Overview

Dataset statistics

Number of variables37
Number of observations151
Missing cells1684
Missing cells (%)30.1%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory47.3 KiB
Average record size in memory320.9 B

Variable types

Numeric10
Categorical13
Unsupported9
Text4
DateTime1

Dataset

Description2021-01-04
Author지방행정인허가공개데이터
URLhttps://bigdata.busan.go.kr/data/bigDataDetailView.do?menuCode=M00000000007&hdfs_file_sn=20230901050101123151

Alerts

개방서비스명 has constant value ""Constant
개방서비스id has constant value ""Constant
환경업무구분명 has constant value ""Constant
휴업시작일자 is highly imbalanced (91.4%)Imbalance
휴업종료일자 is highly imbalanced (94.3%)Imbalance
재개업일자 is highly imbalanced (94.3%)Imbalance
업태구분명 is highly imbalanced (59.9%)Imbalance
업종구분명 is highly imbalanced (59.9%)Imbalance
인허가취소일자 has 151 (100.0%) missing valuesMissing
폐업일자 has 48 (31.8%) missing valuesMissing
소재지전화 has 60 (39.7%) missing valuesMissing
소재지면적 has 151 (100.0%) missing valuesMissing
소재지우편번호 has 22 (14.6%) missing valuesMissing
도로명전체주소 has 47 (31.1%) missing valuesMissing
도로명우편번호 has 108 (71.5%) missing valuesMissing
좌표정보(x) has 20 (13.2%) missing valuesMissing
좌표정보(y) has 20 (13.2%) missing valuesMissing
종별명 has 151 (100.0%) missing valuesMissing
주생산품명 has 151 (100.0%) missing valuesMissing
배출시설조업시간 has 151 (100.0%) missing valuesMissing
배출시설연간가동일수 has 151 (100.0%) missing valuesMissing
방지시설조업시간 has 151 (100.0%) missing valuesMissing
방지시설연간가동일수 has 151 (100.0%) missing valuesMissing
Unnamed: 36 has 151 (100.0%) missing valuesMissing
번호 has unique valuesUnique
관리번호 has unique valuesUnique
최종수정시점 has unique valuesUnique
인허가취소일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
소재지면적 is an unsupported type, check if it needs cleaning or further analysisUnsupported
종별명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
주생산품명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
배출시설조업시간 is an unsupported type, check if it needs cleaning or further analysisUnsupported
배출시설연간가동일수 is an unsupported type, check if it needs cleaning or further analysisUnsupported
방지시설조업시간 is an unsupported type, check if it needs cleaning or further analysisUnsupported
방지시설연간가동일수 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 36 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-04-16 10:36:28.605731
Analysis finished2024-04-16 10:36:29.045607
Duration0.44 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct151
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean76
Minimum1
Maximum151
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2024-04-16T19:36:29.099924image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile8.5
Q138.5
median76
Q3113.5
95-th percentile143.5
Maximum151
Range150
Interquartile range (IQR)75

Descriptive statistics

Standard deviation43.734045
Coefficient of variation (CV)0.57544796
Kurtosis-1.2
Mean76
Median Absolute Deviation (MAD)38
Skewness0
Sum11476
Variance1912.6667
MonotonicityStrictly increasing
2024-04-16T19:36:29.210297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.7%
105 1
 
0.7%
98 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%
106 1
 
0.7%
Other values (141) 141
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 (%)
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%
142 1
0.7%

개방서비스명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
개인하수처리시설관리업(사업장)
151 

Length

Max length16
Median length16
Mean length16
Min length16

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row개인하수처리시설관리업(사업장)
2nd row개인하수처리시설관리업(사업장)
3rd row개인하수처리시설관리업(사업장)
4th row개인하수처리시설관리업(사업장)
5th row개인하수처리시설관리업(사업장)

Common Values

ValueCountFrequency (%)
개인하수처리시설관리업(사업장) 151
100.0%

Length

2024-04-16T19:36:29.332714image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T19:36:29.433762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
개인하수처리시설관리업(사업장 151
100.0%

개방서비스id
Categorical

CONSTANT 

Distinct1
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
09_30_03_P
151 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row09_30_03_P
2nd row09_30_03_P
3rd row09_30_03_P
4th row09_30_03_P
5th row09_30_03_P

Common Values

ValueCountFrequency (%)
09_30_03_P 151
100.0%

Length

2024-04-16T19:36:29.517226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T19:36:29.596161image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
09_30_03_p 151
100.0%

개방자치단체코드
Real number (ℝ)

Distinct16
Distinct (%)10.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3335298
Minimum3250000
Maximum3400000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2024-04-16T19:36:29.664421image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3250000
5-th percentile3275000
Q13300000
median3330000
Q33370000
95-th percentile3400000
Maximum3400000
Range150000
Interquartile range (IQR)70000

Descriptive statistics

Standard deviation40146.531
Coefficient of variation (CV)0.012036865
Kurtosis-1.0782357
Mean3335298
Median Absolute Deviation (MAD)30000
Skewness0.10347102
Sum5.0363 × 108
Variance1.6117439 × 109
MonotonicityNot monotonic
2024-04-16T19:36:29.757037image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
3350000 23
15.2%
3300000 19
12.6%
3390000 16
10.6%
3290000 16
10.6%
3400000 13
8.6%
3310000 13
8.6%
3320000 11
7.3%
3330000 9
 
6.0%
3370000 9
 
6.0%
3340000 5
 
3.3%
Other values (6) 17
11.3%
ValueCountFrequency (%)
3250000 1
 
0.7%
3260000 3
 
2.0%
3270000 4
 
2.6%
3280000 2
 
1.3%
3290000 16
10.6%
3300000 19
12.6%
3310000 13
8.6%
3320000 11
7.3%
3330000 9
6.0%
3340000 5
 
