
Other values (1932) 4126
53.9%
2024-04-18T09:18:23.468434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
7581
18.2%
3348
 
8.0%
2055
 
4.9%
1 1959
 
4.7%
1910
 
4.6%
1878
 
4.5%
1737
 
4.2%
1707
 
4.1%
1706
 
4.1%
1657
 
4.0%
Other values (263) 16185
38.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 23296
55.8%
Decimal Number 8970
 
21.5%
Space Separator 7581
 
18.2%
Dash Punctuation 1516
 
3.6%
Close Punctuation 156
 
0.4%
Open Punctuation 156
 
0.4%
Uppercase Letter 25
 
0.1%
Other Punctuation 22
 
0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
3348
14.4%
2055
 
8.8%
1910
 
8.2%
1878
 
8.1%
1737
 
7.5%
1707
 
7.3%
1706
 
7.3%
1657
 
7.1%
543
 
2.3%
532
 
2.3%
Other values (238) 6223
26.7%
Decimal Number
ValueCountFrequency (%)
1 1959
21.8%
2 1244
13.9%
0 1134
12.6%
3 958
10.7%
4 731
 
8.1%
5 662
 
7.4%
6 615
 
6.9%
8 582
 
6.5%
7 581
 
6.5%
9 504
 
5.6%
Uppercase Letter
ValueCountFrequency (%)
B 8
32.0%
A 7
28.0%
C 4
16.0%
D 2
 
8.0%
M 1
 
4.0%
R 1
 
4.0%
H 1
 
4.0%
S 1
 
4.0%
Other Punctuation
ValueCountFrequency (%)
, 20
90.9%
. 2
 
9.1%
Space Separator
ValueCountFrequency (%)
7581
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1516
100.0%
Close Punctuation
ValueCountFrequency (%)
) 156
100.0%
Open Punctuation
ValueCountFrequency (%)
( 156
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 23296
55.8%
Common 18402
44.1%
Latin 25
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
3348
14.4%
2055
 
8.8%
1910
 
8.2%
1878
 
8.1%
1737
 
7.5%
1707
 
7.3%
1706
 
7.3%
1657
 
7.1%
543
 
2.3%
532
 
2.3%
Other values (238) 6223
26.7%
Common
ValueCountFrequency (%)
7581
41.2%
1 1959
 
10.6%
- 1516
 
8.2%
2 1244
 
6.8%
0 1134
 
6.2%
3 958
 
5.2%
4 731
 
4.0%
5 662
 
3.6%
6 615
 
3.3%
8 582
 
3.2%
Other values (7) 1420
 
7.7%
Latin
ValueCountFrequency (%)
B 8
32.0%
A 7
28.0%
C 4
16.0%
D 2
 
8.0%
M 1
 
4.0%
R 1
 
4.0%
H 1
 
4.0%
S 1
 
4.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 23296
55.8%
ASCII 18427
44.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
7581
41.1%
1 1959
 
10.6%
- 1516
 
8.2%
2 1244
 
6.8%
0 1134
 
6.2%
3 958
 
5.2%
4 731
 
4.0%
5 662
 
3.6%
6 615
 
3.3%
8 582
 
3.2%
Other values (15) 1445
 
7.8%
Hangul
ValueCountFrequency (%)
3348
14.4%
2055
 
8.8%
1910
 
8.2%
1878
 
8.1%
1737
 
7.5%
1707
 
7.3%
1706
 
7.3%
1657
 
7.1%
543
 
2.3%
532
 
2.3%
Other values (238) 6223
26.7%

도로명전체주소
Text

MISSING 

Distinct1057
Distinct (%)95.1%
Missing595
Missing (%)34.9%
Memory size13.5 KiB
2024-04-18T09:18:23.826975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length53
Median length48
Mean length29.279028
Min length20

Characters and Unicode

Total characters32529
Distinct characters303
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1012 ?
Unique (%)91.1%

Sample

1st row대구광역시 중구 동덕로 115, 1503호 (삼덕동2가, 진석타워)
2nd row대구광역시 중구 남산로13길 9 (남산동, 지상1층)
3rd row대구광역시 중구 서성로 20 (계산동2가, 외3필지 지상9층)
4th row대구광역시 중구 남산로7길 75 (남산동)
5th row대구광역시 중구 국채보상로 655 (동인동2가, 화성파크드림시티 402호)
ValueCountFrequency (%)
대구광역시 1111
 
16.7%
달서구 238
 
3.6%
1층 210
 
3.2%
동구 199
 
3.0%
수성구 199
 
3.0%
2층 178
 
2.7%
남구 120
 
1.8%
북구 109
 
1.6%
중구 96
 
1.4%
서구 91
 
1.4%
Other values (1510) 4083
61.5%
2024-04-18T09:18:24.342683image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5523
 
17.0%
2307
 
7.1%
1499
 
4.6%
1433
 
4.4%
1 1260
 
3.9%
1149
 
3.5%
1115
 
3.4%
( 1114
 
3.4%
) 1114
 
3.4%
1114
 
3.4%
Other values (293) 14901
45.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 18357
56.4%
Space Separator 5523
 
17.0%
Decimal Number 5276
 
16.2%
Open Punctuation 1114
 
3.4%
Close Punctuation 1114
 
3.4%
Other Punctuation 904
 
2.8%
Dash Punctuation 210
 
0.6%
Uppercase Letter 29
 
0.1%
Math Symbol 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
2307
 
12.6%
1499
 
8.2%
1433
 
7.8%
1149
 
6.3%
1115
 
6.1%
1114
 
6.1%
1074
 
5.9%
733
 
4.0%
571
 
3.1%
433
 
2.4%
Other values (268) 6929
37.7%
Decimal Number
ValueCountFrequency (%)
1 1260
23.9%
2 942
17.9%
3 636
12.1%
4 459
 
