Overview

Dataset statistics

Number of variables37
Number of observations141
Missing cells1606
Missing cells (%)30.8%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory44.2 KiB
Average record size in memory320.9 B

Variable types

Numeric10
Categorical14
Unsupported9
Text4

Dataset

Description2021-03-01
Author지방행정인허가공개데이터
URLhttps://bigdata.busan.go.kr/data/bigDataDetailView.do?menuCode=M00000000007&hdfs_file_sn=20230901050101123155

Alerts

개방서비스명 has constant value ""Constant
개방서비스id has constant value ""Constant
환경업무구분명 has constant value ""Constant
상세영업상태코드 is highly imbalanced (53.3%)Imbalance
상세영업상태명 is highly imbalanced (53.3%)Imbalance
휴업시작일자 is highly imbalanced (88.3%)Imbalance
휴업종료일자 is highly imbalanced (88.3%)Imbalance
재개업일자 is highly imbalanced (93.9%)Imbalance
데이터갱신일자 is highly imbalanced (68.8%)Imbalance
업태구분명 is highly imbalanced (58.7%)Imbalance
업종구분명 is highly imbalanced (58.7%)Imbalance
인허가일자 has 27 (19.1%) missing valuesMissing
인허가취소일자 has 141 (100.0%) missing valuesMissing
폐업일자 has 34 (24.1%) missing valuesMissing
소재지전화 has 60 (42.6%) missing valuesMissing
소재지면적 has 141 (100.0%) missing valuesMissing
소재지우편번호 has 16 (11.3%) missing valuesMissing
소재지전체주소 has 3 (2.1%) missing valuesMissing
도로명전체주소 has 38 (27.0%) missing valuesMissing
도로명우편번호 has 105 (74.5%) missing valuesMissing
좌표정보(x) has 27 (19.1%) missing valuesMissing
좌표정보(y) has 27 (19.1%) missing valuesMissing
종별명 has 141 (100.0%) missing valuesMissing
주생산품명 has 141 (100.0%) missing valuesMissing
배출시설조업시간 has 141 (100.0%) missing valuesMissing
배출시설연간가동일수 has 141 (100.0%) missing valuesMissing
방지시설조업시간 has 141 (100.0%) missing valuesMissing
방지시설연간가동일수 has 141 (100.0%) missing valuesMissing
Unnamed: 36 has 141 (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 started2024-04-18 01:12:59.417309
Analysis finished2024-04-18 01:12:59.815806
Duration0.4 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct141
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean71
Minimum1
Maximum141
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2024-04-18T10:12:59.868861image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile8
Q136
median71
Q3106
95-th percentile134
Maximum141
Range140
Interquartile range (IQR)70

Descriptive statistics

Standard deviation40.847277
Coefficient of variation (CV)0.57531375
Kurtosis-1.2
Mean71
Median Absolute Deviation (MAD)35
Skewness0
Sum10011
Variance1668.5
MonotonicityStrictly increasing
2024-04-18T10:12:59.975280image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
0.7%
98 1
 
0.7%
92 1
 
0.7%
93 1
 
0.7%
94 1
 
0.7%
95 1
 
0.7%
96 1
 
0.7%
97 1
 
0.7%
99 1
 
0.7%
90 1
 
0.7%
Other values (131) 131
92.9%
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 (%)
141 1
0.7%
140 1
0.7%
139 1
0.7%
138 1
0.7%
137 1
0.7%
136 1
0.7%
135 1
0.7%
134 1
0.7%
133 1
0.7%
132 1
0.7%

개방서비스명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
단독정화조/오수처리시설설계시공업
141 

Length

Max length17
Median length17
Mean length17
Min length17

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row단독정화조/오수처리시설설계시공업
2nd row단독정화조/오수처리시설설계시공업
3rd row단독정화조/오수처리시설설계시공업
4th row단독정화조/오수처리시설설계시공업
5th row단독정화조/오수처리시설설계시공업

Common Values

ValueCountFrequency (%)
단독정화조/오수처리시설설계시공업 141
100.0%

Length

2024-04-18T10:13:00.102637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T10:13:00.197448image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
단독정화조/오수처리시설설계시공업 141
100.0%

개방서비스id
Categorical

CONSTANT 

Distinct1
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
09_30_07_P
141 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row09_30_07_P
2nd row09_30_07_P
3rd row09_30_07_P
4th row09_30_07_P
5th row09_30_07_P

Common Values

ValueCountFrequency (%)
09_30_07_P 141
100.0%

Length

2024-04-18T10:13:00.299013image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T10:13:00.396284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
09_30_07_p 141
100.0%

개방자치단체코드
Real number (ℝ)

Distinct15
Distinct (%)10.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3330141.8
Minimum3260000
Maximum3400000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2024-04-18T10:13:00.494049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3260000
5-th percentile3270000
Q13300000
median3330000
Q33360000
95-th percentile3390000
Maximum3400000
Range140000
Interquartile range (IQR)60000

Descriptive statistics

Standard deviation39856.633
Coefficient of variation (CV)0.011968449
Kurtosis-1.0950727
Mean3330141.8
Median Absolute Deviation (MAD)30000
Skewness0.11505279
Sum4.6955 × 108
Variance1.5885512 × 109
MonotonicityNot monotonic
2024-04-18T10:13:00.600970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)
ValueCountFrequency (%)
3350000 27
19.1%
3300000 26
18.4%
3290000 13
9.2%
3390000 13
9.2%
3270000 9
 
6.4%
3330000 7
 
5.0%
3400000 7
 
5.0%
3360000 7
 
5.0%
3310000 6
 
4.3%
3370000 6
 
4.3%
Other values (5) 20
14.2%
ValueCountFrequency (%)
3260000 4
 
2.8%
3270000 9
 
6.4%
3280000 3
 
2.1%
3290000 13
9.2%
3300000 26
18.4%
3310000 6
 
4.3%
3320000 5
 
3.5%
3330000 7
 
5.0%
3340000 5
 
3.5%
3350000 27
19.1%
ValueCountFrequency (%)
3400000 7
 
5.0%
3390000 13
9.2%
3380000 3
 
2.1%
3370000 6
 
4.3%
3360000 7
 
5.0%
3350000 27
19.1%
3340000 5
 
3.5%
3330000 7
 
5.0%
3320000 5
 
3.5%
3310000 6
 
4.3%

관리번호
Real number (ℝ)

UNIQUE 

Distinct141
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.3301424 × 1017
Minimum3.2600005 × 1017
Maximum3.4000005 × 1017
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2024-04-18T10:13:00.723575image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.2600005 × 1017
5-th percentile3.2700005 × 1017
Q13.3000005 × 1017
median3.3300005 × 1017
Q33.3600005 × 1017
95-th percentile3.3900005 × 1017
Maximum3.4000005 × 1017
Range1.4 × 1016
Interquartile range (IQR)6 × 1015

Descriptive statistics

Standard deviation3.9856633 × 1015
Coefficient of variation (CV)0.011968447
Kurtosis-1.0950727
Mean3.3301424 × 1017
Median Absolute Deviation (MAD)3 × 1015
Skewness0.1150528
Sum-8.3852246 × 1018
Variance1.5885512 × 1031
MonotonicityNot monotonic
2024-04-18T10:13:00.845914image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
333000054201900001 1
 