3.3%
ValueCountFrequency (%)
3400000 13
8.6%
3390000 16
10.6%
3380000 3
 
2.0%
3370000 9
 
6.0%
3360000 4
 
2.6%
3350000 23
15.2%
3340000 5
 
3.3%
3330000 9
 
6.0%
3320000 11
7.3%
3310000 13
8.6%

관리번호
Real number (ℝ)

UNIQUE 

Distinct151
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.3352985 × 1017
Minimum3.2500005 × 1017
Maximum3.4000005 × 1017
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2024-04-16T19:36:30.091757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.2500005 × 1017
5-th percentile3.2750005 × 1017
Q13.3000005 × 1017
median3.3300005 × 1017
Q33.3700005 × 1017
95-th percentile3.4000005 × 1017
Maximum3.4000005 × 1017
Range1.5 × 1016
Interquartile range (IQR)7 × 1015

Descriptive statistics

Standard deviation4.0146531 × 1015
Coefficient of variation (CV)0.012036863
Kurtosis-1.0782357
Mean3.3352985 × 1017
Median Absolute Deviation (MAD)3 × 1015
Skewness0.10347103
Sum-4.9772242 × 1018
Variance1.6117439 × 1031
MonotonicityNot monotonic
2024-04-16T19:36:30.204800image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
333000053201900001 1
 
0.7%
335000053201200001 1
 
0.7%
334000053200700001 1
 
0.7%
334000053200000005 1
 
0.7%
336000053201000001 1
 
0.7%
336000053200100001 1
 
0.7%
336000053201200001 1
 
0.7%
335000053000000016 1
 
0.7%
335000053000000015 1
 
0.7%
335000053201000002 1
 
0.7%
Other values (141) 141
93.4%
ValueCountFrequency (%)
325000053200800001 1
0.7%
326000053200400001 1
0.7%
326000053200400002 1
0.7%
326000053200417784 1
0.7%
327000053200000001 1
0.7%
327000053200200001 1
0.7%
327000053200900001 1
0.7%
327000053201000001 1
0.7%
328000053199900011 1
0.7%
328000053200300001 1
0.7%
ValueCountFrequency (%)
340000053201700001 1
0.7%
340000053201400001 1
0.7%
340000053201000002 1
0.7%
340000053201000001 1
0.7%
340000053200600001 1
0.7%
340000053200400002 1
0.7%
340000053200400001 1
0.7%
340000053200100001 1
0.7%
340000053200000004 1
0.7%
340000053200000003 1
0.7%

인허가일자
Real number (ℝ)

Distinct130
Distinct (%)86.1%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20040041
Minimum19990830
Maximum20190218
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2024-04-16T19:36:30.328472image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19990830
5-th percentile20000107
Q120000810
median20021221
Q320061115
95-th percentile20125818
Maximum20190218
Range199388
Interquartile range (IQR)60305

Descriptive statistics

Standard deviation44838.834
Coefficient of variation (CV)0.0022374622
Kurtosis0.53850516
Mean20040041
Median Absolute Deviation (MAD)20818
Skewness1.0836785
Sum3.0260462 × 109
Variance2.010521 × 109
MonotonicityNot monotonic
2024-04-16T19:36:30.447144image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20000107 7
 
4.6%
20000810 5
 
3.3%
20000728 3
 
2.0%
20000814 3
 
2.0%
20110317 2
 
1.3%
20000303 2
 
1.3%
20100713 2
 
1.3%
20040602 2
 
1.3%
20030808 2
 
1.3%
20000904 2
 
1.3%
Other values (120) 121
80.1%
ValueCountFrequency (%)
19990830 1
 
0.7%
19990921 1
 
0.7%
19991013 1
 
0.7%
19991101 1
 
0.7%
19991105 1
 
0.7%
19991203 1
 
0.7%
20000103 1
 
0.7%
20000107 7
4.6%
20000208 1
 
0.7%
20000215 1
 
0.7%
ValueCountFrequency (%)
20190218 1
0.7%
20170328 1
0.7%
20161212 1
0.7%
20151204 1
0.7%
20150703 1
0.7%
20141010 1
0.7%
20140115 1
0.7%
20130522 1
0.7%
20121113 1
0.7%
20120216 1
0.7%

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing151
Missing (%)100.0%
Memory size1.5 KiB
Distinct4
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
3
76 
1
72 
2
 
2
4
 
1

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique1 ?
Unique (%)0.7%

Sample

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

Common Values

ValueCountFrequency (%)
3 76
50.3%
1 72
47.7%
2 2
 
1.3%
4 1
 
0.7%

Length

2024-04-16T19:36:30.578960image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T19:36:30.665998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 76
50.3%
1 72
47.7%
2 2
 
1.3%
4 1
 
0.7%

영업상태명
Categorical

Distinct4
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
폐업
76 
영업/정상
72 
휴업
 
2
취소/말소/만료/정지/중지
 
1

Length

Max length14
Median length2
Mean length3.5099338
Min length2

Unique

Unique1 ?
Unique (%)0.7%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 76
50.3%
영업/정상 72
47.7%
휴업 2
 
1.3%
취소/말소/만료/정지/중지 1
 
0.7%

Length

2024-04-16T19:36:30.782293image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T19:36:30.885383image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 76
50.3%
영업/정상 72
47.7%
휴업 2
 
1.3%
취소/말소/만료/정지/중지 1
 
0.7%
Distinct5
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2
76 
11
71 
1
 
