Overview

Dataset statistics

Number of variables34
Number of observations152
Missing cells1452
Missing cells (%)28.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory43.5 KiB
Average record size in memory292.9 B

Variable types

Numeric11
Categorical11
Unsupported7
Text4
DateTime1

Dataset

Description6270000_대구광역시_09_30_05_P_건설폐기물처리업_9월
Author대구광역시
URLhttp://data.daegu.go.kr/open/data/dataView.do?dataSetId=DMI_0000086183&dataSetDetailId=DDI_0000086208&provdMethod=FILE

Alerts

개방서비스명 has constant value ""Constant
개방서비스ID has constant value ""Constant
환경업무구분명 has constant value ""Constant
휴업시작일자 is highly imbalanced (92.8%)Imbalance
폐기물처리업구분명 is highly imbalanced (69.9%)Imbalance
폐기물구분명 is highly imbalanced (58.9%)Imbalance
인허가취소일자 has 152 (100.0%) missing valuesMissing
폐업일자 has 89 (58.6%) missing valuesMissing
휴업종료일자 has 152 (100.0%) missing valuesMissing
재개업일자 has 152 (100.0%) missing valuesMissing
소재지전화 has 36 (23.7%) missing valuesMissing
소재지면적 has 152 (100.0%) missing valuesMissing
소재지우편번호 has 51 (33.6%) missing valuesMissing
소재지전체주소 has 16 (10.5%) missing valuesMissing
도로명전체주소 has 19 (12.5%) missing valuesMissing
도로명우편번호 has 72 (47.4%) missing valuesMissing
업태구분명 has 152 (100.0%) missing valuesMissing
좌표정보(X) has 11 (7.2%) missing valuesMissing
좌표정보(Y) has 11 (7.2%) missing valuesMissing
폐기물처리업별처리구분명 has 152 (100.0%) missing valuesMissing
허용보관량 has 82 (53.9%) missing valuesMissing
허용보관량내용 has 152 (100.0%) missing valuesMissing
번호 has unique valuesUnique
관리번호 has unique valuesUnique
인허가취소일자 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
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
폐기물처리업별처리구분명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
허용보관량내용 is an unsupported type, check if it needs cleaning or further analysisUnsupported
허용보관량 has 65 (42.8%) zerosZeros

Reproduction

Analysis started2023-12-10 20:20:45.617127
Analysis finished2023-12-10 20:20:46.626065
Duration1.01 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct152
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean76.5
Minimum1
Maximum152
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2023-12-11T05:20:46.781466image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile8.55
Q138.75
median76.5
Q3114.25
95-th percentile144.45
Maximum152
Range151
Interquartile range (IQR)75.5

Descriptive statistics

Standard deviation44.022721
Coefficient of variation (CV)0.57546041
Kurtosis-1.2
Mean76.5
Median Absolute Deviation (MAD)38
Skewness0
Sum11628
Variance1938
MonotonicityStrictly increasing
2023-12-11T05:20:47.023832image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.7%
106 1
 
0.7%
99 1
 
0.7%
100 1
 
0.7%
101 1
 
0.7%
102 1
 
0.7%
103 1
 
0.7%
104 1
 
0.7%
105 1
 
0.7%
107 1
 
0.7%
Other values (142) 142
93.4%
ValueCountFrequency (%)
1 1
0.7%
2 1
0.7%
3 1
0.7%
4 1
0.7%
5 1
0.7%
6 1
0.7%
7 1
0.7%
8 1
0.7%
9 1
0.7%
10 1
0.7%
ValueCountFrequency (%)
152 1
0.7%
151 1
0.7%
150 1
0.7%
149 1
0.7%
148 1
0.7%
147 1
0.7%
146 1
0.7%
145 1
0.7%
144 1
0.7%
143 1
0.7%

개방서비스명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
건설폐기물처리업
152 

Length

Max length8
Median length8
Mean length8
Min length8

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
건설폐기물처리업 152
100.0%

Length

2023-12-11T05:20:47.312164image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T05:20:47.535109image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
건설폐기물처리업 152
100.0%

개방서비스ID
Categorical

CONSTANT 

Distinct1
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
09_30_05_P
152 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row09_30_05_P
2nd row09_30_05_P
3rd row09_30_05_P
4th row09_30_05_P
5th row09_30_05_P

Common Values

ValueCountFrequency (%)
09_30_05_P 152
100.0%

Length

2023-12-11T05:20:47.752141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T05:20:47.960490image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
09_30_05_p 152
100.0%

개방자치단체코드
Real number (ℝ)

Distinct8
Distinct (%)5.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3463618.4
Minimum3410000
Maximum3480000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2023-12-11T05:20:48.141357image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3410000
5-th percentile3420000
Q13460000
median3470000
Q33480000
95-th percentile3480000
Maximum3480000
Range70000
Interquartile range (IQR)20000

Descriptive statistics

Standard deviation18143.991
Coefficient of variation (CV)0.0052384499
Kurtosis0.81875895
Mean3463618.4
Median Absolute Deviation (MAD)10000
Skewness-1.3142985
Sum5.2647 × 108
Variance3.2920443 × 108
MonotonicityIncreasing
2023-12-11T05:20:48.355920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
3470000 57
37.5%
3480000 44
28.9%
3450000 14
 
9.2%
3460000 14
 
9.2%
3420000 8
 
5.3%
3430000 8
 
5.3%
3440000 5
 
3.3%
3410000 2
 
1.3%
ValueCountFrequency (%)
3410000 2
 
1.3%
3420000 8
 
5.3%
3430000 8
 
5.3%
3440000 5
 
3.3%
3450000 14
 
9.2%
3460000 14
 
9.2%
3470000 57
37.5%
3480000 44
28.9%
ValueCountFrequency (%)
3480000 44
28.9%
3470000 57
37.5%
3460000 14
 
9.2%
3450000 14
 
9.2%
3440000 5
 
3.3%
3430000 8
 
5.3%
3420000 8
 
5.3%
3410000 2
 
1.3%

관리번호
Real number (ℝ)

UNIQUE 

Distinct152
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.4636193 × 1017
Minimum3.4100009 × 1017
Maximum3.4800009 × 1017
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2023-12-11T05:20:48.599914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.4100009 × 1017
5-th percentile3.4200009 × 1017
Q13.4600009 × 1017
median3.4700009 × 1017
Q33.4800009 × 1017
95-th percentile3.4800009 × 1017
Maximum3.4800009 × 1017
Range7 × 1015
Interquartile range (IQR)2 × 1015