0.7%
339000054201600001 1
 
0.7%
326000054200417783 1
 
0.7%
326000054200400002 1
 
0.7%
326000054200400001 1
 
0.7%
326000054200000001 1
 
0.7%
339000054201900001 1
 
0.7%
339000054201800001 1
 
0.7%
339000054201400001 1
 
0.7%
327000054199400001 1
 
0.7%
Other values (131) 131
92.9%
ValueCountFrequency (%)
326000054200000001 1
0.7%
326000054200400001 1
0.7%
326000054200400002 1
0.7%
326000054200417783 1
0.7%
327000054199400001 1
0.7%
327000054199800001 1
0.7%
327000054199900001 1
0.7%
327000054199900002 1
0.7%
327000054200100001 1
0.7%
327000054200200001 1
0.7%
ValueCountFrequency (%)
340000054201400001 1
0.7%
340000054201300001 1
0.7%
340000054200600001 1
0.7%
340000054200300001 1
0.7%
340000054200200001 1
0.7%
340000054199900001 1
0.7%
340000054199800001 1
0.7%
339000054201900001 1
0.7%
339000054201800001 1
0.7%
339000054201600001 1
0.7%

인허가일자
Real number (ℝ)

MISSING 

Distinct95
Distinct (%)83.3%
Missing27
Missing (%)19.1%
Infinite0
Infinite (%)0.0%
Mean20033225
Minimum19830722
Maximum20191015
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2024-04-18T10:13:00.970776image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19830722
5-th percentile19946952
Q120003360
median20030772
Q320058043
95-th percentile20133658
Maximum20191015
Range360293
Interquartile range (IQR)54682.5

Descriptive statistics

Standard deviation58308.679
Coefficient of variation (CV)0.0029105987
Kurtosis1.3835405
Mean20033225
Median Absolute Deviation (MAD)29599
Skewness-0.01984273
Sum2.2837876 × 109
Variance3.399902 × 109
MonotonicityNot monotonic
2024-04-18T10:13:01.112206image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20030627 14
 
9.9%
20031110 4
 
2.8%
20030424 2
 
1.4%
20040625 2
 
1.4%
20120928 2
 
1.4%
20040603 1
 
0.7%
20130129 1
 
0.7%
20140213 1
 
0.7%
20160225 1
 
0.7%
20180220 1
 
0.7%
Other values (85) 85
60.3%
(Missing) 27
 
19.1%
ValueCountFrequency (%)
19830722 1
0.7%
19890216 1
0.7%
19921104 1
0.7%
19921201 1
0.7%
19930513 1
0.7%
19940704 1
0.7%
19950316 1
0.7%
19950413 1
0.7%
19950530 1
0.7%
19950615 1
0.7%
ValueCountFrequency (%)
20191015 1
0.7%
20181206 1
0.7%
20180220 1
0.7%
20160225 1
0.7%
20140827 1
0.7%
20140213 1
0.7%
20130129 1
0.7%
20120928 2
1.4%
20120309 1
0.7%
20111007 1
0.7%

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing141
Missing (%)100.0%
Memory size1.4 KiB

영업상태구분코드
Categorical

Distinct3
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
3
110 
1
26 
2
 
5

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
3 110
78.0%
1 26
 
18.4%
2 5
 
3.5%

Length

2024-04-18T10:13:01.229141image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T10:13:01.312816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
3 110
78.0%
1 26
 
18.4%
2 5
 
3.5%

영업상태명
Categorical

Distinct3
Distinct (%)2.1%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
폐업
110 
영업/정상
26 
휴업
 
5

Length

Max length5
Median length2
Mean length2.5531915
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 110
78.0%
영업/정상 26
 
18.4%
휴업 5
 
3.5%

Length

2024-04-18T10:13:01.413590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T10:13:01.503064image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 110
78.0%
영업/정상 26
 
18.4%
휴업 5
 
3.5%

상세영업상태코드
Categorical

IMBALANCE 

Distinct5
Distinct (%)3.5%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2
107 
11
25 
1
 
5
4
 
3
3
 
1

Length

Max length2
Median length1
Mean length1.177305
Min length1

Unique

Unique1 ?
Unique (%)0.7%

Sample

1st row11
2nd row11
3rd row11
4th row11
5th row11

Common Values

ValueCountFrequency (%)
2 107
75.9%
11 25
 
17.7%
1 5
 
3.5%
4 3
 
2.1%
3 1
 
0.7%

Length

2024-04-18T10:13:01.595799image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T10:13:01.707595image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2 107
75.9%
11 25
 
17.7%
1 5
 
3.5%
4 3
 
2.1%
3 1
 
0.7%

상세영업상태명
Categorical

IMBALANCE 

Distinct5
Distinct (%)3.5%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
폐업
107 
영업
25 
휴업
 
5
폐쇄
 
3
재개업
 
1

Length

Max length3
Median length2
Mean length2.0070922
Min length2

Unique

Unique1 ?
Unique (%)0.7%

Sample

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

Common Values

ValueCountFrequency (%)
폐업 107
75.9%
영업 25
 
17.7%
휴업 5
 
3.5%
폐쇄 3
 
2.1%
재개업 1
 
0.7%

Length

2024-04-18T10:13:01.805699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T10:13:01.914786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
폐업 107
75.9%
영업 25
 
17.7%
휴업 5
 
3.5%
폐쇄 3
 
2.1%
재개업 1
 
0.7%

폐업일자
Real number (ℝ)

MISSING 

Distinct89
Distinct (%)83.2%
Missing34
Missing (%)24.1%
Infinite0
Infinite (%)0.0%
Mean20100060
Minimum19950530
Maximum20320531
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2024-04-18T10:13:02.020460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19950530
5-th percentile20033905
Q120055676
median20080704
Q320140806
95-th percentile20200131
Maximum20320531
Range370001
Interquartile range (IQR)85130.5

Descriptive statistics

Standard deviation58248.47
Coefficient of variation (CV)0.0028979252
Kurtosis0.91604817
Mean20100060
Median Absolute Deviation (MAD)39473
Skewness0.64014145
Sum2.1507064 × 109
Variance3.3928843 × 109
MonotonicityNot monotonic
2024-04-18T10:13:02.148335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20200131 5
 
3.5%
20070518 4
 
2.8%
20060124 3
 
2.1%
20120312 2
 
1.4%
20141229 2
 
1.4%
20130523 2
 
1.4%
20140806 2
 
1.4%
20050201 2
 
1.4%
20071220 2
 
1.4%
20050630 2
 
1.4%
Other values (79) 81
57.4%
(Missing) 34
24.1%
ValueCountFrequency (%)
19950530 1
0.7%
19970813 1
0.7%
20031001 1
0.7%
20031007 1
0.7%
20031122 1
0.7%
20031205 1
0.7%
20040204 1
0.7%
20040510 1
0.7%
20040618 1
0.7%
20040831 1
0.7%
ValueCountFrequency (%)
20320531 1
 
