Overview

Dataset statistics

Number of variables33
Number of observations624
Missing cells6886
Missing cells (%)33.4%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory171.4 KiB
Average record size in memory281.2 B

Variable types

Numeric7
DateTime4
Unsupported6
Categorical10
Text6

Dataset

Description개방자치단체코드,관리번호,인허가일자,인허가취소일자,영업상태코드,영업상태명,상세영업상태코드,상세영업상태명,폐업일자,휴업시작일자,휴업종료일자,재개업일자,전화번호,소재지면적,소재지우편번호,지번주소,도로명주소,도로명우편번호,사업장명,최종수정일자,데이터갱신구분,데이터갱신일자,업태구분명,좌표정보(X),좌표정보(Y),환경업무구분명,업종구분명,종별명,주생산품명,배출시설조업시간,배출시설연간가동일수,방지시설조업시간,방지시설연간가동일수
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-16121/S/1/datasetView.do

Alerts

재개업일자 is highly imbalanced (97.4%)Imbalance
업태구분명 is highly imbalanced (57.2%)Imbalance
환경업무구분명 is highly imbalanced (69.8%)Imbalance
업종구분명 is highly imbalanced (59.6%)Imbalance
배출시설연간가동일수 is highly imbalanced (86.3%)Imbalance
방지시설연간가동일수 is highly imbalanced (86.3%)Imbalance
인허가취소일자 has 624 (100.0%) missing valuesMissing
폐업일자 has 349 (55.9%) missing valuesMissing
휴업시작일자 has 606 (97.1%) missing valuesMissing
휴업종료일자 has 615 (98.6%) missing valuesMissing
전화번호 has 378 (60.6%) missing valuesMissing
소재지면적 has 624 (100.0%) missing valuesMissing
소재지우편번호 has 98 (15.7%) missing valuesMissing
도로명주소 has 298 (47.8%) missing valuesMissing
도로명우편번호 has 504 (80.8%) missing valuesMissing
좌표정보(X) has 146 (23.4%) missing valuesMissing
좌표정보(Y) has 146 (23.4%) missing valuesMissing
종별명 has 624 (100.0%) missing valuesMissing
주생산품명 has 624 (100.0%) missing valuesMissing
배출시설조업시간 has 624 (100.0%) missing valuesMissing
방지시설조업시간 has 624 (100.0%) missing valuesMissing
최종수정일자 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
방지시설조업시간 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-05-11 08:50:58.786243
Analysis finished2024-05-11 08:51:00.609458
Duration1.82 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Real number (ℝ)

Distinct25
Distinct (%)4.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3153685.9
Minimum3000000
Maximum3240000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.6 KiB
2024-05-11T08:51:00.934622image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3000000
5-th percentile3010000
Q13100000
median3180000
Q33210000
95-th percentile3230000
Maximum3240000
Range240000
Interquartile range (IQR)110000

Descriptive statistics

Standard deviation74716.397
Coefficient of variation (CV)0.023691769
Kurtosis-0.75682477
Mean3153685.9
Median Absolute Deviation (MAD)40000
Skewness-0.83502009
Sum1.9679 × 109
Variance5.58254 × 109
MonotonicityNot monotonic
2024-05-11T08:51:01.431335image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
3210000 169
27.1%
3220000 55
 
8.8%
3180000 50
 
8.0%
3010000 42
 
6.7%
3230000 34
 
5.4%
3160000 27
 
4.3%
3100000 26
 
4.2%
3150000 21
 
3.4%
3200000 19
 
3.0%
3130000 19
 
3.0%
Other values (15) 162
26.0%
ValueCountFrequency (%)
3000000 11
 
1.8%
3010000 42
6.7%
3020000 18
2.9%
3030000 11
 
1.8%
3040000 14
 
2.2%
3050000 17
2.7%
3060000 15
 
2.4%
3070000 3
 
0.5%
3080000 6
 
1.0%
3090000 5
 
0.8%
ValueCountFrequency (%)
3240000 16
 
2.6%
3230000 34
 
5.4%
3220000 55
 
8.8%
3210000 169
27.1%
3200000 19
 
3.0%
3190000 3
 
0.5%
3180000 50
 
8.0%
3170000 18
 
2.9%
3160000 27
 
4.3%
3150000 21
 
3.4%

관리번호
Real number (ℝ)