Descriptive statistics

Standard deviation1.8143994 × 1015
Coefficient of variation (CV)0.0052384493
Kurtosis0.81875561
Mean3.4636193 × 1017
Median Absolute Deviation (MAD)1 × 1015
Skewness-1.3142976
Sum-2.6932183 × 1018
Variance3.2920453 × 1030
MonotonicityNot monotonic
2023-12-11T05:20:48.827196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
341000092200100001 1
 
0.7%
347000092200300001 1
 
0.7%
347000092201000002 1
 
0.7%
347000092200900001 1
 
0.7%
347000092200000001 1
 
0.7%
347000092199600002 1
 
0.7%
347000092200400001 1
 
0.7%
347000092200300004 1
 
0.7%
347000092200300003 1
 
0.7%
347000092200200004 1
 
0.7%
Other values (142) 142
93.4%
ValueCountFrequency (%)
341000092200100001 1
0.7%
341000092200700001 1
0.7%
342000092200000081 1
0.7%
342000092200100101 1
0.7%
342000092200900001 1
0.7%
342000092201200001 1
0.7%
342000092201400002 1
0.7%
342000092201600002 1
0.7%
342000092201600003 1
0.7%
342000092202000001 1
0.7%
ValueCountFrequency (%)
348000092202000005 1
0.7%
348000092202000004 1
0.7%
348000092202000003 1
0.7%
348000092202000002 1
0.7%
348000092202000001 1
0.7%
348000092201900002 1
0.7%
348000092201900001 1
0.7%
348000092201800002 1
0.7%
348000092201800001 1
0.7%
348000092201700003 1
0.7%

인허가일자
Real number (ℝ)

Distinct144
Distinct (%)95.4%
Missing1
Missing (%)0.7%
Infinite0
Infinite (%)0.0%
Mean20105060
Minimum19951207
Maximum20200918
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2023-12-11T05:20:49.060146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19951207
5-th percentile19980620
Q120070208
median20101108
Q320160806
95-th percentile20200516
Maximum20200918
Range249711
Interquartile range (IQR)90599

Descriptive statistics

Standard deviation64930.607
Coefficient of variation (CV)0.0032295655
Kurtosis-0.54804846
Mean20105060
Median Absolute Deviation (MAD)49882
Skewness-0.38193117
Sum3.035864 × 109
Variance4.2159837 × 109
MonotonicityNot monotonic
2023-12-11T05:20:49.310024image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20180320 3
 
2.0%
20170727 2
 
1.3%
20200918 2
 
1.3%
20080307 2
 
1.3%
20130213 2
 
1.3%
20061222 2
 
1.3%
20160415 1
 
0.7%
20051212 1
 
0.7%
20020617 1
 
0.7%
20190612 1
 
0.7%
Other values (134) 134
88.2%
ValueCountFrequency (%)
19951207 1
0.7%
19960312 1
0.7%
19960516 1
0.7%
19960629 1
0.7%
19960911 1
0.7%
19961201 1
0.7%
19970220 1
0.7%
19980112 1
0.7%
19981127 1
0.7%
20000119 1
0.7%
ValueCountFrequency (%)
20200918 2
1.3%
20200818 1
0.7%
20200723 1
0.7%
20200624 1
0.7%
20200615 1
0.7%
20200529 1
0.7%
20200519 1
0.7%
20200512 1
0.7%
20200413 1
0.7%
20200319 1
0.7%

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing152
Missing (%)100.0%
Memory size1.5 KiB

영업상태구분코드
Categorical

Distinct4
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
1
88 
3
61 
2
 
2
4
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)0.7%

Sample

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

Common Values

ValueCountFrequency (%)
1 88
57.9%
3 61
40.1%
2 2
 
1.3%
4 1
 
0.7%

Length

2023-12-11T05:20:49.534948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T05:20:49.701641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 88
57.9%
3 61
40.1%
2 2
 
1.3%
4 1
 
0.7%

영업상태명
Categorical

Distinct4
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
영업/정상
88 
폐업
61 
휴업
 
2
취소/말소/만료/정지/중지
 
1

Length

Max length14
Median length5
Mean length3.8157895
Min length2

Unique

Unique1 ?
Unique (%)0.7%

Sample

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

Common Values

ValueCountFrequency (%)
영업/정상 88
57.9%
폐업 61
40.1%
휴업 2
 
1.3%
취소/말소/만료/정지/중지 1
 
0.7%

Length

2023-12-11T05:20:49.889280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T05:20:50.106083image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 88
57.9%
폐업 61
40.1%
휴업 2
 
1.3%
취소/말소/만료/정지/중지 1
 
0.7%

상세영업상태코드
Categorical

Distinct4
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
BBBB
88 
2
61 
1
 
2
4
 
1

Length

Max length4
Median length4
Mean length2.7368421
Min length1

Unique

Unique1 ?
Unique (%)0.7%

Sample

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

Common Values

ValueCountFrequency (%)
BBBB 88
57.9%
2 61
40.1%
1 2
 
1.3%
4 1
 
0.7%

Length

2023-12-11T05:20:50.281136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T05:20:50.450287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
bbbb 88
57.9%
2 61
40.1%
1 2
 
1.3%
4 1
 
0.7%

상세영업상태명
Categorical

Distinct4
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
영업
88 
폐업
61 
휴업
 
2
폐쇄
 
1

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique1 ?
Unique (%)0.7%

Sample

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

Common Values

ValueCountFrequency (%)
영업 88
57.9%
폐업 61
40.1%
휴업 2
 
1.3%
폐쇄 1
 
0.7%

Length

2023-12-11T05:20:50.628287image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T05:20:51.145833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업 88
57.9%
폐업 61
40.1%
휴업 2
 
1.3%
폐쇄 1
 
0.7%

폐업일자
Real number (ℝ)

MISSING 

Distinct57
Distinct (%)90.5%
Missing89
Missing (%)58.6%
Infinite0
Infinite (%)0.0%
Mean20117101
Minimum20001113
Maximum20200519
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2023-12-11T05:20:51.367663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20001113
5-th percentile20020413
Q120085207
median20121126
Q320160205
95-th percentile20190215
Maximum20200519
Range199406
Interquartile range (IQR)74998

Descriptive statistics

Standard deviation51416.112
Coefficient of variation (CV)0.0025558411
Kurtosis-0.55072961
Mean20117101
Median Absolute Deviation (MAD)39079
Skewness-0.44939378
Sum1.2673773 × 109
Variance2.6436165 × 109
MonotonicityNot monotonic
2023-12-11T05:20:51.608861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20160205 7
 
