Overview

Dataset statistics

Number of variables35
Number of observations373
Missing cells3598
Missing cells (%)27.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory109.8 KiB
Average record size in memory301.4 B

Variable types

Numeric12
Categorical12
Unsupported6
Text4
DateTime1

Dataset

Description2021-03-01
Author지방행정인허가공개데이터
URLhttps://bigdata.busan.go.kr/data/bigDataDetailView.do?menuCode=M00000000007&hdfs_file_sn=20230901050101123153

Alerts

개방서비스명 has constant value ""Constant
개방서비스id has constant value ""Constant
환경업무구분명 has constant value ""Constant
상세영업상태코드 is highly imbalanced (53.9%)Imbalance
상세영업상태명 is highly imbalanced (53.9%)Imbalance
휴업종료일자 is highly imbalanced (97.3%)Imbalance
재개업일자 is highly imbalanced (97.3%)Imbalance
폐기물처리업구분명 is highly imbalanced (55.9%)Imbalance
폐기물구분명 is highly imbalanced (88.1%)Imbalance
인허가취소일자 has 373 (100.0%) missing valuesMissing
폐업일자 has 253 (67.8%) missing valuesMissing
휴업시작일자 has 367 (98.4%) missing valuesMissing
소재지전화 has 96 (25.7%) missing valuesMissing
소재지면적 has 373 (100.0%) missing valuesMissing
소재지우편번호 has 159 (42.6%) missing valuesMissing
소재지전체주소 has 43 (11.5%) missing valuesMissing
도로명전체주소 has 33 (8.8%) missing valuesMissing
도로명우편번호 has 131 (35.1%) missing valuesMissing
업태구분명 has 373 (100.0%) missing valuesMissing
좌표정보(x) has 16 (4.3%) missing valuesMissing
좌표정보(y) has 16 (4.3%) missing valuesMissing
폐기물처리업별처리구분명 has 373 (100.0%) missing valuesMissing
허용보관량 has 246 (66.0%) missing valuesMissing
허용보관량내용 has 373 (100.0%) missing valuesMissing
Unnamed: 34 has 373 (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
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
Unnamed: 34 is an unsupported type, check if it needs cleaning or further analysisUnsupported
허용보관량 has 70 (18.8%) zerosZeros

Reproduction

Analysis started2024-04-17 01:03:38.712398
Analysis finished2024-04-17 01:03:39.197004
Duration0.48 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct373
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean187
Minimum1
Maximum373
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.4 KiB
2024-04-17T10:03:39.255352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile19.6
Q194
median187
Q3280
95-th percentile354.4
Maximum373
Range372
Interquartile range (IQR)186

Descriptive statistics

Standard deviation107.82007
Coefficient of variation (CV)0.57657789
Kurtosis-1.2
Mean187
Median Absolute Deviation (MAD)93
Skewness0
Sum69751
Variance11625.167
MonotonicityStrictly increasing
2024-04-17T10:03:39.359586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.3%
247 1
 
0.3%
256 1
 
0.3%
255 1
 
0.3%
254 1
 
0.3%
253 1
 
0.3%
252 1
 
0.3%
251 1
 
0.3%
250 1
 
0.3%
249 1
 
0.3%
Other values (363) 363
97.3%
ValueCountFrequency (%)
1 1
0.3%
2 1
0.3%
3 1
0.3%
4 1
0.3%
5 1
0.3%
6 1
0.3%
7 1
0.3%
8 1
0.3%
9 1
0.3%
10 1
0.3%
ValueCountFrequency (%)
373 1
0.3%
372 1
0.3%
371 1
0.3%
370 1
0.3%
369 1
0.3%
368 1
0.3%
367 1
0.3%
366 1
0.3%
365 1
0.3%
364 1
0.3%

개방서비스명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
건설폐기물처리업
373 

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 373
100.0%

Length

2024-04-17T10:03:39.465110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T10:03:39.543245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
건설폐기물처리업 373
100.0%

개방서비스id
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
09_30_05_P
373 

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 373
100.0%

Length

2024-04-17T10:03:39.624460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T10:03:39.702982image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
09_30_05_p 373
100.0%

개방자치단체코드
Real number (ℝ)

Distinct16
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3348337.8
Minimum3250000
Maximum3400000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.4 KiB
2024-04-17T10:03:39.777580image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3250000
5-th percentile3280000
Q13320000
median3350000
Q33390000
95-th percentile3400000
Maximum3400000
Range150000
Interquartile range (IQR)70000

Descriptive statistics

Standard deviation37985.9
Coefficient of variation (CV)0.011344704
Kurtosis-0.74644913
Mean3348337.8
Median Absolute Deviation (MAD)30000
Skewness-0.35145537
Sum1.24893 × 109
Variance1.4429286 × 109
MonotonicityNot monotonic
2024-04-17T10:03:39.879040image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
3360000 58
15.5%
3400000 51
13.7%
3390000 50
13.4%
3340000 45
12.1%
3350000 39
10.5%
3300000 28
7.5%
3330000 25
6.7%
3280000 19
 
5.1%
3310000 14
 
3.8%
3320000 14
 
3.8%
Other values (6) 30
8.0%
ValueCountFrequency (%)
3250000 1
 
0.3%
3260000 4
 
1.1%
3270000 4
 
1.1%
3280000 19
5.1%
3290000 10
 
2.7%
3300000 28
7.5%
3310000 14
 
3.8%
3320000 14
 
3.8%
3330000 25
6.7%
3340000 45
12.1%
ValueCountFrequency (%)
3400000 51
13.7%
3390000 50
13.4%
3380000 7
 
1.9%
3370000 4
 
1.1%
3360000 58
15.5%
3350000 39
10.5%
3340000 45
12.1%
3330000 25
6.7%
3320000 14
 
3.8%
3310000 14
 
3.8%

관리번호
Real number (ℝ)

UNIQUE 

Distinct373
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.3483387 × 1017
Minimum3.2500009 × 1017
Maximum3.4000009 × 1017
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.4 KiB
2024-04-17T10:03:39.997630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.2500009 × 1017
5-th percentile3.2800009 × 1017
Q13.3200009 × 1017
median3.3500009 × 1017
Q33.3900009 × 1017
95-th percentile3.4000009 × 1017
Maximum3.4000009 × 1017
Range1.5000001 × 1016
Interquartile range (IQR)7 × 1015

Descriptive statistics

Standard deviation3.7985898 × 1015
Coefficient of variation (CV)0.0113447
Kurtosis-0.7464491
Mean3.3483387 × 1017
Median Absolute Deviation (MAD)3 × 1015
Skewness-0.35145554
Sum-4.2341742 × 1018
Variance1.4429284 × 1031
MonotonicityNot monotonic
2024-04-17T10:03:40.122510image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
340000092201200002 1
 
