Overview

Dataset statistics

Number of variables37
Number of observations70
Missing cells970
Missing cells (%)37.5%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory22.0 KiB
Average record size in memory321.9 B

Variable types

Numeric10
Categorical11
Unsupported12
Text4

Dataset

Description2021-03-01
Author지방행정인허가공개데이터
URLhttps://bigdata.busan.go.kr/data/bigDataDetailView.do?menuCode=M00000000007&hdfs_file_sn=20230901050101123158

Alerts

개방서비스명 has constant value ""Constant
개방서비스id has constant value ""Constant
환경업무구분명 has constant value ""Constant
업태구분명 is highly imbalanced (62.0%)Imbalance
업종구분명 is highly imbalanced (62.0%)Imbalance
인허가취소일자 has 70 (100.0%) missing valuesMissing
폐업일자 has 50 (71.4%) missing valuesMissing
휴업시작일자 has 70 (100.0%) missing valuesMissing
휴업종료일자 has 70 (100.0%) missing valuesMissing
재개업일자 has 70 (100.0%) missing valuesMissing
소재지전화 has 11 (15.7%) missing valuesMissing
소재지면적 has 70 (100.0%) missing valuesMissing
소재지우편번호 has 27 (38.6%) missing valuesMissing
소재지전체주소 has 2 (2.9%) missing valuesMissing
도로명전체주소 has 8 (11.4%) missing valuesMissing
도로명우편번호 has 20 (28.6%) missing valuesMissing
좌표정보(x) has 6 (8.6%) missing valuesMissing
좌표정보(y) has 6 (8.6%) missing valuesMissing
종별명 has 70 (100.0%) missing valuesMissing
주생산품명 has 70 (100.0%) missing valuesMissing
배출시설조업시간 has 70 (100.0%) missing valuesMissing
배출시설연간가동일수 has 70 (100.0%) missing valuesMissing
방지시설조업시간 has 70 (100.0%) missing valuesMissing
방지시설연간가동일수 has 70 (100.0%) missing valuesMissing
Unnamed: 36 has 70 (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
휴업시작일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
휴업종료일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
재개업일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
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 19:53:22.368473
Analysis finished2024-04-16 19:53:22.766071
Duration0.4 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

번호
Real number (ℝ)

UNIQUE 

Distinct70
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.5
Minimum1
Maximum70
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size762.0 B
2024-04-17T04:53:22.831767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile4.45
Q118.25
median35.5
Q352.75
95-th percentile66.55
Maximum70
Range69
Interquartile range (IQR)34.5

Descriptive statistics

Standard deviation20.351085
Coefficient of variation (CV)0.57327
Kurtosis-1.2
Mean35.5
Median Absolute Deviation (MAD)17.5
Skewness0
Sum2485
Variance414.16667
MonotonicityStrictly increasing
2024-04-17T04:53:22.978763image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
1 1
 
1.4%
46 1
 
1.4%
52 1
 
1.4%
51 1
 
1.4%
50 1
 
1.4%
49 1
 
1.4%
48 1
 
1.4%
47 1
 
1.4%
45 1
 
1.4%
54 1
 
1.4%
Other values (60) 60
85.7%
ValueCountFrequency (%)
1 1
1.4%
2 1
1.4%
3 1
1.4%
4 1
1.4%
5 1
1.4%
6 1
1.4%
7 1
1.4%
8 1
1.4%
9 1
1.4%
10 1
1.4%
ValueCountFrequency (%)
70 1
1.4%
69 1
1.4%
68 1
1.4%
67 1
1.4%
66 1
1.4%
65 1
1.4%
64 1
1.4%
63 1
1.4%
62 1
1.4%
61 1
1.4%

개방서비스명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size692.0 B
분뇨수집운반업
70 

Length

Max length7
Median length7
Mean length7
Min length7

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
분뇨수집운반업 70
100.0%

Length

2024-04-17T04:53:23.110740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T04:53:23.216604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
분뇨수집운반업 70
100.0%

개방서비스id
Categorical

CONSTANT 

Distinct1
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size692.0 B
09_30_10_P
70 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row09_30_10_P
2nd row09_30_10_P
3rd row09_30_10_P
4th row09_30_10_P
5th row09_30_10_P

Common Values

ValueCountFrequency (%)
09_30_10_P 70
100.0%

Length

2024-04-17T04:53:23.310956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T04:53:23.399882image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
09_30_10_p 70
100.0%

개방자치단체코드
Real number (ℝ)

Distinct16
Distinct (%)22.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3321142.9
Minimum3250000
Maximum3400000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size762.0 B
2024-04-17T04:53:23.482612image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3250000
5-th percentile3260000
Q13280000
median3320000
Q33367500
95-th percentile3400000
Maximum3400000
Range150000
Interquartile range (IQR)87500

Descriptive statistics

Standard deviation48500.496
Coefficient of variation (CV)0.014603556
Kurtosis-1.2851932
Mean3321142.9
Median Absolute Deviation (MAD)40000
Skewness0.24916653
Sum2.3248 × 108
Variance2.3522981 × 109
MonotonicityNot monotonic
2024-04-17T04:53:23.629073image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
3280000 9
12.9%
3400000 7
10.0%
3260000 6
 
8.6%
3270000 6
 
8.6%
3340000 5
 
7.1%
3320000 5
 
7.1%
3300000 4
 
5.7%
3370000 4
 
5.7%
3380000 4
 
5.7%
3350000 3
 
4.3%
Other values (6) 17
24.3%
ValueCountFrequency (%)
3250000 3
 
4.3%
3260000 6
8.6%
3270000 6
8.6%
3280000 9
12.9%
3290000 3
 
4.3%
3300000 4
5.7%
3310000 3
 
4.3%
3320000 5
7.1%
3330000 3
 
4.3%
3340000 5
7.1%
ValueCountFrequency (%)
3400000 7
10.0%
3390000 3
4.3%
3380000 4
5.7%
3370000 4
5.7%
3360000 2
 
2.9%
3350000 3
4.3%
3340000 5
7.1%
3330000 3
4.3%
3320000 5
7.1%
3310000 3
4.3%

관리번호
Real number (ℝ)

UNIQUE 

Distinct70
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.3211434 × 1017
Minimum3.2500005 × 1017
Maximum3.4000005 × 1017
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size762.0 B
2024-04-17T04:53:23.763920image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.2500005 × 1017
5-th percentile3.2600005 × 1017
Q13.2800005 × 1017
median3.3200005 × 1017
Q33.3675005 × 1017
95-th percentile3.4000005 × 1017
Maximum3.4000005 × 1017
Range1.5 × 1016
Interquartile range (IQR)8.75 × 1015