0.7%
20200907 1
 
0.7%
20200131 5
3.5%
20200106 1
 
0.7%
20191028 1
 
0.7%
20191023 1
 
0.7%
20190819 1
 
0.7%
20181224 1
 
0.7%
20171205 1
 
0.7%
20171026 1
 
0.7%

휴업시작일자
Categorical

IMBALANCE 

Distinct6
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
<NA>
136 
20190701
 
1
20040925
 
1
20071129
 
1
20120127
 
1

Length

Max length8
Median length4
Mean length4.141844
Min length4

Unique

Unique5 ?
Unique (%)3.5%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 136
96.5%
20190701 1
 
0.7%
20040925 1
 
0.7%
20071129 1
 
0.7%
20120127 1
 
0.7%
20090101 1
 
0.7%

Length

2024-04-18T10:13:02.290095image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T10:13:02.403427image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 136
96.5%
20190701 1
 
0.7%
20040925 1
 
0.7%
20071129 1
 
0.7%
20120127 1
 
0.7%
20090101 1
 
0.7%

휴업종료일자
Categorical

IMBALANCE 

Distinct6
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
<NA>
136 
20191201
 
1
20050303
 
1
20080301
 
1
20130126
 
1

Length

Max length8
Median length4
Mean length4.141844
Min length4

Unique

Unique5 ?
Unique (%)3.5%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 136
96.5%
20191201 1
 
0.7%
20050303 1
 
0.7%
20080301 1
 
0.7%
20130126 1
 
0.7%
20091231 1
 
0.7%

Length

2024-04-18T10:13:02.541970image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T10:13:02.650263image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 136
96.5%
20191201 1
 
0.7%
20050303 1
 
0.7%
20080301 1
 
0.7%
20130126 1
 
0.7%
20091231 1
 
0.7%

재개업일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
<NA>
140 
20130124
 
1

Length

Max length8
Median length4
Mean length4.0283688
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> 140
99.3%
20130124 1
 
0.7%

Length

2024-04-18T10:13:02.777134image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T10:13:02.886482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 140
99.3%
20130124 1
 
0.7%

소재지전화
Text

MISSING 

Distinct72
Distinct (%)88.9%
Missing60
Missing (%)42.6%
Memory size1.2 KiB
2024-04-18T10:13:03.066140image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length10.753086
Min length7

Characters and Unicode

Total characters871
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

Unique65 ?
Unique (%)80.2%

Sample

1st row743-0312
2nd row051-912-6661
3rd row051-724-1277
4th row051 3375040
5th row2942370
ValueCountFrequency (%)
051 35
26.1%
051-912-6661 3
 
2.2%
5546522 3
 
2.2%
4331 2
 
1.5%
1101 2
 
1.5%
804 2
 
1.5%
5152842 2
 
1.5%
635 2
 
1.5%
0515835141 2
 
1.5%
743-0312 2
 
1.5%
Other values (79) 79
59.0%
2024-04-18T10:13:03.394104image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 151
17.3%
1 146
16.8%
0 132
15.2%
2 75
8.6%
6 62
7.1%
3 56
 
6.4%
53
 
6.1%
8 47
 
5.4%
4 46
 
5.3%
7 39
 
4.5%
Other values (2) 64
7.3%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 782
89.8%
Space Separator 53
 
6.1%
Dash Punctuation 36
 
4.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 151
19.3%
1 146
18.7%
0 132
16.9%
2 75
9.6%
6 62
7.9%
3 56
 
7.2%
8 47
 
6.0%
4 46
 
5.9%
7 39
 
5.0%
9 28
 
3.6%
Space Separator
ValueCountFrequency (%)
53
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 36
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 871
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 151
17.3%
1 146
16.8%
0 132
15.2%
2 75
8.6%
6 62
7.1%
3 56
 
6.4%
53
 
6.1%
8 47
 
5.4%
4 46
 
5.3%
7 39
 
4.5%
Other values (2) 64
7.3%

Most occurring blocks

ValueCountFrequency (%)
ASCII 871
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 151
17.3%
1 146
16.8%
0 132
15.2%
2 75
8.6%
6 62
7.1%
3 56
 
6.4%
53
 
6.1%
8 47
 
5.4%
4 46
 
5.3%
7 39
 
4.5%
Other values (2) 64
7.3%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing141
Missing (%)100.0%
Memory size1.4 KiB

소재지우편번호
Real number (ℝ)

MISSING 

Distinct83
Distinct (%)66.4%
Missing16
Missing (%)11.3%
Infinite0
Infinite (%)0.0%
Mean610599.42
Minimum601062
Maximum619963
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2024-04-18T10:13:03.515666image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum601062
5-th percentile601831.2
Q1607100
median609350
Q3614854
95-th percentile619681.8
Maximum619963
Range18901
Interquartile range (IQR)7754

Descriptive statistics

Standard deviation5296.7742
Coefficient of variation (CV)0.0086747121
Kurtosis-0.87560793
Mean610599.42
Median Absolute Deviation (MAD)3465
Skewness0.14224043
Sum76324927
Variance28055817
MonotonicityNot monotonic
2024-04-18T10:13:03.631110image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
617837 7
 
5.0%
609323 4
 
2.8%
609350 3
 
2.1%
607837 3
 
2.1%
609310 3
 
2.1%
609312 3
 
2.1%
609390 3
 
2.1%
614031 3
 
2.1%
602815 3
 
2.1%
607100 3
 
2.1%
Other values (73) 90
63.8%
(Missing) 16
 
11.3%
ValueCountFrequency (%)
601062 3
2.1%
601715 1
 
0.7%
601812 1
 
0.7%
601830 2
1.4%
601836 1
 
0.7%
601839 1
 
0.7%
602808 1
 
0.7%
602813 1
 
0.7%
602815 3
2.1%
602826 1
 
0.7%
ValueCountFrequency (%)
619963 1
 
0.7%
619952 1
 
0.7%
619906 1
 
0.7%
619903 3
2.1%
619901 1
 
0.7%
618805 1
 
0.7%
618803 1
 
0.7%
618802 1
 
0.7%
618210 2
1.4%
617844 1
 
0.7%

소재지전체주소
Text

MISSING 

Distinct112
Distinct (%)81.2%
Missing3
Missing (%)2.1%
Memory size1.2 KiB
2024-04-18T10:13:03.910197image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length35
Median length34
Mean length20.789855
Min length12

Characters and Unicode

Total characters2869
Distinct characters135
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

Unique97 ?
Unique (%)70.3%

Sample

1st row부산광역시 해운대구 재송동 1216 벽산이센텀클래스원
2nd row부산광역시 해운대구 재송동 1212 큐비이센텀
3rd row부산광역시 기장군 기장읍 청강리 164-11
4th row부산광역시 북구 덕천동 14 부산기능대학 창업보육센타 114호
5th row부산광역시 수영구 광안동 116-5 동트레아파트 상가 505호
ValueCountFrequency (%)
부산광역시 138
23.1%
금정구 27
 