0.3%
336000092201600002 1
 
0.3%
336000092201200003 1
 
0.3%
336000092201200002 1
 
0.3%
336000092201600008 1
 
0.3%
336000092201600007 1
 
0.3%
336000092201600005 1
 
0.3%
336000092200800001 1
 
0.3%
336000092200700003 1
 
0.3%
336000092200700001 1
 
0.3%
Other values (363) 363
97.3%
ValueCountFrequency (%)
325000092200900001 1
0.3%
326000092200600001 1
0.3%
326000092200800001 1
0.3%
326000092200800002 1
0.3%
326000092201500001 1
0.3%
327000092200300118 1
0.3%
327000092200900001 1
0.3%
327000092201500001 1
0.3%
327000092202000001 1
0.3%
328000092199600001 1
0.3%
ValueCountFrequency (%)
340000093201700002 1
0.3%
340000092202000003 1
0.3%
340000092202000002 1
0.3%
340000092202000001 1
0.3%
340000092201900002 1
0.3%
340000092201900001 1
0.3%
340000092201800002 1
0.3%
340000092201800001 1
0.3%
340000092201700001 1
0.3%
340000092201600001 1
0.3%

인허가일자
Real number (ℝ)

Distinct350
Distinct (%)93.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20064143
Minimum2007
Maximum20210122
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.4 KiB
2024-04-17T10:03:40.252906image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2007
5-th percentile20010472
Q120071130
median20120601
Q320161026
95-th percentile20200888
Maximum20210122
Range20208115
Interquartile range (IQR)89896

Descriptive statistics

Standard deviation1043151.5
Coefficient of variation (CV)0.051990834
Kurtosis370.7255
Mean20064143
Median Absolute Deviation (MAD)40485
Skewness-19.225114
Sum7.4839254 × 109
Variance1.0881651 × 1012
MonotonicityNot monotonic
2024-04-17T10:03:40.380226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20061030 3
 
0.8%
20160115 3
 
0.8%
20000807 3
 
0.8%
20181101 2
 
0.5%
20170621 2
 
0.5%
20190812 2
 
0.5%
20050128 2
 
0.5%
20090121 2
 
0.5%
20060223 2
 
0.5%
20100115 2
 
0.5%
Other values (340) 350
93.8%
ValueCountFrequency (%)
2007 1
 
0.3%
19960919 1
 
0.3%
19961004 1
 
0.3%
19970106 1
 
0.3%
19970814 1
 
0.3%
19971028 1
 
0.3%
19990426 1
 
0.3%
20000308 1
 
0.3%
20000802 1
 
0.3%
20000807 3
0.8%
ValueCountFrequency (%)
20210122 1
0.3%
20210114 1
0.3%
20210113 1
0.3%
20210111 1
0.3%
20210108 1
0.3%
20210107 1
0.3%
20210105 1
0.3%
20201229 1
0.3%
20201224 1
0.3%
20201217 1
0.3%

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing373
Missing (%)100.0%
Memory size3.4 KiB

영업상태구분코드
Categorical

Distinct4
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
1
247 
3
120 
2
 
5
4
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)0.3%

Sample

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

Common Values

ValueCountFrequency (%)
1 247
66.2%
3 120
32.2%
2 5
 
1.3%
4 1
 
0.3%

Length

2024-04-17T10:03:40.496228image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T10:03:40.581371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 247
66.2%
3 120
32.2%
2 5
 
1.3%
4 1
 
0.3%

영업상태명
Categorical

Distinct4
Distinct (%)1.1%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
영업/정상
247 
폐업
120 
휴업
 
5
취소/말소/만료/정지/중지
 
1

Length

Max length14
Median length5
Mean length4.0187668
Min length2

Unique

Unique1 ?
Unique (%)0.3%

Sample

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

Common Values

ValueCountFrequency (%)
영업/정상 247
66.2%
폐업 120
32.2%
휴업 5
 
1.3%
취소/말소/만료/정지/중지 1
 
0.3%

Length

2024-04-17T10:03:40.673315image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T10:03:40.763853image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 247
66.2%
폐업 120
32.2%
휴업 5
 
1.3%
취소/말소/만료/정지/중지 1
 
0.3%

상세영업상태코드
Categorical

IMBALANCE 

Distinct5
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
BBBB
245 
2
120 
1
 
5
3
 
2
4
 
1

Length

Max length4
Median length4
Mean length2.9705094
Min length1

Unique

Unique1 ?
Unique (%)0.3%

Sample

1st row4
2nd row2
3rd row2
4th row2
5th row2

Common Values

ValueCountFrequency (%)
BBBB 245
65.7%
2 120
32.2%
1 5
 
1.3%
3 2
 
0.5%
4 1
 
0.3%

Length

2024-04-17T10:03:40.869212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T10:03:40.958137image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
bbbb 245
65.7%
2 120
32.2%
1 5
 
1.3%
3 2
 
0.5%
4 1
 
0.3%

상세영업상태명
Categorical

IMBALANCE 

Distinct5
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
영업
245 
폐업
120 
휴업
 
5
재개업
 
2
폐쇄
 
1

Length

Max length3
Median length2
Mean length2.0053619
Min length2

Unique

Unique1 ?
Unique (%)0.3%

Sample

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

Common Values

ValueCountFrequency (%)
영업 245
65.7%
폐업 120
32.2%
휴업 5
 
1.3%
재개업 2
 
0.5%
폐쇄 1
 
0.3%

Length

2024-04-17T10:03:41.063089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T10:03:41.157280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업 245
65.7%
폐업 120
32.2%
휴업 5
 
1.3%
재개업 2
 
0.5%
폐쇄 1
 
0.3%

폐업일자
Real number (ℝ)

MISSING 

Distinct116
Distinct (%)96.7%
Missing253
Missing (%)67.8%
Infinite0
Infinite (%)0.0%
Mean20133555
Minimum20060222
Maximum20210114
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.4 KiB
2024-04-17T10:03:41.264000image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20060222
5-th percentile20071119
Q120100586
median20131231
Q320161130
95-th percentile20200531
Maximum20210114
Range149892
Interquartile range (IQR)60544.25

Descriptive statistics

Standard deviation39242.693
Coefficient of variation (CV)0.0019491189
Kurtosis-1.0587739
Mean20133555
Median Absolute Deviation (MAD)30269
Skewness0.073455551
Sum2.4160266 × 109
Variance1.539989 × 109
MonotonicityNot monotonic
2024-04-17T10:03:41.416414image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20131231 4
 
1.1%
20161130 2
 
0.5%
20160430 1
 
0.3%
20090123 1
 
0.3%
20110216 1
 
0.3%
20080605 1
 
0.3%
20121105 1
 
0.3%
20080818 1
 
0.3%
20140612 1
 
0.3%
20080124 1
 
0.3%
Other values (106) 106
28.4%
(Missing) 253
67.8%
ValueCountFrequency (%)
20060222 1
0.3%
20061114 1
0.3%
20070731 1
0.3%
20070802 1
0.3%
20070808 1
0.3%
20070914 1
0.3%
20071130 1
0.3%
20071224 1
0.3%
20080124 1
0.3%
20080204 1
0.3%
ValueCountFrequency (%)
20210114 1
0.3%
20201221 1
0.3%
20201119 1
0.3%
20201112 1
0.3%
20201016 1
0.3%
20200626 1
0.3%
20200526 1
0.3%
20200305 1
0.3%
20191101 1
0.3%
20191007 1
0.3%