Descriptive statistics

Standard deviation4.8500496 × 1015
Coefficient of variation (CV)0.014603554
Kurtosis-1.2851932
Mean3.3211434 × 1017
Median Absolute Deviation (MAD)4 × 1015
Skewness0.24916653
Sum4.8012596 × 1018
Variance2.3522981 × 1031
MonotonicityNot monotonic
2024-04-17T04:53:23.907135image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
340000053199900001 1
 
1.4%
325000053199200001 1
 
1.4%
340000053199300005 1
 
1.4%
340000053199900002 1
 
1.4%
330000053199200001 1
 
1.4%
330000053198400001 1
 
1.4%
325000053198400001 1
 
1.4%
325000053198400002 1
 
1.4%
326000053199200001 1
 
1.4%
340000053199300002 1
 
1.4%
Other values (60) 60
85.7%
ValueCountFrequency (%)
325000053198400001 1
1.4%
325000053198400002 1
1.4%
325000053199200001 1
1.4%
326000053199200001 1
1.4%
326000053199200002 1
1.4%
326000053199200003 1
1.4%
326000053199700001 1
1.4%
326000053200200001 1
1.4%
326000053201700001 1
1.4%
327000053200000003 1
1.4%
ValueCountFrequency (%)
340000053199900002 1
1.4%
340000053199900001 1
1.4%
340000053199300005 1
1.4%
340000053199300004 1
1.4%
340000053199300003 1
1.4%
340000053199300002 1
1.4%
340000053188300001 1
1.4%
339000053199500003 1
1.4%
339000053199500002 1
1.4%
339000053199500001 1
1.4%

인허가일자
Real number (ℝ)

Distinct55
Distinct (%)78.6%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean19960900
Minimum19780704
Maximum20170721
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size762.0 B
2024-04-17T04:53:24.050661image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19780704
5-th percentile19831228
Q119920331
median19940722
Q320007774
95-th percentile20135754
Maximum20170721
Range390017
Interquartile range (IQR)87442.5

Descriptive statistics

Standard deviation92514.795
Coefficient of variation (CV)0.0046348007
Kurtosis-0.33780071
Mean19960900
Median Absolute Deviation (MAD)50198.5
Skewness0.36952491
Sum1.397263 × 109
Variance8.5589873 × 109
MonotonicityNot monotonic
2024-04-17T04:53:24.202469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
19960109 3
 
4.3%
19840419 3
 
4.3%
19990921 3
 
4.3%
19831230 2
 
2.9%
20000101 2
 
2.9%
19930624 2
 
2.9%
19921231 2
 
2.9%
19920107 2
 
2.9%
19920331 2
 
2.9%
19930130 2
 
2.9%
Other values (45) 47
67.1%
ValueCountFrequency (%)
19780704 1
 
1.4%
19800125 1
 
1.4%
19831031 1
 
1.4%
19831226 1
 
1.4%
19831230 2
2.9%
19840101 1
 
1.4%
19840331 1
 
1.4%
19840415 1
 
1.4%
19840419 3
4.3%
19850601 1
 
1.4%
ValueCountFrequency (%)
20170721 1
1.4%
20141104 1
1.4%
20140211 1
1.4%
20140113 1
1.4%
20130426 1
1.4%
20121206 1
1.4%
20121128 1
1.4%
20121126 1
1.4%
20090409 1
1.4%
20061228 1
1.4%

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing70
Missing (%)100.0%
Memory size762.0 B

영업상태구분코드
Categorical

Distinct3
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Memory size692.0 B
1
48 
3
20 
4
 
2

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 (%)
1 48
68.6%
3 20
28.6%
4 2
 
2.9%

Length

2024-04-17T04:53:24.344547image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T04:53:24.454117image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 48
68.6%
3 20
28.6%
4 2
 
2.9%

영업상태명
Categorical

Distinct3
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Memory size692.0 B
영업/정상
48 
폐업
20 
취소/말소/만료/정지/중지
 
2

Length

Max length14
Median length5
Mean length4.4
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 (%)
영업/정상 48
68.6%
폐업 20
28.6%
취소/말소/만료/정지/중지 2
 
2.9%

Length

2024-04-17T04:53:24.569460image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T04:53:24.687587image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 48
68.6%
폐업 20
28.6%
취소/말소/만료/정지/중지 2
 
2.9%

상세영업상태코드
Categorical

Distinct3
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Memory size692.0 B
11
48 
2
20 
4
 
2

Length

Max length2
Median length2
Mean length1.6857143
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
11 48
68.6%
2 20
28.6%
4 2
 
2.9%

Length

2024-04-17T04:53:24.789440image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T04:53:24.905605image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
11 48
68.6%
2 20
28.6%
4 2
 
2.9%

상세영업상태명
Categorical

Distinct3
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Memory size692.0 B
영업
48 
폐업
20 
폐쇄
 
2

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업 48
68.6%
폐업 20
28.6%
폐쇄 2
 
2.9%

Length

2024-04-17T04:53:25.012978image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T04:53:25.133233image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업 48
68.6%
폐업 20
28.6%
폐쇄 2
 
2.9%

폐업일자
Real number (ℝ)

MISSING 

Distinct16
Distinct (%)80.0%
Missing50
Missing (%)71.4%
Infinite0
Infinite (%)0.0%
Mean20078680
Minimum19920331
Maximum20190725
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size762.0 B
2024-04-17T04:53:25.313952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum19920331
5-th percentile19996980
Q120030739
median20085366
Q320123461
95-th percentile20171897
Maximum20190725
Range270394
Interquartile range (IQR)92722.25

Descriptive statistics

Standard deviation71325.323
Coefficient of variation (CV)0.0035522915
Kurtosis-0.42693457
Mean20078680
Median Absolute Deviation (MAD)44799.5
Skewness-0.36750241
Sum4.0157359 × 108
Variance5.0873017 × 109
MonotonicityNot monotonic
2024-04-17T04:53:25.473100image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=16)
ValueCountFrequency (%)
20121210 3
 
4.3%
20160415 2
 
2.9%
20050524 2
 
2.9%
20001024 1
 
1.4%
19920331 1
 
1.4%
20040615 1
 
1.4%
20190725 1
 
1.4%
20001014 1
 
1.4%
20130214 1
 
1.4%
20001110 1
 
1.4%
Other values (6) 6
 
8.6%
(Missing) 50
71.4%
ValueCountFrequency (%)
19920331 1
1.4%
20001014 1
1.4%
20001024 1
1.4%
20001101 1
1.4%
20001110 1
1.4%
20040615 1
1.4%
20050107 1
1.4%
20050524 2
2.9%
20080422 1
1.4%
20090309 1
1.4%
ValueCountFrequency (%)
20190725 1
 
1.4%
20170906 1
 
1.4%
20160415 2
2.9%
20130214 1
 
1.4%
20121210 3
4.3%
20110208 1
 
1.4%
20090309 1
 
1.4%
20080422 1
 
1.4%
20050524 2
2.9%
20050107 1
 
1.4%

휴업시작일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing70
Missing (%)100.0%
Memory size762.0 B