Distinct623
Distinct (%)99.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.1536223 × 1017
Minimum3.0000005 × 1017
Maximum3.2400005 × 1017
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.6 KiB
2024-05-11T08:51:01.914762image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.0000005 × 1017
5-th percentile3.0100005 × 1017
Q13.1000005 × 1017
median3.1800005 × 1017
Q33.2100005 × 1017
95-th percentile3.2300005 × 1017
Maximum3.2400005 × 1017
Range2.4 × 1016
Interquartile range (IQR)1.1 × 1016

Descriptive statistics

Standard deviation7.4813999 × 1015
Coefficient of variation (CV)0.023723195
Kurtosis-0.75893013
Mean3.1536223 × 1017
Median Absolute Deviation (MAD)4 × 1015
Skewness-0.83520326
Sum-6.128151 × 1018
Variance5.5971344 × 1031
MonotonicityNot monotonic
2024-05-11T08:51:02.509721image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
302000054200000001 2
 
0.3%
304000054199600003 1
 
0.2%
321000054200000073 1
 
0.2%
321000054200400021 1
 
0.2%
321000054199900062 1
 
0.2%
321000054200000041 1
 
0.2%
321000054200000066 1
 
0.2%
321000054200000067 1
 
0.2%
321000054200000072 1
 
0.2%
321000054200400006 1
 
0.2%
Other values (613) 613
98.2%
ValueCountFrequency (%)
300000054197400001 1
0.2%
300000054198300002 1
0.2%
300000054198700002 1
0.2%
300000054198800002 1
0.2%
300000054199800003 1
0.2%
300000054199800005 1
0.2%
300000054201300001 1
0.2%
300000054201400001 1
0.2%
300000054201400002 1
0.2%
300000054202100001 1
0.2%
ValueCountFrequency (%)
324000054200500002 1
0.2%
324000054200500001 1
0.2%
324000054200400014 1
0.2%
324000054200400009 1
0.2%
324000054200400005 1
0.2%
324000054200400002 1
0.2%
324000054200400001 1
0.2%
324000054200300001 1
0.2%
324000054200200001 1
0.2%
324000054200100002 1
0.2%

인허가일자
Date

Distinct525
Distinct (%)84.1%
Missing0
Missing (%)0.0%
Memory size5.0 KiB
Minimum1974-04-12 00:00:00
Maximum2024-04-25 00:00:00
2024-05-11T08:51:03.037727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T08:51:03.527390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing624
Missing (%)100.0%
Memory size5.6 KiB

영업상태코드
Categorical

Distinct4
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size5.0 KiB
1
306 
3
283 
2
 
18
5
 
17

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 (%)
1 306
49.0%
3 283
45.4%
2 18
 
2.9%
5 17
 
2.7%

Length

2024-05-11T08:51:04.310297image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:51:04.741540image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 306
49.0%
3 283
45.4%
2 18
 
2.9%
5 17
 
2.7%

영업상태명
Categorical

Distinct4
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size5.0 KiB
영업/정상
306 
폐업
283 
휴업
 
18
제외/삭제/전출
 
17

Length

Max length8
Median length5
Mean length3.6346154
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 306
49.0%
폐업 283
45.4%
휴업 18
 
2.9%
제외/삭제/전출 17
 
2.7%

Length

2024-05-11T08:51:05.243343image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:51:05.632731image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 306
49.0%
폐업 283
45.4%
휴업 18
 
2.9%
제외/삭제/전출 17
 
2.7%

상세영업상태코드
Real number (ℝ)

Distinct6
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean6.4535256
Minimum1
Maximum11
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.6 KiB
2024-05-11T08:51:06.121613image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum1
5-th percentile2
Q12
median5
Q311
95-th percentile11
Maximum11
Range10
Interquartile range (IQR)9

Descriptive statistics

Standard deviation4.456433
Coefficient of variation (CV)0.69054238
Kurtosis-1.9693297
Mean6.4535256
Median Absolute Deviation (MAD)4
Skewness0.017664214
Sum4027
Variance19.859795
MonotonicityNot monotonic
2024-05-11T08:51:06.539187image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
11 303
48.6%
2 275
44.1%
1 18
 
2.9%
5 17
 
2.7%
4 8
 
1.3%
3 3
 
0.5%
ValueCountFrequency (%)
1 18
 
2.9%
2 275
44.1%
3 3
 
0.5%
4 8
 
1.3%
5 17
 
2.7%
11 303
48.6%
ValueCountFrequency (%)
11 303
48.6%
5 17
 
2.7%
4 8
 
1.3%
3 3
 
0.5%
2 275
44.1%
1 18
 
2.9%

상세영업상태명
Categorical

Distinct6
Distinct (%)1.0%
Missing0
Missing (%)0.0%
Memory size5.0 KiB
영업
303 
폐업
275 
휴업
 