휴업시작일자
Real number (ℝ)

MISSING 

Distinct6
Distinct (%)100.0%
Missing367
Missing (%)98.4%
Infinite0
Infinite (%)0.0%
Mean20157581
Minimum20081231
Maximum20201012
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.4 KiB
2024-04-17T10:03:41.552747image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20081231
5-th percentile20098600
Q120150736
median20160713
Q320185984
95-th percentile20198537
Maximum20201012
Range119781
Interquartile range (IQR)35247.75

Descriptive statistics

Standard deviation42666.891
Coefficient of variation (CV)0.0021166672
Kurtosis1.9530361
Mean20157581
Median Absolute Deviation (MAD)20202.5
Skewness-1.2509369
Sum1.2094549 × 108
Variance1.8204636 × 109
MonotonicityNot monotonic
2024-04-17T10:03:41.681961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
20191112 1
 
0.3%
20150825 1
 
0.3%
20201012 1
 
0.3%
20150707 1
 
0.3%
20170601 1
 
0.3%
20081231 1
 
0.3%
(Missing) 367
98.4%
ValueCountFrequency (%)
20081231 1
0.3%
20150707 1
0.3%
20150825 1
0.3%
20170601 1
0.3%
20191112 1
0.3%
20201012 1
0.3%
ValueCountFrequency (%)
20201012 1
0.3%
20191112 1
0.3%
20170601 1
0.3%
20150825 1
0.3%
20150707 1
0.3%
20081231 1
0.3%

휴업종료일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
<NA>
372 
20090706
 
1

Length

Max length8
Median length4
Mean length4.0107239
Min length4

Unique

Unique1 ?
Unique (%)0.3%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 372
99.7%
20090706 1
 
0.3%

Length

2024-04-17T10:03:41.864386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T10:03:42.005953image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 372
99.7%
20090706 1
 
0.3%

재개업일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
<NA>
372 
20090706
 
1

Length

Max length8
Median length4
Mean length4.0107239
Min length4

Unique

Unique1 ?
Unique (%)0.3%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 372
99.7%
20090706 1
 
0.3%

Length

2024-04-17T10:03:42.163630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T10:03:42.304023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 372
99.7%
20090706 1
 
0.3%

소재지전화
Text

MISSING 

Distinct241
Distinct (%)87.0%
Missing96
Missing (%)25.7%
Memory size3.0 KiB
2024-04-17T10:03:42.570649image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length13
Mean length10.162455
Min length7

Characters and Unicode

Total characters2815
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

Unique215 ?
Unique (%)77.6%

Sample

1st row704-7281
2nd row3165-366
3rd row5182897
4th row051-291-4322
5th row0515582570
ValueCountFrequency (%)
051 14
 
4.7%
051-928-6161 5
 
1.7%
0517271823 4
 
1.3%
7221231 3
 
1.0%
051-973-7940 3
 
1.0%
317-6076 3
 
1.0%
5534949 3
 
1.0%
051-316-4160 3
 
1.0%
0514036677 3
 
1.0%
0519732504 2
 
0.7%
Other values (237) 255
85.6%
2024-04-17T10:03:42.942893image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 414
14.7%
0 397
14.1%
5 387
13.7%
2 270
9.6%
- 251
8.9%
7 241
8.6%
3 225
8.0%
6 211
7.5%
4 156
 
5.5%
8 139
 
4.9%
Other values (2) 124
 
4.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2543
90.3%
Dash Punctuation 251
 
8.9%
Space Separator 21
 
0.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 414
16.3%
0 397
15.6%
5 387
15.2%
2 270
10.6%
7 241
9.5%
3 225
8.8%
6 211
8.3%
4 156
 
6.1%
8 139
 
5.5%
9 103
 
4.1%
Dash Punctuation
ValueCountFrequency (%)
- 251
100.0%
Space Separator
ValueCountFrequency (%)
21
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2815
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
1 414
14.7%
0 397
14.1%
5 387
13.7%
2 270
9.6%
- 251
8.9%
7 241
8.6%
3 225
8.0%
6 211
7.5%
4 156
 
5.5%
8 139
 
4.9%
Other values (2) 124
 
4.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2815
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 414
14.7%
0 397
14.1%
5 387
13.7%
2 270
9.6%
- 251
8.9%
7 241
8.6%
3 225
8.0%
6 211
7.5%
4 156
 
5.5%
8 139
 
4.9%
Other values (2) 124
 
4.4%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing373
Missing (%)100.0%
Memory size3.4 KiB

소재지우편번호
Real number (ℝ)

MISSING 

Distinct124
Distinct (%)57.9%
Missing159
Missing (%)42.6%
Infinite0
Infinite (%)0.0%
Mean611772.64
Minimum600072
Maximum619963
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.4 KiB
2024-04-17T10:03:43.069371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum600072
5-th percentile604030
Q1607050
median611786.5
Q3617050
95-th percentile619912.35
Maximum619963
Range19891
Interquartile range (IQR)10000

Descriptive statistics

Standard deviation5613.7281
Coefficient of variation (CV)0.0091761673
Kurtosis-1.3561356
Mean611772.64
Median Absolute Deviation (MAD)5224.5
Skewness-0.0081542455
Sum1.3091934 × 108
Variance31513943
MonotonicityNot monotonic
2024-04-17T10:03:43.232053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
607050 8
 
2.1%
617050 8
 
2.1%
617030 7
 
1.9%
604040 6
 
1.6%
609430 5
 
1.3%
604060 5
 
1.3%
609410 4
 
1.1%
607060 4
 
1.1%
607040 4
 
1.1%
612040 4
 
1.1%
Other values (114) 159
42.6%
(Missing) 159
42.6%
ValueCountFrequency (%)
600072 1
 
0.3%
601030 1
 
0.3%
601065 1
 
0.3%
602070 1
 
0.3%
602093 1
 
0.3%
602807 1
 
0.3%
604020 2
 
0.5%
604022 2
 
0.5%
604030 2
 
0.5%
604040 6
1.6%
ValueCountFrequency (%)
619963 1
 
0.3%
619962 1
 
0.3%
619961 3
0.8%
619953 3
0.8%
619951 2
0.5%
619913 1
 
0.3%
619912 1
 
0.3%
619906 3
0.8%
619905 1
 
0.3%
619901 3
0.8%

소재지전체주소
Text

MISSING 

Distinct277
Distinct (%)83.9%
Missing43
Missing (%)11.5%
Memory size3.0 KiB
2024-04-17T10:03:43.579743image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length43
Median length39
Mean length22.60303
Min length5

Characters and Unicode

Total characters7459
Distinct characters197
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

Unique232 ?
Unique (%)70.3%

Sample

1st row부산광역시 중구 부평동2가 55-5번지 3층
2nd row부산광역시 동래구 사직동 140-49번지
3rd row부산광역시 동래구 사직동 131-7번지
4th row부산광역시 동래구 수안동 40-13번지
5th row부산광역시 동래구 수안동 41-13번지
ValueCountFrequency (%)
부산광역시 329
 