4.5%
동래구 25
 
4.2%
부산진구 12
 
2.0%
사상구 11
 
1.8%
온천동 9
 
1.5%
동구 9
 
1.5%
4층 8
 
1.3%
구서동 8
 
1.3%
안락동 7
 
1.2%
Other values (194) 343
57.5%
2024-04-18T10:13:04.315697image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
461
16.1%
동 174
 
6.1%
산 168
 
5.9%
부 165
 
5.8%
구 142
 
4.9%
광 140
 
4.9%
시 140
 
4.9%
역 138
 
4.8%
1 131
 
4.6%
- 114
 
4.0%
Other values (125) 1096
38.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1655
57.7%
Decimal Number 634
 
22.1%
Space Separator 461
 
16.1%
Dash Punctuation 114
 
4.0%
Uppercase Letter 3
 
0.1%
Close Punctuation 1
 
< 0.1%
Open Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 174
 
10.5%
산 168
 
10.2%
부 165
 
10.0%
구 142
 
8.6%
광 140
 
8.5%
시 140
 
8.5%
역 138
 
8.3%
정 31
 
1.9%
래 29
 
1.8%
금 27
 
1.6%
Other values (110) 501
30.3%
Decimal Number
ValueCountFrequency (%)
1 131
20.7%
3 80
12.6%
2 79
12.5%
4 74
11.7%
5 62
9.8%
6 49
 
7.7%
7 49
 
7.7%
0 43
 
6.8%
9 38
 
6.0%
8 29
 
4.6%
Space Separator
ValueCountFrequency (%)
461
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 114
100.0%
Uppercase Letter
ValueCountFrequency (%)
B 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1655
57.7%
Common 1211
42.2%
Latin 3
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 174
 
10.5%
산 168
 
10.2%
부 165
 
10.0%
구 142
 
8.6%
광 140
 
8.5%
시 140
 
8.5%
역 138
 
8.3%
정 31
 
1.9%
래 29
 
1.8%
금 27
 
1.6%
Other values (110) 501
30.3%
Common
ValueCountFrequency (%)
461
38.1%
1 131
 
10.8%
- 114
 
9.4%
3 80
 
6.6%
2 79
 
6.5%
4 74
 
6.1%
5 62
 
5.1%
6 49
 
4.0%
7 49
 
4.0%
0 43
 
3.6%
Other values (4) 69
 
5.7%
Latin
ValueCountFrequency (%)
B 3
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1655
57.7%
ASCII 1214
42.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
461
38.0%
1 131
 
10.8%
- 114
 
9.4%
3 80
 
6.6%
2 79
 
6.5%
4 74
 
6.1%
5 62
 
5.1%
6 49
 
4.0%
7 49
 
4.0%
0 43
 
3.5%
Other values (5) 72
 
5.9%
Hangul
ValueCountFrequency (%)
동 174
 
10.5%
산 168
 
10.2%
부 165
 
10.0%
구 142
 
8.6%
광 140
 
8.5%
시 140
 
8.5%
역 138
 
8.3%
정 31
 
1.9%
래 29
 
1.8%
금 27
 
1.6%
Other values (110) 501
30.3%

도로명전체주소
Text

MISSING 

Distinct83
Distinct (%)80.6%
Missing38
Missing (%)27.0%
Memory size1.2 KiB
2024-04-18T10:13:04.579209image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length46
Median length39
Mean length27.252427
Min length21

Characters and Unicode

Total characters2807
Distinct characters172
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

Unique71 ?
Unique (%)68.9%

Sample

1st row부산광역시 해운대구 센텀동로 99, 벽산이센텀클래스원 209호 (재송동)
2nd row부산광역시 해운대구 센텀중앙로 90, 큐비이센텀 2403호 (재송동)
3rd row부산광역시 기장군 기장읍 청강로57번길 5
4th row부산광역시 강서구 낙동남로622번길 78-2 (녹산동)
5th row부산광역시 강서구 제도로 675 (강동동)
ValueCountFrequency (%)
부산광역시 103
 
19.4%
금정구 22
 
4.1%
동래구 18
 
3.4%
사상구 13
 
2.4%
부산진구 10
 
1.9%
백양대로 8
 
1.5%
483 7
 
1.3%
주례동 7
 
1.3%
온천동 7
 
1.3%
구서동 7
 
1.3%
Other values (204) 330
62.0%
2024-04-18T10:13:04.978384image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
491
 
17.5%
동 133
 
4.7%
부 130
 
4.6%
산 129
 
4.6%
구 109
 
3.9%
광 104
 
3.7%
시 104
 
3.7%
역 103
 
3.7%
로 101
 
3.6%
) 98
 
3.5%
Other values (162) 1305
46.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1683
60.0%
Space Separator 491
 
17.5%
Decimal Number 402
 
14.3%
Close Punctuation 98
 
3.5%
Open Punctuation 98
 
3.5%
Other Punctuation 18
 
0.6%
Dash Punctuation 14
 
0.5%
Uppercase Letter 3
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 133
 
7.9%
부 130
 
7.7%
산 129
 
7.7%
구 109
 
6.5%
광 104
 
6.2%
시 104
 
6.2%
역 103
 
6.1%
로 101
 
6.0%
대 42
 
2.5%
길 41
 
2.4%
Other values (146) 687
40.8%
Decimal Number
ValueCountFrequency (%)
2 81
20.1%
1 69
17.2%
3 46
11.4%
8 35
8.7%
6 34
8.5%
7 29
 
7.2%
0 29
 
7.2%
4 28
 
7.0%
5 28
 
7.0%
9 23
 
5.7%
Space Separator
ValueCountFrequency (%)
491
100.0%
Close Punctuation
ValueCountFrequency (%)
) 98
100.0%
Open Punctuation
ValueCountFrequency (%)
( 98
100.0%
Other Punctuation
ValueCountFrequency (%)
, 18
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 14
100.0%
Uppercase Letter
ValueCountFrequency (%)
B 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1683
60.0%
Common 1121
39.9%
Latin 3
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 133
 
7.9%
부 130
 
7.7%
산 129
 
7.7%
구 109
 
6.5%
광 104
 
6.2%
시 104
 
6.2%
역 103
 
6.1%
로 101
 
6.0%
대 42
 
2.5%
길 41
 
2.4%
Other values (146) 687
40.8%
Common
ValueCountFrequency (%)
491
43.8%
) 98
 
8.7%
( 98
 
8.7%
2 81
 
7.2%
1 69
 
6.2%
3 46
 
4.1%
8 35
 
3.1%
6 34
 
3.0%
7 29
 
2.6%
0 29
 
2.6%
Other values (5) 111
 
9.9%
Latin
ValueCountFrequency (%)
B 3
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1683
60.0%
ASCII 1124
40.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
491
43.7%
) 98
 