18
제외사항
 
17
폐쇄
 
8

Length

Max length4
Median length2
Mean length2.0592949
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업 303
48.6%
폐업 275
44.1%
휴업 18
 
2.9%
제외사항 17
 
2.7%
폐쇄 8
 
1.3%
재개업 3
 
0.5%

Length

2024-05-11T08:51:06.929265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:51:07.344537image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업 303
48.6%
폐업 275
44.1%
휴업 18
 
2.9%
제외사항 17
 
2.7%
폐쇄 8
 
1.3%
재개업 3
 
0.5%

폐업일자
Date

MISSING 

Distinct205
Distinct (%)74.5%
Missing349
Missing (%)55.9%
Memory size5.0 KiB
Minimum1998-09-01 00:00:00
Maximum2024-01-31 00:00:00
2024-05-11T08:51:07.840246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T08:51:08.594049image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Real number (ℝ)

MISSING 

Distinct8
Distinct (%)44.4%
Missing606
Missing (%)97.1%
Infinite0
Infinite (%)0.0%
Mean20149853
Minimum20021231
Maximum20200916
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.6 KiB
2024-05-11T08:51:09.090615image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20021231
5-th percentile20080711
Q120093588
median20165966
Q320200916
95-th percentile20200916
Maximum20200916
Range179685
Interquartile range (IQR)107327.5

Descriptive statistics

Standard deviation57089.9
Coefficient of variation (CV)0.0028332662
Kurtosis-0.59106339
Mean20149853
Median Absolute Deviation (MAD)34950.5
Skewness-0.70589276
Sum3.6269736 × 108
Variance3.2592566 × 109
MonotonicityNot monotonic
2024-05-11T08:51:09.536088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=8)
ValueCountFrequency (%)
20200916 8
 
1.3%
20091208 4
 
0.6%
20151222 1
 
0.2%
20151101 1
 
0.2%
20180709 1
 
0.2%
20021231 1
 
0.2%
20100730 1
 
0.2%
20120209 1
 
0.2%
(Missing) 606
97.1%
ValueCountFrequency (%)
20021231 1
 
0.2%
20091208 4
0.6%
20100730 1
 
0.2%
20120209 1
 
0.2%
20151101 1
 
0.2%
20151222 1
 
0.2%
20180709 1
 
0.2%
20200916 8
1.3%
ValueCountFrequency (%)
20200916 8
1.3%
20180709 1
 
0.2%
20151222 1
 
0.2%
20151101 1
 
0.2%
20120209 1
 
0.2%
20100730 1
 
0.2%
20091208 4
0.6%
20021231 1
 
0.2%

휴업종료일자
Real number (ℝ)

MISSING 

Distinct6
Distinct (%)66.7%
Missing615
Missing (%)98.6%
Infinite0
Infinite (%)0.0%
Mean20113130
Minimum20031001
Maximum20180831
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.6 KiB
2024-05-11T08:51:09.918314image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum20031001
5-th percentile20059083
Q120101207
median20101207
Q320130208
95-th percentile20172939
Maximum20180831
Range149830
Interquartile range (IQR)29001

Descriptive statistics

Standard deviation42571.534
Coefficient of variation (CV)0.0021166041
Kurtosis1.2974852
Mean20113130
Median Absolute Deviation (MAD)8994
Skewness-0.28142662
Sum1.8101817 × 108
Variance1.8123355 × 109
MonotonicityNot monotonic
2024-05-11T08:51:10.448621image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=6)
ValueCountFrequency (%)
20101207 4
 
0.6%
20161101 1
 
0.2%
20180831 1
 
0.2%
20031001 1
 
0.2%
20110201 1
 
0.2%
20130208 1
 
0.2%
(Missing) 615
98.6%
ValueCountFrequency (%)
20031001 1
 
0.2%
20101207 4
0.6%
20110201 1
 
0.2%
20130208 1
 
0.2%
20161101 1
 
0.2%
20180831 1
 
0.2%
ValueCountFrequency (%)
20180831 1
 
0.2%
20161101 1
 
0.2%
20130208 1
 
0.2%
20110201 1
 
0.2%
20101207 4
0.6%
20031001 1
 
0.2%

재개업일자
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.6%
Missing0
Missing (%)0.0%
Memory size5.0 KiB
<NA>
621 
20030603
 