22.6%
사상구 49
 
3.4%
강서구 45
 
3.1%
사하구 44
 
3.0%
기장군 40
 
2.7%
금정구 32
 
2.2%
동래구 26
 
1.8%
해운대구 23
 
1.6%
영도구 19
 
1.3%
감전동 19
 
1.3%
Other values (462) 830
57.0%
2024-04-17T10:03:44.024455image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1137
 
15.2%
1 396
 
5.3%
부 350
 
4.7%
산 348
 
4.7%
동 348
 
4.7%
광 334
 
4.5%
시 329
 
4.4%
역 329
 
4.4%
구 308
 
4.1%
- 293
 
3.9%
Other values (187) 3287
44.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4477
60.0%
Decimal Number 1539
 
20.6%
Space Separator 1137
 
15.2%
Dash Punctuation 293
 
3.9%
Uppercase Letter 5
 
0.1%
Lowercase Letter 4
 
0.1%
Open Punctuation 2
 
< 0.1%
Close Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
부 350
 
7.8%
산 348
 
7.8%
동 348
 
7.8%
광 334
 
7.5%
시 329
 
7.3%
역 329
 
7.3%
구 308
 
6.9%
지 249
 
5.6%
번 238
 
5.3%
사 107
 
2.4%
Other values (165) 1537
34.3%
Decimal Number
ValueCountFrequency (%)
1 396
25.7%
2 182
11.8%
4 178
11.6%
3 151
 
9.8%
5 145
 
9.4%
7 115
 
7.5%
0 108
 
7.0%
9 97
 
6.3%
8 88
 
5.7%
6 79
 
5.1%
Uppercase Letter
ValueCountFrequency (%)
A 2
40.0%
S 1
20.0%
E 1
20.0%
I 1
20.0%
Lowercase Letter
ValueCountFrequency (%)
f 1
25.0%
l 1
25.0%
e 1
25.0%
s 1
25.0%
Space Separator
ValueCountFrequency (%)
1137
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 293
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4477
60.0%
Common 2973
39.9%
Latin 9
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
부 350
 
7.8%
산 348
 
7.8%
동 348
 
7.8%
광 334
 
7.5%
시 329
 
7.3%
역 329
 
7.3%
구 308
 
6.9%
지 249
 
5.6%
번 238
 
5.3%
사 107
 
2.4%
Other values (165) 1537
34.3%
Common
ValueCountFrequency (%)
1137
38.2%
1 396
 
13.3%
- 293
 
9.9%
2 182
 
6.1%
4 178
 
6.0%
3 151
 
5.1%
5 145
 
4.9%
7 115
 
3.9%
0 108
 
3.6%
9 97
 
3.3%
Other values (4) 171
 
5.8%
Latin
ValueCountFrequency (%)
A 2
22.2%
S 1
11.1%
f 1
11.1%
l 1
11.1%
e 1
11.1%
s 1
11.1%
E 1
11.1%
I 1
11.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4477
60.0%
ASCII 2982
40.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1137
38.1%
1 396
 
13.3%
- 293
 
9.8%
2 182
 
6.1%
4 178
 
6.0%
3 151
 
5.1%
5 145
 
4.9%
7 115
 
3.9%
0 108
 
3.6%
9 97
 
3.3%
Other values (12) 180
 
6.0%
Hangul
ValueCountFrequency (%)
부 350
 
7.8%
산 348
 
7.8%
동 348
 
7.8%
광 334
 
7.5%
시 329
 
7.3%
역 329
 
7.3%
구 308
 
6.9%
지 249
 
5.6%
번 238
 
5.3%
사 107
 
2.4%
Other values (165) 1537
34.3%

도로명전체주소
Text

MISSING 

Distinct286
Distinct (%)84.1%
Missing33
Missing (%)8.8%
Memory size3.0 KiB
2024-04-17T10:03:44.317914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length51
Median length45
Mean length28.338235
Min length20

Characters and Unicode

Total characters9635
Distinct characters253
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

Unique248 ?
Unique (%)72.9%

Sample

1st row부산광역시 기장군 정관면 정관로 819-15
2nd row부산광역시 중구 부평1길 5 (부평동2가,3층)
3rd row부산광역시 동래구 여고로113번길 55 (사직동)
4th row부산광역시 동래구 아시아드대로108번길 71 (사직동)
5th row부산광역시 동래구 수안로8번길 35 (수안동)
ValueCountFrequency (%)
부산광역시 339
 
18.3%
강서구 52
 
2.8%
사상구 51
 
2.7%
기장군 47
 
2.5%
사하구 44
 
2.4%
금정구 38
 
2.0%
동래구 22
 
1.2%
해운대구 20
 
1.1%
감전동 19
 
1.0%
장림동 18
 
1.0%
Other values (619) 1205
65.0%
2024-04-17T10:03:44.949423image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1568
 
16.3%
동 417
 
4.3%
산 389
 
4.0%
부 359
 
3.7%
시 350
 
3.6%
광 348
 
3.6%
역 339
 
3.5%
1 334
 
3.5%
구 327
 
3.4%
로 316
 
3.3%
Other values (243) 4888
50.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5729
59.5%
Space Separator 1568
 
16.3%
Decimal Number 1534
 
15.9%
Close Punctuation 299
 
3.1%
Open Punctuation 299
 
3.1%
Other Punctuation 119
 
1.2%
Dash Punctuation 70
 
0.7%
Uppercase Letter 13
 
0.1%
Lowercase Letter 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 417
 
7.3%
산 389
 
6.8%
부 359
 
6.3%
시 350
 
6.1%
광 348
 
6.1%
역 339
 
5.9%
구 327
 
5.7%
로 316
 
5.5%
길 151
 
2.6%
대 150
 
2.6%
Other values (218) 2583
45.1%
Decimal Number
ValueCountFrequency (%)
1 334
21.8%
2 240
15.6%
3 188
12.3%
0 133
 
8.7%
5 132
 
8.6%
6 118
 
7.7%
4 107
 
7.0%
9 101
 
6.6%
7 98
 
6.4%
8 83
 
5.4%
Uppercase Letter
ValueCountFrequency (%)
A 8
61.5%
P 1
 
7.7%
E 1
 
7.7%
C 1
 
7.7%
I 1
 
7.7%
S 1
 
7.7%
Lowercase Letter
ValueCountFrequency (%)
s 1
25.0%
e 1
25.0%
l 1
25.0%
f 1
25.0%
Space Separator
ValueCountFrequency (%)
1568
100.0%
Close Punctuation
ValueCountFrequency (%)
) 299
100.0%
Open Punctuation
ValueCountFrequency (%)
( 299
100.0%
Other Punctuation
ValueCountFrequency (%)
, 119
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 70
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5729
59.5%
Common 3889
40.4%
Latin 17
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 417
 
7.3%
산 389
 
6.8%
부 359
 
6.3%
시 350
 
6.1%
광 348
 
6.1%
역 339
 
5.9%
구 327
 
5.7%
로 316
 
5.5%
길 151
 
2.6%
대 150
 
2.6%
Other values (218) 2583
45.1%
Common
ValueCountFrequency (%)
1568
40.3%
1 334
 