휴업종료일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing70
Missing (%)100.0%
Memory size762.0 B

재개업일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing70
Missing (%)100.0%
Memory size762.0 B

소재지전화
Text

MISSING 

Distinct54
Distinct (%)91.5%
Missing11
Missing (%)15.7%
Memory size692.0 B
2024-04-17T04:53:25.682153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length11
Min length8

Characters and Unicode

Total characters649
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

Unique50 ?
Unique (%)84.7%

Sample

1st row051-722-1488
2nd row051-722-6660
3rd row0513133623
4th row0513017777
5th row051-322-5400
ValueCountFrequency (%)
051 12
 
15.6%
0515583535 3
 
3.9%
7222275 2
 
2.6%
051-637-4173 2
 
2.6%
051-243-4448 2
 
2.6%
051-253-2048 1
 
1.3%
8920087 1
 
1.3%
7226565 1
 
1.3%
051-722-1488 1
 
1.3%
051-245-3959 1
 
1.3%
Other values (51) 51
66.2%
2024-04-17T04:53:26.013113image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 95
14.6%
1 89
13.7%
0 88
13.6%
2 72
11.1%
- 57
8.8%
3 50
7.7%
4 48
7.4%
7 41
6.3%
6 37
 
5.7%
8 29
 
4.5%
Other values (3) 43
6.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 566
87.2%
Dash Punctuation 57
 
8.8%
Space Separator 23
 
3.5%
Close Punctuation 3
 
0.5%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 95
16.8%
1 89
15.7%
0 88
15.5%
2 72
12.7%
3 50
8.8%
4 48
8.5%
7 41
7.2%
6 37
 
6.5%
8 29
 
5.1%
9 17
 
3.0%
Dash Punctuation
ValueCountFrequency (%)
- 57
100.0%
Space Separator
ValueCountFrequency (%)
23
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 649
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 95
14.6%
1 89
13.7%
0 88
13.6%
2 72
11.1%
- 57
8.8%
3 50
7.7%
4 48
7.4%
7 41
6.3%
6 37
 
5.7%
8 29
 
4.5%
Other values (3) 43
6.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 649
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 95
14.6%
1 89
13.7%
0 88
13.6%
2 72
11.1%
- 57
8.8%
3 50
7.7%
4 48
7.4%
7 41
6.3%
6 37
 
5.7%
8 29
 
4.5%
Other values (3) 43
6.6%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing70
Missing (%)100.0%
Memory size762.0 B

소재지우편번호
Real number (ℝ)

MISSING 

Distinct27
Distinct (%)62.8%
Missing27
Missing (%)38.6%
Infinite0
Infinite (%)0.0%
Mean610757.07
Minimum600816
Maximum619903
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size762.0 B
2024-04-17T04:53:26.174952image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum600816
5-th percentile600916.7
Q1604834
median611713
Q3616929
95-th percentile619903
Maximum619903
Range19087
Interquartile range (IQR)12095

Descriptive statistics

Standard deviation6608.2264
Coefficient of variation (CV)0.01081973
Kurtosis-1.3323138
Mean610757.07
Median Absolute Deviation (MAD)6011
Skewness-0.094059287
Sum26262554
Variance43668656
MonotonicityNot monotonic
2024-04-17T04:53:26.339089image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=27)
ValueCountFrequency (%)
619903 7
 
10.0%
608828 3
 
4.3%
600816 3
 
4.3%
614859 2
 
2.9%
611713 2
 
2.9%
609311 2
 
2.9%
601823 2
 
2.9%
607823 2
 
2.9%
601836 2
 
2.9%
602093 1
 
1.4%
Other values (17) 17
24.3%
(Missing) 27
38.6%
ValueCountFrequency (%)
600816 3
4.3%
601823 2
2.9%
601836 2
2.9%
602093 1
 
1.4%
602821 1
 
1.4%
602826 1
 
1.4%
604818 1
 
1.4%
604850 1
 
1.4%
604866 1
 
1.4%
607823 2
2.9%
ValueCountFrequency (%)
619903 7
10.0%
617825 1
 
1.4%
617724 1
 
1.4%
617070 1
 
1.4%
617052 1
 
1.4%
616806 1
 
1.4%
614859 2
 
2.9%
614802 1
 
1.4%
614010 1
 
1.4%
613814 1
 
1.4%

소재지전체주소
Text

MISSING 

Distinct49
Distinct (%)72.1%
Missing2
Missing (%)2.9%
Memory size692.0 B
2024-04-17T04:53:26.617791image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length28.5
Mean length22.485294
Min length18

Characters and Unicode

Total characters1529
Distinct characters115
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

Unique34 ?
Unique (%)50.0%

Sample

1st row부산광역시 기장군 기장읍 대라리 406-3
2nd row부산광역시 기장군 기장읍 대라리 406-3
3rd row부산광역시 사상구 감전동 116-7 삼주오피스텔
4th row부산광역시 사상구 삼락동 71-1
5th row부산광역시 사상구 엄궁동 643-8 철강판매단지 202호
ValueCountFrequency (%)
부산광역시 68
 
21.7%
영도구 9
 
2.9%
사상구 7
 
2.2%
기장읍 7
 
2.2%
기장군 7
 
2.2%
대라리 7
 
2.2%
청학동 7
 
2.2%
서구 6
 
1.9%
부산진구 5
 
1.6%
동구 5
 
1.6%
Other values (105) 186
59.2%
2024-04-17T04:53:27.041936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
249
 
16.3%
부 75
 
4.9%
산 74
 
4.8%
동 73
 
4.8%
광 69
 
4.5%
역 68
 
4.4%
시 68
 
4.4%
구 66
 
4.3%
1 66
 
4.3%
- 62
 
4.1%
Other values (105) 659
43.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 893
58.4%
Decimal Number 316
 
20.7%
Space Separator 249
 
16.3%
Dash Punctuation 62
 
4.1%
Uppercase Letter 6
 
0.4%
Open Punctuation 1
 
0.1%
Close Punctuation 1
 
0.1%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
부 75
 
8.4%
산 74
 
8.3%
동 73
 
8.2%
광 69
 
7.7%
역 68
 
7.6%
시 68
 
7.6%
구 66
 
7.4%
대 18
 
2.0%
장 15
 
1.7%
서 14
 
1.6%
Other values (86) 353
39.5%
Decimal Number
ValueCountFrequency (%)
1 66
20.9%
4 38
12.0%
6 38
12.0%
3 37
11.7%
2 36
11.4%
7 25
 