2
4
 
1
3
 
1

Length

Max length2
Median length1
Mean length1.4701987
Min length1

Unique

Unique2 ?
Unique (%)1.3%

Sample

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

Common Values

ValueCountFrequency (%)
2 76
50.3%
11 71
47.0%
1 2
 
1.3%
4 1
 
0.7%
3 1
 
0.7%

Length

2024-04-16T19:36:30.979506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T19:36:31.064944image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 76
50.3%
11 71
47.0%
1 2
 
1.3%
4 1
 
0.7%
3 1
 
0.7%
Distinct5
Distinct (%)3.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
폐업
76 
영업
71 
휴업
 
2
폐쇄
 
1
재개업
 
1

Length

Max length3
Median length2
Mean length2.0066225
Min length2

Unique

Unique2 ?
Unique (%)1.3%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 76
50.3%
영업 71
47.0%
휴업 2
 
1.3%
폐쇄 1
 
0.7%
재개업 1
 
0.7%

Length

2024-04-16T19:36:31.165230image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T19:36:31.251835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 76
50.3%
영업 71
47.0%
휴업 2
 
1.3%
폐쇄 1
 
0.7%
재개업 1
 
0.7%

폐업일자
Real number (ℝ)

MISSING 

Distinct96
Distinct (%)93.2%
Missing48
Missing (%)31.8%
Infinite0
Infinite (%)0.0%
Mean20855656
Minimum20000601
Maximum99991231
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2024-04-16T19:36:31.351796image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20000601
5-th percentile20001220
Q120035727
median20070830
Q320121159
95-th percentile20170984
Maximum99991231
Range79990630
Interquartile range (IQR)85432

Descriptive statistics

Standard deviation7874078.2
Coefficient of variation (CV)0.37755121
Kurtosis102.9907
Mean20855656
Median Absolute Deviation (MAD)40416
Skewness10.148211
Sum2.1481326 × 109
Variance6.2001108 × 1013
MonotonicityNot monotonic
2024-04-16T19:36:31.494789image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20130207 3
 
2.0%
20141006 3
 
2.0%
20080617 2
 
1.3%
20181018 2
 
1.3%
20070105 2
 
1.3%
20101231 1
 
0.7%
20070517 1
 
0.7%
20040527 1
 
0.7%
20031010 1
 
0.7%
20060630 1
 
0.7%
Other values (86) 86
57.0%
(Missing) 48
31.8%
ValueCountFrequency (%)
20000601 1
0.7%
20000730 1
0.7%
20000904 1
0.7%
20000908 1
0.7%
20001218 1
0.7%
20001220 1
0.7%
20001222 1
0.7%
20011027 1
0.7%
20011129 1
0.7%
20011207 1
0.7%
ValueCountFrequency (%)
99991231 1
0.7%
20190830 1
0.7%
20181018 2
1.3%
20180515 1
0.7%
20171026 1
0.7%
20170608 1
0.7%
20170111 1
0.7%
20161206 1
0.7%
20160706 1
0.7%
20160516 1
0.7%

휴업시작일자
Categorical

IMBALANCE 

Distinct4
Distinct (%)2.6%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
<NA>
148 
20071231
 
1
20201223
 
1
20130207
 
1

Length

Max length8
Median length4
Mean length4.0794702
Min length4

Unique

Unique3 ?
Unique (%)2.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 148
98.0%
20071231 1
 
0.7%
20201223 1
 
0.7%
20130207 1
 
0.7%

Length

2024-04-16T19:36:31.642976image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T19:36:31.745701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 148
98.0%
20071231 1
 
0.7%
20201223 1
 
0.7%
20130207 1
 
0.7%

휴업종료일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
<NA>
150 
20160223
 
1

Length

Max length8
Median length4
Mean length4.0264901
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> 150
99.3%
20160223 1
 
0.7%

Length

2024-04-16T19:36:31.845572image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T19:36:31.935863image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 150
99.3%
20160223 1
 
0.7%

재개업일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
<NA>
150 
20160223
 
1

Length

Max length8
Median length4
Mean length4.0264901
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> 150
99.3%
20160223 1
 
0.7%

Length

2024-04-16T19:36:32.029402image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T19:36:32.120666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 150
99.3%
20160223 1
 
0.7%

소재지전화
Text

MISSING 

Distinct89
Distinct (%)97.8%
Missing60
Missing (%)39.7%
Memory size1.3 KiB
2024-04-16T19:36:32.274474image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length10.923077
Min length7

Characters and Unicode

Total characters994
Distinct characters13
Distinct categories4 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique87 ?
Unique (%)95.6%

Sample

1st row051-743-0312
2nd row005107034884
3rd row005105213436
4th row051-722-6660
5th row0513618360
ValueCountFrequency (%)
051 35
 
25.2%
0512478115 2
 
1.4%
051-722-6660 2
 
1.4%
817 2
 
1.4%
2478115 2
 
1.4%
0517273932 1
 
0.7%
0515288201 1
 
0.7%
3135335 1
 
0.7%
3169212 1
 
0.7%
3100252 1
 
0.7%
Other values (91) 91
65.5%
2024-04-16T19:36:32.552453image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 168
16.9%
1 165
16.6%
0 156
15.7%
2 95
9.6%
3 80
8.0%
6 76
7.6%
8 55
 
5.5%
49
 
4.9%
7 47
 
4.7%
4 45
 
4.5%
Other values (3) 58
 
5.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 907
91.2%
Space Separator 49
 
4.9%
Dash Punctuation 37
 
3.7%
Close Punctuation 1
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 168
18.5%
1 165
18.2%
0 156
17.2%
2 95
10.5%
3 80
8.8%
6 76
8.4%
8 55
 
6.1%
7 47
 
5.2%
4 45
 
5.0%
9 20
 
2.2%
Space Separator
ValueCountFrequency (%)
49
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 37
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 994
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 168
16.9%
1 165
16.6%
0 156
15.7%
2 95
9.6%
3 80
8.0%
6 76
7.6%
8 55
 