4.6%
20130611 1
 
0.7%
20130710 1
 
0.7%
20020524 1
 
0.7%
20010219 1
 
0.7%
20031016 1
 
0.7%
20070117 1
 
0.7%
20001113 1
 
0.7%
20070130 1
 
0.7%
20100105 1
 
0.7%
Other values (47) 47
30.9%
(Missing) 89
58.6%
ValueCountFrequency (%)
20001113 1
0.7%
20010219 1
0.7%
20010225 1
0.7%
20020401 1
0.7%
20020524 1
0.7%
20031016 1
0.7%
20040621 1
0.7%
20060123 1
0.7%
20070117 1
0.7%
20070119 1
0.7%
ValueCountFrequency (%)
20200519 1
0.7%
20191129 1
0.7%
20190530 1
0.7%
20190226 1
0.7%
20190114 1
0.7%
20181214 1
0.7%
20180713 1
0.7%
20180625 1
0.7%
20170727 1
0.7%
20170418 1
0.7%

휴업시작일자
Categorical

IMBALANCE 

Distinct3
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
<NA>
150 
20200320
 
1
20170206
 
1

Length

Max length8
Median length4
Mean length4.0526316
Min length4

Unique

Unique2 ?
Unique (%)1.3%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 150
98.7%
20200320 1
 
0.7%
20170206 1
 
0.7%

Length

2023-12-11T05:20:51.813895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T05:20:51.972318image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 150
98.7%
20200320 1
 
0.7%
20170206 1
 
0.7%

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing152
Missing (%)100.0%
Memory size1.5 KiB

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing152
Missing (%)100.0%
Memory size1.5 KiB

소재지전화
Text

MISSING 

Distinct97
Distinct (%)83.6%
Missing36
Missing (%)23.7%
Memory size1.3 KiB
2023-12-11T05:20:52.265325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length10.62931
Min length7

Characters and Unicode

Total characters1233
Distinct characters12
Distinct categories3 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique81 ?
Unique (%)69.8%

Sample

1st row4282-720
2nd row2548860
3rd row964-0438
4th row243-9506
5th row0534248271
ValueCountFrequency (%)
053 20
 
14.2%
053-586-3860 3
 
2.1%
053-639-4982 3
 
2.1%
053-583-9122 3
 
2.1%
635 3
 
2.1%
0537920104 2
 
1.4%
053-555-1144 2
 
1.4%
053-939-0011 2
 
1.4%
0536538575 2
 
1.4%
0536547799 2
 
1.4%
Other values (91) 99
70.2%
2023-12-11T05:20:52.821121image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 227
18.4%
0 192
15.6%
3 183
14.8%
6 94
7.6%
- 89
 
7.2%
1 89
 
7.2%
2 73
 
5.9%
4 73
 
5.9%
8 70
 
5.7%
9 66
 
5.4%
Other values (2) 77
 
6.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1119
90.8%
Dash Punctuation 89
 
7.2%
Space Separator 25
 
2.0%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 227
20.3%
0 192
17.2%
3 183
16.4%
6 94
8.4%
1 89
 
8.0%
2 73
 
6.5%
4 73
 
6.5%
8 70
 
6.3%
9 66
 
5.9%
7 52
 
4.6%
Dash Punctuation
ValueCountFrequency (%)
- 89
100.0%
Space Separator
ValueCountFrequency (%)
25
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1233
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 227
18.4%
0 192
15.6%
3 183
14.8%
6 94
7.6%
- 89
 
7.2%
1 89
 
7.2%
2 73
 
5.9%
4 73
 
5.9%
8 70
 
5.7%
9 66
 
5.4%
Other values (2) 77
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1233
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 227
18.4%
0 192
15.6%
3 183
14.8%
6 94
7.6%
- 89
 
7.2%
1 89
 
7.2%
2 73
 
5.9%
4 73
 
5.9%
8 70
 
5.7%
9 66
 
5.4%
Other values (2) 77
 
6.2%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing152
Missing (%)100.0%
Memory size1.5 KiB

소재지우편번호
Real number (ℝ)

MISSING 

Distinct70
Distinct (%)69.3%
Missing51
Missing (%)33.6%
Infinite0
Infinite (%)0.0%
Mean706145.85
Minimum700081
Maximum711893
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2023-12-11T05:20:53.017989image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum700081
5-th percentile701864
Q1704160
median704807
Q3706847
95-th percentile711874
Maximum711893
Range11812
Interquartile range (IQR)2687

Descriptive statistics

Standard deviation3508.5611
Coefficient of variation (CV)0.0049686068
Kurtosis-0.79916494
Mean706145.85
Median Absolute Deviation (MAD)1213
Skewness0.74810229
Sum71320731
Variance12310001
MonotonicityNot monotonic
2023-12-11T05:20:53.217374image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
711834 5
 
3.3%
706020 4
 
2.6%
711874 4
 
2.6%
704390 3
 
2.0%
704180 3
 
2.0%
704807 3
 
2.0%
704160 3
 
2.0%
703090 3
 
2.0%
701807 2
 
1.3%
704400 2
 
1.3%
Other values (60) 69
45.4%
(Missing) 51
33.6%
ValueCountFrequency (%)
700081 1
0.7%
700821 1
0.7%
700823 1
0.7%
701807 2
1.3%
701864 1
0.7%
702020 2
1.3%
702030 1
0.7%
702280 1
0.7%
702800 1
0.7%
702812 1
0.7%
ValueCountFrequency (%)
711893 2
1.3%
711891 1
 
0.7%
711874 4
2.6%
711872 1
 
0.7%
711858 2
1.3%
711857 2
1.3%
711856 1
 
0.7%
711852 1
 
0.7%
711845 1
 
0.7%
711841 1
 
0.7%

소재지전체주소
Text

MISSING 

Distinct122
Distinct (%)89.7%
Missing16
Missing (%)10.5%
Memory size1.3 KiB
2023-12-11T05:20:53.657637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length40
Median length35
Mean length23.794118
Min length18

Characters and Unicode

Total characters3236
Distinct characters124
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique111 ?
Unique (%)81.6%

Sample

1st row대구광역시 중구 봉산동 203-6번지
2nd row대구광역시 중구 동산동 357번지 동산맨션 상가 5호
3rd row대구광역시 동구 용계동 931번지
4th row대구광역시 동구 신암동 116번지 2층
5th row대구광역시 동구 입석동 480-3번지
ValueCountFrequency (%)
대구광역시 136
22.0%
달서구 54
 