7.9%
0 25
 
7.9%
5 22
 
7.0%
8 15
 
4.7%
9 14
 
4.4%
Uppercase Letter
ValueCountFrequency (%)
L 2
33.3%
G 2
33.3%
P 1
16.7%
O 1
16.7%
Space Separator
ValueCountFrequency (%)
249
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 62
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%
Other Punctuation
ValueCountFrequency (%)
/ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 893
58.4%
Common 630
41.2%
Latin 6
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
부 75
 
8.4%
산 74
 
8.3%
동 73
 
8.2%
광 69
 
7.7%
역 68
 
7.6%
시 68
 
7.6%
구 66
 
7.4%
대 18
 
2.0%
장 15
 
1.7%
서 14
 
1.6%
Other values (86) 353
39.5%
Common
ValueCountFrequency (%)
249
39.5%
1 66
 
10.5%
- 62
 
9.8%
4 38
 
6.0%
6 38
 
6.0%
3 37
 
5.9%
2 36
 
5.7%
7 25
 
4.0%
0 25
 
4.0%
5 22
 
3.5%
Other values (5) 32
 
5.1%
Latin
ValueCountFrequency (%)
L 2
33.3%
G 2
33.3%
P 1
16.7%
O 1
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 893
58.4%
ASCII 636
41.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
249
39.2%
1 66
 
10.4%
- 62
 
9.7%
4 38
 
6.0%
6 38
 
6.0%
3 37
 
5.8%
2 36
 
5.7%
7 25
 
3.9%
0 25
 
3.9%
5 22
 
3.5%
Other values (9) 38
 
6.0%
Hangul
ValueCountFrequency (%)
부 75
 
8.4%
산 74
 
8.3%
동 73
 
8.2%
광 69
 
7.7%
역 68
 
7.6%
시 68
 
7.6%
구 66
 
7.4%
대 18
 
2.0%
장 15
 
1.7%
서 14
 
1.6%
Other values (86) 353
39.5%

도로명전체주소
Text

MISSING 

Distinct42
Distinct (%)67.7%
Missing8
Missing (%)11.4%
Memory size692.0 B
2024-04-17T04:53:27.280972image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length46
Median length38
Mean length29.032258
Min length21

Characters and Unicode

Total characters1800
Distinct characters140
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

Unique27 ?
Unique (%)43.5%

Sample

1st row부산광역시 기장군 기장읍 차성로 265
2nd row부산광역시 기장군 기장읍 차성로 265
3rd row부산광역시 사상구 괘감로 131, 513호 (감전동)
4th row부산광역시 사상구 낙동대로 1514 (삼락동)
5th row부산광역시 사상구 강변대로532번길 41, 철강판매단지 202호 (엄궁동)
ValueCountFrequency (%)
부산광역시 62
 
17.5%
영도구 9
 
2.5%
청학동 7
 
2.0%
사상구 7
 
2.0%
태종로 6
 
1.7%
중앙대로 6
 
1.7%
290 5
 
1.4%
태종로주유소 5
 
1.4%
서구 5
 
1.4%
2층 5
 
1.4%
Other values (125) 238
67.0%
2024-04-17T04:53:27.881495image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
299
 
16.6%
동 75
 
4.2%
부 68
 
3.8%
로 68
 
3.8%
산 67
 
3.7%
광 64
 
3.6%
역 63
 
3.5%
시 63
 
3.5%
구 62
 
3.4%
( 59
 
3.3%
Other values (130) 912
50.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1068
59.3%
Space Separator 299
 
16.6%
Decimal Number 262
 
14.6%
Open Punctuation 59
 
3.3%
Close Punctuation 59
 
3.3%
Other Punctuation 39
 
2.2%
Dash Punctuation 8
 
0.4%
Uppercase Letter 6
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 75
 
7.0%
부 68
 
6.4%
로 68
 
6.4%
산 67
 
6.3%
광 64
 
6.0%
역 63
 
5.9%
시 63
 
5.9%
구 62
 
5.8%
대 27
 
2.5%
호 20
 
1.9%
Other values (110) 491
46.0%
Decimal Number
ValueCountFrequency (%)
1 57
21.8%
2 45
17.2%
0 33
12.6%
3 25
9.5%
5 25
9.5%
4 25
9.5%
6 25
9.5%
9 11
 
4.2%
7 10
 
3.8%
8 6
 
2.3%
Uppercase Letter
ValueCountFrequency (%)
L 2
33.3%
G 2
33.3%
P 1
16.7%
O 1
16.7%
Other Punctuation
ValueCountFrequency (%)
, 38
97.4%
/ 1
 
2.6%
Space Separator
ValueCountFrequency (%)
299
100.0%
Open Punctuation
ValueCountFrequency (%)
( 59
100.0%
Close Punctuation
ValueCountFrequency (%)
) 59
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1068
59.3%
Common 726
40.3%
Latin 6
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 75
 
7.0%
부 68
 
6.4%
로 68
 
6.4%
산 67
 
6.3%
광 64
 
6.0%
역 63
 
5.9%
시 63
 
5.9%
구 62
 
5.8%
대 27
 
2.5%
호 20
 
1.9%
Other values (110) 491
46.0%
Common
ValueCountFrequency (%)
299
41.2%
( 59
 
8.1%
) 59
 
8.1%
1 57
 
7.9%
2 45
 
6.2%
, 38
 
5.2%
0 33
 
4.5%
3 25
 
3.4%
5 25
 
3.4%
4 25
 
3.4%
Other values (6) 61
 
8.4%
Latin
ValueCountFrequency (%)
L 2
33.3%
G 2
33.3%
P 1
16.7%
O 1
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1068
59.3%
ASCII 732
40.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
299
40.8%
( 59
 
8.1%
) 59
 
8.1%
1 57
 
7.8%
2 45
 
6.1%
, 38
 
5.2%
0 33
 
4.5%
3 25
 
3.4%
5 25
 
3.4%
4 25
 
3.4%
Other values (10) 67
 
9.2%
Hangul
ValueCountFrequency (%)
동 75
 
7.0%
부 68
 
6.4%
로 68
 
6.4%
산 67
 
6.3%
광 64
 
6.0%
역 63
 
5.9%
시 63
 
5.9%
구 62
 
5.8%
대 27
 
2.5%
호 20
 
1.9%
Other values (110) 491
46.0%

도로명우편번호
Real number (ℝ)

MISSING 

Distinct32
Distinct (%)64.0%
Missing20
Missing (%)28.6%
Infinite0
Infinite (%)0.0%
Mean306001.36
Minimum46702
Maximum619903
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size762.0 B
2024-04-17T04:53:27.993080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum46702
5-th percentile47004.05
Q148849
median49366
Q3607083.75
95-th percentile616490.3
Maximum619903
Range573201
Interquartile range (IQR)558234.75