5.5%
49
 
4.9%
7 47
 
4.7%
4 45
 
4.5%
Other values (3) 58
 
5.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 994
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 168
16.9%
1 165
16.6%
0 156
15.7%
2 95
9.6%
3 80
8.0%
6 76
7.6%
8 55
 
5.5%
49
 
4.9%
7 47
 
4.7%
4 45
 
4.5%
Other values (3) 58
 
5.8%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing151
Missing (%)100.0%
Memory size1.5 KiB

소재지우편번호
Real number (ℝ)

MISSING 

Distinct105
Distinct (%)81.4%
Missing22
Missing (%)14.6%
Infinite0
Infinite (%)0.0%
Mean611836.82
Minimum600074
Maximum619963
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2024-04-16T19:36:32.674803image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum600074
5-th percentile602810.8
Q1608021
median611081
Q3616807
95-th percentile619903
Maximum619963
Range19889
Interquartile range (IQR)8786

Descriptive statistics

Standard deviation5040.5548
Coefficient of variation (CV)0.0082383973
Kurtosis-0.82088461
Mean611836.82
Median Absolute Deviation (MAD)3266
Skewness-0.07796235
Sum78926950
Variance25407193
MonotonicityNot monotonic
2024-04-16T19:36:32.793158image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
619903 3
 
2.0%
609320 3
 
2.0%
609811 3
 
2.0%
607823 2
 
1.3%
614080 2
 
1.3%
619900 2
 
1.3%
608023 2
 
1.3%
608040 2
 
1.3%
609390 2
 
1.3%
617814 2
 
1.3%
Other values (95) 106
70.2%
(Missing) 22
 
14.6%
ValueCountFrequency (%)
600074 1
0.7%
601011 1
0.7%
601807 1
0.7%
601830 1
0.7%
601839 1
0.7%
602070 1
0.7%
602808 1
0.7%
602815 1
0.7%
604040 1
0.7%
604762 1
0.7%
ValueCountFrequency (%)
619963 1
 
0.7%
619952 2
1.3%
619912 1
 
0.7%
619906 1
 
0.7%
619903 3
2.0%
619901 1
 
0.7%
619900 2
1.3%
618802 1
 
0.7%
618210 1
 
0.7%
618140 1
 
0.7%
Distinct145
Distinct (%)96.0%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2024-04-16T19:36:33.139742image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length41
Median length39
Mean length23.854305
Min length14

Characters and Unicode

Total characters3602
Distinct characters159
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique139 ?
Unique (%)92.1%

Sample

1st row부산광역시 해운대구 재송동 1216 벽산이센텀클래스원
2nd row부산광역시 해운대구 반여동 1355-19번지
3rd row부산광역시 해운대구 반여동 763-78번지
4th row부산광역시 해운대구 석대동 558-1번지
5th row부산광역시 해운대구 반여동 907-12번지
ValueCountFrequency (%)
부산광역시 151
 
21.9%
금정구 23
 
3.3%
동래구 19
 
2.8%
사상구 16
 
2.3%
부산진구 16
 
2.3%
남구 13
 
1.9%
기장군 13
 
1.9%
번지 12
 
1.7%
북구 11
 
1.6%
해운대구 9
 
1.3%
Other values (261) 405
58.9%
2024-04-16T19:36:33.526436image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
555
 
15.4%
187
 
5.2%
183
 
5.1%
174
 
4.8%
1 158
 
4.4%
154
 
4.3%
153
 
4.2%
151
 
4.2%
146
 
4.1%
140
 
3.9%
Other values (149) 1601
44.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2164
60.1%
Decimal Number 739
 
20.5%
Space Separator 555
 
15.4%
Dash Punctuation 137
 
3.8%
Uppercase Letter 5
 
0.1%
Close Punctuation 1
 
< 0.1%
Open Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
187
 
8.6%
183
 
8.5%
174
 
8.0%
154
 
7.1%
153
 
7.1%
151
 
7.0%
146
 
6.7%
140
 
6.5%
139
 
6.4%
34
 
1.6%
Other values (132) 703
32.5%
Decimal Number
ValueCountFrequency (%)
1 158
21.4%
2 110
14.9%
3 75
10.1%
4 75
10.1%
0 68
9.2%
5 64
8.7%
6 59
 
8.0%
8 50
 
6.8%
7 47
 
6.4%
9 33
 
4.5%
Uppercase Letter
ValueCountFrequency (%)
B 3
60.0%
E 1
 
20.0%
C 1
 
20.0%
Space Separator
ValueCountFrequency (%)
555
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 137
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2164
60.1%
Common 1433
39.8%
Latin 5
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
187
 
8.6%
183
 
8.5%
174
 
8.0%
154
 
7.1%
153
 
7.1%
151
 
7.0%
146
 
6.7%
140
 
6.5%
139
 
6.4%
34
 
1.6%
Other values (132) 703
32.5%
Common
ValueCountFrequency (%)
555
38.7%
1 158
 
11.0%
- 137
 
9.6%
2 110
 
7.7%
3 75
 
5.2%
4 75
 
5.2%
0 68
 
4.7%
5 64
 
4.5%
6 59
 
4.1%
8 50
 
3.5%
Other values (4) 82
 
5.7%
Latin
ValueCountFrequency (%)
B 3
60.0%
E 1
 
20.0%
C 1
 
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2164
60.1%
ASCII 1438
39.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
555
38.6%
1 158
 