1
20110523
 
1
20040203
 
1

Length

Max length8
Median length4
Mean length4.0192308
Min length4

Unique

Unique3 ?
Unique (%)0.5%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 621
99.5%
20030603 1
 
0.2%
20110523 1
 
0.2%
20040203 1
 
0.2%

Length

2024-05-11T08:51:11.191764image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:51:11.636242image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 621
99.5%
20030603 1
 
0.2%
20110523 1
 
0.2%
20040203 1
 
0.2%

전화번호
Text

MISSING 

Distinct188
Distinct (%)76.4%
Missing378
Missing (%)60.6%
Memory size5.0 KiB
2024-05-11T08:51:12.525727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length11
Mean length9.6300813
Min length7

Characters and Unicode

Total characters2369
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

Unique156 ?
Unique (%)63.4%

Sample

1st row024559281
2nd row02-2247-5678
3rd row02-489-8419
4th row02-6150-7433
5th row0234345800
ValueCountFrequency (%)
02 45
 
13.9%
025458965 8
 
2.5%
025906554 6
 
1.9%
02-489-8419 5
 
1.5%
5892365 5
 
1.5%
025135500 4
 
1.2%
5906554 4
 
1.2%
34982600 4
 
1.2%
9785900 4
 
1.2%
02-975-8422 3
 
0.9%
Other values (208) 236
72.8%
2024-05-11T08:51:13.989786image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 404
17.1%
2 363
15.3%
5 252
10.6%
4 193
8.1%
8 179
7.6%
3 179
7.6%
1 168
7.1%
6 161
 
6.8%
9 155
 
6.5%
7 125
 
5.3%
Other values (2) 190
8.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2179
92.0%
Dash Punctuation 97
 
4.1%
Space Separator 93
 
3.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 404
18.5%
2 363
16.7%
5 252
11.6%
4 193
8.9%
8 179
8.2%
3 179
8.2%
1 168
7.7%
6 161
 
7.4%
9 155
 
7.1%
7 125
 
5.7%
Dash Punctuation
ValueCountFrequency (%)
- 97
100.0%
Space Separator
ValueCountFrequency (%)
93
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2369
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 404
17.1%
2 363
15.3%
5 252
10.6%
4 193
8.1%
8 179
7.6%
3 179
7.6%
1 168
7.1%
6 161
 
6.8%
9 155
 
6.5%
7 125
 
5.3%
Other values (2) 190
8.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2369
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 404
17.1%
2 363
15.3%
5 252
10.6%
4 193
8.1%
8 179
7.6%
3 179
7.6%
1 168
7.1%
6 161
 
6.8%
9 155
 
6.5%
7 125
 
5.3%
Other values (2) 190
8.0%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing624
Missing (%)100.0%
Memory size5.6 KiB

소재지우편번호
Text

MISSING 

Distinct252
Distinct (%)47.9%
Missing98
Missing (%)15.7%
Memory size5.0 KiB
2024-05-11T08:51:14.672975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.0380228
Min length6

Characters and Unicode

Total characters3176
Distinct characters15
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique159 ?
Unique (%)30.2%

Sample

1st row151-060
2nd row151-010
3rd row151-069
4th row151-069
5th row151-018
ValueCountFrequency (%)
null 21
 
4.0%
137073 16
 
3.0%
150010 15
 
2.9%
137071 13
 
2.5%
137062 12
 
2.3%
137132 11
 
2.1%
138160 9
 
1.7%
137074 8
 
1.5%
133120 7
 
1.3%
150070 6
 
1.1%
Other values (242) 408
77.6%
2024-05-11T08:51:15.909977image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 794
25.0%
0 685
21.6%
3 419
13.2%
7 255
 
8.0%
5 253
 
8.0%
2 233
 
7.3%
4 129
 
4.1%
8 113
 
3.6%
6 75
 
2.4%
9 74
 
2.3%
Other values (5) 146
 
4.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 3030
95.4%
Lowercase Letter 84
 
2.6%
Space Separator 42
 
1.3%
Dash Punctuation 20
 
0.6%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 794
26.2%
0 685
22.6%
3 419
13.8%
7 255
 