Descriptive statistics

Standard deviation281970.95
Coefficient of variation (CV)0.9214696
Kurtosis-2.0552475
Mean306001.36
Median Absolute Deviation (MAD)2511
Skewness0.16623085
Sum15300068
Variance7.9507616 × 1010
MonotonicityNot monotonic
2024-04-17T04:53:28.134439image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=32)
ValueCountFrequency (%)
49021 5
 
7.1%
600816 3
 
4.3%
608828 3
 
4.3%
49476 2
 
2.9%
601823 2
 
2.9%
49256 2
 
2.9%
601836 2
 
2.9%
47846 2
 
2.9%
48001 2
 
2.9%
619903 2
 
2.9%
Other values (22) 25
35.7%
(Missing) 20
28.6%
ValueCountFrequency (%)
46702 1
1.4%
46728 1
1.4%
46982 1
1.4%
47031 2
2.9%
47270 1
1.4%
47846 2
2.9%
48001 2
2.9%
48268 1
1.4%
48285 1
1.4%
48792 1
1.4%
ValueCountFrequency (%)
619903 2
2.9%
617825 1
 
1.4%
614859 2
2.9%
614802 1
 
1.4%
611713 2
2.9%
611071 1
 
1.4%
608828 3
4.3%
607823 1
 
1.4%
604866 1
 
1.4%
604850 1
 
1.4%

사업장명
Text

Distinct64
Distinct (%)91.4%
Missing0
Missing (%)0.0%
Memory size692.0 B
2024-04-17T04:53:28.436635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length29
Median length17
Mean length6.9285714
Min length4

Characters and Unicode

Total characters485
Distinct characters88
Distinct categories6 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique58 ?
Unique (%)82.9%

Sample

1st row차성정화
2nd row(주)신라정화사
3rd row북부위생(주)
4th row(주)유성정화
5th row사북환경
ValueCountFrequency (%)
주)오성정화 2
 
2.6%
사북환경 2
 
2.6%
주)북부산정화 2
 
2.6%
해동환경(주)한일영업소 2
 
2.6%
주)사하환경 2
 
2.6%
주)유성정화 2
 
2.6%
동래정화(주 2
 
2.6%
주)광안환경 2
 
2.6%
차성정화 1
 
1.3%
동구위생 1
 
1.3%
Other values (58) 58
76.3%
2024-04-17T04:53:28.801943image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
( 45
 
9.3%
) 44
 
9.1%
주 42
 
8.7%
정 40
 
8.2%
화 39
 
8.0%
사 17
 
3.5%
동 16
 
3.3%
생 15
 
3.1%
위 15
 
3.1%
환 13
 
2.7%
Other values (78) 199
41.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 381
78.6%
Open Punctuation 45
 
9.3%
Close Punctuation 44
 
9.1%
Space Separator 6
 
1.2%
Decimal Number 6
 
1.2%
Other Punctuation 3
 
0.6%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 42
 
11.0%
정 40
 
10.5%
화 39
 
10.2%
사 17
 
4.5%
동 16
 
4.2%
생 15
 
3.9%
위 15
 
3.9%
환 13
 
3.4%
경 13
 
3.4%
부 12
 
3.1%
Other values (69) 159
41.7%
Decimal Number
ValueCountFrequency (%)
1 2
33.3%
8 1
16.7%
4 1
16.7%
2 1
16.7%
3 1
16.7%
Open Punctuation
ValueCountFrequency (%)
( 45
100.0%
Close Punctuation
ValueCountFrequency (%)
) 44
100.0%
Space Separator
ValueCountFrequency (%)
6
100.0%
Other Punctuation
ValueCountFrequency (%)
, 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 381
78.6%
Common 104
 
21.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 42
 
11.0%
정 40
 
10.5%
화 39
 
10.2%
사 17
 
4.5%
동 16
 
4.2%
생 15
 
3.9%
위 15
 
3.9%
환 13
 
3.4%
경 13
 
3.4%
부 12
 
3.1%
Other values (69) 159
41.7%
Common
ValueCountFrequency (%)
( 45
43.3%
) 44
42.3%
6
 
5.8%
, 3
 
2.9%
1 2
 
1.9%
8 1
 
1.0%
4 1
 
1.0%
2 1
 
1.0%
3 1
 
1.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 381
78.6%
ASCII 104
 
21.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
( 45
43.3%
) 44
42.3%
6
 
5.8%
, 3
 
2.9%
1 2
 
1.9%
8 1
 
1.0%
4 1
 
1.0%
2 1
 
1.0%
3 1
 
1.0%
Hangul
ValueCountFrequency (%)
주 42
 
11.0%
정 40
 
10.5%
화 39
 
10.2%
사 17
 
4.5%
동 16
 
4.2%
생 15
 
3.9%
위 15
 
3.9%
환 13
 
3.4%
경 13
 
3.4%
부 12
 
3.1%
Other values (69) 159
41.7%

최종수정시점
Real number (ℝ)

UNIQUE 

Distinct70
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean2.0172508 × 1013
Minimum2.0000915 × 1013
Maximum2.0210122 × 1013
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size762.0 B
2024-04-17T04:53:28.955487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2.0000915 × 1013
5-th percentile2.0070764 × 1013
Q12.0173533 × 1013
median2.0200466 × 1013
Q32.0200994 × 1013
95-th percentile2.0201211 × 1013
Maximum2.0210122 × 1013
Range2.0920706 × 1011
Interquartile range (IQR)2.7460221 × 1010

Descriptive statistics

Standard deviation5.0112377 × 1010
Coefficient of variation (CV)0.0024841917
Kurtosis2.4381496
Mean2.0172508 × 1013
Median Absolute Deviation (MAD)7.424948 × 108
Skewness-1.8485388
Sum1.4120756 × 1015
Variance2.5112504 × 1021
MonotonicityNot monotonic
2024-04-17T04:53:29.081883image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
20161228131650 1
 
1.4%
20200701144631 1
 
1.4%
20030902145327 1
 
1.4%
20130214093116 1
 
1.4%
20120118152514 1
 
1.4%
20120118152423 1
 
1.4%
20191011172049 1
 
1.4%
20200701144626 1
 
1.4%
20201215171204 1
 
1.4%
20110208152437 1
 
1.4%
Other values (60) 60
85.7%
ValueCountFrequency (%)
20000915113537 1
1.4%
20030902142008 1
1.4%
20030902145327 1
1.4%
20070712144619 1
1.4%
20070828095748 1
1.4%
20080110150758 1
1.4%
20080422095223 1
1.4%
20080904171515 1
1.4%
20090204162904 1
1.4%
20110208151451 1
1.4%
ValueCountFrequency (%)
20210122171346 1
1.4%
20201215171204 1
1.4%
20201214110645 1
1.4%
20201214110401 1
1.4%
20201208173619 1
1.4%
20201208142826 1
1.4%
20201208142113 1
1.4%
20201208141855 1
1.4%
20201208141807 1
1.4%
20201208141647 1
1.4%