11.0%
- 137
 
9.5%
2 110
 
7.6%
3 75
 
5.2%
4 75
 
5.2%
0 68
 
4.7%
5 64
 
4.5%
6 59
 
4.1%
8 50
 
3.5%
Other values (7) 87
 
6.1%
Hangul
ValueCountFrequency (%)
187
 
8.6%
183
 
8.5%
174
 
8.0%
154
 
7.1%
153
 
7.1%
151
 
7.0%
146
 
6.7%
140
 
6.5%
139
 
6.4%
34
 
1.6%
Other values (132) 703
32.5%

도로명전체주소
Text

MISSING 

Distinct98
Distinct (%)94.2%
Missing47
Missing (%)31.1%
Memory size1.3 KiB
2024-04-16T19:36:33.778772image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length43
Median length37
Mean length27.807692
Min length20

Characters and Unicode

Total characters2892
Distinct characters165
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

Unique92 ?
Unique (%)88.5%

Sample

1st row부산광역시 해운대구 센텀동로 99, 벽산이센텀클래스원 912호 (재송동)
2nd row부산광역시 해운대구 반여로 21 (반여동)
3rd row부산광역시 해운대구 선수촌로207번가길 26 (반여동)
4th row부산광역시 해운대구 반여로 21 (반여동)
5th row부산광역시 기장군 기장읍 차성로190번길 97
ValueCountFrequency (%)
부산광역시 104
 
19.0%
금정구 22
 
4.0%
사상구 16
 
2.9%
남구 13
 
2.4%
부산진구 13
 
2.4%
기장군 8
 
1.5%
부곡동 8
 
1.5%
북구 7
 
1.3%
구포동 6
 
1.1%
연제구 6
 
1.1%
Other values (235) 343
62.8%
2024-04-16T19:36:34.131309image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
501
 
17.3%
136
 
4.7%
132
 
4.6%
121
 
4.2%
110
 
3.8%
107
 
3.7%
105
 
3.6%
104
 
3.6%
102
 
3.5%
( 98
 
3.4%
Other values (155) 1376
47.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1722
59.5%
Space Separator 501
 
17.3%
Decimal Number 433
 
15.0%
Open Punctuation 98
 
3.4%
Close Punctuation 98
 
3.4%
Other Punctuation 26
 
0.9%
Dash Punctuation 10
 
0.3%
Uppercase Letter 4
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
136
 
7.9%
132
 
7.7%
121
 
7.0%
110
 
6.4%
107
 
6.2%
105
 
6.1%
104
 
6.0%
102
 
5.9%
43
 
2.5%
40
 
2.3%
Other values (137) 722
41.9%
Decimal Number
ValueCountFrequency (%)
1 95
21.9%
2 84
19.4%
3 45
10.4%
6 43
9.9%
0 39
9.0%
7 30
 
6.9%
4 27
 
6.2%
8 26
 
6.0%
9 23
 
5.3%
5 21
 
4.8%
Uppercase Letter
ValueCountFrequency (%)
B 2
50.0%
C 1
25.0%
E 1
25.0%
Space Separator
ValueCountFrequency (%)
501
100.0%
Open Punctuation
ValueCountFrequency (%)
( 98
100.0%
Close Punctuation
ValueCountFrequency (%)
) 98
100.0%
Other Punctuation
ValueCountFrequency (%)
, 26
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 10
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1722
59.5%
Common 1166
40.3%
Latin 4
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
136
 
7.9%
132
 
7.7%
121
 
7.0%
110
 
6.4%
107
 
6.2%
105
 
6.1%
104
 
6.0%
102
 
5.9%
43
 
2.5%
40
 
2.3%
Other values (137) 722
41.9%
Common
ValueCountFrequency (%)
501
43.0%
( 98
 
8.4%
) 98
 
8.4%
1 95
 
8.1%
2 84
 
7.2%
3 45
 
3.9%
6 43
 
3.7%
0 39
 
3.3%
7 30
 
2.6%
4 27
 
2.3%
Other values (5) 106
 
9.1%
Latin
ValueCountFrequency (%)
B 2
50.0%
C 1
25.0%
E 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1722
59.5%
ASCII 1170
40.5%

Most frequent character per block

ASCII
ValueCountFrequency (%)
501
42.8%
( 98
 
8.4%
) 98
 
8.4%
1 95
 
8.1%
2 84
 
7.2%
3 45
 
3.8%
6 43
 
3.7%
0 39
 
3.3%
7 30
 
2.6%
4 27
 
2.3%
Other values (8) 110
 
9.4%
Hangul
ValueCountFrequency (%)
136
 
7.9%
132
 
7.7%
121
 
7.0%
110
 
6.4%
107
 
6.2%
105
 
6.1%
104
 
6.0%
102
 
5.9%
43
 
2.5%
40
 
2.3%
Other values (137) 722
41.9%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct33
Distinct (%)76.7%
Missing108
Missing (%)71.5%
Infinite0
Infinite (%)0.0%
Mean377212.14
Minimum46033
Maximum619952
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2024-04-16T19:36:34.234900image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum46033
5-th percentile46740.4
Q147811
median609766
Q3617375.5
95-th percentile619911.4
Maximum619952
Range573919
Interquartile range (IQR)569564.5

Descriptive statistics

Standard deviation283030.97
Coefficient of variation (CV)0.75032306
Kurtosis-1.9769328
Mean377212.14
Median Absolute Deviation (MAD)10140
Skewness-0.34158848
Sum16220122
Variance8.0106528 × 1010
MonotonicityNot monotonic
2024-04-16T19:36:34.329942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=33)
ValueCountFrequency (%)
617814 3
 