8.7%
0 424
 
8.0%
5 391
 
7.4%
6 345
 
6.5%
7 344
 
6.5%
8 252
 
4.8%
9 223
 
4.2%
Uppercase Letter
ValueCountFrequency (%)
A 11
37.9%
B 7
24.1%
C 5
17.2%
R 2
 
6.9%
D 2
 
6.9%
M 1
 
3.4%
H 1
 
3.4%
Other Punctuation
ValueCountFrequency (%)
, 902
99.8%
. 1
 
0.1%
· 1
 
0.1%
Space Separator
ValueCountFrequency (%)
5523
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1114
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1114
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 210
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 18357
56.4%
Common 14143
43.5%
Latin 29
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
2307
 
12.6%
1499
 
8.2%
1433
 
7.8%
1149
 
6.3%
1115
 
6.1%
1114
 
6.1%
1074
 
5.9%
733
 
4.0%
571
 
3.1%
433
 
2.4%
Other values (268) 6929
37.7%
Common
ValueCountFrequency (%)
5523
39.1%
1 1260
 
8.9%
( 1114
 
7.9%
) 1114
 
7.9%
2 942
 
6.7%
, 902
 
6.4%
3 636
 
4.5%
4 459
 
3.2%
0 424
 
3.0%
5 391
 
2.8%
Other values (8) 1378
 
9.7%
Latin
ValueCountFrequency (%)
A 11
37.9%
B 7
24.1%
C 5
17.2%
R 2
 
6.9%
D 2
 
6.9%
M 1
 
3.4%
H 1
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 18357
56.4%
ASCII 14171
43.6%
None 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5523
39.0%
1 1260
 
8.9%
( 1114
 
7.9%
) 1114
 
7.9%
2 942
 
6.6%
, 902
 
6.4%
3 636
 
4.5%
4 459
 
3.2%
0 424
 
3.0%
5 391
 
2.8%
Other values (14) 1406
 
9.9%
Hangul
ValueCountFrequency (%)
2307
 
12.6%
1499
 
8.2%
1433
 
7.8%
1149
 
6.3%
1115
 
6.1%
1114
 
6.1%
1074
 
5.9%
733
 
4.0%
571
 
3.1%
433
 
2.4%
Other values (268) 6929
37.7%
None
ValueCountFrequency (%)
· 1
100.0%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct574
Distinct (%)52.0%
Missing603
Missing (%)35.3%
Infinite0
Infinite (%)0.0%
Mean42061.879
Minimum41017
Maximum43023
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size15.1 KiB
2024-04-18T09:18:25.158051image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum41017
5-th percentile41111.1
Q141569.5
median42117
Q342615.5
95-th percentile42914
Maximum43023
Range2006
Interquartile range (IQR)1046

Descriptive statistics

Standard deviation577.90159
Coefficient of variation (CV)0.013739319
Kurtosis-1.1336835
Mean42061.879
Median Absolute Deviation (MAD)521
Skewness-0.22783296
Sum46394253
Variance333970.24
MonotonicityNot monotonic
2024-04-18T09:18:25.313436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
42661 11
 
0.6%
42612 9
 
0.5%
42696 8
 
0.5%
42022 8
 
0.5%
42664 8
 
0.5%
42132 7
 
0.4%
42733 7
 
0.4%
42449 7
 
0.4%
42679 7
 
0.4%
42819 6
 
0.4%
Other values (564) 1025
60.1%
(Missing) 603
35.3%
ValueCountFrequency (%)
41017 2
0.1%
41026 2
0.1%
41029 1
 
0.1%
41033 1
 
0.1%
41034 3
0.2%
41035 1
 
0.1%
41036 3
0.2%
41042 1
 
0.1%
41048 1
 
0.1%
41051 1
 
0.1%
ValueCountFrequency (%)
43023 1
0.1%
43017 2
0.1%
43009 1
0.1%
43004 1
0.1%
43002 1
0.1%
42999 2
0.1%
42998 1
0.1%
42996 1
0.1%
42985 1
0.1%
42981 1
0.1%
Distinct1436
Distinct (%)84.2%
Missing0
Missing (%)0.0%
Memory size13.5 KiB
2024-04-18T09:18:25.569500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length21
Mean length7.2215709
Min length1

Characters and Unicode

Total characters12320
Distinct characters452
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1227 ?
Unique (%)71.9%

Sample

1st row신천종합관리주식회사
2nd row(주)휴마나
3rd row현대티엠에스(주)
4th row대구중구지역자활센터(말끄미청소사업단)
5th row(주)한라비엠
ValueCountFrequency (%)
주식회사 55
 
3.0%
22
 
1.2%
하이캅주식회사 7
 
0.4%
청소박사 7
 
0.4%
대상비에이치 6
 
0.3%
오성씨에스티(주 5
 
0.3%
주)대성티에스 5
 
0.3%
주)상원에스앤씨 5
 
0.3%
현대종합관리 4
 
0.2%
c 4
 
0.2%
Other values (1474) 1739
93.5%
2024-04-18T09:18:25.960624image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
981
 
8.0%
) 896
 
7.3%
( 886
 
7.2%
375
 
3.0%
312
 
2.5%
282
 
2.3%
257
 
2.1%
251
 
2.0%
234
 
1.9%
219
 
1.8%
Other values (442) 7627
61.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 10157
82.4%
Close Punctuation 896
 
7.3%
Open Punctuation 886
 
7.2%
Space Separator 156
 
1.3%
Uppercase Letter 125
 
1.0%
Lowercase Letter 43
 
0.3%
Other Punctuation 40
 
0.3%
Decimal Number 12
 
0.1%
Other Symbol 4
 
< 0.1%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
981
 
9.7%
375
 
3.7%
312
 
3.1%
282
 
2.8%
257
 
2.5%
251
 
2.5%
234
 
2.3%
219
 
2.2%
200
 
2.0%
199
 
2.0%
Other values (397) 6847
67.4%
Uppercase Letter
ValueCountFrequency (%)
S 25
20.0%
C 24
19.2%
M 16
12.8%
K 10
 
8.0%
E 9
 
7.2%
T 8
 
6.4%
D 5
 
4.0%
G 5
 
4.0%
H 4
 
3.2%
N 4
 
3.2%
Other values (8) 15
12.0%
Lowercase Letter
ValueCountFrequency (%)
n 6
14.0%
e 6
14.0%
a 5
11.6%
o 5
11.6%
c 5
11.6%
d 3
7.0%
l 3
7.0%
i 2
 