8.6%
) 299
 
7.7%
( 299
 
7.7%
2 240
 
6.2%
3 188
 
4.8%
0 133
 
3.4%
5 132
 
3.4%
, 119
 
3.1%
6 118
 
3.0%
Other values (5) 459
 
11.8%
Latin
ValueCountFrequency (%)
A 8
47.1%
P 1
 
5.9%
E 1
 
5.9%
C 1
 
5.9%
s 1
 
5.9%
e 1
 
5.9%
l 1
 
5.9%
f 1
 
5.9%
I 1
 
5.9%
S 1
 
5.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5729
59.5%
ASCII 3906
40.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1568
40.1%
1 334
 
8.6%
) 299
 
7.7%
( 299
 
7.7%
2 240
 
6.1%
3 188
 
4.8%
0 133
 
3.4%
5 132
 
3.4%
, 119
 
3.0%
6 118
 
3.0%
Other values (15) 476
 
12.2%
Hangul
ValueCountFrequency (%)
동 417
 
7.3%
산 389
 
6.8%
부 359
 
6.3%
시 350
 
6.1%
광 348
 
6.1%
역 339
 
5.9%
구 327
 
5.7%
로 316
 
5.5%
길 151
 
2.6%
대 150
 
2.6%
Other values (218) 2583
45.1%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct159
Distinct (%)65.7%
Missing131
Missing (%)35.1%
Infinite0
Infinite (%)0.0%
Mean295391.24
Minimum46006
Maximum619961
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.4 KiB
2024-04-17T10:03:45.056507image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum46006
5-th percentile46027
Q146725
median49358
Q3612791.25
95-th percentile619899.5
Maximum619961
Range573955
Interquartile range (IQR)566066.25

Descriptive statistics

Standard deviation281534.99
Coefficient of variation (CV)0.95309187
Kurtosis-1.9519676
Mean295391.24
Median Absolute Deviation (MAD)3327
Skewness0.25192969
Sum71484680
Variance7.9261951 × 1010
MonotonicityNot monotonic
2024-04-17T10:03:45.169205image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
46721 8
 
2.1%
617829 7
 
1.9%
604842 7
 
1.9%
46023 5
 
1.3%
46708 5
 
1.3%
619961 5
 
1.3%
617805 4
 
1.1%
46706 4
 
1.1%
46702 4
 
1.1%
617804 4
 
1.1%
Other values (149) 189
50.7%
(Missing) 131
35.1%
ValueCountFrequency (%)
46006 1
 
0.3%
46018 2
 
0.5%
46020 1
 
0.3%
46023 5
1.3%
46026 2
 
0.5%
46027 3
0.8%
46031 2
 
0.5%
46033 1
 
0.3%
46041 1
 
0.3%
46046 1
 
0.3%
ValueCountFrequency (%)
619961 5
1.3%
619953 1
 
0.3%
619951 1
 
0.3%
619913 1
 
0.3%
619906 3
0.8%
619901 2
 
0.5%
619871 1
 
0.3%
618817 1
 
0.3%
618808 1
 
0.3%
618803 3
0.8%

사업장명
Text

Distinct298
Distinct (%)79.9%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
2024-04-17T10:03:45.421585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length6.4906166
Min length2

Characters and Unicode

Total characters2421
Distinct characters211
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique241 ?
Unique (%)64.6%

Sample

1st row하나자원
2nd row(주)현우
3rd row에스엔리사이클링(주)
4th row국보환경
5th row우리산업
ValueCountFrequency (%)
주식회사 5
 
1.3%
주)그린포트 4
 
1.0%
주)지원 4
 
1.0%
주)대양디앤씨 4
 
1.0%
대성기업 4
 
1.0%
건설환경(주 3
 
0.8%
주)호생환경 3
 
0.8%
더조은환경 3
 
0.8%
주)정열중기건설 3
 
0.8%
남일환경산업 3
 
0.8%
Other values (296) 350
90.7%
2024-04-17T10:03:45.809376image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 217
 
9.0%
) 206
 
8.5%
( 204
 
8.4%
경 146
 
6.0%
환 138
 
5.7%
업 110
 
4.5%
산 101
 
4.2%
대 42
 
1.7%
성 40
 
1.7%
이 36
 
1.5%
Other values (201) 1181
48.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1948
80.5%
Close Punctuation 206
 
8.5%
Open Punctuation 204
 
8.4%
Uppercase Letter 43
 
1.8%
Space Separator 13
 
0.5%
Decimal Number 3
 
0.1%
Lowercase Letter 3
 
0.1%
Other Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 217
 
11.1%
경 146
 
7.5%
환 138
 
7.1%
업 110
 
5.6%
산 101
 
5.2%
대 42
 
2.2%
성 40
 
2.1%
이 36
 
1.8%
발 35
 
1.8%
개 35
 
1.8%
Other values (180) 1048
53.8%
Uppercase Letter
ValueCountFrequency (%)
E 10
23.3%
N 9
20.9%
C 6
14.0%
T 5
11.6%
G 3
 
7.0%
S 3
 
7.0%
H 2
 
4.7%
M 2
 
4.7%
L 1
 
2.3%
B 1
 
2.3%
Decimal Number
ValueCountFrequency (%)
2 1
33.3%
1 1
33.3%
3 1
33.3%
Lowercase Letter
ValueCountFrequency (%)
t 1
33.3%
i 1
33.3%
o 1
33.3%
Close Punctuation
ValueCountFrequency (%)
) 206
100.0%
Open Punctuation
ValueCountFrequency (%)
( 204
100.0%
Space Separator
ValueCountFrequency (%)
13
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1949
80.5%
Common 426
 
17.6%
Latin 46
 
1.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 217
 
11.1%
경 146
 
7.5%
환 138
 
7.1%
업 110
 
5.6%
산 101
 
5.2%
대 42
 
2.2%
성 40
 
2.1%
이 36
 
1.8%
발 35
 
1.8%
개 35
 
1.8%
Other values (181) 1049
53.8%
Latin
ValueCountFrequency (%)
E 10
21.7%
N 9
19.6%
C 6
13.0%
T 5
10.9%
G 3
 
6.5%
S 3
 
6.5%
H 2
 
4.3%
M 2
 
4.3%
L 1
 
2.2%
B 1
 
2.2%
Other values (4) 4
 
8.7%
Common
ValueCountFrequency (%)
) 206
48.4%
( 204
47.9%
13
 
3.1%
2 1
 
0.2%
1 1
 
0.2%
3 1
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1948
80.5%
ASCII 472
 
19.5%
None 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 217
 
11.1%
경 146
 
7.5%
환 138
 
7.1%
업 110
 
5.6%
산 101
 
5.2%
대 42
 
2.2%
성 40
 
2.1%
이 36
 
1.8%
발 35
 
1.8%
개 35
 
1.8%
Other values (180) 1048
53.8%
ASCII
ValueCountFrequency (%)
) 206
43.6%
( 204
43.2%
13
 