8.7%
달성군 36
 
5.8%
수성구 14
 
2.3%
화원읍 12
 
1.9%
북구 11
 
1.8%
천내리 9
 
1.5%
월성동 8
 
1.3%
서구 8
 
1.3%
논공읍 7
 
1.1%
Other values (221) 323
52.3%
2023-12-11T05:20:54.189038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
620
19.2%
구 241
 
7.4%
대 143
 
4.4%
광 136
 
4.2%
역 136
 
4.2%
시 136
 
4.2%
1 128
 
4.0%
지 125
 
3.9%
번 119
 
3.7%
동 111
 
3.4%
Other values (114) 1341
41.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1884
58.2%
Space Separator 620
 
19.2%
Decimal Number 620
 
19.2%
Dash Punctuation 109
 
3.4%
Other Punctuation 1
 
< 0.1%
Open Punctuation 1
 
< 0.1%
Close Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 241
12.8%
대 143
 
7.6%
광 136
 
7.2%
역 136
 
7.2%
시 136
 
7.2%
지 125
 
6.6%
번 119
 
6.3%
동 111
 
5.9%
달 90
 
4.8%
성 67
 
3.6%
Other values (99) 580
30.8%
Decimal Number
ValueCountFrequency (%)
1 128
20.6%
2 95
15.3%
3 63
10.2%
0 53
8.5%
6 53
8.5%
5 51
 
8.2%
4 48
 
7.7%
7 47
 
7.6%
9 46
 
7.4%
8 36
 
5.8%
Space Separator
ValueCountFrequency (%)
620
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 109
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1884
58.2%
Common 1352
41.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 241
12.8%
대 143
 
7.6%
광 136
 
7.2%
역 136
 
7.2%
시 136
 
7.2%
지 125
 
6.6%
번 119
 
6.3%
동 111
 
5.9%
달 90
 
4.8%
성 67
 
3.6%
Other values (99) 580
30.8%
Common
ValueCountFrequency (%)
620
45.9%
1 128
 
9.5%
- 109
 
8.1%
2 95
 
7.0%
3 63
 
4.7%
0 53
 
3.9%
6 53
 
3.9%
5 51
 
3.8%
4 48
 
3.6%
7 47
 
3.5%
Other values (5) 85
 
6.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1884
58.2%
ASCII 1352
41.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
620
45.9%
1 128
 
9.5%
- 109
 
8.1%
2 95
 
7.0%
3 63
 
4.7%
0 53
 
3.9%
6 53
 
3.9%
5 51
 
3.8%
4 48
 
3.6%
7 47
 
3.5%
Other values (5) 85
 
6.3%
Hangul
ValueCountFrequency (%)
구 241
12.8%
대 143
 
7.6%
광 136
 
7.2%
역 136
 
7.2%
시 136
 
7.2%
지 125
 
6.6%
번 119
 
6.3%
동 111
 
5.9%
달 90
 
4.8%
성 67
 
3.6%
Other values (99) 580
30.8%

도로명전체주소
Text

MISSING 

Distinct115
Distinct (%)86.5%
Missing19
Missing (%)12.5%
Memory size1.3 KiB
2023-12-11T05:20:54.522639image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length51
Median length42
Mean length26.616541
Min length20

Characters and Unicode

Total characters3540
Distinct characters162
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

Unique101 ?
Unique (%)75.9%

Sample

1st row대구광역시 중구 명륜로 147 (봉산동)
2nd row대구광역시 중구 달구벌대로 2035, 5호 (동산동,동산맨션 상가)
3rd row대구광역시 동구 동북로 433, 3층 302호 (효목동)
4th row대구광역시 동구 공항로 143 (불로동)
5th row대구광역시 동구 동북로 412, 2층 (신암동)
ValueCountFrequency (%)
대구광역시 133
 
18.4%
달서구 52
 
7.2%
달성군 38
 
5.3%
북구 14
 
1.9%
수성구 11
 
1.5%
화원읍 10
 
1.4%
2층 9
 
1.2%
11 8
 
1.1%
논공읍 8
 
1.1%
월성동 7
 
1.0%
Other values (287) 432
59.8%
2023-12-11T05:20:55.070048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
620
 
17.5%
구 246
 
6.9%
대 153
 
4.3%
역 133
 
3.8%
광 133
 
3.8%
시 133
 
3.8%
1 130
 
3.7%
동 122
 
3.4%
로 122
 
3.4%
달 98
 
2.8%
Other values (152) 1650
46.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2086
58.9%
Space Separator 620
 
17.5%
Decimal Number 563
 
15.9%
Close Punctuation 97
 
2.7%
Open Punctuation 97
 
2.7%
Other Punctuation 45
 
1.3%
Dash Punctuation 31
 
0.9%
Uppercase Letter 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 246
 
11.8%
대 153
 
7.3%
역 133
 
6.4%
광 133
 
6.4%
시 133
 
6.4%
동 122
 
5.8%
로 122
 
5.8%
달 98
 
4.7%
서 81
 
3.9%
성 75
 
3.6%
Other values (136) 790
37.9%
Decimal Number
ValueCountFrequency (%)
1 130
23.1%
2 89
15.8%
0 60
10.7%
6 51
 
9.1%
4 48
 
8.5%
3 47
 
8.3%
9 42
 
7.5%
5 37
 
6.6%
7 35
 
6.2%
8 24
 
4.3%
Space Separator
ValueCountFrequency (%)
620
100.0%
Close Punctuation
ValueCountFrequency (%)
) 97
100.0%
Open Punctuation
ValueCountFrequency (%)
( 97
100.0%
Other Punctuation
ValueCountFrequency (%)
, 45
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 31
100.0%
Uppercase Letter
ValueCountFrequency (%)
A 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2086
58.9%
Common 1453
41.0%
Latin 1
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 246
 
11.8%
대 153
 
7.3%
역 133
 
6.4%
광 133
 
6.4%
시 133
 
6.4%
동 122
 
5.8%
로 122
 
5.8%
달 98
 
4.7%
서 81
 
3.9%
성 75
 
3.6%
Other values (136) 790
37.9%
Common
ValueCountFrequency (%)
620
42.7%
1 130
 
8.9%
) 97
 
6.7%
( 97
 
6.7%
2 89
 
6.1%
0 60
 
4.1%
6 51
 
3.5%
4 48
 
3.3%
3 47
 
3.2%
, 45
 
3.1%
Other values (5) 169
 
11.6%
Latin
ValueCountFrequency (%)
A 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2086
58.9%
ASCII 1454
41.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
620
42.6%
1 130
 