8.7%
( 98
 
8.7%
2 81
 
7.2%
1 69
 
6.1%
3 46
 
4.1%
8 35
 
3.1%
6 34
 
3.0%
7 29
 
2.6%
0 29
 
2.6%
Other values (6) 114
 
10.1%
Hangul
ValueCountFrequency (%)
동 133
 
7.9%
부 130
 
7.7%
산 129
 
7.7%
구 109
 
6.5%
광 104
 
6.2%
시 104
 
6.2%
역 103
 
6.1%
로 101
 
6.0%
대 42
 
2.5%
길 41
 
2.4%
Other values (146) 687
40.8%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct26
Distinct (%)72.2%
Missing105
Missing (%)74.5%
Infinite0
Infinite (%)0.0%
Mean457648.08
Minimum46228
Maximum619952
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2024-04-18T10:13:05.086540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum46228
5-th percentile46732
Q148399
median612820.5
Q3617837
95-th percentile619903.75
Maximum619952
Range573724
Interquartile range (IQR)569438

Descriptive statistics

Standard deviation257965.5
Coefficient of variation (CV)0.56367656
Kurtosis-0.98508221
Mean457648.08
Median Absolute Deviation (MAD)5016.5
Skewness-1.0353669
Sum16475331
Variance6.6546199 × 1010
MonotonicityNot monotonic
2024-04-18T10:13:05.200076image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=26)
ValueCountFrequency (%)
617837 7
 
5.0%
48059 3
 
2.1%
611811 2
 
1.4%
617829 2
 
1.4%
609817 1
 
0.7%
611807 1
 
0.7%
614871 1
 
0.7%
617844 1
 
0.7%
46736 1
 
0.7%
604842 1
 
0.7%
Other values (16) 16
 
11.3%
(Missing) 105
74.5%
ValueCountFrequency (%)
46228 1
 
0.7%
46720 1
 
0.7%
46736 1
 
0.7%
47104 1
 
0.7%
47882 1
 
0.7%
48059 3
2.1%
48099 1
 
0.7%
48499 1
 
0.7%
604842 1
 
0.7%
609817 1
 
0.7%
ValueCountFrequency (%)
619952 1
 
0.7%
619906 1
 
0.7%
619903 1
 
0.7%
618803 1
 
0.7%
617844 1
 
0.7%
617837 7
5.0%
617829 2
 
1.4%
617810 1
 
0.7%
614871 1
 
0.7%
614854 1
 
0.7%

사업장명
Text

Distinct105
Distinct (%)74.5%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2024-04-18T10:13:05.389584image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length11
Mean length8.3333333
Min length4

Characters and Unicode

Total characters1175
Distinct characters130
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

Unique84 ?
Unique (%)59.6%

Sample

1st row비알테크놀로지(주)
2nd row청우에이스(주)
3rd row(주)태광환경이엔지
4th row더난건설(주)
5th row(주)미래테크닉스
ValueCountFrequency (%)
주)영동엔지니어링 7
 
4.8%
주식회사 5
 
3.4%
주)정원환경개발 4
 
2.7%
오케이엔지니어링 4
 
2.7%
주)우일환경테크닉스 4
 
2.7%
삼영이엔테크(주 3
 
2.1%
청우에이스(주 3
 
2.1%
녹수건설(주 3
 
2.1%
주)한국환경이엔지 3
 
2.1%
주)청호이.엔.지 2
 
1.4%
Other values (96) 108
74.0%
2024-04-18T10:13:05.687057image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 123
 
10.5%
) 117
 
10.0%
( 117
 
10.0%
경 50
 
4.3%
엔 49
 
4.2%
환 48
 
4.1%
지 44
 
3.7%
이 36
 
3.1%
니 27
 
2.3%
어 27
 
2.3%
Other values (120) 537
45.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 924
78.6%
Close Punctuation 117
 
10.0%
Open Punctuation 117
 
10.0%
Uppercase Letter 6
 
0.5%
Space Separator 5
 
0.4%
Other Punctuation 4
 
0.3%
Decimal Number 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 123
 
13.3%
경 50
 
5.4%
엔 49
 
5.3%
환 48
 
5.2%
지 44
 
4.8%
이 36
 
3.9%
니 27
 
2.9%
어 27
 
2.9%
링 27
 
2.9%
건 23
 
2.5%
Other values (109) 470
50.9%
Uppercase Letter
ValueCountFrequency (%)
E 2
33.3%
A 1
16.7%
C 1
16.7%
N 1
16.7%
G 1
16.7%
Decimal Number
ValueCountFrequency (%)
2 1
50.0%
1 1
50.0%
Close Punctuation
ValueCountFrequency (%)
) 117
100.0%
Open Punctuation
ValueCountFrequency (%)
( 117
100.0%
Space Separator
ValueCountFrequency (%)
5
100.0%
Other Punctuation
ValueCountFrequency (%)
. 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 924
78.6%
Common 245
 
20.9%
Latin 6
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 123
 
13.3%
경 50
 
5.4%
엔 49
 
5.3%
환 48
 
5.2%
지 44
 
4.8%
이 36
 
3.9%
니 27
 
2.9%
어 27
 
2.9%
링 27
 
2.9%
건 23
 
2.5%
Other values (109) 470
50.9%
Common
ValueCountFrequency (%)
) 117
47.8%
( 117
47.8%
5
 
2.0%
. 4
 
1.6%
2 1
 
0.4%
1 1
 
0.4%
Latin
ValueCountFrequency (%)
E 2
33.3%
A 1
16.7%
C 1
16.7%
N 1
16.7%
G 1
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 924
78.6%
ASCII 251
 
21.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 123
 
13.3%
경 50
 
5.4%
엔 49
 
5.3%
환 48
 
5.2%
지 44
 
4.8%
이 36
 
3.9%
니 27
 
2.9%
어 27
 
2.9%
링 27
 
2.9%
건 23
 
2.5%
Other values (109) 470
50.9%
ASCII
ValueCountFrequency (%)
) 117
46.6%
( 117
46.6%
5
 
2.0%
. 4
 
1.6%
E 2
 
0.8%
2 1
 
0.4%
1 1
 
0.4%
A 1
 
0.4%
C 1
 
0.4%
N 1
 
0.4%

최종수정시점
Real number (ℝ)

UNIQUE 

Distinct141
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0114773 × 1013
Minimum2.0030703 × 1013
Maximum2.021012 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2024-04-18T10:13:06.436278image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.0030703 × 1013
5-th percentile2.0030828 × 1013
Q12.0071031 × 1013
median2.0120109 × 1013
Q32.0151113 × 1013
95-th percentile2.0200907 × 1013
Maximum2.021012 × 1013
Range1.7941702 × 1011
Interquartile range (IQR)8.0082061 × 1010

Descriptive statistics

Standard deviation5.364721 × 1010
Coefficient of variation (CV)0.0026670552
Kurtosis-1.0723398
Mean2.0114773 × 1013
Median Absolute Deviation (MAD)4.8990028 × 1010
Skewness0.11660534
Sum2.836183 × 1015
Variance2.8780231 × 1021
MonotonicityNot monotonic
2024-04-18T10:13:06.558927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20200720142850 1
 