2.8%
E 10
 
2.1%
N 9
 
1.9%
C 6
 
1.3%
T 5
 
1.1%
G 3
 
0.6%
S 3
 
0.6%
H 2
 
0.4%
Other values (10) 11
 
2.3%
None
ValueCountFrequency (%)
㈜ 1
100.0%

최종수정시점
Real number (ℝ)

Distinct345
Distinct (%)92.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0162695 × 1013
Minimum2.0070714 × 1013
Maximum2.0210127 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.4 KiB
2024-04-17T10:03:45.926967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.0070714 × 1013
5-th percentile2.0080299 × 1013
Q12.0130828 × 1013
median2.0180521 × 1013
Q32.0200726 × 1013
95-th percentile2.0210105 × 1013
Maximum2.0210127 × 1013
Range1.3941303 × 1011
Interquartile range (IQR)6.9898009 × 1010

Descriptive statistics

Standard deviation4.3281415 × 1010
Coefficient of variation (CV)0.0021466087
Kurtosis-0.76668427
Mean2.0162695 × 1013
Median Absolute Deviation (MAD)2.0605008 × 1010
Skewness-0.77811922
Sum7.5206851 × 1015
Variance1.8732809 × 1021
MonotonicityNot monotonic
2024-04-17T10:03:46.050962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20070714104309 5
 
1.3%
20201126160848 4
 
1.1%
20201217155322 3
 
0.8%
20180220112609 3
 
0.8%
20200907145633 2
 
0.5%
20200529171844 2
 
0.5%
20200305172744 2
 
0.5%
20201019133228 2
 
0.5%
20180823101834 2
 
0.5%
20200305153525 2
 
0.5%
Other values (335) 346
92.8%
ValueCountFrequency (%)
20070714104309 5
1.3%
20070721100711 2
 
0.5%
20070721105746 1
 
0.3%
20070731163210 1
 
0.3%
20070808113331 1
 
0.3%
20070903134844 1
 
0.3%
20070914115408 1
 
0.3%
20070917170855 1
 
0.3%
20071024113840 1
 
0.3%
20071116094738 1
 
0.3%
ValueCountFrequency (%)
20210127133800 1
0.3%
20210123140951 1
0.3%
20210122124927 1
0.3%
20210122114042 1
0.3%
20210122092108 1
0.3%
20210121080858 1
0.3%
20210118120830 1
0.3%
20210115141052 1
0.3%
20210114110149 1
0.3%
20210113173321 2
0.5%

데이터갱신구분
Categorical

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
I
200 
U
173 

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 200
53.6%
U 173
46.4%

Length

2024-04-17T10:03:46.160158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T10:03:46.248048image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 200
53.6%
u 173
46.4%

데이터갱신일자
Date

Distinct125
Distinct (%)33.5%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
Minimum2018-08-31 23:59:59
Maximum2021-01-29 02:40:00
2024-04-17T10:03:46.335845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-17T10:03:46.447874image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing373
Missing (%)100.0%
Memory size3.4 KiB

좌표정보(x)
Real number (ℝ)

MISSING 

Distinct279
Distinct (%)78.2%
Missing16
Missing (%)4.3%
Infinite0
Infinite (%)0.0%
Mean386584.07
Minimum366439.47
Maximum406858.1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.4 KiB
2024-04-17T10:03:46.571222image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum366439.47
5-th percentile375643.94
Q1379356.23
median386608.48
Q3392430.77
95-th percentile401628.47
Maximum406858.1
Range40418.634
Interquartile range (IQR)13074.543

Descriptive statistics

Standard deviation8571.3186
Coefficient of variation (CV)0.022171939
Kurtosis-0.62145578
Mean386584.07
Median Absolute Deviation (MAD)6587.1504
Skewness0.27989678
Sum1.3801051 × 108
Variance73467502
MonotonicityNot monotonic
2024-04-17T10:03:46.690554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
378260.668626959 5
 
1.3%
378589.860456269 5
 
1.3%
401196.848117724 4
 
1.1%
377988.03993089 4
 
1.1%
368089.614964646 4
 
1.1%
382353.871142329 4
 
1.1%
390193.925155478 3
 
0.8%
380317.55169 3
 
0.8%
379312.623204831 3
 
0.8%
378937.311798492 3
 
0.8%
Other values (269) 319
85.5%
(Missing) 16
 
4.3%
ValueCountFrequency (%)
366439.465041604 1
 
0.3%
366677.276623893 1
 
0.3%
368089.614964646 4
1.1%
371215.782352599 1
 
0.3%
371224.0 1
 
0.3%
371224.086997335 1
 
0.3%
371584.492406946 1
 
0.3%
372198.36276397 1
 
0.3%
372232.583624406 2
0.5%
373017.818475368 2
0.5%
ValueCountFrequency (%)
406858.099098331 1
0.3%
406174.5480396 1
0.3%
405551.209138678 1
0.3%
404240.894431611 1
0.3%
403893.32984136 2
0.5%
403758.915671676 1
0.3%
403277.28877757 1
0.3%
403123.961701308 1
0.3%
402169.503589912 1
0.3%
402026.783850946 1
0.3%

좌표정보(y)
Real number (ℝ)

MISSING 

Distinct279
Distinct (%)78.2%
Missing16
Missing (%)4.3%
Infinite0
Infinite (%)0.0%
Mean188376.46
Minimum175696.94
Maximum209851.1
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size3.4 KiB
2024-04-17T10:03:46.812170image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum175696.94
5-th percentile176833.69
Q1182032.89
median187798.94
Q3192924
95-th percentile204742.91
Maximum209851.1
Range34154.164
Interquartile range (IQR)10891.11

Descriptive statistics

Standard deviation7892.6499
Coefficient of variation (CV)0.041898282
Kurtosis-0.32344379
Mean188376.46
Median Absolute Deviation (MAD)5563.9822
Skewness0.49486198
Sum67250395
Variance62293923
MonotonicityNot monotonic
2024-04-17T10:03:46.940337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
186989.385407123 5
 
1.3%
176478.096857031 5
 
1.3%
205367.602874154 4
 
1.1%
187305.367579412 4
 
1.1%
180652.410177711 4
 
1.1%
185336.557698793 4
 
1.1%
190341.672770588 3
 
0.8%
192238.260837 3
 
0.8%
184099.176407529 3
 
0.8%
182130.775973072 3
 
0.8%
Other values (269) 319
85.5%
(Missing) 16
 
4.3%
ValueCountFrequency (%)
175696.937178813 1
 
0.3%
176226.0 1
 
0.3%
176478.096857031 5
1.3%
176512.687604912 1
 
0.3%
176534.696092493 1
 
0.3%
176563.292260915 2
 
0.5%
176580.102067648 2
 
0.5%
176590.960960834 1
 
0.3%
176684.483764729 1
 
0.3%
176707.343737259 3
0.8%
ValueCountFrequency (%)
209851.101446622 1
 
0.3%
207595.887833263 1
 
0.3%
207206.781336235 1
 
0.3%
207197.760049176 1
 
0.3%
206936.64279115 1
 
0.3%
205765.522103629 2
0.5%
205541.016032793 1
 
0.3%
205526.940124255 1
 
0.3%
205371.510345 1
 
0.3%
205367.602874154 4
1.1%

환경업무구분명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
건설폐기물처리업사업계획(허가)신청
373 