4.7%
h 2
 
4.7%
s 2
 
4.7%
Other values (3) 4
9.3%
Decimal Number
ValueCountFrequency (%)
1 6
50.0%
9 2
 
16.7%
2 1
 
8.3%
5 1
 
8.3%
6 1
 
8.3%
3 1
 
8.3%
Other Punctuation
ValueCountFrequency (%)
. 31
77.5%
& 8
 
20.0%
: 1
 
2.5%
Close Punctuation
ValueCountFrequency (%)
) 896
100.0%
Open Punctuation
ValueCountFrequency (%)
( 886
100.0%
Space Separator
ValueCountFrequency (%)
156
100.0%
Other Symbol
ValueCountFrequency (%)
4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 10161
82.5%
Common 1991
 
16.2%
Latin 168
 
1.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
981
 
9.7%
375
 
3.7%
312
 
3.1%
282
 
2.8%
257
 
2.5%
251
 
2.5%
234
 
2.3%
219
 
2.2%
200
 
2.0%
199
 
2.0%
Other values (398) 6851
67.4%
Latin
ValueCountFrequency (%)
S 25
14.9%
C 24
14.3%
M 16
 
9.5%
K 10
 
6.0%
E 9
 
5.4%
T 8
 
4.8%
n 6
 
3.6%
e 6
 
3.6%
a 5
 
3.0%
o 5
 
3.0%
Other values (21) 54
32.1%
Common
ValueCountFrequency (%)
) 896
45.0%
( 886
44.5%
156
 
7.8%
. 31
 
1.6%
& 8
 
0.4%
1 6
 
0.3%
9 2
 
0.1%
2 1
 
0.1%
5 1
 
0.1%
: 1
 
0.1%
Other values (3) 3
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 10157
82.4%
ASCII 2159
 
17.5%
None 4
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
981
 
9.7%
375
 
3.7%
312
 
3.1%
282
 
2.8%
257
 
2.5%
251
 
2.5%
234
 
2.3%
219
 
2.2%
200
 
2.0%
199
 
2.0%
Other values (397) 6847
67.4%
ASCII
ValueCountFrequency (%)
) 896
41.5%
( 886
41.0%
156
 
7.2%
. 31
 
1.4%
S 25
 
1.2%
C 24
 
1.1%
M 16
 
0.7%
K 10
 
0.5%
E 9
 
0.4%
& 8
 
0.4%
Other values (34) 98
 
4.5%
None
ValueCountFrequency (%)
4
100.0%

최종수정시점
Real number (ℝ)

Distinct1506
Distinct (%)88.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0123064 × 1013
Minimum2.0011006 × 1013
Maximum2.0200827 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size15.1 KiB
2024-04-18T09:18:26.103495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.0011006 × 1013
5-th percentile2.0020819 × 1013
Q12.0070549 × 1013
median2.0130312 × 1013
Q32.018069 × 1013
95-th percentile2.0200409 × 1013
Maximum2.0200827 × 1013
Range1.8982117 × 1011
Interquartile range (IQR)1.1014086 × 1011

Descriptive statistics

Standard deviation6.0773635 × 1010
Coefficient of variation (CV)0.0030200986
Kurtosis-1.2994534
Mean2.0123064 × 1013
Median Absolute Deviation (MAD)5.0717998 × 1010
Skewness-0.32638544
Sum3.4329946 × 1016
Variance3.6934347 × 1021
MonotonicityNot monotonic
2024-04-18T09:18:26.273997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20020412000000 20
 
1.2%
20020816000000 12
 
0.7%
20020411000000 12
 
0.7%
20031202000000 11
 
0.6%
20020814000000 11
 
0.6%
20031210000000 10
 
0.6%
20030930000000 8
 
0.5%
20020829000000 8
 
0.5%
20031001000000 8
 
0.5%
20020404000000 7
 
0.4%
Other values (1496) 1599
93.7%
ValueCountFrequency (%)
20011006000000 2
 
0.1%
20020201000000 3
 
0.2%
20020204000000 6
 
0.4%
20020404000000 7
 
0.4%
20020408000000 2
 
0.1%
20020411000000 12
0.7%
20020412000000 20
1.2%
20020501000000 1
 
0.1%
20020715000000 1
 
0.1%
20020725000000 1
 
0.1%
ValueCountFrequency (%)
20200827172013 1
0.1%
20200827155055 1
0.1%
20200827145032 1
0.1%
20200826152713 1
0.1%
20200826152222 1
0.1%
20200824103342 1
0.1%
20200821175047 1
0.1%
20200820102826 1
0.1%
20200819141423 1
0.1%
20200818173244 1
0.1%
Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size13.5 KiB
I
1333 
U
373 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 1333
78.1%
U 373
 
21.9%

Length

2024-04-18T09:18:26.406984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T09:18:26.503740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 1333
78.1%
u 373
 
21.9%
Distinct273
Distinct (%)16.0%
Missing0
Missing (%)0.0%
Memory size13.5 KiB
Minimum2018-08-31 23:59:59
Maximum2020-08-29 02:40:00
2024-04-18T09:18:26.609973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-18T09:18:26.735867image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size13.5 KiB
건물위생관리업
1694 
건물위생관리업 기타
 
12

Length

Max length10
Median length7
Mean length7.021102
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
건물위생관리업 1694
99.3%
건물위생관리업 기타 12
 
0.7%

Length

2024-04-18T09:18:26.860995image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T09:18:26.964936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
건물위생관리업 1706
99.3%
기타 12
 
0.7%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct1405
Distinct (%)83.6%
Missing26
Missing (%)1.5%
Infinite0
Infinite (%)0.0%
Mean343586.14
Minimum326210.51
Maximum358663.13
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size15.1 KiB
2024-04-18T09:18:27.067432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum326210.51
5-th percentile335568
Q1340224.84
median343784.29
Q3346651.45
95-th percentile353079.73
Maximum358663.13
Range32452.624
Interquartile range (IQR)6426.6046