8.4%
5 253
 
8.3%
2 233
 
7.7%
4 129
 
4.3%
8 113
 
3.7%
6 75
 
2.5%
9 74
 
2.4%
Lowercase Letter
ValueCountFrequency (%)
l 42
50.0%
n 21
25.0%
u 21
25.0%
Space Separator
ValueCountFrequency (%)
42
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 20
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3092
97.4%
Latin 84
 
2.6%

Most frequent character per script

Common
ValueCountFrequency (%)
1 794
25.7%
0 685
22.2%
3 419
13.6%
7 255
 
8.2%
5 253
 
8.2%
2 233
 
7.5%
4 129
 
4.2%
8 113
 
3.7%
6 75
 
2.4%
9 74
 
2.4%
Other values (2) 62
 
2.0%
Latin
ValueCountFrequency (%)
l 42
50.0%
n 21
25.0%
u 21
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3176
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 794
25.0%
0 685
21.6%
3 419
13.2%
7 255
 
8.0%
5 253
 
8.0%
2 233
 
7.3%
4 129
 
4.1%
8 113
 
3.6%
6 75
 
2.4%
9 74
 
2.3%
Other values (5) 146
 
4.6%

지번주소
Text

Distinct506
Distinct (%)81.4%
Missing2
Missing (%)0.3%
Memory size5.0 KiB
2024-05-11T08:51:16.778945image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length44
Median length39
Mean length23.231511
Min length13

Characters and Unicode

Total characters14450
Distinct characters271
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique432 ?
Unique (%)69.5%

Sample

1st row서울특별시 광진구 구의동 592-36
2nd row서울특별시 동대문구 휘경동 268-3
3rd row서울특별시 서초구 염곡동 300-4
4th row서울특별시 영등포구 여의도동 23-10 삼성생명(주)여의도빌딩 4층
5th row서울특별시 송파구 신천동 7-19
ValueCountFrequency (%)
서울특별시 618
 
22.1%
서초구 166
 
5.9%
강남구 55
 
2.0%
서초동 51
 
1.8%
영등포구 51
 
1.8%
방배동 47
 
1.7%
중구 42
 
1.5%
송파구 34
 
1.2%
양재동 29
 
1.0%
구로구 27
 
1.0%
Other values (838) 1681
60.0%
2024-05-11T08:51:18.123824image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2970
20.6%
서 883
 
6.1%
동 678
 
4.7%
구 671
 
4.6%
1 657
 
4.5%
시 632
 
4.4%
울 624
 
4.3%
특 618
 
4.3%
별 618
 
4.3%
- 528
 
3.7%
Other values (261) 5571
38.6%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7941
55.0%
Space Separator 2970
 
20.6%
Decimal Number 2968
 
20.5%
Dash Punctuation 528
 
3.7%
Uppercase Letter 31
 
0.2%
Other Punctuation 4
 
< 0.1%
Close Punctuation 3
 
< 0.1%
Open Punctuation 3
 
< 0.1%
Letter Number 1
 
< 0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 883
 
11.1%
동 678
 
8.5%
구 671
 
8.4%
시 632
 
8.0%
울 624
 
7.9%
특 618
 
7.8%
별 618
 
7.8%
초 217
 
2.7%
강 105
 
1.3%
가 101
 
1.3%
Other values (235) 2794
35.2%
Decimal Number
ValueCountFrequency (%)
1 657
22.1%
2 399
13.4%
3 341
11.5%
4 293
9.9%
0 278
9.4%
5 256
 
8.6%
6 218
 
7.3%
7 207
 
7.0%
9 168
 
5.7%
8 151
 
5.1%
Uppercase Letter
ValueCountFrequency (%)
A 8
25.8%
C 7
22.6%
J 6
19.4%
K 3
 
9.7%
T 3
 
9.7%
B 2
 
6.5%
G 1
 
3.2%
L 1
 
3.2%
Other Punctuation
ValueCountFrequency (%)
, 3
75.0%
/ 1
 
25.0%
Space Separator
ValueCountFrequency (%)
2970
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 528
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 1
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 7941
55.0%
Common 6477
44.8%
Latin 32
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 883
 
11.1%
동 678
 
8.5%
구 671
 
8.4%
시 632
 
8.0%
울 624
 
7.9%
특 618
 
7.8%
별 618
 
7.8%
초 217
 
2.7%
강 105
 
1.3%
가 101
 
1.3%
Other values (235) 2794
35.2%
Common
ValueCountFrequency (%)
2970
45.9%
1 657
 