2.0%
609843 3
 
2.0%
619903 2
 
1.3%
619952 2
 
1.3%
46033 2
 
1.3%
47213 2
 
1.3%
48059 2
 
1.3%
617721 2
 
1.3%
617030 1
 
0.7%
607805 1
 
0.7%
Other values (23) 23
 
15.2%
(Missing) 108
71.5%
ValueCountFrequency (%)
46033 2
1.3%
46700 1
0.7%
47104 1
0.7%
47211 1
0.7%
47213 2
1.3%
47257 1
0.7%
47562 1
0.7%
47568 1
0.7%
47585 1
0.7%
48037 1
0.7%
ValueCountFrequency (%)
619952 2
1.3%
619912 1
 
0.7%
619906 1
 
0.7%
619903 2
1.3%
617814 3
2.0%
617721 2
1.3%
617030 1
 
0.7%
614868 1
 
0.7%
614839 1
 
0.7%
611814 1
 
0.7%
Distinct120
Distinct (%)79.5%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
2024-04-16T19:36:34.528870image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length11
Mean length7.9602649
Min length4

Characters and Unicode

Total characters1202
Distinct characters139
Distinct categories7 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique96 ?
Unique (%)63.6%

Sample

1st row비알테크놀로지(주)
2nd row(주)세일엔지니어링
3rd row일진환경
4th row연어환경
5th row(주)석정크린텍
ValueCountFrequency (%)
주식회사 8
 
5.0%
주)은경이엔지 3
 
1.9%
주)한신환경 3
 
1.9%
주)정원환경개발 3
 
1.9%
녹수건설(주 3
 
1.9%
주)세일엔지니어링 3
 
1.9%
주)동해환경 3
 
1.9%
주)신라정화사 3
 
1.9%
주)금목환경 2
 
1.2%
더난환경 2
 
1.2%
Other values (113) 128
79.5%
2024-04-16T19:36:34.823835image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
121
 
10.1%
( 111
 
9.2%
) 111
 
9.2%
73
 
6.1%
68
 
5.7%
43
 
3.6%
36
 
3.0%
26
 
2.2%
26
 
2.2%
25
 
2.1%
Other values (129) 562
46.8%

Most occurring categories

ValueCountFrequency (%)
Other Letter 963
80.1%
Open Punctuation 111
 
9.2%
Close Punctuation 111
 
9.2%
Space Separator 10
 
0.8%
Uppercase Letter 3
 
0.2%
Other Punctuation 2
 
0.2%
Decimal Number 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
121
 
12.6%
73
 
7.6%
68
 
7.1%
43
 
4.5%
36
 
3.7%
26
 
2.7%
26
 
2.7%
25
 
2.6%
25
 
2.6%
20
 
2.1%
Other values (120) 500
51.9%
Uppercase Letter
ValueCountFrequency (%)
A 1
33.3%
E 1
33.3%
C 1
33.3%
Decimal Number
ValueCountFrequency (%)
1 1
50.0%
2 1
50.0%
Open Punctuation
ValueCountFrequency (%)
( 111
100.0%
Close Punctuation
ValueCountFrequency (%)
) 111
100.0%
Space Separator
ValueCountFrequency (%)
10
100.0%
Other Punctuation
ValueCountFrequency (%)
. 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 963
80.1%
Common 236
 
19.6%
Latin 3
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
121
 
12.6%
73
 
7.6%
68
 
7.1%
43
 
4.5%
36
 
3.7%
26
 
2.7%
26
 
2.7%
25
 
2.6%
25
 
2.6%
20
 
2.1%
Other values (120) 500
51.9%
Common
ValueCountFrequency (%)
( 111
47.0%
) 111
47.0%
10
 
4.2%
. 2
 
0.8%
1 1
 
0.4%
2 1
 
0.4%
Latin
ValueCountFrequency (%)
A 1
33.3%
E 1
33.3%
C 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 963
80.1%
ASCII 239
 
19.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
121
 
12.6%
73
 
7.6%
68
 
7.1%
43
 
4.5%
36
 
3.7%
26
 
2.7%
26
 
2.7%
25
 
2.6%
25
 
2.6%
20
 
2.1%
Other values (120) 500
51.9%
ASCII
ValueCountFrequency (%)
( 111
46.4%
) 111
46.4%
10
 
4.2%
. 2
 
0.8%
1 1
 
0.4%
2 1
 
0.4%
A 1
 
0.4%
E 1
 
0.4%
C 1
 
0.4%

최종수정시점
Real number (ℝ)

UNIQUE 

Distinct151
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0102248 × 1013
Minimum2.0000712 × 1013
Maximum2.0201223 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2024-04-16T19:36:34.950136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.0000712 × 1013
5-th percentile2.0000906 × 1013
Q12.0041158 × 1013
median2.0100721 × 1013
Q32.0150657 × 1013
95-th percentile2.0200769 × 1013
Maximum2.0201223 × 1013
Range2.0051108 × 1011
Interquartile range (IQR)1.0949899 × 1011

Descriptive statistics

Standard deviation6.3272887 × 1010
Coefficient of variation (CV)0.0031475529
Kurtosis-1.1978745
Mean2.0102248 × 1013
Median Absolute Deviation (MAD)5.949195 × 1010
Skewness-0.029449448
Sum3.0354394 × 1015
Variance4.0034583 × 1021
MonotonicityNot monotonic
2024-04-16T19:36:35.077386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20200720141034 1
 