Descriptive statistics

Standard deviation4838.0198
Coefficient of variation (CV)0.014080951
Kurtosis0.56232444
Mean343586.14
Median Absolute Deviation (MAD)3219.9102
Skewness0.02683448
Sum5.7722472 × 108
Variance23406435
MonotonicityNot monotonic
2024-04-18T09:18:27.201151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
341316.891342 9
 
0.5%
344686.259338 6
 
0.4%
343573.731766 5
 
0.3%
343372.286819 4
 
0.2%
343843.928958 4
 
0.2%
342088.066453 4
 
0.2%
338880.044416 4
 
0.2%
346732.617793 4
 
0.2%
355563.442146 4
 
0.2%
346651.44681 4
 
0.2%
Other values (1395) 1632
95.7%
(Missing) 26
 
1.5%
ValueCountFrequency (%)
326210.511333 1
0.1%
328039.908607 1
0.1%
329304.754444 1
0.1%
329636.455817 1
0.1%
330067.502557 1
0.1%
330158.953163 1
0.1%
330159.609349 1
0.1%
330178.690655 1
0.1%
330191.979801 1
0.1%
330318.772524 1
0.1%
ValueCountFrequency (%)
358663.134909 1
 
0.1%
358037.876254 1
 
0.1%
356519.71742 1
 
0.1%
356484.612255 1
 
0.1%
356361.266528 3
0.2%
356354.352971 1
 
0.1%
356335.999166 1
 
0.1%
356309.882171 1
 
0.1%
356282.048426 1
 
0.1%
356247.145225 1
 
0.1%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct1405
Distinct (%)83.6%
Missing26
Missing (%)1.5%
Infinite0
Infinite (%)0.0%
Mean263203.08
Minimum240434.83
Maximum273573.03
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size15.1 KiB
2024-04-18T09:18:27.337019image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum240434.83
5-th percentile257809.87
Q1261485.73
median263332.03
Q3265097.71
95-th percentile268622.11
Maximum273573.03
Range33138.203
Interquartile range (IQR)3611.9799

Descriptive statistics

Standard deviation3615.3335
Coefficient of variation (CV)0.013735909
Kurtosis6.2761795
Mean263203.08
Median Absolute Deviation (MAD)1790.4653
Skewness-1.1069671
Sum4.4218118 × 108
Variance13070636
MonotonicityNot monotonic
2024-04-18T09:18:27.494398image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
263332.034503 9
 
0.5%
263958.880864 6
 
0.4%
261561.703079 5
 
0.3%
265533.584398 4
 
0.2%
264721.595597 4
 
0.2%
262923.056685 4
 
0.2%
260454.397717 4
 
0.2%
257024.522765 4
 
0.2%
264416.151915 4
 
0.2%
261806.63828 4
 
0.2%
Other values (1395) 1632
95.7%
(Missing) 26
 
1.5%
ValueCountFrequency (%)
240434.828496 1
0.1%
243936.93126 1
0.1%
244266.488939 1
0.1%
244500.705818 1
0.1%
244584.666286 1
0.1%
244592.555106 1
0.1%
244870.803521 1
0.1%
245067.112646 1
0.1%
245077.466013 1
0.1%
245096.11462 2
0.1%
ValueCountFrequency (%)
273573.031508 1
0.1%
273548.124057 2
0.1%
273403.295146 1
0.1%
273399.187427 1
0.1%
273256.398256 1
0.1%
273085.642493 1
0.1%
273071.732817 1
0.1%
272984.209477 1
0.1%
272892.862308 1
0.1%
272889.980552 1
0.1%

위생업태명
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size13.5 KiB
건물위생관리업
1694 
건물위생관리업 기타
 
12

Length

Max length10
Median length7
Mean length7.021102
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
건물위생관리업 1694
99.3%
건물위생관리업 기타 12
 
0.7%

Length

2024-04-18T09:18:27.634816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T09:18:27.738263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
건물위생관리업 1706
99.3%
기타 12
 
0.7%

건물지상층수
Real number (ℝ)

MISSING  ZEROS 

Distinct23
Distinct (%)1.5%
Missing175
Missing (%)10.3%
Infinite0
Infinite (%)0.0%
Mean3.175049
Minimum0
Maximum31
Zeros283
Zeros (%)16.6%
Negative0
Negative (%)0.0%
Memory size15.1 KiB
2024-04-18T09:18:27.827786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q12
median3
Q34
95-th percentile7.5
Maximum31
Range31
Interquartile range (IQR)2

Descriptive statistics

Standard deviation3.2736906
Coefficient of variation (CV)1.0310677
Kurtosis19.089981
Mean3.175049
Median Absolute Deviation (MAD)1
Skewness3.5605846
Sum4861
Variance10.71705
MonotonicityNot monotonic
2024-04-18T09:18:27.936304image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=23)
ValueCountFrequency (%)
3 400
23.4%
0 283
16.6%
4 281
16.5%
2 247
14.5%
5 136
 
8.0%
1 77
 
4.5%
6 23
 
1.3%
15 14
 
0.8%
8 10
 
0.6%
20 10
 
0.6%
Other values (13) 50
 
2.9%
(Missing) 175
10.3%
ValueCountFrequency (%)
0 283
16.6%
1 77
 
4.5%
2 247
14.5%
3 400
23.4%
4 281
16.5%
5 136
 
8.0%
6 23
 
1.3%
7 7
 
0.4%
8 10
 
0.6%
9 9
 
0.5%
ValueCountFrequency (%)
31 2
 
0.1%
29 1
 
0.1%
26 1
 
0.1%
23 1
 
0.1%
21 5
 
0.3%
20 10
0.6%
16 1
 
0.1%
15 14
0.8%
14 5
 
0.3%
13 1
 
0.1%

건물지하층수
Real number (ℝ)

MISSING  ZEROS 

Distinct9
Distinct (%)0.7%
Missing348
Missing (%)20.4%
Infinite0
Infinite (%)0.0%
Mean0.6089838
Minimum0
Maximum9
Zeros716
Zeros (%)42.0%
Negative0
Negative (%)0.0%
Memory size15.1 KiB
2024-04-18T09:18:28.037775image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile2
Maximum9
Range9
Interquartile range (IQR)1