10.1%
- 528
 
8.2%
2 399
 
6.2%
3 341
 
5.3%
4 293
 
4.5%
0 278
 
4.3%
5 256
 
4.0%
6 218
 
3.4%
7 207
 
3.2%
Other values (7) 330
 
5.1%
Latin
ValueCountFrequency (%)
A 8
25.0%
C 7
21.9%
J 6
18.8%
K 3
 
9.4%
T 3
 
9.4%
B 2
 
6.2%
G 1
 
3.1%
L 1
 
3.1%
Ⅱ 1
 
3.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 7941
55.0%
ASCII 6508
45.0%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2970
45.6%
1 657
 
10.1%
- 528
 
8.1%
2 399
 
6.1%
3 341
 
5.2%
4 293
 
4.5%
0 278
 
4.3%
5 256
 
3.9%
6 218
 
3.3%
7 207
 
3.2%
Other values (15) 361
 
5.5%
Hangul
ValueCountFrequency (%)
서 883
 
11.1%
동 678
 
8.5%
구 671
 
8.4%
시 632
 
8.0%
울 624
 
7.9%
특 618
 
7.8%
별 618
 
7.8%
초 217
 
2.7%
강 105
 
1.3%
가 101
 
1.3%
Other values (235) 2794
35.2%
Number Forms
ValueCountFrequency (%)
Ⅱ 1
100.0%

도로명주소
Text

MISSING 

Distinct245
Distinct (%)75.2%
Missing298
Missing (%)47.8%
Memory size5.0 KiB
2024-05-11T08:51:18.858654image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length56
Median length45
Mean length29.165644
Min length21

Characters and Unicode

Total characters9508
Distinct characters264
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique194 ?
Unique (%)59.5%

Sample

1st row서울특별시 광진구 뚝섬로67길 5, 디와이즈빌딩 3층 (구의동)
2nd row서울특별시 동대문구 망우로 62 (휘경동)
3rd row서울특별시 서초구 양재대로 246 (염곡동)
4th row서울특별시 영등포구 국제금융로2길 24, 삼성생명(주)여의도빌딩 4층 (여의도동)
5th row서울특별시 송파구 올림픽로 289 (신천동, 잠실시그마타워)
ValueCountFrequency (%)
서울특별시 324
 
18.1%
서초구 108
 
6.0%
영등포구 32
 
1.8%
방배동 27
 
1.5%
서초동 25
 
1.4%
구로구 25
 
1.4%
중구 25
 
1.4%
노원구 24
 
1.3%
금천구 18
 
1.0%
마포구 16
 
0.9%
Other values (584) 1164
65.1%
2024-05-11T08:51:20.266921image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1646
 
17.3%
서 497
 
5.2%
로 383
 
4.0%
구 371
 
3.9%
동 363
 
3.8%
시 340
 
3.6%
) 329
 
3.5%
( 329
 
3.5%
울 326
 
3.4%
특 324
 
3.4%
Other values (254) 4600
48.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5690
59.8%
Space Separator 1646
 
17.3%
Decimal Number 1305
 
13.7%
Close Punctuation 329
 
3.5%
Open Punctuation 329
 
3.5%
Other Punctuation 150
 
1.6%
Dash Punctuation 28
 
0.3%
Uppercase Letter 28
 
0.3%
Math Symbol 2
 
< 0.1%
Letter Number 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
서 497
 
8.7%
로 383
 
6.7%
구 371
 
6.5%
동 363
 
6.4%
시 340
 
6.0%
울 326
 
5.7%
특 324
 
5.7%
별 324
 
5.7%
초 153
 
2.7%
길 129
 
2.3%
Other values (232) 2480
43.6%
Decimal Number
ValueCountFrequency (%)
2 235
18.0%
1 229
17.5%
3 137
10.5%
4 134
10.3%
6 127
9.7%
0 99
7.6%
5 95
7.3%
7 91
 
7.0%
9 87
 
6.7%
8 71
 
5.4%
Uppercase Letter
ValueCountFrequency (%)
C 11
39.3%
J 10
35.7%
A 6
21.4%
B 1
 
3.6%
Other Punctuation
ValueCountFrequency (%)
, 149
99.3%
/ 1
 
0.7%
Space Separator
ValueCountFrequency (%)
1646
100.0%
Close Punctuation
ValueCountFrequency (%)
) 329
100.0%
Open Punctuation
ValueCountFrequency (%)
( 329
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 28
100.0%
Math Symbol
ValueCountFrequency (%)
~ 2
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5690
59.8%
Common 3789
39.9%
Latin 29
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
서 497
 