0.7%
20120126153108 1
 
0.7%
20171013143711 1
 
0.7%
20000814154050 1
 
0.7%
20160929143840 1
 
0.7%
20160929143904 1
 
0.7%
20190326112516 1
 
0.7%
20001116090958 1
 
0.7%
20001114171828 1
 
0.7%
20110216150550 1
 
0.7%
Other values (141) 141
93.4%
ValueCountFrequency (%)
20000712101531 1
0.7%
20000814154050 1
0.7%
20000823091303 1
0.7%
20000823093449 1
0.7%
20000830161356 1
0.7%
20000830171027 1
0.7%
20000831113727 1
0.7%
20000904103124 1
0.7%
20000908105135 1
0.7%
20000909114130 1
0.7%
ValueCountFrequency (%)
20201223181313 1
0.7%
20201214105808 1
0.7%
20201214105722 1
0.7%
20201214105641 1
0.7%
20201208150714 1
0.7%
20201118093815 1
0.7%
20200928084726 1
0.7%
20200814112427 1
0.7%
20200723134815 1
0.7%
20200720145101 1
0.7%
Distinct2
Distinct (%)1.3%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
I
132 
U
19 

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 132
87.4%
U 19
 
12.6%

Length

2024-04-16T19:36:35.204371image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T19:36:35.315722image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 132
87.4%
u 19
 
12.6%
Distinct21
Distinct (%)13.9%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
Minimum2018-08-31 23:59:59
Maximum2020-12-25 02:40:00
2024-04-16T19:36:35.395810image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-04-16T19:36:35.496938image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=21)

업태구분명
Categorical

IMBALANCE 

Distinct12
Distinct (%)7.9%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
<NA>
118 
분뇨 처리업
 
9
하수처리, 폐기물처리 및 청소관련 서비스업
 
6
하수, 분뇨 및 축산폐기물 처리업
 
4
분뇨 및 축산폐기물 처리업
 
2
Other values (7)
12 

Length

Max length23
Median length4
Mean length6.2317881
Min length4

Unique

Unique2 ?
Unique (%)1.3%

Sample

1st row<NA>
2nd row분뇨 처리업
3rd row<NA>
4th row<NA>
5th row하수처리, 폐기물처리 및 청소관련 서비스업

Common Values

ValueCountFrequency (%)
<NA> 118
78.1%
분뇨 처리업 9
 
6.0%
하수처리, 폐기물처리 및 청소관련 서비스업 6
 
4.0%
하수, 분뇨 및 축산폐기물 처리업 4
 
2.6%
분뇨 및 축산폐기물 처리업 2
 
1.3%
그외 기타 분류안된 모든 서비스업 2
 
1.3%
하수, 폐수 및 분뇨 처리업 2
 
1.3%
폐기물 처리 및 오염방지시설 건설업 2
 
1.3%
환경상담 및 관련 엔지니어링 서비스업 2
 
1.3%
하수 처리업 2
 
1.3%
Other values (2) 2
 
1.3%

Length

2024-04-16T19:36:35.609458image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 118
48.6%
처리업 19
 
7.8%
18
 
7.4%
분뇨 17
 
7.0%
서비스업 11
 
4.5%
하수 8
 
3.3%
하수처리 6
 
2.5%
폐기물처리 6
 
2.5%
청소관련 6
 
2.5%
축산폐기물 6
 
2.5%
Other values (16) 28
 
11.5%

좌표정보(x)
Real number (ℝ)

MISSING 

Distinct121
Distinct (%)92.4%
Missing20
Missing (%)13.2%
Infinite0
Infinite (%)0.0%
Mean387969.71
Minimum371768
Maximum405926.8
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2024-04-16T19:36:35.718065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum371768
5-th percentile379243.4
Q1383927.4
median388532.94
Q3390624.26
95-th percentile401514.71
Maximum405926.8
Range34158.808
Interquartile range (IQR)6696.8543

Descriptive statistics

Standard deviation6031.1761
Coefficient of variation (CV)0.015545482
Kurtosis1.1928953
Mean387969.71
Median Absolute Deviation (MAD)3093.0636
Skewness0.47029613
Sum50824031
Variance36375086
MonotonicityNot monotonic
2024-04-16T19:36:36.055068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
390144.111432534 2
 
1.3%
388825.788637512 2
 
1.3%
388423.564378881 2
 
1.3%
392177.054040305 2
 
1.3%
388532.936821714 2
 
1.3%
390624.256291267 2
 
1.3%
392951.242519577 2
 
1.3%
380482.767624189 2
 
1.3%
379554.826788136 2
 
1.3%
384136.095305462 2
 
1.3%
Other values (111) 111
73.5%
(Missing) 20
 
13.2%
ValueCountFrequency (%)
371767.995757446 1
0.7%
374396.116306859 1
0.7%
378045.177941748 1
0.7%
378592.907593612 1
0.7%
378735.89049941 1
0.7%
378824.101502951 1
0.7%
379122.254409162 1
0.7%
379364.542272391 1
0.7%
379554.826788136 2
1.3%
379688.803735537 1
0.7%
ValueCountFrequency (%)
405926.804044414 1
0.7%
405397.470560958 1
0.7%
403947.265423154 1
0.7%
403845.485106494 1
0.7%
403109.054674373 1
0.7%
402094.490620577 1
0.7%
401638.040844059 1
0.7%
401391.375537312 1
0.7%
393607.260373715 1
0.7%
393605.930358633 1
0.7%

좌표정보(y)
Real number (ℝ)

MISSING 

Distinct121
Distinct (%)92.4%
Missing20
Missing (%)13.2%
Infinite0
Infinite (%)0.0%
Mean189173.32
Minimum176619.87
Maximum206746.79
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 KiB
2024-04-16T19:36:36.169073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum176619.87
5-th percentile180294.15
Q1184487.97
median188789.43
Q3192208.04
95-th percentile199382.14
Maximum206746.79
Range30126.916
Interquartile range (IQR)7720.0714

Descriptive statistics

Standard deviation6111.6845
Coefficient of variation (CV)0.032307328
Kurtosis0.067280256
Mean189173.32
Median Absolute Deviation (MAD)4010.7677
Skewness0.43887306
Sum24781705
Variance37352687
MonotonicityNot monotonic
2024-04-16T19:36:36.278724image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
190453.524937101 2
 