Descriptive statistics

Standard deviation0.94948708
Coefficient of variation (CV)1.5591336
Kurtosis18.984286
Mean0.6089838
Median Absolute Deviation (MAD)0
Skewness3.6325471
Sum827
Variance0.90152572
MonotonicityNot monotonic
2024-04-18T09:18:28.132446image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
0 716
42.0%
1 569
33.4%
2 36
 
2.1%
6 18
 
1.1%
3 9
 
0.5%
4 5
 
0.3%
5 3
 
0.2%
9 1
 
0.1%
7 1
 
0.1%
(Missing) 348
20.4%
ValueCountFrequency (%)
0 716
42.0%
1 569
33.4%
2 36
 
2.1%
3 9
 
0.5%
4 5
 
0.3%
5 3
 
0.2%
6 18
 
1.1%
7 1
 
0.1%
9 1
 
0.1%
ValueCountFrequency (%)
9 1
 
0.1%
7 1
 
0.1%
6 18
 
1.1%
5 3
 
0.2%
4 5
 
0.3%
3 9
 
0.5%
2 36
 
2.1%
1 569
33.4%
0 716
42.0%

사용시작지상층
Real number (ℝ)

MISSING  ZEROS 

Distinct20
Distinct (%)1.4%
Missing261
Missing (%)15.3%
Infinite0
Infinite (%)0.0%
Mean2.0560554
Minimum0
Maximum21
Zeros164
Zeros (%)9.6%
Negative0
Negative (%)0.0%
Memory size15.1 KiB
2024-04-18T09:18:28.233557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median2
Q33
95-th percentile5
Maximum21
Range21
Interquartile range (IQR)2

Descriptive statistics

Standard deviation2.1217218
Coefficient of variation (CV)1.0319381
Kurtosis22.67058
Mean2.0560554
Median Absolute Deviation (MAD)1
Skewness3.8707101
Sum2971
Variance4.5017033
MonotonicityNot monotonic
2024-04-18T09:18:28.340287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
1 517
30.3%
2 381
22.3%
3 206
 
12.1%
0 164
 
9.6%
4 85
 
5.0%
5 42
 
2.5%
7 8
 
0.5%
6 7
 
0.4%
9 6
 
0.4%
8 5
 
0.3%
Other values (10) 24
 
1.4%
(Missing) 261
15.3%
ValueCountFrequency (%)
0 164
 
9.6%
1 517
30.3%
2 381
22.3%
3 206
 
12.1%
4 85
 
5.0%
5 42
 
2.5%
6 7
 
0.4%
7 8
 
0.5%
8 5
 
0.3%
9 6
 
0.4%
ValueCountFrequency (%)
21 1
 
0.1%
20 1
 
0.1%
19 2
 
0.1%
17 1
 
0.1%
16 1
 
0.1%
15 2
 
0.1%
14 4
0.2%
13 3
0.2%
11 5
0.3%
10 4
0.2%

사용끝지상층
Real number (ℝ)

MISSING  ZEROS 

Distinct20
Distinct (%)1.5%
Missing396
Missing (%)23.2%
Infinite0
Infinite (%)0.0%
Mean2.151145
Minimum0
Maximum21
Zeros102
Zeros (%)6.0%
Negative0
Negative (%)0.0%
Memory size15.1 KiB
2024-04-18T09:18:28.443937image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median2
Q33
95-th percentile5
Maximum21
Range21
Interquartile range (IQR)2

Descriptive statistics

Standard deviation2.1487953
Coefficient of variation (CV)0.99890766
Kurtosis22.992574
Mean2.151145
Median Absolute Deviation (MAD)1
Skewness3.960848
Sum2818
Variance4.6173211
MonotonicityNot monotonic
2024-04-18T09:18:28.542836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=20)
ValueCountFrequency (%)
1 486
28.5%
2 354
20.8%
3 200
11.7%
0 102
 
6.0%
4 82
 
4.8%
5 38
 
2.2%
7 8
 
0.5%
6 7
 
0.4%
8 5
 
0.3%
11 5
 
0.3%
Other values (10) 23
 
1.3%
(Missing) 396
23.2%
ValueCountFrequency (%)
0 102
 
6.0%
1 486
28.5%
2 354
20.8%
3 200
11.7%
4 82
 
4.8%
5 38
 
2.2%
6 7
 
0.4%
7 8
 
0.5%
8 5
 
0.3%
9 4
 
0.2%
ValueCountFrequency (%)
21 1
 
0.1%
20 1
 
0.1%
19 2
 
0.1%
17 1
 
0.1%
16 1
 
0.1%
15 2
 
0.1%
14 4
0.2%
13 3
0.2%
11 5
0.3%
10 4
0.2%
Distinct4
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size13.5 KiB
0
987 
<NA>
653 
1
 
65
6
 
1

Length

Max length4
Median length1
Mean length2.1483001
Min length1

Unique

Unique1 ?
Unique (%)0.1%

Sample

1st row0
2nd row0
3rd row0
4th row<NA>
5th row0

Common Values

ValueCountFrequency (%)
0 987
57.9%
<NA> 653
38.3%
1 65
 
3.8%
6 1
 
0.1%

Length

2024-04-18T09:18:28.652972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T09:18:28.749742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 987
57.9%
na 653
38.3%
1 65
 
3.8%
6 1
 
0.1%
Distinct4
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size13.5 KiB
0
860 
<NA>
786 
1
 
59
6
 
1

Length

Max length4
Median length1
Mean length2.3821805
Min length1

Unique

Unique1 ?
Unique (%)0.1%

Sample

1st row0
2nd row0
3rd row0
4th row<NA>
5th row0

Common Values

ValueCountFrequency (%)
0 860
50.4%
<NA> 786
46.1%
1 59
 
3.5%
6 1
 
0.1%

Length

2024-04-18T09:18:28.851395image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T09:18:28.963344image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 860
50.4%
na 786
46.1%
1 59
 
3.5%
6 1
 
0.1%

한실수
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size13.5 KiB
0
1192 
<NA>
514 

Length

Max length4
Median length1
Mean length1.9038687
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row<NA>
5th row0

Common Values

ValueCountFrequency (%)
0 1192
69.9%
<NA> 514
30.1%

Length

2024-04-18T09:18:29.091296image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T09:18:29.191554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1192
69.9%
na 514
30.1%