8.9%
) 97
 
6.7%
( 97
 
6.7%
2 89
 
6.1%
0 60
 
4.1%
6 51
 
3.5%
4 48
 
3.3%
3 47
 
3.2%
, 45
 
3.1%
Other values (6) 170
 
11.7%
Hangul
ValueCountFrequency (%)
구 246
 
11.8%
대 153
 
7.3%
역 133
 
6.4%
광 133
 
6.4%
시 133
 
6.4%
동 122
 
5.8%
로 122
 
5.8%
달 98
 
4.7%
서 81
 
3.9%
성 75
 
3.6%
Other values (136) 790
37.9%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct66
Distinct (%)82.5%
Missing72
Missing (%)47.4%
Infinite0
Infinite (%)0.0%
Mean299564.99
Minimum41167
Maximum711874
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2023-12-11T05:20:55.266984image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum41167
5-th percentile41407
Q142697.75
median42971
Q3704390
95-th percentile711821.65
Maximum711874
Range670707
Interquartile range (IQR)661692.25

Descriptive statistics

Standard deviation325269.33
Coefficient of variation (CV)1.0858056
Kurtosis-1.8243642
Mean299564.99
Median Absolute Deviation (MAD)1427.5
Skewness0.47084264
Sum23965199
Variance1.0580014 × 1011
MonotonicityNot monotonic
2023-12-11T05:20:55.427741image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
704390 3
 
2.0%
43002 3
 
2.0%
42723 3
 
2.0%
42900 2
 
1.3%
711834 2
 
1.3%
711813 2
 
1.3%
42713 2
 
1.3%
41407 2
 
1.3%
42946 2
 
1.3%
42974 2
 
1.3%
Other values (56) 57
37.5%
(Missing) 72
47.4%
ValueCountFrequency (%)
41167 1
0.7%
41188 1
0.7%
41201 1
0.7%
41407 2
1.3%
41434 1
0.7%
41465 1
0.7%
41468 1
0.7%
41494 1
0.7%
41593 1
0.7%
41598 1
0.7%
ValueCountFrequency (%)
711874 1
0.7%
711839 1
0.7%
711834 2
1.3%
711821 1
0.7%
711813 2
1.3%
706818 1
0.7%
705815 1
0.7%
705802 1
0.7%
704945 1
0.7%
704940 1
0.7%

사업장명
Text

Distinct127
Distinct (%)83.6%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2023-12-11T05:20:55.749902image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length14
Mean length7.1052632
Min length2

Characters and Unicode

Total characters1080
Distinct characters138
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique108 ?
Unique (%)71.1%

Sample

1st row동보환경
2nd row(주)아울산업
3rd row대경환경(대구)
4th row(주)형우산업
5th row(주)녹색환경산업사
ValueCountFrequency (%)
성실환경 3
 
2.0%
주)태연산업개발 3
 
2.0%
주)정일운수 3
 
2.0%
주)윤성산업개발 3
 
2.0%
주)초성환경 3
 
2.0%
미래골재환경 3
 
2.0%
주)태성환경 2
 
1.3%
안성환경 2
 
1.3%
오성기업(주 2
 
1.3%
주)디앤지산업 2
 
1.3%
Other values (118) 127
83.0%
2023-12-11T05:20:56.192404image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
( 121
 
11.2%
) 121
 
11.2%
주 120
 
11.1%
경 88
 
8.1%
환 81
 
7.5%
업 49
 
4.5%
산 43
 
4.0%
개 25
 
2.3%
성 25
 
2.3%
대 24
 
2.2%
Other values (128) 383
35.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 835
77.3%
Open Punctuation 121
 
11.2%
Close Punctuation 121
 
11.2%
Decimal Number 2
 
0.2%
Space Separator 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 120
 
14.4%
경 88
 
10.5%
환 81
 
9.7%
업 49
 
5.9%
산 43
 
5.1%
개 25
 
3.0%
성 25
 
3.0%
대 24
 
2.9%
발 24
 
2.9%
기 13
 
1.6%
Other values (123) 343
41.1%
Decimal Number
ValueCountFrequency (%)
0 1
50.0%
8 1
50.0%
Open Punctuation
ValueCountFrequency (%)
( 121
100.0%
Close Punctuation
ValueCountFrequency (%)
) 121
100.0%
Space Separator
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 835
77.3%
Common 245
 
22.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 120
 
14.4%
경 88
 
10.5%
환 81
 
9.7%
업 49
 
5.9%
산 43
 
5.1%
개 25
 
3.0%
성 25
 
3.0%
대 24
 
2.9%
발 24
 
2.9%
기 13
 
1.6%
Other values (123) 343
41.1%
Common
ValueCountFrequency (%)
( 121
49.4%
) 121
49.4%
0 1
 
0.4%
8 1
 
0.4%
1
 
0.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 835
77.3%
ASCII 245
 
22.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
( 121
49.4%
) 121
49.4%
0 1
 
0.4%
8 1
 
0.4%
1
 
0.4%
Hangul
ValueCountFrequency (%)
주 120
 
14.4%
경 88
 
10.5%
환 81
 
9.7%
업 49
 
5.9%
산 43
 
5.1%
개 25
 
3.0%
성 25
 
3.0%
대 24
 
2.9%
발 24
 
2.9%
기 13
 
1.6%
Other values (123) 343
41.1%

최종수정시점
Real number (ℝ)

Distinct133
Distinct (%)87.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0151553 × 1013
Minimum2.007063 × 1013
Maximum2.0200923 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2023-12-11T05:20:56.333834image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.007063 × 1013
5-th percentile2.0070714 × 1013
Q12.0100584 × 1013
median2.017072 × 1013
Q32.0200307 × 1013
95-th percentile2.0200819 × 1013
Maximum2.0200923 × 1013
Range1.3029307 × 1011
Interquartile range (IQR)9.9723276 × 1010

Descriptive statistics

Standard deviation4.971405 × 1010
Coefficient of variation (CV)0.0024670084
Kurtosis-1.4098469
Mean2.0151553 × 1013
Median Absolute Deviation (MAD)2.9987026 × 1010
Skewness-0.48579575
Sum3.063036 × 1015
Variance2.4714867 × 1021
MonotonicityNot monotonic
2023-12-11T05:20:56.519681image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20070714122950 12
 