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 373
100.0%

Length

2024-04-17T10:03:47.082605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T10:03:47.177929image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
건설폐기물처리업사업계획(허가)신청 373
100.0%

폐기물처리업구분명
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.8%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
수집운반업(건설폐기물)
323 
중간처분업(건설폐기물)
 
30
<NA>
 
20

Length

Max length12
Median length12
Mean length11.571046
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row수집운반업(건설폐기물)
2nd row수집운반업(건설폐기물)
3rd row수집운반업(건설폐기물)
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
수집운반업(건설폐기물) 323
86.6%
중간처분업(건설폐기물) 30
 
8.0%
<NA> 20
 
5.4%

Length

2024-04-17T10:03:47.286265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T10:03:47.380903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
수집운반업(건설폐기물 323
86.6%
중간처분업(건설폐기물 30
 
8.0%
na 20
 
5.4%

폐기물처리업별처리구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing373
Missing (%)100.0%
Memory size3.4 KiB

폐기물구분명
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size3.0 KiB
<NA>
367 
건설폐기물
 
6

Length

Max length5
Median length4
Mean length4.0160858
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 367
98.4%
건설폐기물 6
 
1.6%

Length

2024-04-17T10:03:47.472126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T10:03:47.559191image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 367
98.4%
건설폐기물 6
 
1.6%

허용보관량
Real number (ℝ)

MISSING  ZEROS 

Distinct43
Distinct (%)33.9%
Missing246
Missing (%)66.0%
Infinite0
Infinite (%)0.0%
Mean3377.3867
Minimum0
Maximum203688
Zeros70
Zeros (%)18.8%
Negative0
Negative (%)0.0%
Memory size3.4 KiB
2024-04-17T10:03:47.646208image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q3448.125
95-th percentile17136.48
Maximum203688
Range203688
Interquartile range (IQR)448.125

Descriptive statistics

Standard deviation18653.943
Coefficient of variation (CV)5.5231883
Kurtosis107.66127
Mean3377.3867
Median Absolute Deviation (MAD)0
Skewness10.035212
Sum428928.11
Variance3.4796957 × 108
MonotonicityNot monotonic
2024-04-17T10:03:47.761188image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=43)
ValueCountFrequency (%)
0.0 70
 
18.8%
450.0 8
 
2.1%
1.0 6
 
1.6%
300.0 3
 
0.8%
150.0 2
 
0.5%
562.0 1
 
0.3%
6150.0 1
 
0.3%
11600.0 1
 
0.3%
18120.0 1
 
0.3%
28000.0 1
 
0.3%
Other values (33) 33
 
8.8%
(Missing) 246
66.0%
ValueCountFrequency (%)
0.0 70
18.8%
1.0 6
 
1.6%
10.0 1
 
0.3%
45.0 1
 
0.3%
83.0 1
 
0.3%
85.0 1
 
0.3%
100.0 1
 
0.3%
150.0 2
 
0.5%
155.0 1
 
0.3%
200.0 1
 
0.3%
ValueCountFrequency (%)
203688.0 1
0.3%
28000.0 1
0.3%
24000.0 1
0.3%
20368.8 1
0.3%
20368.0 1
0.3%
19040.0 1
0.3%
18120.0 1
0.3%
14841.6 1
0.3%
13248.0 1
0.3%
12400.0 1
0.3%

허용보관량내용
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing373
Missing (%)100.0%
Memory size3.4 KiB

Unnamed: 34
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing373
Missing (%)100.0%
Memory size3.4 KiB