데이터갱신구분
Categorical

Distinct2
Distinct (%)2.9%
Missing0
Missing (%)0.0%
Memory size692.0 B
U
47 
I
23 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
U 47
67.1%
I 23
32.9%

Length

2024-04-17T04:53:29.206459image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T04:53:29.296500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
u 47
67.1%
i 23
32.9%

데이터갱신일자
Categorical

Distinct31
Distinct (%)44.3%
Missing0
Missing (%)0.0%
Memory size692.0 B
2018-08-31 23:59:59.0
21 
2020-09-18 02:40:00.0
8 
2020-12-10 02:40:00.0
7 
2019-08-30 02:40:00.0
 
2
2020-07-03 02:40:00.0
 
2
Other values (26)
30 

Length

Max length21
Median length21
Mean length21
Min length21

Unique

Unique22 ?
Unique (%)31.4%

Sample

1st row2018-08-31 23:59:59.0
2nd row2020-06-17 02:40:00.0
3rd row2018-12-13 02:40:00.0
4th row2020-06-19 02:40:00.0
5th row2020-10-24 02:40:00.0

Common Values

ValueCountFrequency (%)
2018-08-31 23:59:59.0 21
30.0%
2020-09-18 02:40:00.0 8
 
11.4%
2020-12-10 02:40:00.0 7
 
10.0%
2019-08-30 02:40:00.0 2
 
2.9%
2020-07-03 02:40:00.0 2
 
2.9%
2020-07-11 02:40:00.0 2
 
2.9%
2020-12-16 02:40:00.0 2
 
2.9%
2019-10-16 00:22:51.0 2
 
2.9%
2020-12-02 02:40:00.0 2
 
2.9%
2020-06-24 02:40:00.0 1
 
1.4%
Other values (21) 21
30.0%

Length

2024-04-17T04:53:29.387529image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
02:40:00.0 46
32.9%
23:59:59.0 22
15.7%
2018-08-31 21
15.0%
2020-09-18 8
 
5.7%
2020-12-10 7
 
5.0%
2019-10-16 3
 
2.1%
2020-12-16 2
 
1.4%
00:22:51.0 2
 
1.4%
2020-12-02 2
 
1.4%
2020-07-11 2
 
1.4%
Other values (23) 25
17.9%

업태구분명
Categorical

IMBALANCE 

Distinct5
Distinct (%)7.1%
Missing0
Missing (%)0.0%
Memory size692.0 B
<NA>
59 
분뇨 처리업
6 
하수처리, 폐기물처리 및 청소관련 서비스업
 
3
하수, 폐수 및 분뇨 처리업
 
1
폐기물 수집운반업
 
1

Length

Max length23
Median length4
Mean length5.2142857
Min length4

Unique

Unique2 ?
Unique (%)2.9%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 59
84.3%
분뇨 처리업 6
 
8.6%
하수처리, 폐기물처리 및 청소관련 서비스업 3
 
4.3%
하수, 폐수 및 분뇨 처리업 1
 
1.4%
폐기물 수집운반업 1
 
1.4%

Length

2024-04-17T04:53:29.504946image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T04:53:29.609341image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 59
63.4%
분뇨 7
 
7.5%
처리업 7
 
7.5%
및 4
 
4.3%
하수처리 3
 
3.2%
폐기물처리 3
 
3.2%
청소관련 3
 
3.2%
서비스업 3
 
3.2%
하수 1
 
1.1%
폐수 1
 
1.1%
Other values (2) 2
 
2.2%

좌표정보(x)
Real number (ℝ)

MISSING 

Distinct38
Distinct (%)59.4%
Missing6
Missing (%)8.6%
Infinite0
Infinite (%)0.0%
Mean387139.22
Minimum372685.06
Maximum401638.04
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size762.0 B
2024-04-17T04:53:29.709245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum372685.06
5-th percentile379148.52
Q1382874.72
median387301.15
Q3390104.87
95-th percentile400459.3
Maximum401638.04
Range28952.98
Interquartile range (IQR)7230.1582

Descriptive statistics

Standard deviation5836.3375
Coefficient of variation (CV)0.015075552
Kurtosis0.79471993
Mean387139.22
Median Absolute Deviation (MAD)2803.7209
Skewness0.5054856
Sum24776910
Variance34062836
MonotonicityNot monotonic
2024-04-17T04:53:29.816281image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=38)
ValueCountFrequency (%)
387553.854312358 5
 
7.1%
390104.874018285 4
 
5.7%
385770.249057193 3
 
4.3%
389498.499881834 3
 
4.3%
386101.6969961 3
 
4.3%
381144.366063273 3
 
4.3%
389078.690511467 3
 
4.3%
380678.16763994 2
 
2.9%
395177.565954913 2
 
2.9%
386651.248332511 2
 
2.9%
Other values (28) 34
48.6%
(Missing) 6
 
8.6%
ValueCountFrequency (%)
372685.061202322 1
 
1.4%
378946.523907966 1
 
1.4%
379143.35099743 2
2.9%
379177.817491247 1
 
1.4%
379573.066234446 1
 
1.4%
380624.551554055 2
2.9%
380678.16763994 2
2.9%
381144.366063273 3
4.3%
381760.147631373 1
 
1.4%
381788.610751429 1
 
1.4%
ValueCountFrequency (%)
401638.040844059 2
2.9%
401391.375537312 2
2.9%
395177.565954913 2
2.9%
393339.479016586 1
 
1.4%
392732.201545831 1
 
1.4%
392552.298493486 1
 
1.4%
392207.132591733 1
 
1.4%
392016.787788396 1
 
1.4%
390786.529323286 2
2.9%
390104.874018285 4
5.7%

좌표정보(y)
Real number (ℝ)

MISSING 

Distinct38
Distinct (%)59.4%
Missing6
Missing (%)8.6%
Infinite0
Infinite (%)0.0%
Mean185202.77
Minimum174595.56
Maximum196432
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size762.0 B
2024-04-17T04:53:30.019105image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum174595.56
5-th percentile177442.82
Q1179875.12
median184609.44
Q3190388.18
95-th percentile195703.35
Maximum196432
Range21836.438
Interquartile range (IQR)10513.063

Descriptive statistics

Standard deviation5886.1188
Coefficient of variation (CV)0.031782024
Kurtosis-0.95512168
Mean185202.77
Median Absolute Deviation (MAD)5022.4873
Skewness0.31284234
Sum11852977
Variance34646394
MonotonicityNot monotonic
2024-04-17T04:53:30.154725image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=38)
ValueCountFrequency (%)
179586.953378975 5
 