7.9%
20170209102449 3
 
2.0%
20200114131106 2
 
1.3%
20200108132119 2
 
1.3%
20090213120615 2
 
1.3%
20191212160032 2
 
1.3%
20191004104754 2
 
1.3%
20070630104619 2
 
1.3%
20140115155925 1
 
0.7%
20121126113756 1
 
0.7%
Other values (123) 123
80.9%
ValueCountFrequency (%)
20070630104619 2
 
1.3%
20070714112355 1
 
0.7%
20070714114235 1
 
0.7%
20070714122950 12
7.9%
20070723171749 1
 
0.7%
20071005163844 1
 
0.7%
20071119141710 1
 
0.7%
20080114094109 1
 
0.7%
20080131115309 1
 
0.7%
20080131162201 1
 
0.7%
ValueCountFrequency (%)
20200923174804 1
0.7%
20200921130940 1
0.7%
20200918175937 1
0.7%
20200918173113 1
0.7%
20200918141149 1
0.7%
20200916145942 1
0.7%
20200915142252 1
0.7%
20200819203344 1
0.7%
20200818085832 1
0.7%
20200807175754 1
0.7%

데이터갱신구분
Categorical

Distinct2
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
I
90 
U
62 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 90
59.2%
U 62
40.8%

Length

2023-12-11T05:20:56.675629image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T05:20:56.790412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 90
59.2%
u 62
40.8%

데이터갱신일자
Date

Distinct59
Distinct (%)38.8%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
Minimum2018-08-31 23:59:59
Maximum2020-09-25 02:40:00
2023-12-11T05:20:56.900721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T05:20:57.044498image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing152
Missing (%)100.0%
Memory size1.5 KiB

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct117
Distinct (%)83.0%
Missing11
Missing (%)7.2%
Infinite0
Infinite (%)0.0%
Mean338141.67
Minimum325101.68
Maximum354410.5
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2023-12-11T05:20:57.231382image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum325101.68
5-th percentile327795.77
Q1334620.1
median338407.74
Q3340874
95-th percentile348039.79
Maximum354410.5
Range29308.823
Interquartile range (IQR)6253.8958

Descriptive statistics

Standard deviation6276.5029
Coefficient of variation (CV)0.018561755
Kurtosis-0.089596102
Mean338141.67
Median Absolute Deviation (MAD)3667.9366
Skewness0.21572363
Sum47677976
Variance39394489
MonotonicityNot monotonic
2023-12-11T05:20:57.401443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
328862.176441 4
 
2.6%
338879.836201 3
 
2.0%
337269.002487 3
 
2.0%
327795.770757 3
 
2.0%
337011.857233 3
 
2.0%
334962.37345 2
 
1.3%
346764.80045 2
 
1.3%
353654.082315 2
 
1.3%
330182.0 2
 
1.3%
338081.698879 2
 
1.3%
Other values (107) 115
75.7%
(Missing) 11
 
7.2%
ValueCountFrequency (%)
325101.677227 2
1.3%
326499.333064 1
 
0.7%
327674.911105 2
1.3%
327795.770757 3
2.0%
328139.110009 1
 
0.7%
328862.176441 4
2.6%
329045.586204 1
 
0.7%
329152.95659 1
 
0.7%
329535.013237 1
 
0.7%
330182.0 2
1.3%
ValueCountFrequency (%)
354410.500233 1
0.7%
353654.082315 2
1.3%
352172.250469 2
1.3%
349055.228599 1
0.7%
348470.685338 1
0.7%
348039.794138 1
0.7%
347603.532517 1
0.7%
347496.499725 1
0.7%
347299.052395 1
0.7%
347109.805039 1
0.7%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct117
Distinct (%)83.0%
Missing11
Missing (%)7.2%
Infinite0
Infinite (%)0.0%
Mean259852.43
Minimum240460.07
Maximum272458.89
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2023-12-11T05:20:57.547729image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum240460.07
5-th percentile244760.02
Q1257617.06
median261002.98
Q3263655.96
95-th percentile269268.72
Maximum272458.89
Range31998.812
Interquartile range (IQR)6038.9032

Descriptive statistics

Standard deviation6755.6232
Coefficient of variation (CV)0.025997922
Kurtosis0.89064948
Mean259852.43
Median Absolute Deviation (MAD)3009.435
Skewness-1.0443631
Sum36639193
Variance45638445
MonotonicityNot monotonic
2023-12-11T05:20:57.742686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
244760.02006 4
 
2.6%
263629.498799 3
 
2.0%
260035.1324 3
 
2.0%
267967.620941 3
 
2.0%
257993.546136 3
 
2.0%
257180.630289 2
 
1.3%
269292.414577 2
 
1.3%
261706.889393 2
 
1.3%
254471.0 2
 
1.3%
259892.692613 2
 
1.3%
Other values (107) 115
75.7%
(Missing) 11
 
7.2%
ValueCountFrequency (%)
240460.074049 1
 
0.7%
241637.0 1
 
0.7%
241797.125481 2
1.3%
244707.288931 2
1.3%
244760.02006 4
2.6%
244778.070211 1
 
0.7%
246678.337148 1
 
0.7%
246898.793845 1
 
0.7%
248700.52888 1
 
0.7%
248759.697321 1
 
0.7%
ValueCountFrequency (%)
272458.885968 1
 
0.7%
270679.374104 1
 
0.7%
270535.470741 1
 
0.7%
269320.223386 2
1.3%
269292.414577 2
1.3%
269268.723656 1
 
0.7%
268059.947096 1
 
0.7%
268017.488042 1
 
0.7%
267967.620941 3
2.0%
267553.08549 1
 
0.7%

환경업무구분명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
건설폐기물처리업사업계획(허가)신청
152 

Length

Max length18
Median length18
Mean length18
Min length18

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row건설폐기물처리업사업계획(허가)신청
2nd row건설폐기물처리업사업계획(허가)신청
3rd row건설폐기물처리업사업계획(허가)신청
4th row건설폐기물처리업사업계획(허가)신청
5th row건설폐기물처리업사업계획(허가)신청

Common Values

ValueCountFrequency (%)
건설폐기물처리업사업계획(허가)신청 152
100.0%

Length

2023-12-11T05:20:57.935434image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T05:20:58.059710image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
건설폐기물처리업사업계획(허가)신청 152
100.0%

폐기물처리업구분명
Categorical

IMBALANCE 

Distinct3
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
수집운반업(건설폐기물)
140 
<NA>
 
6
중간처분업(건설폐기물)
 
6

Length

Max length12
Median length12
Mean length11.684211
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row수집운반업(건설폐기물)
2nd row수집운반업(건설폐기물)
3rd row수집운반업(건설폐기물)
4th row수집운반업(건설폐기물)
5th row수집운반업(건설폐기물)