0.7%
20161027170148 1
 
0.7%
20081015102740 1
 
0.7%
20080617094436 1
 
0.7%
20081015102606 1
 
0.7%
20081015102429 1
 
0.7%
20200907160509 1
 
0.7%
20181224160514 1
 
0.7%
20141229163235 1
 
0.7%
20090825093045 1
 
0.7%
Other values (131) 131
92.9%
ValueCountFrequency (%)
20030703143332 1
0.7%
20030703154826 1
0.7%
20030818100945 1
0.7%
20030818110712 1
0.7%
20030818112019 1
0.7%
20030818131249 1
0.7%
20030818133750 1
0.7%
20030828103053 1
0.7%
20030828105014 1
0.7%
20031002101654 1
0.7%
ValueCountFrequency (%)
20210120164714 1
0.7%
20210114133248 1
0.7%
20201214111010 1
0.7%
20201109181628 1
0.7%
20200921105221 1
0.7%
20200921105128 1
0.7%
20200921105033 1
0.7%
20200907160509 1
0.7%
20200720142850 1
0.7%
20200720115130 1
0.7%

데이터갱신구분
Categorical

Distinct2
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
I
120 
U
21 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 120
85.1%
U 21
 
14.9%

Length

2024-04-18T10:13:06.666586image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T10:13:06.744752image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 120
85.1%
u 21
 
14.9%

데이터갱신일자
Categorical

IMBALANCE 

Distinct22
Distinct (%)15.6%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
2018-08-31 23:59:59.0
117 
2020-09-23 02:40:00.0
 
3
2019-10-31 02:40:00.0
 
2
2020-07-22 02:40:00.0
 
1
2020-07-10 02:40:00.0
 
1
Other values (17)
17 

Length

Max length21
Median length21
Mean length21
Min length21

Unique

Unique19 ?
Unique (%)13.5%

Sample

1st row2020-07-22 00:23:16.0
2nd row2020-07-22 02:40:00.0
3rd row2018-08-31 23:59:59.0
4th row2018-08-31 23:59:59.0
5th row2018-08-31 23:59:59.0

Common Values

ValueCountFrequency (%)
2018-08-31 23:59:59.0 117
83.0%
2020-09-23 02:40:00.0 3
 
2.1%
2019-10-31 02:40:00.0 2
 
1.4%
2020-07-22 02:40:00.0 1
 
0.7%
2020-07-10 02:40:00.0 1
 
0.7%
2019-05-23 02:21:15.0 1
 
0.7%
2019-01-30 02:40:00.0 1
 
0.7%
2021-01-22 00:23:04.0 1
 
0.7%
2020-04-26 02:40:00.0 1
 
0.7%
2019-12-11 02:40:00.0 1
 
0.7%
Other values (12) 12
 
8.5%

Length

2024-04-18T10:13:06.831897image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
2018-08-31 117
41.5%
23:59:59.0 117
41.5%
02:40:00.0 20
 
7.1%
2020-09-23 3
 
1.1%
2019-10-31 2
 
0.7%
2020-07-22 2
 
0.7%
2020-02-08 1
 
0.4%
00:23:16.0 1
 
0.4%
2021-01-16 1
 
0.4%
2020-09-09 1
 
0.4%
Other values (17) 17
 
6.0%

업태구분명
Categorical

IMBALANCE 

Distinct13
Distinct (%)9.2%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
<NA>
108 
그외 기타 분류안된 모든 서비스업
 
9
분뇨 처리업
 
5
하수처리, 폐기물처리 및 청소관련 서비스업
 
4
환경상담 및 관련 엔지니어링 서비스업
 
3
Other values (8)
12 

Length

Max length23
Median length4
Mean length6.6950355
Min length4

Unique

Unique5 ?
Unique (%)3.5%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 108
76.6%
그외 기타 분류안된 모든 서비스업 9
 
6.4%
분뇨 처리업 5
 
3.5%
하수처리, 폐기물처리 및 청소관련 서비스업 4
 
2.8%
환경상담 및 관련 엔지니어링 서비스업 3
 
2.1%
폐기물 처리 및 오염방지시설 건설업 3
 
2.1%
하수, 폐수 및 분뇨 처리업 2
 
1.4%
기타 서비스업 2
 
1.4%
하수, 분뇨 및 축산폐기물 처리업 1
 
0.7%
고무 및 플라스틱제품 제조업 1
 
0.7%
Other values (3) 3
 
2.1%

Length

2024-04-18T10:13:06.944053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 108
43.9%
서비스업 19
 
7.7%
및 15
 
6.1%
기타 12
 
4.9%
분류안된 10
 
4.1%
그외 10
 
4.1%
모든 9
 
3.7%
분뇨 9
 
3.7%
처리업 9
 
3.7%
하수처리 4
 
1.6%
Other values (17) 41
 
16.7%

좌표정보(x)
Real number (ℝ)

MISSING 

Distinct88
Distinct (%)77.2%
Missing27
Missing (%)19.1%
Infinite0
Infinite (%)0.0%
Mean387934.98
Minimum371768
Maximum405926.8
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2024-04-18T10:13:07.054522image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum371768
5-th percentile378627.29
Q1384179.07
median389082.64
Q3390619.33
95-th percentile397067.32
Maximum405926.8
Range34158.808
Interquartile range (IQR)6440.2617

Descriptive statistics

Standard deviation5959.1376
Coefficient of variation (CV)0.015361176
Kurtosis1.1868881
Mean387934.98
Median Absolute Deviation (MAD)2459.2185
Skewness-0.17105679
Sum44224588
Variance35511321
MonotonicityNot monotonic
2024-04-18T10:13:07.167709image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
382070.620479643 7
 
5.0%
392287.216248758 3
 
2.1%
390012.369265357 3
 
2.1%
389635.415888168 3
 
2.1%
388645.591323777 2
 
1.4%
379809.907618382 2
 
1.4%
384136.095305462 2
 
1.4%
385591.248001476 2
 
1.4%
389281.604853879 2
 
1.4%
390226.191823568 2
 
1.4%
Other values (78) 86
61.0%
(Missing) 27
 
19.1%
ValueCountFrequency (%)
371767.995757446 2
1.4%
372204.188026676 1
0.7%
374396.116306859 1
0.7%
377886.055777011 1
0.7%
378526.329288 1
0.7%
378681.646451458 1
0.7%
378820.309152572 1
0.7%
379584.35365473 1
0.7%
379688.803735537 1
0.7%
379809.907618382 2
1.4%
ValueCountFrequency (%)
405926.804044414 1
0.7%
402094.490620577 1
0.7%
401638.040844059 1
0.7%
401566.670767291 1
0.7%
401391.375537312 1
0.7%
397216.86090988 1
0.7%
396986.803116153 1
0.7%
394035.249095 1
0.7%
393679.154888123 1
0.7%
393607.260373715 2
1.4%

좌표정보(y)
Real number (ℝ)

MISSING 

Distinct88
Distinct (%)77.2%
Missing27
Missing (%)19.1%
Infinite0
Infinite (%)0.0%
Mean189682.65
Minimum176725.71
Maximum206457.79
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.4 KiB
2024-04-18T10:13:07.276497image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum176725.71
5-th percentile180300.48
Q1185570.9
median190001.63
Q3193919.25
95-th percentile199300.98
Maximum206457.79
Range29732.078
Interquartile range (IQR)8348.3482

Descriptive statistics

Standard deviation5960.111
Coefficient of variation (CV)0.031421488
Kurtosis-0.24754771
Mean189682.65
Median Absolute Deviation (MAD)4430.7276
Skewness0.11748279
Sum21623822
Variance35522923
MonotonicityNot monotonic
2024-04-18T10:13:07.409060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
185570.898130941 7
 