7.1%
190388.180325274 4
 
5.7%
181062.506282925 3
 
4.3%
190511.175423307 3
 
4.3%
182087.688303863 3
 
4.3%
185965.49006812 3
 
4.3%
183697.200816703 3
 
4.3%
186308.485624343 2
 
2.9%
193400.758919247 2
 
2.9%
183362.036248495 2
 
2.9%
Other values (28) 34
48.6%
(Missing) 6
 
8.6%
ValueCountFrequency (%)
174595.56005647 1
1.4%
176065.871770331 1
1.4%
176709.756119219 1
1.4%
177442.817428718 2
2.9%
178275.156929713 1
1.4%
178279.998453376 1
1.4%
178433.306634037 1
1.4%
178818.39014774 1
1.4%
178947.759943428 1
1.4%
179170.707601447 1
1.4%
ValueCountFrequency (%)
196431.998159584 2
2.9%
195774.67538181 2
2.9%
195299.187228319 2
2.9%
193400.758919247 2
2.9%
192606.711128673 1
 
1.4%
192419.618476909 1
 
1.4%
190989.969028434 1
 
1.4%
190511.175423307 3
4.3%
190388.180325274 4
5.7%
190038.493733291 2
2.9%

환경업무구분명
Categorical

CONSTANT 

Distinct1
Distinct (%)1.4%
Missing0
Missing (%)0.0%
Memory size692.0 B
분뇨등관련영업관리
70 

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 70
100.0%

Length

2024-04-17T04:53:30.274192image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T04:53:30.416816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
분뇨등관련영업관리 70
100.0%

업종구분명
Categorical

IMBALANCE 

Distinct5
Distinct (%)7.1%
Missing0
Missing (%)0.0%
Memory size692.0 B
<NA>
59 
분뇨 처리업
6 
하수처리, 폐기물처리 및 청소관련 서비스업
 
3
하수, 폐수 및 분뇨 처리업
 
1
폐기물 수집운반업
 
1

Length

Max length23
Median length4
Mean length5.2142857
Min length4

Unique

Unique2 ?
Unique (%)2.9%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 59
84.3%
분뇨 처리업 6
 
8.6%
하수처리, 폐기물처리 및 청소관련 서비스업 3
 
4.3%
하수, 폐수 및 분뇨 처리업 1
 
1.4%
폐기물 수집운반업 1
 
1.4%

Length

2024-04-17T04:53:30.552598image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-04-17T04:53:30.698361image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 59
63.4%
분뇨 7
 
7.5%
처리업 7
 
7.5%
및 4
 
4.3%
하수처리 3
 
3.2%
폐기물처리 3
 
3.2%
청소관련 3
 
3.2%
서비스업 3
 
3.2%
하수 1
 
1.1%
폐수 1
 
1.1%
Other values (2) 2
 
2.2%

종별명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing70
Missing (%)100.0%
Memory size762.0 B

주생산품명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing70
Missing (%)100.0%
Memory size762.0 B

배출시설조업시간
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing70
Missing (%)100.0%
Memory size762.0 B

배출시설연간가동일수
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing70
Missing (%)100.0%
Memory size762.0 B

방지시설조업시간
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing70
Missing (%)100.0%
Memory size762.0 B

방지시설연간가동일수
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing70
Missing (%)100.0%
Memory size762.0 B

Unnamed: 36
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing70
Missing (%)100.0%
Memory size762.0 B