Common Values

ValueCountFrequency (%)
수집운반업(건설폐기물) 140
92.1%
<NA> 6
 
3.9%
중간처분업(건설폐기물) 6
 
3.9%

Length

2023-12-11T05:20:58.214939image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T05:20:58.368948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
수집운반업(건설폐기물 140
92.1%
na 6
 
3.9%
중간처분업(건설폐기물 6
 
3.9%

폐기물처리업별처리구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing152
Missing (%)100.0%
Memory size1.5 KiB

폐기물구분명
Categorical

IMBALANCE 

Distinct3
Distinct (%)2.0%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
<NA>
129 
건설폐기물
22 
사업장배출시설계폐기물
 
1

Length

Max length11
Median length4
Mean length4.1907895
Min length4

Unique

Unique1 ?
Unique (%)0.7%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 129
84.9%
건설폐기물 22
 
14.5%
사업장배출시설계폐기물 1
 
0.7%

Length

2023-12-11T05:20:58.580412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T05:20:58.778716image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 129
84.9%
건설폐기물 22
 
14.5%
사업장배출시설계폐기물 1
 
0.7%

허용보관량
Real number (ℝ)

MISSING  ZEROS 

Distinct6
Distinct (%)8.6%
Missing82
Missing (%)53.9%
Infinite0
Infinite (%)0.0%
Mean828.95143
Minimum0
Maximum20179
Zeros65
Zeros (%)42.8%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2023-12-11T05:20:58.926665image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile6137.25
Maximum20179
Range20179
Interquartile range (IQR)0

Descriptive statistics

Standard deviation3483.7389
Coefficient of variation (CV)4.202585
Kurtosis18.425837
Mean828.95143
Median Absolute Deviation (MAD)0
Skewness4.3110444
Sum58026.6
Variance12136437
MonotonicityNot monotonic
2023-12-11T05:20:59.076815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
0.0 65
42.8%
145.0 1
 
0.7%
20179.0 1
 
0.7%
11040.0 1
 
0.7%
14029.0 1
 
0.7%
12633.6 1
 
0.7%
(Missing) 82
53.9%
ValueCountFrequency (%)
0.0 65
42.8%
145.0 1
 
0.7%
11040.0 1
 
0.7%
12633.6 1
 
0.7%
14029.0 1
 
0.7%
20179.0 1
 
0.7%
ValueCountFrequency (%)
20179.0 1
 
0.7%
14029.0 1
 
0.7%
12633.6 1
 
0.7%
11040.0 1
 
0.7%
145.0 1
 
0.7%
0.0 65
42.8%

허용보관량내용
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing152
Missing (%)100.0%
Memory size1.5 KiB