5.0%
190001.625744624 3
 
2.1%
197675.929497619 3
 
2.1%
199385.436227116 3
 
2.1%
191655.314131575 2
 
1.4%
182140.508159068 2
 
1.4%
180300.476056401 2
 
1.4%
181425.423838974 2
 
1.4%
193798.979849947 2
 
1.4%
194536.60816259 2
 
1.4%
Other values (78) 86
61.0%
(Missing) 27
 
19.1%
ValueCountFrequency (%)
176725.707798423 1
0.7%
176901.709838 1
0.7%
179085.546176133 2
1.4%
180298.00973516 1
0.7%
180300.476056401 2
1.4%
180660.89704286 1
0.7%
180812.733614603 2
1.4%
180835.76175833 1
0.7%
181177.438378822 1
0.7%
181425.423838974 2
1.4%
ValueCountFrequency (%)
206457.785803911 1
 
0.7%
204244.121180987 1
 
0.7%
199467.347062416 1
 
0.7%
199385.436227116 3
2.1%
199255.499468693 1
 
0.7%
198539.252320493 2
1.4%
197724.229426368 1
 
0.7%
197676.012711115 1
 
0.7%
197675.929497619 3
2.1%
197209.205847723 1
 
0.7%

환경업무구분명
Categorical

CONSTANT 

Distinct1
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
분뇨등설계시공업관리
141 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
분뇨등설계시공업관리 141
100.0%

Length

2024-04-18T10:13:07.542432image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-18T10:13:07.638283image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
분뇨등설계시공업관리 141
100.0%

업종구분명
Categorical

IMBALANCE 

Distinct13
Distinct (%)9.2%
Missing0
Missing (%)0.0%
Memory size1.2 KiB
<NA>
108 
그외 기타 분류안된 모든 서비스업
 
9
분뇨 처리업
 
5
하수처리, 폐기물처리 및 청소관련 서비스업
 
4
환경상담 및 관련 엔지니어링 서비스업
 
3
Other values (8)
12 

Length

Max length23
Median length4
Mean length6.6950355
Min length4

Unique

Unique5 ?
Unique (%)3.5%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 108
76.6%
그외 기타 분류안된 모든 서비스업 9
 
6.4%
분뇨 처리업 5
 
3.5%
하수처리, 폐기물처리 및 청소관련 서비스업 4
 
2.8%
환경상담 및 관련 엔지니어링 서비스업 3
 
2.1%
폐기물 처리 및 오염방지시설 건설업 3
 
2.1%
하수, 폐수 및 분뇨 처리업 2
 
1.4%
기타 서비스업 2
 
1.4%
하수, 분뇨 및 축산폐기물 처리업 1
 
0.7%
고무 및 플라스틱제품 제조업 1
 
0.7%
Other values (3) 3
 
2.1%

Length

2024-04-18T10:13:07.741676image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 108
43.9%
서비스업 19
 
7.7%
및 15
 
6.1%
기타 12
 
4.9%
분류안된 10
 
4.1%
그외 10
 
4.1%
모든 9
 
3.7%
분뇨 9
 
3.7%
처리업 9
 
3.7%
하수처리 4
 
1.6%
Other values (17) 41
 
16.7%

종별명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing141
Missing (%)100.0%
Memory size1.4 KiB

주생산품명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing141
Missing (%)100.0%
Memory size1.4 KiB

배출시설조업시간
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing141
Missing (%)100.0%
Memory size1.4 KiB

배출시설연간가동일수
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing141
Missing (%)100.0%
Memory size1.4 KiB

방지시설조업시간
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing141
Missing (%)100.0%
Memory size1.4 KiB

방지시설연간가동일수
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing141
Missing (%)100.0%
Memory size1.4 KiB

Unnamed: 36
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing141
Missing (%)100.0%
Memory size1.4 KiB