양실수
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size13.5 KiB
0
1192 
<NA>
514 

Length

Max length4
Median length1
Mean length1.9038687
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row<NA>
5th row0

Common Values

ValueCountFrequency (%)
0 1192
69.9%
<NA> 514
30.1%

Length

2024-04-18T09:18:29.293546image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T09:18:29.388503image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1192
69.9%
na 514
30.1%

욕실수
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size13.5 KiB
0
1192 
<NA>
514 

Length

Max length4
Median length1
Mean length1.9038687
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row<NA>
5th row0

Common Values

ValueCountFrequency (%)
0 1192
69.9%
<NA> 514
30.1%

Length

2024-04-18T09:18:29.486917image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T09:18:29.581744image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1192
69.9%
na 514
30.1%

발한실여부
Boolean

CONSTANT  MISSING 

Distinct1
Distinct (%)0.1%
Missing46
Missing (%)2.7%
Memory size3.5 KiB
False
1660 
(Missing)
 
46
ValueCountFrequency (%)
False 1660
97.3%
(Missing) 46
 
2.7%
2024-04-18T09:18:29.659112image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

의자수
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size13.5 KiB
0
1190 
<NA>
509 
3
 
5
4
 
2

Length

Max length4
Median length1
Mean length1.8950762
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row<NA>
5th row0

Common Values

ValueCountFrequency (%)
0 1190
69.8%
<NA> 509
29.8%
3 5
 
0.3%
4 2
 
0.1%

Length

2024-04-18T09:18:29.771011image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T09:18:29.872066image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1190
69.8%
na 509
29.8%
3 5
 
0.3%
4 2
 
0.1%

조건부허가신고사유
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing1705
Missing (%)99.9%
Memory size13.5 KiB
2024-04-18T09:18:30.014050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length37
Median length37
Mean length37
Min length37

Characters and Unicode

Total characters37
Distinct characters23
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row먼지, 일산화탄소, 이산화탄소를 측정하는 측정장비를 갖추지 아니함.
ValueCountFrequency (%)
먼지 1
14.3%
일산화탄소 1
14.3%
이산화탄소를 1
14.3%
측정하는 1
14.3%
측정장비를 1
14.3%
갖추지 1
14.3%
아니함 1
14.3%
2024-04-18T09:18:30.276698image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
6
16.2%
2
 
5.4%
, 2
 
5.4%
2
 
5.4%
2
 
5.4%
2
 
5.4%
2
 
5.4%
2
 
5.4%
2
 
5.4%
2
 
5.4%
Other values (13) 13
35.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 28
75.7%
Space Separator 6
 
16.2%
Other Punctuation 3
 
8.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
2
 
7.1%
2
 
7.1%
2
 
7.1%
2
 
7.1%
2
 
7.1%
2
 
7.1%
2
 
7.1%
2
 
7.1%
1
 
3.6%
1
 
3.6%
Other values (10) 10
35.7%
Other Punctuation
ValueCountFrequency (%)
, 2
66.7%
. 1
33.3%
Space Separator
ValueCountFrequency (%)
6
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 28
75.7%
Common 9
 
24.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
2
 
7.1%
2
 
7.1%
2
 
7.1%
2
 
7.1%
2
 
7.1%
2
 
7.1%
2
 
7.1%
2
 
7.1%
1
 
3.6%
1
 
3.6%
Other values (10) 10
35.7%
Common
ValueCountFrequency (%)
6
66.7%
, 2
 
22.2%
. 1
 
11.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 28
75.7%
ASCII 9
 
24.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
6
66.7%
, 2
 
22.2%
. 1
 
11.1%
Hangul
ValueCountFrequency (%)
2
 
7.1%
2
 
7.1%
2
 
7.1%
2
 
7.1%
2
 
7.1%
2
 
7.1%
2
 
7.1%
2
 
7.1%
1
 
3.6%
1
 
3.6%
Other values (10) 10
35.7%

조건부허가시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1706
Missing (%)100.0%
Memory size15.1 KiB

조건부허가종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing1706
Missing (%)100.0%
Memory size15.1 KiB
Distinct3
Distinct (%)0.2%
Missing0
Missing (%)0.0%
Memory size13.5 KiB
임대
1049 
<NA>
599 
자가
 
58

Length

Max length4
Median length2
Mean length2.7022274
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
임대 1049
61.5%
<NA> 599
35.1%
자가 58
 
3.4%

Length

2024-04-18T09:18:30.411745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T09:18:30.517125image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
임대 1049
61.5%
na 599
35.1%
자가 58
 
3.4%

세탁기수
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size13.5 KiB
0
1057 
<NA>
649 

Length

Max length4
Median length1
Mean length2.1412661
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row<NA>
5th row0

Common Values

ValueCountFrequency (%)
0 1057
62.0%
<NA> 649
38.0%

Length

2024-04-18T09:18:30.616128image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T09:18:30.707459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 1057
62.0%
na 649
38.0%

여성종사자수
Real number (ℝ)

MISSING  ZEROS 

Distinct12
Distinct (%)3.7%
Missing1383
Missing (%)81.1%
Infinite0
Infinite (%)0.0%
Mean1.1795666
Minimum0
Maximum80
Zeros196
Zeros (%)11.5%
Negative0
Negative (%)0.0%
Memory size15.1 KiB
2024-04-18T09:18:30.788378image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q31
95-th percentile2
Maximum80
Range80
Interquartile range (IQR)1

Descriptive statistics

Standard deviation5.816443
Coefficient of variation (CV)4.9310003
Kurtosis128.97759
Mean1.1795666
Median Absolute Deviation (MAD)0
Skewness10.804197
Sum381
Variance33.83101
MonotonicityNot monotonic
2024-04-18T09:18:30.889283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=12)
ValueCountFrequency (%)
0 196
 