Sample

번호개방서비스명개방서비스ID개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)환경업무구분명폐기물처리업구분명폐기물처리업별처리구분명폐기물구분명허용보관량허용보관량내용
01건설폐기물처리업09_30_05_P341000034100009220010000120090312<NA>3폐업2폐업20090605<NA><NA><NA>4282-720<NA>700823대구광역시 중구 봉산동 203-6번지대구광역시 중구 명륜로 147 (봉산동)700823동보환경20140115155925I2018-08-31 23:59:59.0<NA>344471.970454263440.485006건설폐기물처리업사업계획(허가)신청수집운반업(건설폐기물)<NA><NA>0.0<NA>
12건설폐기물처리업09_30_05_P341000034100009220070000120071005<NA>1영업/정상BBBB영업<NA><NA><NA><NA>2548860<NA>700821대구광역시 중구 동산동 357번지 동산맨션 상가 5호대구광역시 중구 달구벌대로 2035, 5호 (동산동,동산맨션 상가)<NA>(주)아울산업20071005163844I2018-08-31 23:59:59.0<NA>343180.573537264150.016653건설폐기물처리업사업계획(허가)신청수집운반업(건설폐기물)<NA><NA><NA><NA>
23건설폐기물처리업09_30_05_P342000034200009220140000220181214<NA>3폐업2폐업20181214<NA><NA><NA>964-0438<NA><NA>대구광역시 동구 용계동 931번지<NA><NA>대경환경(대구)20200114131106U2020-01-16 02:40:00.0<NA>352172.250469265280.953458건설폐기물처리업사업계획(허가)신청수집운반업(건설폐기물)<NA><NA><NA><NA>
34건설폐기물처리업09_30_05_P342000034200009220160000220200519<NA>3폐업2폐업20200519<NA><NA><NA>243-9506<NA><NA><NA>대구광역시 동구 동북로 433, 3층 302호 (효목동)41167(주)형우산업20200519165557U2020-05-21 02:40:00.0<NA>347496.499725266182.454501건설폐기물처리업사업계획(허가)신청수집운반업(건설폐기물)<NA><NA><NA><NA>
45건설폐기물처리업09_30_05_P342000034200009220090000120100108<NA>1영업/정상BBBB영업<NA><NA><NA><NA>0534248271<NA>701807<NA>대구광역시 동구 공항로 143 (불로동)701807(주)녹색환경산업사20200731141239U2020-08-02 02:40:00.0<NA>347109.805039268017.488042건설폐기물처리업사업계획(허가)신청수집운반업(건설폐기물)<NA><NA>0.0<NA>
56건설폐기물처리업09_30_05_P342000034200009220200000120200529<NA>1영업/정상BBBB영업<NA><NA><NA><NA>053-247-1474<NA><NA>대구광역시 동구 신암동 116번지 2층대구광역시 동구 동북로 412, 2층 (신암동)41188(주)책임산업20200529150610I2020-05-31 00:23:29.0<NA>347299.052395266313.070556건설폐기물처리업사업계획(허가)신청수집운반업(건설폐기물)<NA><NA><NA><NA>
67건설폐기물처리업09_30_05_P342000034200009220120000120120409<NA>1영업/정상BBBB영업<NA><NA><NA><NA><NA><NA>701864대구광역시 동구 입석동 480-3번지대구광역시 동구 입석로3길 50 (입석동)701864거성환경20200519123231I2020-05-21 00:23:19.0<NA>349055.228599267047.886722건설폐기물처리업사업계획(허가)신청수집운반업(건설폐기물)<NA><NA><NA><NA>
78건설폐기물처리업09_30_05_P342000034200009220000008120000324<NA>1영업/정상BBBB영업<NA><NA><NA><NA>964-0438<NA><NA>대구광역시 동구 용계동 931번지<NA><NA>대경환경(대구)20200114131106U2020-01-16 02:40:00.0<NA>352172.250469265280.953458건설폐기물처리업사업계획(허가)신청수집운반업(건설폐기물)<NA><NA><NA><NA>
89건설폐기물처리업09_30_05_P342000034200009220160000320160906<NA>1영업/정상BBBB영업<NA><NA><NA><NA>939-9704<NA><NA>대구광역시 동구 신암동 483-3번지 강남아파트상가 103동 11호대구광역시 동구 신성로 60, 상가103동 1층 11호 (신암동, 강남아파트)41201(주)가야환경20200313103648U2020-03-15 02:40:00.0<NA>345659.732803265550.983713건설폐기물처리업사업계획(허가)신청수집운반업(건설폐기물)<NA><NA><NA><NA>
910건설폐기물처리업09_30_05_P342000034200009220010010120011106<NA>1영업/정상BBBB영업<NA><NA><NA><NA>9836113<NA>701807대구광역시 동구 불로동 941-1<NA><NA>대광환경골재20200916145942U2020-09-18 02:40:00.0<NA>347028.575998268059.947096건설폐기물처리업사업계획(허가)신청수집운반업(건설폐기물)<NA><NA>0.0<NA>
번호개방서비스명개방서비스ID개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)환경업무구분명폐기물처리업구분명폐기물처리업별처리구분명폐기물구분명허용보관량허용보관량내용
142143건설폐기물처리업09_30_05_P348000034800009219970000120160104<NA>1영업/정상BBBB영업<NA><NA><NA><NA>0535527005<NA>711893대구광역시 달성군 구지면 징리 235번지대구광역시 달성군 구지면 구지서로10길 19<NA>대한환경산업(주)20191028094011U2019-10-30 02:40:00.0<NA>325101.677227241797.125481건설폐기물처리업사업계획(허가)신청중간처분업(건설폐기물)<NA><NA>12633.6<NA>
143144건설폐기물처리업09_30_05_P348000034800009220200000520200918<NA>1영업/정상BBBB영업<NA><NA><NA><NA>0536114511<NA><NA>대구광역시 달성군 옥포읍 교항리 2903 601호대구광역시 달성군 옥포읍 돌미상업로1길 13, 6층 601호42974(주)기간20200918175937U2020-09-20 02:40:00.0<NA>330182.0254471.0건설폐기물처리업사업계획(허가)신청수집운반업(건설폐기물)<NA><NA><NA><NA>
144145건설폐기물처리업09_30_05_P348000034800009220200000420200818<NA>1영업/정상BBBB영업<NA><NA><NA><NA>0536371702<NA><NA>대구광역시 달성군 화원읍 천내리 101-2대구광역시 달성군 화원읍 사문진로 409-142948(주)수림운수20200918141149U2020-09-20 02:40:00.0<NA>334962.37345257180.630289건설폐기물처리업사업계획(허가)신청수집운반업(건설폐기물)<NA><NA><NA><NA>
145146건설폐기물처리업09_30_05_P348000034800009220200000320200723<NA>1영업/정상BBBB영업<NA><NA><NA><NA><NA><NA><NA>대구광역시 달성군 현풍읍 원교리 794-2대구광역시 달성군 현풍읍 현풍서로 12243002(주)월드환경개발20200723161828I2020-07-25 00:23:15.0<NA>328862.176441244760.02006건설폐기물처리업사업계획(허가)신청중간처분업(건설폐기물)<NA><NA><NA><NA>
146147건설폐기물처리업09_30_05_P348000034800009219960000319960629<NA>1영업/정상BBBB영업<NA><NA><NA><NA>053-637-6535<NA><NA>대구광역시 달성군 화원읍 명곡리 202-2대구광역시 달성군 화원읍 성화로 25, 1층42946(주)팔공골재환경20200818085832U2020-08-20 02:40:00.0<NA>334586.315065256648.569504건설폐기물처리업사업계획(허가)신청수집운반업(건설폐기물)<NA><NA>0.0<NA>
147148건설폐기물처리업09_30_05_P348000034800009220200000120200512<NA>1영업/정상BBBB영업<NA><NA><NA><NA><NA><NA><NA>대구광역시 달성군 논공읍 노이리 1103번지대구광역시 달성군 논공읍 노이길 19842975(주)디에이치환경20200512102805I2020-05-14 00:23:19.0<NA>329535.013237252063.798179건설폐기물처리업사업계획(허가)신청수집운반업(건설폐기물)<NA><NA><NA><NA>
148149건설폐기물처리업09_30_05_P348000034800009220200000220200615<NA>1영업/정상BBBB영업<NA><NA><NA><NA>0536371702<NA><NA>대구광역시 달성군 화원읍 천내리 101-2번지대구광역시 달성군 화원읍 사문진로 409-142948수림건설폐기물수집운반(주)20200615165151I2020-06-17 00:23:27.0<NA>334962.37345257180.630289건설폐기물처리업사업계획(허가)신청수집운반업(건설폐기물)<NA><NA><NA><NA>
149150건설폐기물처리업09_30_05_P348000034800009220180000220180320<NA>1영업/정상BBBB영업<NA><NA><NA><NA>053-586-3860<NA><NA>대구광역시 달성군 옥포읍 교항리 2903번지대구광역시 달성군 옥포읍 돌미상업로1길 13, 5층42974(주)태연산업개발20200512145150U2020-05-14 02:40:00.0<NA>330182.0254471.0건설폐기물처리업사업계획(허가)신청수집운반업(건설폐기물)<NA><NA><NA><NA>
150151건설폐기물처리업09_30_05_P348000034800009220190000220190806<NA>1영업/정상BBBB영업<NA><NA><NA><NA><NA><NA><NA>대구광역시 달성군 화원읍 천내리 39-19번지대구광역시 달성군 화원읍 화원로1길 45-1142955(주)진광산업20190806091040U2019-08-08 02:40:00.0<NA>335413.088628257057.197769건설폐기물처리업사업계획(허가)신청수집운반업(건설폐기물)<NA><NA><NA><NA>
151152건설폐기물처리업09_30_05_P348000034800009220140000120141001<NA>3폐업2폐업20140929<NA><NA><NA>0535252750<NA><NA><NA>대구광역시 달성군 다사읍 서재본길 49711813오성기업(주)20141001160928I2018-08-31 23:59:59.0<NA>334672.532301264618.583219건설폐기물처리업사업계획(허가)신청수집운반업(건설폐기물)<NA><NA><NA><NA>