Sample

번호개방서비스명개방서비스id개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(x)좌표정보(y)환경업무구분명폐기물처리업구분명폐기물처리업별처리구분명폐기물구분명허용보관량허용보관량내용Unnamed: 34
01건설폐기물처리업09_30_05_P340000034000009220120000220181204<NA>4취소/말소/만료/정지/중지4폐쇄<NA><NA><NA><NA>704-7281<NA><NA><NA>부산광역시 기장군 정관면 정관로 819-15619961하나자원20181204174555U2018-12-06 02:40:00.0<NA>400198.205306205371.510345건설폐기물처리업사업계획(허가)신청수집운반업(건설폐기물)<NA><NA><NA><NA><NA>
12건설폐기물처리업09_30_05_P325000032500009220090000120090709<NA>3폐업2폐업20091109<NA><NA><NA>3165-366<NA>600072부산광역시 중구 부평동2가 55-5번지 3층부산광역시 중구 부평1길 5 (부평동2가,3층)<NA>(주)현우20091114130225I2018-08-31 23:59:59.0<NA>384631.174351179724.677772건설폐기물처리업사업계획(허가)신청수집운반업(건설폐기물)<NA><NA>0.0<NA><NA>
23건설폐기물처리업09_30_05_P330000033000009220090000220111216<NA>3폐업2폐업20111216<NA><NA><NA>5182897<NA>607123부산광역시 동래구 사직동 140-49번지부산광역시 동래구 여고로113번길 55 (사직동)607813에스엔리사이클링(주)20111216151015I2018-08-31 23:59:59.0<NA>388834.447466191017.292089건설폐기물처리업사업계획(허가)신청수집운반업(건설폐기물)<NA><NA><NA><NA><NA>
34건설폐기물처리업09_30_05_P330000033000009220060000120060222<NA>3폐업2폐업20060222<NA><NA><NA><NA><NA>607123부산광역시 동래구 사직동 131-7번지부산광역시 동래구 아시아드대로108번길 71 (사직동)<NA>국보환경20070714104309I2018-08-31 23:59:59.0<NA>388493.056064190392.731783건설폐기물처리업사업계획(허가)신청<NA><NA><NA><NA><NA><NA>
45건설폐기물처리업09_30_05_P330000033000009220060000220060315<NA>3폐업2폐업20080516<NA><NA><NA><NA><NA>607050부산광역시 동래구 수안동 40-13번지부산광역시 동래구 수안로8번길 35 (수안동)<NA>우리산업20080519103057I2018-08-31 23:59:59.0<NA>390253.665914190416.187816건설폐기물처리업사업계획(허가)신청<NA><NA><NA><NA><NA><NA>
56건설폐기물처리업09_30_05_P330000033000009220060001020061107<NA>3폐업2폐업20090209<NA><NA><NA><NA><NA>607050부산광역시 동래구 수안동 41-13번지부산광역시 동래구 온천천로 323 (수안동)<NA>운종20090210111826I2018-08-31 23:59:59.0<NA>390193.925155190341.672771건설폐기물처리업사업계획(허가)신청수집운반업(건설폐기물)<NA><NA><NA><NA><NA>
67건설폐기물처리업09_30_05_P330000033000009220070000320160616<NA>3폐업2폐업20160613<NA><NA><NA>051-291-4322<NA>607020부산광역시 동래구 복천동 286-6번지부산광역시 동래구 동래로148번길 22 (복천동)607020(주)금광환경20160616104833I2018-08-31 23:59:59.0<NA>389871.880741191484.76978건설폐기물처리업사업계획(허가)신청수집운반업(건설폐기물)<NA><NA><NA><NA><NA>
78건설폐기물처리업09_30_05_P330000033000009220050000120051031<NA>3폐업2폐업20070808<NA><NA><NA>0515582570<NA>607060부산광역시 동래구 온천동 1431-10번지 정심파크빌 1층부산광역시 동래구 중앙대로1333번길 61 (온천동,정심파크빌 1층)<NA>유창개발20070808113331I2018-08-31 23:59:59.0<NA>388798.004078191685.057388건설폐기물처리업사업계획(허가)신청수집운반업(건설폐기물)<NA><NA><NA><NA><NA>
89건설폐기물처리업09_30_05_P330000033000009220040003720041216<NA>3폐업2폐업20160307<NA><NA><NA>552-1022<NA><NA><NA>부산광역시 동래구 명륜로 265 (명륜동)607802동래환경산업20180315162601I2018-08-31 23:59:59.0<NA>389786.281371192845.64565건설폐기물처리업사업계획(허가)신청수집운반업(건설폐기물)<NA><NA>83.0<NA><NA>
910건설폐기물처리업09_30_05_P330000033000009219960000120100122<NA>3폐업2폐업20100122<NA><NA><NA><NA><NA>607050부산광역시 동래구 수안동 41-13번지부산광역시 동래구 온천천로 323 (수안동)<NA>유성산업20100122143225I2018-08-31 23:59:59.0<NA>390193.925155190341.672771건설폐기물처리업사업계획(허가)신청수집운반업(건설폐기물)<NA><NA>450.0<NA><NA>
번호개방서비스명개방서비스id개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(x)좌표정보(y)환경업무구분명폐기물처리업구분명폐기물처리업별처리구분명폐기물구분명허용보관량허용보관량내용Unnamed: 34
363364건설폐기물처리업09_30_05_P333000033300009220090000220091009<NA>1영업/정상BBBB영업<NA><NA><NA><NA>554-7766<NA>612060부산광역시 해운대구 반여동 748-1번지부산광역시 해운대구 선수촌로 220-1 (반여동)612810동래덤프20190708165004U2019-07-10 02:40:00.0<NA>393577.215081192348.059016건설폐기물처리업사업계획(허가)신청수집운반업(건설폐기물)<NA><NA>0.0<NA><NA>
364365건설폐기물처리업09_30_05_P333000033300009219970000119970106<NA>1영업/정상BBBB영업<NA><NA><NA><NA>0517847707<NA><NA>부산광역시 해운대구 송정동 87-9번지부산광역시 해운대구 송정2로 9 (송정동)<NA>(주)아세아산업20181119160901U2018-11-21 02:38:18.0<NA>400815.862217190439.846083건설폐기물처리업사업계획(허가)신청수집운반업(건설폐기물)<NA><NA>150.0<NA><NA>
365366건설폐기물처리업09_30_05_P333000033300009220040000120040706<NA>1영업/정상BBBB영업<NA><NA><NA><NA>701-2443<NA>612040부산광역시 해운대구 송정동 140-8번지<NA><NA>태양환경20161201162759I2018-08-31 23:59:59.0<NA>400296.30051189268.817099건설폐기물처리업사업계획(허가)신청수집운반업(건설폐기물)<NA><NA>450.0<NA><NA>
366367건설폐기물처리업09_30_05_P333000033300009220130000120130318<NA>1영업/정상BBBB영업<NA><NA><NA><NA><NA><NA>612011부산광역시 해운대구 중동 1754-1번지 뉴대원빌딩 501호부산광역시 해운대구 좌동순환로 11, 501호 (중동,뉴대원빌딩)<NA>부산폐기물공사20130318131719I2018-08-31 23:59:59.0<NA>397359.910631187519.041394건설폐기물처리업사업계획(허가)신청<NA><NA><NA><NA><NA><NA>
367368건설폐기물처리업09_30_05_P333000033300009220120000520121224<NA>1영업/정상BBBB영업<NA><NA><NA><NA>264-0358<NA><NA>부산광역시 해운대구 반송동 895부산광역시 해운대구 윗반송로 64 (반송동)48008서봉리사이를링(주)20210122092108U2021-01-24 02:40:00.0<NA>396264.054017194390.729083건설폐기물처리업사업계획(허가)신청수집운반업(건설폐기물)<NA><NA><NA><NA><NA>
368369건설폐기물처리업09_30_05_P333000033300009220140000120141219<NA>1영업/정상BBBB영업<NA><NA><NA><NA><NA><NA>612083부산광역시 해운대구 반송동 250번지<NA><NA>일성환경20161018131241I2018-08-31 23:59:59.0<NA>395987.602581193597.907863건설폐기물처리업사업계획(허가)신청수집운반업(건설폐기물)<NA><NA><NA><NA><NA>
369370건설폐기물처리업09_30_05_P333000033300009220150000120151126<NA>1영업/정상BBBB영업<NA><NA><NA><NA><NA><NA><NA>부산광역시 해운대구 송정동 99-5번지부산광역시 해운대구 해운대로 1199-23 (송정동)48068대동환경20200611175955U2020-06-13 02:40:00.0<NA>400672.11913190237.398891건설폐기물처리업사업계획(허가)신청수집운반업(건설폐기물)<NA><NA><NA><NA><NA>
370371건설폐기물처리업09_30_05_P333000033300009220160000120160812<NA>1영업/정상BBBB영업<NA><NA><NA><NA>781-5552<NA><NA>부산광역시 해운대구 재송동 1023번지 센텀삼익아파트부산광역시 해운대구 해운대로61번가길 6, 상가동동 201호 (재송동, 센텀삼익아파트)48051주식회사 명진디엔씨20190814110816U2019-08-16 02:40:00.0<NA>393493.362116190063.418959건설폐기물처리업사업계획(허가)신청수집운반업(건설폐기물)<NA><NA><NA><NA><NA>
371372건설폐기물처리업09_30_05_P333000033300009220120000220120704<NA>1영업/정상BBBB영업<NA><NA><NA><NA>051-506-8837<NA><NA>부산광역시 해운대구 반여동 1291-1182번지부산광역시 해운대구 해운대로61번길 84-58 (반여동)48051SH TECH20191031111720U2019-11-02 02:40:00.0<NA>393703.236092190410.305041건설폐기물처리업사업계획(허가)신청수집운반업(건설폐기물)<NA><NA><NA><NA><NA>
372373건설폐기물처리업09_30_05_P333000033300009220210000120210122<NA>1영업/정상BBBB영업<NA><NA><NA><NA>051-505-9906<NA><NA>부산광역시 해운대구 석대동 314부산광역시 해운대구 반송로623번길 30 (석대동)48001수성스틸20210122114042I2021-01-24 00:23:04.0<NA>394030.339661193362.918117건설폐기물처리업사업계획(허가)신청수집운반업(건설폐기물)<NA><NA><NA><NA><NA>