Sample

번호개방서비스명개방서비스id개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(x)좌표정보(y)환경업무구분명업종구분명종별명주생산품명배출시설조업시간배출시설연간가동일수방지시설조업시간방지시설연간가동일수Unnamed: 36
01단독정화조/오수처리시설설계시공업09_30_07_P3330000333000054201900001<NA><NA>1영업/정상11영업<NA><NA><NA><NA>743-0312<NA><NA>부산광역시 해운대구 재송동 1216 벽산이센텀클래스원부산광역시 해운대구 센텀동로 99, 벽산이센텀클래스원 209호 (재송동)48059비알테크놀로지(주)20200720142850I2020-07-22 00:23:16.0<NA>393607.260374188408.076688분뇨등설계시공업관리<NA><NA><NA><NA><NA><NA><NA><NA>
12단독정화조/오수처리시설설계시공업09_30_07_P3330000333000054201300001<NA><NA>1영업/정상11영업<NA><NA><NA><NA>051-912-6661<NA><NA>부산광역시 해운대구 재송동 1212 큐비이센텀부산광역시 해운대구 센텀중앙로 90, 큐비이센텀 2403호 (재송동)48059청우에이스(주)20200720115130U2020-07-22 02:40:00.0<NA>394035.249095188368.648651분뇨등설계시공업관리<NA><NA><NA><NA><NA><NA><NA><NA>
23단독정화조/오수처리시설설계시공업09_30_07_P340000034000005420030000120030826<NA>1영업/정상11영업<NA><NA><NA><NA>051-724-1277<NA>619906부산광역시 기장군 기장읍 청강리 164-11부산광역시 기장군 기장읍 청강로57번길 5619906(주)태광환경이엔지20131202125608I2018-08-31 23:59:59.0<NA>402094.490621195368.068622분뇨등설계시공업관리<NA><NA><NA><NA><NA><NA><NA><NA>
34단독정화조/오수처리시설설계시공업09_30_07_P332000033200005419990000119990726<NA>1영업/정상11영업<NA><NA><NA><NA>051 3375040<NA>616814부산광역시 북구 덕천동 14 부산기능대학 창업보육센타 114호<NA><NA>더난건설(주)20031213121449I2018-08-31 23:59:59.0분뇨 처리업<NA><NA>분뇨등설계시공업관리분뇨 처리업<NA><NA><NA><NA><NA><NA><NA>
45단독정화조/오수처리시설설계시공업09_30_07_P338000033800005420060000120060718<NA>1영업/정상11영업<NA><NA><NA><NA><NA><NA>613802부산광역시 수영구 광안동 116-5 동트레아파트 상가 505호<NA><NA>(주)미래테크닉스20071119143010I2018-08-31 23:59:59.0<NA>392612.309619186862.700819분뇨등설계시공업관리<NA><NA><NA><NA><NA><NA><NA><NA>
56단독정화조/오수처리시설설계시공업09_30_07_P334000033400005420090000120090609<NA>1영업/정상11영업<NA><NA><NA><NA>2942370<NA>604850부산광역시 사하구 하단동 596-34<NA><NA>(주)정원환경개발20200708094106U2020-07-10 02:40:00.0<NA>378820.309153180298.009735분뇨등설계시공업관리<NA><NA><NA><NA><NA><NA><NA><NA>
67단독정화조/오수처리시설설계시공업09_30_07_P336000033600005420100000220100920<NA>1영업/정상11영업<NA><NA><NA><NA>0513058886<NA><NA>부산광역시 강서구 녹산동 172-27부산광역시 강서구 낙동남로622번길 78-2 (녹산동)46736(주)국제환경기술20190521134522I2019-05-23 02:21:15.0<NA>372204.188027180835.761758분뇨등설계시공업관리<NA><NA><NA><NA><NA><NA><NA><NA>
78단독정화조/오수처리시설설계시공업09_30_07_P336000033600005420100000120100802<NA>1영업/정상11영업<NA><NA><NA><NA><NA><NA>618802부산광역시 강서구 강동동 3227-5부산광역시 강서구 제도로 675 (강동동)<NA>주식회사 동양환경20190128163613U2019-01-30 02:40:00.0하수, 폐수 및 분뇨 처리업374396.116307187682.783246분뇨등설계시공업관리하수, 폐수 및 분뇨 처리업<NA><NA><NA><NA><NA><NA><NA>
89단독정화조/오수처리시설설계시공업09_30_07_P3350000335000054202100001<NA><NA>1영업/정상11영업<NA><NA><NA><NA>0519126661<NA><NA>부산광역시 금정구 구서동 1009-4부산광역시 금정구 두실로 37 (구서동)46228주식회사 이피엘20210120164714I2021-01-22 00:23:04.0하수, 폐수 및 분뇨 처리업389848.518466197724.229426분뇨등설계시공업관리하수, 폐수 및 분뇨 처리업<NA><NA><NA><NA><NA><NA><NA>
910단독정화조/오수처리시설설계시공업09_30_07_P335000033500005420070000120070222<NA>1영업/정상11영업<NA><NA><NA><NA>051-519-4556<NA>609817부산광역시 금정구 부곡동 15-23부산광역시 금정구 중앙대로1778번길 27 (부곡동)609817(주)영진환경20141113114255I2018-08-31 23:59:59.0<NA>390604.539437195761.851026분뇨등설계시공업관리<NA><NA><NA><NA><NA><NA><NA><NA>
번호개방서비스명개방서비스id개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(x)좌표정보(y)환경업무구분명업종구분명종별명주생산품명배출시설조업시간배출시설연간가동일수방지시설조업시간방지시설연간가동일수Unnamed: 36
131132단독정화조/오수처리시설설계시공업09_30_07_P3300000330000054200200013<NA><NA>3폐업2폐업20200131<NA><NA><NA>051 5546522<NA><NA>부산광역시 동래구 칠산동 317-3<NA><NA>오케이엔지니어링20130121180200I2018-08-31 23:59:59.0<NA><NA><NA>분뇨등설계시공업관리<NA><NA><NA><NA><NA><NA><NA><NA>
132133단독정화조/오수처리시설설계시공업09_30_07_P3300000330000054200200012<NA><NA>3폐업2폐업20200131<NA><NA><NA>051 5546522<NA><NA>부산광역시 동래구 칠산동 317-3<NA><NA>오케이엔지니어링20130121180115I2018-08-31 23:59:59.0<NA><NA><NA>분뇨등설계시공업관리<NA><NA><NA><NA><NA><NA><NA><NA>
133134단독정화조/오수처리시설설계시공업09_30_07_P330000033000005420010000920010713<NA>3폐업2폐업20050804<NA><NA><NA>051 5573421<NA>607837부산광역시 동래구 온천동 1129-4부산광역시 동래구 금정마을로 120 (온천동)<NA>동아엔바이로(주)20030818131249I2018-08-31 23:59:59.0<NA>388100.30129192130.913902분뇨등설계시공업관리<NA><NA><NA><NA><NA><NA><NA><NA>
134135단독정화조/오수처리시설설계시공업09_30_07_P330000033000005420010000820010604<NA>3폐업2폐업20170123<NA><NA><NA>051 5542990<NA>607829부산광역시 동래구 안락동 792-7<NA><NA>세원환경20170123182959I2018-08-31 23:59:59.0<NA>390764.59659190811.348862분뇨등설계시공업관리<NA><NA><NA><NA><NA><NA><NA><NA>
135136단독정화조/오수처리시설설계시공업09_30_07_P330000033000005419990000719990329<NA>3폐업2폐업20041120<NA><NA><NA>051 5556511<NA>607823부산광역시 동래구 수안동 40-2<NA><NA>한국종항환경산업(주)20030818112019I2018-08-31 23:59:59.0<NA><NA><NA>분뇨등설계시공업관리<NA><NA><NA><NA><NA><NA><NA><NA>
136137단독정화조/오수처리시설설계시공업09_30_07_P330000033000005419980000619980722<NA>3폐업2폐업20031001<NA><NA><NA>051 5075257<NA>607843부산광역시 동래구 온천동 1465-1<NA><NA>(주)메르덤건설20030818110712I2018-08-31 23:59:59.0<NA><NA><NA>분뇨등설계시공업관리<NA><NA><NA><NA><NA><NA><NA><NA>
137138단독정화조/오수처리시설설계시공업09_30_07_P330000033000005419950000519950316<NA>3폐업2폐업20050411<NA><NA><NA>051 5532545<NA>607768부산광역시 동래구 수안동 34-1 새동래3차아파트 6동 202호부산광역시 동래구 온천천로285번길 28, 6동 202호 (수안동,새동래3차아파트)<NA>(주)그린환경20030818133750I2018-08-31 23:59:59.0<NA>389948.103105190500.388095분뇨등설계시공업관리<NA><NA><NA><NA><NA><NA><NA><NA>
138139단독정화조/오수처리시설설계시공업09_30_07_P330000033000005419920000319921201<NA>3폐업2폐업20040510<NA><NA><NA>051 5312267<NA>607830부산광역시 동래구 안락동 448-6<NA><NA>(주)세계건설20030818100945I2018-08-31 23:59:59.0<NA><NA><NA>분뇨등설계시공업관리<NA><NA><NA><NA><NA><NA><NA><NA>
139140단독정화조/오수처리시설설계시공업09_30_07_P330000033000005419920000219921104<NA>3폐업2폐업20200131<NA><NA><NA>051 8617141<NA>607837부산광역시 동래구 온천동 929-13부산광역시 동래구 우장춘로 22-1 (온천동)<NA>(주)나라건업20130121175803I2018-08-31 23:59:59.0<NA>388476.852092192013.163312분뇨등설계시공업관리<NA><NA><NA><NA><NA><NA><NA><NA>
140141단독정화조/오수처리시설설계시공업09_30_07_P330000033000005419830000119830722<NA>3폐업2폐업20080630<NA><NA><NA>051 5562123<NA>607837부산광역시 동래구 온천동 1428-30부산광역시 동래구 충렬대로 91 (온천동)<NA>대영건설(주)20080630173605I2018-08-31 23:59:59.0<NA>388532.936822191774.030081분뇨등설계시공업관리<NA><NA><NA><NA><NA><NA><NA><NA>