11.5%
1 83
 
4.9%
2 29
 
1.7%
3 5
 
0.3%
10 2
 
0.1%
5 2
 
0.1%
80 1
 
0.1%
16 1
 
0.1%
35 1
 
0.1%
4 1
 
0.1%
Other values (2) 2
 
0.1%
(Missing) 1383
81.1%
ValueCountFrequency (%)
0 196
11.5%
1 83
4.9%
2 29
 
1.7%
3 5
 
0.3%
4 1
 
0.1%
5 2
 
0.1%
6 1
 
0.1%
10 2
 
0.1%
16 1
 
0.1%
35 1
 
0.1%
ValueCountFrequency (%)
80 1
 
0.1%
54 1
 
0.1%
35 1
 
0.1%
16 1
 
0.1%
10 2
 
0.1%
6 1
 
0.1%
5 2
 
0.1%
4 1
 
0.1%
3 5
 
0.3%
2 29
1.7%

남성종사자수
Real number (ℝ)

MISSING  ZEROS 

Distinct24
Distinct (%)4.8%
Missing1201
Missing (%)70.4%
Infinite0
Infinite (%)0.0%
Mean4.5623762
Minimum0
Maximum500
Zeros123
Zeros (%)7.2%
Negative0
Negative (%)0.0%
Memory size15.1 KiB
2024-04-18T09:18:31.018745image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q11
median1
Q33
95-th percentile7.8
Maximum500
Range500
Interquartile range (IQR)2

Descriptive statistics

Standard deviation25.779756
Coefficient of variation (CV)5.6505107
Kurtosis278.20836
Mean4.5623762
Median Absolute Deviation (MAD)1
Skewness15.417037
Sum2304
Variance664.5958
MonotonicityNot monotonic
2024-04-18T09:18:31.124594image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=24)
ValueCountFrequency (%)
1 137
 
8.0%
0 123
 
7.2%
2 93
 
5.5%
3 64
 
3.8%
4 28
 
1.6%
5 20
 
1.2%
6 11
 
0.6%
10 6
 
0.4%
8 3
 
0.2%
14 3
 
0.2%
Other values (14) 17
 
1.0%
(Missing) 1201
70.4%
ValueCountFrequency (%)
0 123
7.2%
1 137
8.0%
2 93
5.5%
3 64
3.8%
4 28
 
1.6%
5 20
 
1.2%
6 11
 
0.6%
7 3
 
0.2%
8 3
 
0.2%
9 1
 
0.1%
ValueCountFrequency (%)
500 1
0.1%
180 1
0.1%
149 1
0.1%
105 1
0.1%
104 1
0.1%
67 1
0.1%
56 1
0.1%
53 1
0.1%
40 1
0.1%
35 2
0.1%

회수건조수
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size13.5 KiB
0
956 
<NA>
750 

Length

Max length4
Median length1
Mean length2.3188746
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row<NA>
5th row0

Common Values

ValueCountFrequency (%)
0 956
56.0%
<NA> 750
44.0%

Length

2024-04-18T09:18:31.234813image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T09:18:31.328273image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 956
56.0%
na 750
44.0%

침대수
Categorical

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size13.5 KiB
0
942 
<NA>
764 

Length

Max length4
Median length1
Mean length2.3434936
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row0
2nd row0
3rd row0
4th row<NA>
5th row0

Common Values

ValueCountFrequency (%)
0 942
55.2%
<NA> 764
44.8%

Length

2024-04-18T09:18:31.422879image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T09:18:31.515326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
0 942
55.2%
na 764
44.8%

다중이용업소여부
Boolean

IMBALANCE 

Distinct2
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size1.8 KiB
False
1701 
True
 
5
ValueCountFrequency (%)
False 1701
99.7%
True 5
 
0.3%
2024-04-18T09:18:31.594005image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Sample