1.3%
184487.967513063 2
 
1.3%
187785.194320347 2
 
1.3%
181177.438378822 2
 
1.3%
191774.030080915 2
 
1.3%
193959.335175462 2
 
1.3%
190453.463973418 2
 
1.3%
185582.274947583 2
 
1.3%
184301.128962735 2
 
1.3%
180300.476056401 2
 
1.3%
Other values (111) 111
73.5%
(Missing) 20
 
13.2%
ValueCountFrequency (%)
176619.874913911 1
0.7%
176725.707798423 1
0.7%
179085.546176133 1
0.7%
179817.73255814 1
0.7%
179959.257076341 1
0.7%
180133.289122155 1
0.7%
180287.829011373 1
0.7%
180300.476056401 2
1.3%
180660.89704286 1
0.7%
180812.733614603 1
0.7%
ValueCountFrequency (%)
206746.790462324 1
0.7%
206457.785803911 1
0.7%
203912.486795312 1
0.7%
203667.051343927 1
0.7%
199895.428934097 1
0.7%
199467.347062416 1
0.7%
199385.436227116 1
0.7%
199378.846451463 1
0.7%
199255.499468693 1
0.7%
198691.191617025 1
0.7%

환경업무구분명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
분뇨등관련영업관리
151 

Length

Max length9
Median length9
Mean length9
Min length9

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
분뇨등관련영업관리 151
100.0%

Length

2024-04-16T19:36:36.388244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-16T19:36:36.475691image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
분뇨등관련영업관리 151
100.0%

업종구분명
Categorical

IMBALANCE 

Distinct12
Distinct (%)7.9%
Missing0
Missing (%)0.0%
Memory size1.3 KiB
<NA>
118 
분뇨 처리업
 
9
하수처리, 폐기물처리 및 청소관련 서비스업
 
6
하수, 분뇨 및 축산폐기물 처리업
 
4
분뇨 및 축산폐기물 처리업
 
2
Other values (7)
12 

Length

Max length23
Median length4
Mean length6.2317881
Min length4

Unique

Unique2 ?
Unique (%)1.3%

Sample

1st row<NA>
2nd row분뇨 처리업
3rd row<NA>
4th row<NA>
5th row하수처리, 폐기물처리 및 청소관련 서비스업

Common Values

ValueCountFrequency (%)
<NA> 118
78.1%
분뇨 처리업 9
 
6.0%
하수처리, 폐기물처리 및 청소관련 서비스업 6
 
4.0%
하수, 분뇨 및 축산폐기물 처리업 4
 
2.6%
분뇨 및 축산폐기물 처리업 2
 
1.3%
그외 기타 분류안된 모든 서비스업 2
 
1.3%
하수, 폐수 및 분뇨 처리업 2
 
1.3%
폐기물 처리 및 오염방지시설 건설업 2
 
1.3%
환경상담 및 관련 엔지니어링 서비스업 2
 
1.3%
하수 처리업 2
 
1.3%
Other values (2) 2
 
1.3%

Length

2024-04-16T19:36:36.567837image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 118
48.6%
처리업 19
 
7.8%
18
 
7.4%
분뇨 17
 
7.0%
서비스업 11
 
4.5%
하수 8
 
3.3%
하수처리 6
 
2.5%
폐기물처리 6
 
2.5%
청소관련 6
 
2.5%
축산폐기물 6
 
2.5%
Other values (16) 28
 
11.5%

종별명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing151
Missing (%)100.0%
Memory size1.5 KiB

주생산품명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing151
Missing (%)100.0%
Memory size1.5 KiB

배출시설조업시간
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing151
Missing (%)100.0%
Memory size1.5 KiB

배출시설연간가동일수
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing151
Missing (%)100.0%
Memory size1.5 KiB

방지시설조업시간
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing151
Missing (%)100.0%
Memory size1.5 KiB

방지시설연간가동일수
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing151
Missing (%)100.0%
Memory size1.5 KiB

Unnamed: 36
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing151
Missing (%)100.0%
Memory size1.5 KiB

Sample

번호개방서비스명개방서비스id개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(x)좌표정보(y)환경업무구분명업종구분명종별명주생산품명배출시설조업시간배출시설연간가동일수방지시설조업시간방지시설연간가동일수Unnamed: 36
01개인하수처리시설관리업(사업장)09_30_03_P333000033300005320190000120190218<NA>4취소/말소/만료/정지/중지4폐쇄<NA><NA><NA><NA>051-743-0312<NA><NA>부산광역시 해운대구 재송동 1216 벽산이센텀클래스원부산광역시 해운대구 센텀동로 99, 벽산이센텀클래스원 912호 (재송동)48059비알테크놀로지(주)20200720141034U2020-07-22 02:40:00.0<NA>393607.260374188408.076688분뇨등관련영업관리<NA><NA><NA><NA><NA><NA><NA><NA>
12개인하수처리시설관리업(사업장)09_30_03_P333000033300005320060000120060213<NA>3폐업2폐업20070105<NA><NA><NA><NA><NA>612061부산광역시 해운대구 반여동 1355-19번지부산광역시 해운대구 반여로 21 (반여동)<NA>(주)세일엔지니어링20080214142058I2018-08-31 23:59:59.0분뇨 처리업392951.24252190453.463973분뇨등관련영업관리분뇨 처리업<NA><NA><NA><NA><NA><NA><NA>
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번호개방서비스명개방서비스id개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(x)좌표정보(y)환경업무구분명업종구분명종별명주생산품명배출시설조업시간배출시설연간가동일수방지시설조업시간방지시설연간가동일수Unnamed: 36
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