8.7%
로 383
 
6.7%
구 371
 
6.5%
동 363
 
6.4%
시 340
 
6.0%
울 326
 
5.7%
특 324
 
5.7%
별 324
 
5.7%
초 153
 
2.7%
길 129
 
2.3%
Other values (232) 2480
43.6%
Common
ValueCountFrequency (%)
1646
43.4%
) 329
 
8.7%
( 329
 
8.7%
2 235
 
6.2%
1 229
 
6.0%
, 149
 
3.9%
3 137
 
3.6%
4 134
 
3.5%
6 127
 
3.4%
0 99
 
2.6%
Other values (7) 375
 
9.9%
Latin
ValueCountFrequency (%)
C 11
37.9%
J 10
34.5%
A 6
20.7%
B 1
 
3.4%
Ⅱ 1
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5690
59.8%
ASCII 3817
40.1%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1646
43.1%
) 329
 
8.6%
( 329
 
8.6%
2 235
 
6.2%
1 229
 
6.0%
, 149
 
3.9%
3 137
 
3.6%
4 134
 
3.5%
6 127
 
3.3%
0 99
 
2.6%
Other values (11) 403
 
10.6%
Hangul
ValueCountFrequency (%)
서 497
 
8.7%
로 383
 
6.7%
구 371
 
6.5%
동 363
 
6.4%
시 340
 
6.0%
울 326
 
5.7%
특 324
 
5.7%
별 324
 
5.7%
초 153
 
2.7%
길 129
 
2.3%
Other values (232) 2480
43.6%
Number Forms
ValueCountFrequency (%)
Ⅱ 1
100.0%

도로명우편번호
Text

MISSING 

Distinct77
Distinct (%)64.2%
Missing504
Missing (%)80.8%
Memory size5.0 KiB
2024-05-11T08:51:21.201641image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length5.45
Min length5

Characters and Unicode

Total characters654
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique55 ?
Unique (%)45.8%

Sample

1st row05049
2nd row02496
3rd row06792
4th row07325
5th row05510
ValueCountFrequency (%)
06792 7
 
5.8%
06703 6
 
5.0%
139856 5
 
4.2%
06575 4
 
3.3%
137896 4
 
3.3%
01610 3
 
2.5%
153801 3
 
2.5%
02072 3
 
2.5%
06697 3
 
2.5%
153803 3
 
2.5%
Other values (67) 79
65.8%
2024-05-11T08:51:22.454808image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 120
18.3%
1 94
14.4%
3 79
12.1%
6 68
10.4%
7 68
10.4%
5 56
8.6%
8 46
 
7.0%
9 44
 
6.7%
2 44
 
6.7%
4 30
 
4.6%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 649
99.2%
Dash Punctuation 5
 
0.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 120
18.5%
1 94
14.5%
3 79
12.2%
6 68
10.5%
7 68
10.5%
5 56
8.6%
8 46
 
7.1%
9 44
 
6.8%
2 44
 
6.8%
4 30
 
4.6%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 654
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 120
18.3%
1 94
14.4%
3 79
12.1%
6 68
10.4%
7 68
10.4%
5 56
8.6%
8 46
 
7.0%
9 44
 
6.7%
2 44
 
6.7%
4 30
 
4.6%

Most occurring blocks

ValueCountFrequency (%)
ASCII 654
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 120
18.3%
1 94
14.4%
3 79
12.1%
6 68
10.4%
7 68
10.4%
5 56
8.6%
8 46
 
7.0%
9 44
 
6.7%
2 44
 
6.7%
4 30
 
4.6%

사업장명
Text

Distinct447
Distinct (%)71.6%
Missing0
Missing (%)0.0%
Memory size5.0 KiB
2024-05-11T08:51:23.093265image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length17
Mean length8.2644231
Min length3

Characters and Unicode

Total characters5157
Distinct characters263
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

Unique341 ?
Unique (%)54.6%

Sample

1st row누리환경(주)
2nd row동양종합건업
3rd row에스지씨이테크건설 주식회사
4th row(주)동양
5th row에이치엘디앤아이한라 주식회사
ValueCountFrequency (%)
주식회사 29
 