번호개방서비스명개방서비스ID개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층한실수양실수욕실수발한실여부의자수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조수침대수다중이용업소여부
01건물위생관리업09_30_04_P34100003410000-206-1998-0000419981211<NA>1영업/정상1영업<NA><NA><NA><NA>053 4296199110.44700412대구광역시 중구 삼덕동2가 0210-0001번지 1503호대구광역시 중구 동덕로 115, 1503호 (삼덕동2가, 진석타워)41940신천종합관리주식회사20190415172901U2019-04-17 02:40:00.0건물위생관리업344686.259338263958.880864건물위생관리업206151500000N0<NA><NA><NA><NA>0<NA><NA>00N
12건물위생관리업09_30_04_P34100003410000-206-2012-0000520120622<NA>1영업/정상1영업<NA><NA><NA><NA>053 252445240.0700837대구광역시 중구 남산동 2466-0092번지 지상1층대구광역시 중구 남산로13길 9 (남산동, 지상1층)41978(주)휴마나20120705090920I2018-08-31 23:59:59.0건물위생관리업342807.803776263521.781179건물위생관리업1021100000N0<NA><NA><NA><NA>0<NA><NA>00N
23건물위생관리업09_30_04_P34100003410000-206-2003-0000620030718<NA>1영업/정상1영업<NA><NA><NA><NA>053 5596661132.0700082대구광역시 중구 계산동2가 0050번지 외3필지 지상9층대구광역시 중구 서성로 20 (계산동2가, 외3필지 지상9층)41933현대티엠에스(주)20120905095042I2018-08-31 23:59:59.0건물위생관리업343307.679331264290.767739건물위생관리업1129900000N0<NA><NA><NA>임대0<NA><NA>00N
34건물위생관리업09_30_04_P34100003410000-206-2004-0000920040812<NA>1영업/정상1영업<NA><NA><NA><NA>053 256308316.49700837대구광역시 중구 남산동 2482-0458번지대구광역시 중구 남산로7길 75 (남산동)41977대구중구지역자활센터(말끄미청소사업단)20120829160956I2018-08-31 23:59:59.0건물위생관리업342565.585038263288.453034건물위생관리업1111<NA><NA><NA><NA><NA>N<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>N
45건물위생관리업09_30_04_P34100003410000-206-2014-0000420140417<NA>1영업/정상1영업<NA><NA><NA><NA>053 253350444.6700842대구광역시 중구 동인동2가 0051번지 화성파크드림시티 402호대구광역시 중구 국채보상로 655 (동인동2가, 화성파크드림시티 402호)41914(주)한라비엠20160322173950I2018-08-31 23:59:59.0건물위생관리업344633.379801264504.727592건물위생관리업2944400000N0<NA><NA><NA><NA>0<NA><NA>00N
56건물위생관리업09_30_04_P34100003410000-206-2007-0000820070828<NA>1영업/정상1영업<NA><NA><NA><NA>053 4220797110.89700845대구광역시 중구 동인동3가 0211-0002번지 지상2층대구광역시 중구 동덕로36길 127, 2층 (동인동3가)41907에스앤티(주)20161102164327I2018-08-31 23:59:59.0건물위생관리업345450.496411264454.150134건물위생관리업312200000N0<NA><NA><NA>임대0<NA><NA>00N
67건물위생관리업09_30_04_P34100003410000-206-2015-0000420150730<NA>1영업/정상1영업<NA><NA><NA><NA>053 525716149.5700840대구광역시 중구 달성동 0121-0004번지 지상3층대구광역시 중구 태평로 17 (달성동, 지상3층)41900주식회사 원 피앤에프20161102163559I2018-08-31 23:59:59.0건물위생관리업342618.637553265366.448074건물위생관리업313300000N0<NA><NA><NA><NA>0<NA><NA>00N
78건물위생관리업09_30_04_P34100003410000-206-2007-0000520070625<NA>1영업/정상1영업<NA><NA><NA><NA>053 253254676.98700850대구광역시 중구 수창동 0101-0011번지대구광역시 중구 서성로 81 (수창동)41920(주)대경티엠에스20180725122446I2018-08-31 23:59:59.0건물위생관리업343279.67038264919.667698건물위생관리업5333<NA><NA><NA><NA><NA>N<NA><NA><NA><NA>임대<NA><NA><NA><NA><NA>N
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번호개방서비스명개방서비스ID개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)위생업태명건물지상층수건물지하층수사용시작지상층사용끝지상층사용시작지하층사용끝지하층한실수양실수욕실수발한실여부의자수조건부허가신고사유조건부허가시작일자조건부허가종료일자건물소유구분명세탁기수여성종사자수남성종사자수회수건조수침대수다중이용업소여부
16961697건물위생관리업09_30_04_P34800003480000-206-2018-0000520180723<NA>1영업/정상1영업<NA><NA><NA><NA>053 638 1938204.83<NA>대구광역시 달성군 현풍읍 중리 497-2번지 5층 401호대구광역시 달성군 현풍읍 테크노상업로 30, 5층 401호43017주)엠허브서비스20190621104336U2019-06-23 02:40:00.0건물위생관리업331393.936784244500.705818건물위생관리업915500000N0<NA><NA><NA>자가03<NA>00N
16971698건물위생관리업09_30_04_P34800003480000-206-2016-0000320160504<NA>1영업/정상1영업<NA><NA><NA><NA>053 644 508730.33711836대구광역시 달성군 화원읍 천내리 761-13번지 외1필지대구광역시 달성군 화원읍 인흥길 5942961알밤플러스크리닝20160517085523I2018-08-31 23:59:59.0건물위생관리업335633.424472256579.857678건물위생관리업001100000N0<NA><NA><NA><NA>00000N
16981699건물위생관리업09_30_04_P34800003480000-206-2014-0000620140717<NA>1영업/정상1영업<NA><NA><NA><NA>053 744 130530.43<NA>대구광역시 달성군 현풍읍 부리 440번지대구광역시 달성군 현풍읍 현풍중앙로16길 1442999(주)세현솔루션20181231102711U2019-01-02 02:40:00.0건물위생관리업330567.11783245096.11462건물위생관리업000000000N0<NA><NA><NA><NA>0<NA><NA>00N
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17001701건물위생관리업09_30_04_P34800003480000-206-2016-0000520161114<NA>1영업/정상1영업<NA><NA><NA><NA>053 616 342734.93711843대구광역시 달성군 옥포면 기세리 268-3번지 3층대구광역시 달성군 옥포면 비슬로 2280, 3층42972(주)양지건설20161124164743I2018-08-31 23:59:59.0건물위생관리업332880.580406255431.094349건물위생관리업000000000N0<NA><NA><NA><NA>0<NA><NA>00N
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17021703건물위생관리업09_30_04_P34800003480000-206-2010-0000620100311<NA>1영업/정상1영업<NA><NA><NA><NA>053 622 748233.0711834대구광역시 달성군 화원읍 천내리 117번지 천내보성타운 108동 202호대구광역시 달성군 화원읍 화원로 37, 108동 202호 (천내보성타운)42948(주)원창20170320103110I2018-08-31 23:59:59.0건물위생관리업335323.131874257420.542234건물위생관리업31<NA><NA>11000N0<NA><NA><NA>임대0<NA><NA>00N
17031704건물위생관리업09_30_04_P34800003480000-206-2017-0000320171110<NA>1영업/정상1영업<NA><NA><NA><NA>053 765 748425.92711832대구광역시 달성군 화원읍 명곡리 138번지 명곡미래빌4단지대구광역시 달성군 화원읍 화암로 88, 상가동 207호42959주식회사 와이엔티20180313102041I2018-08-31 23:59:59.0건물위생관리업335371.838542256357.152972건물위생관리업202200000N0<NA><NA><NA><NA>0<NA><NA>00N
17041705건물위생관리업09_30_04_P34800003480000-206-2015-0000220150126<NA>1영업/정상1영업<NA><NA><NA><NA><NA>13.23711864대구광역시 달성군 가창면 용계리 565-44번지대구광역시 달성군 가창면 가창로220길 2142934양지산업(주)20150205210943I2018-08-31 23:59:59.0건물위생관리업346732.617793257024.522765건물위생관리업003300000N0<NA><NA><NA>임대00000N
17051706건물위생관리업09_30_04_P34800003480000-206-2015-0000320150619<NA>1영업/정상1영업<NA><NA><NA><NA>053 644 867835.24711834대구광역시 달성군 화원읍 천내리 238-7번지대구광역시 달성군 화원읍 성천로26길 4142954(주)에스디산업개발20190110103414U2019-01-12 02:40:00.0건물위생관리업335197.014546257174.059183건물위생관리업004400000N0<NA><NA><NA>임대00000N