Sample

번호개방서비스명개방서비스id개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(x)좌표정보(y)환경업무구분명업종구분명종별명주생산품명배출시설조업시간배출시설연간가동일수방지시설조업시간방지시설연간가동일수Unnamed: 36
01분뇨수집운반업09_30_10_P340000034000005319990000119930618<NA>1영업/정상11영업<NA><NA><NA><NA>051-722-1488<NA>619903부산광역시 기장군 기장읍 대라리 406-3부산광역시 기장군 기장읍 차성로 265619903차성정화20161228131650I2018-08-31 23:59:59.0<NA>401391.375537195774.675382분뇨등관련영업관리<NA><NA><NA><NA><NA><NA><NA><NA>
12분뇨수집운반업09_30_10_P340000034000005319930000319930624<NA>1영업/정상11영업<NA><NA><NA><NA>051-722-6660<NA>619903부산광역시 기장군 기장읍 대라리 406-3부산광역시 기장군 기장읍 차성로 265619903(주)신라정화사20200615172608U2020-06-17 02:40:00.0<NA>401391.375537195774.675382분뇨등관련영업관리<NA><NA><NA><NA><NA><NA><NA><NA>
23분뇨수집운반업09_30_10_P339000033900005319950000319891229<NA>1영업/정상11영업<NA><NA><NA><NA>0513133623<NA><NA>부산광역시 사상구 감전동 116-7 삼주오피스텔부산광역시 사상구 괘감로 131, 513호 (감전동)46982북부위생(주)20181211142012U2018-12-13 02:40:00.0<NA>381144.366063185965.490068분뇨등관련영업관리<NA><NA><NA><NA><NA><NA><NA><NA>
34분뇨수집운반업09_30_10_P339000033900005319950000219780704<NA>1영업/정상11영업<NA><NA><NA><NA>0513017777<NA>617070부산광역시 사상구 삼락동 71-1부산광역시 사상구 낙동대로 1514 (삼락동)617825(주)유성정화20200617180449U2020-06-19 02:40:00.0<NA>380624.551554190038.493733분뇨등관련영업관리<NA><NA><NA><NA><NA><NA><NA><NA>
45분뇨수집운반업09_30_10_P339000033900005319950000119800125<NA>1영업/정상11영업<NA><NA><NA><NA>051-322-5400<NA><NA>부산광역시 사상구 엄궁동 643-8 철강판매단지 202호부산광역시 사상구 강변대로532번길 41, 철강판매단지 202호 (엄궁동)47031사북환경20201022112826U2020-10-24 02:40:00.0분뇨 처리업380678.16764186308.485624분뇨등관련영업관리분뇨 처리업<NA><NA><NA><NA><NA><NA><NA>
56분뇨수집운반업09_30_10_P338000033800005320090000120090409<NA>1영업/정상11영업<NA><NA><NA><NA>051-751-0572<NA><NA>부산광역시 수영구 민락동 177-1 파로스오피스텔부산광역시 수영구 광안해변로 263, 파로스오피스텔 1006호 (민락동)48285(주)동우위생20201130103902U2020-12-02 02:40:00.0<NA>393339.479017186122.14438분뇨등관련영업관리<NA><NA><NA><NA><NA><NA><NA><NA>
67분뇨수집운반업09_30_10_P338000033800005320060000120060518<NA>1영업/정상11영업<NA><NA><NA><NA>626-8217<NA><NA>부산광역시 수영구 광안동 98-1부산광역시 수영구 수영로666번길 6, 수영역삼정그린코아더시티 1218호 (광안동)48268수영정화20201130103951U2020-12-02 02:40:00.0<NA>392552.298493184819.898745분뇨등관련영업관리<NA><NA><NA><NA><NA><NA><NA><NA>
78분뇨수집운반업09_30_10_P338000033800005320000000120000128<NA>1영업/정상11영업<NA><NA><NA><NA><NA><NA>613011부산광역시 수영구 남천동 12-19부산광역시 수영구 남천동로 7 (남천동)<NA>(주)광안환경 (최초,남부위생)20070828095748I2018-08-31 23:59:59.0<NA>392207.132592184691.37107분뇨등관련영업관리<NA><NA><NA><NA><NA><NA><NA><NA>
89분뇨수집운반업09_30_10_P338000033800005319970000119970722<NA>1영업/정상11영업<NA><NA><NA><NA><NA><NA>613814부산광역시 수영구 남천동 19-30부산광역시 수영구 수영로 396 (남천동)<NA>(주)광안환경20080904171515I2018-08-31 23:59:59.0<NA>392016.787788184527.510266분뇨등관련영업관리<NA><NA><NA><NA><NA><NA><NA><NA>
910분뇨수집운반업09_30_10_P337000033700005320140000120141104<NA>1영업/정상11영업<NA><NA><NA><NA>051-853-1822<NA>611713부산광역시 연제구 거제동 150-6부산광역시 연제구 명륜로 10, 501호 (거제동, 한양타워빌)611713연제환경(주)20201029135407U2020-10-31 02:40:00.0<NA>389498.499882190511.175423분뇨등관련영업관리<NA><NA><NA><NA><NA><NA><NA><NA>
번호개방서비스명개방서비스id개방자치단체코드관리번호인허가일자인허가취소일자영업상태구분코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자소재지전화소재지면적소재지우편번호소재지전체주소도로명전체주소도로명우편번호사업장명최종수정시점데이터갱신구분데이터갱신일자업태구분명좌표정보(x)좌표정보(y)환경업무구분명업종구분명종별명주생산품명배출시설조업시간배출시설연간가동일수방지시설조업시간방지시설연간가동일수Unnamed: 36
6061분뇨수집운반업09_30_10_P328000032800005319990000719990921<NA>3폐업2폐업20001110<NA><NA><NA>051 415 4470<NA><NA>부산광역시 영도구 청학동 59-32부산광역시 영도구 태종로 406-2 (청학동)49020대우정화사20200916181710U2020-09-18 02:40:00.0<NA>388342.537308178818.390148분뇨등관련영업관리<NA><NA><NA><NA><NA><NA><NA><NA>
6162분뇨수집운반업09_30_10_P328000032800005319990000619990921<NA>3폐업2폐업20001024<NA><NA><NA>051 747 7905<NA><NA>부산광역시 영도구 동삼동 499-1부산광역시 영도구 중리북로41번길 6 (동삼동)49118태홍정화사20200916181512U2020-09-18 02:40:00.0<NA>388635.963153176709.756119분뇨등관련영업관리<NA><NA><NA><NA><NA><NA><NA><NA>
6263분뇨수집운반업09_30_10_P328000032800005319990000520020226<NA>3폐업2폐업20160415<NA><NA><NA>0514185778<NA><NA>부산광역시 영도구 청학동 346 태종로주유소부산광역시 영도구 태종로 290, 태종로주유소 (청학동)49021(주)청록정화20200916185403U2020-09-18 02:40:00.0<NA>387553.854312179586.953379분뇨등관련영업관리<NA><NA><NA><NA><NA><NA><NA><NA>
6364분뇨수집운반업09_30_10_P328000032800005319990000419990910<NA>3폐업2폐업20001014<NA><NA><NA>051 416 4994<NA><NA>부산광역시 영도구 청학동 386-212 유한여객(주)부산광역시 영도구 청학서로 37, 유한여객(주) (청학동)49025유일정화사20200916181012U2020-09-18 02:40:00.0<NA>387455.982206179170.707601분뇨등관련영업관리<NA><NA><NA><NA><NA><NA><NA><NA>
6465분뇨수집운반업09_30_10_P327000032700005320000000419831031<NA>3폐업2폐업20121210<NA><NA><NA><NA><NA>601823부산광역시 동구 좌천동 822-6 세원빌라 201호부산광역시 동구 좌천남로 10 (좌천동)601823(주)형제정화산업20201208141807U2020-12-10 02:40:00.0<NA>386651.248333183362.036248분뇨등관련영업관리<NA><NA><NA><NA><NA><NA><NA><NA>
6566분뇨수집운반업09_30_10_P327000032700005320000000319840419<NA>3폐업2폐업20121210<NA><NA><NA>051-637-4173<NA>601823부산광역시 동구 좌천동 822-6부산광역시 동구 좌천남로 10 (좌천동)601823새부산정화산업사20201208141647U2020-12-10 02:40:00.0<NA>386651.248333183362.036248분뇨등관련영업관리<NA><NA><NA><NA><NA><NA><NA><NA>
6667분뇨수집운반업09_30_10_P327000032700005320000000620050107<NA>3폐업2폐업20121210<NA><NA><NA>051-642-6610<NA>614802부산광역시 부산진구 가야동 167-5부산광역시 부산진구 가야대로 532-1 (가야동)614802선무위생20201208141855U2020-12-10 02:40:00.0<NA>384935.14093185685.595693분뇨등관련영업관리<NA><NA><NA><NA><NA><NA><NA><NA>
6768분뇨수집운반업09_30_10_P326000032600005320170000120170721<NA>3폐업2폐업20190725<NA><NA><NA>051-243-4448<NA><NA>부산광역시 서구 남부민동 654 LG마린타워부산광역시 서구 충무대로 181, 423호 (남부민동, LG마린타워)49256부산광역시 서구 충무대로 181, 423호(남부민동,20191014175810U2019-10-16 02:40:00.0<NA>384515.986951178275.15693분뇨등관련영업관리<NA><NA><NA><NA><NA><NA><NA><NA>
6869분뇨수집운반업09_30_10_P326000032600005320020000120040615<NA>3폐업2폐업20040615<NA><NA><NA><NA><NA>602826부산광역시 서구 서대신동3가 486<NA><NA>(주)이수엔지니어링20191014175536I2019-10-16 00:22:51.0<NA><NA><NA>분뇨등관련영업관리<NA><NA><NA><NA><NA><NA><NA><NA>
6970분뇨수집운반업09_30_10_P326000032600005319920000319920331<NA>3폐업2폐업19920331<NA><NA><NA><NA><NA>602093부산광역시 서구 서대신동3가 78-86부산광역시 서구 보수대로 281 (서대신동3가)<NA>해동환경(주)한일영업소20191014180223I2019-10-16 00:22:51.0<NA>383598.187387181736.0413분뇨등관련영업관리<NA><NA><NA><NA><NA><NA><NA><NA>