4.3%
이수건설(주 13
 
1.9%
유덕환경(주 11
 
1.6%
주)한배엔지니어링 9
 
1.3%
롯데건설(주 7
 
1.0%
주)제일엔지니어링 6
 
0.9%
유림환경(주 5
 
0.7%
씨제이대한통운주식회사 5
 
0.7%
청정산업 4
 
0.6%
신성공영(주 4
 
0.6%
Other values (451) 584
86.3%
2024-05-11T08:51:24.680316image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 592
 
11.5%
) 507
 
9.8%
( 504
 
9.8%
이 156
 
3.0%
엔 143
 
2.8%
건 134
 
2.6%
경 127
 
2.5%
설 120
 
2.3%
지 118
 
2.3%
환 117
 
2.3%
Other values (253) 2639
51.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4035
78.2%
Close Punctuation 507
 
9.8%
Open Punctuation 504
 
9.8%
Space Separator 53
 
1.0%
Uppercase Letter 21
 
0.4%
Dash Punctuation 17
 
0.3%
Other Punctuation 16
 
0.3%
Decimal Number 4
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 592
 
14.7%
이 156
 
3.9%
엔 143
 
3.5%
건 134
 
3.3%
경 127
 
3.1%
설 120
 
3.0%
지 118
 
2.9%
환 117
 
2.9%
사 83
 
2.1%
어 70
 
1.7%
Other values (233) 2375
58.9%
Uppercase Letter
ValueCountFrequency (%)
C 6
28.6%
E 5
23.8%
P 2
 
9.5%
J 2
 
9.5%
F 1
 
4.8%
R 1
 
4.8%
N 1
 
4.8%
M 1
 
4.8%
H 1
 
4.8%
I 1
 
4.8%
Other Punctuation
ValueCountFrequency (%)
. 11
68.8%
& 3
 
18.8%
, 2
 
12.5%
Decimal Number
ValueCountFrequency (%)
0 2
50.0%
1 1
25.0%
2 1
25.0%
Close Punctuation
ValueCountFrequency (%)
) 507
100.0%
Open Punctuation
ValueCountFrequency (%)
( 504
100.0%
Space Separator
ValueCountFrequency (%)
53
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 17
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4035
78.2%
Common 1101
 
21.3%
Latin 21
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 592
 
14.7%
이 156
 
3.9%
엔 143
 
3.5%
건 134
 
3.3%
경 127
 
3.1%
설 120
 
3.0%
지 118
 
2.9%
환 117
 
2.9%
사 83
 
2.1%
어 70
 
1.7%
Other values (233) 2375
58.9%
Common
ValueCountFrequency (%)
) 507
46.0%
( 504
45.8%
53
 
4.8%
- 17
 
1.5%
. 11
 
1.0%
& 3
 
0.3%
0 2
 
0.2%
, 2
 
0.2%
1 1
 
0.1%
2 1
 
0.1%
Latin
ValueCountFrequency (%)
C 6
28.6%
E 5
23.8%
P 2
 
9.5%
J 2
 
9.5%
F 1
 
4.8%
R 1
 
4.8%
N 1
 
4.8%
M 1
 
4.8%
H 1
 
4.8%
I 1
 
4.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4035
78.2%
ASCII 1122
 
21.8%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 592
 
14.7%
이 156
 
3.9%
엔 143
 
3.5%
건 134
 
3.3%
경 127
 
3.1%
설 120
 
3.0%
지 118
 
2.9%
환 117
 
2.9%
사 83
 
2.1%
어 70
 
1.7%
Other values (233) 2375
58.9%
ASCII
ValueCountFrequency (%)
) 507
45.2%
( 504
44.9%
53
 
4.7%
- 17
 
1.5%
. 11
 
1.0%
C 6
 
0.5%
E 5
 
0.4%
& 3
 
0.3%
0 2
 
0.2%
P 2
 
0.2%
Other values (10) 12
 
1.1%

최종수정일자
Date

UNIQUE 

Distinct624
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size5.0 KiB
Minimum2000-09-25 11:24:19
Maximum2024-05-09 09:16:11
2024-05-11T08:51:25.169815image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T08:51:25.673671image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.0 KiB
I
542 
U
82 

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 542
86.9%
U 82
 
13.1%

Length

2024-05-11T08:51:26.478023image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:51:26.948325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 542
86.9%
u 82
 
13.1%

데이터갱신일자
Date

Distinct90
Distinct (%)14.4%
Missing0
Missing (%)0.0%
Memory size5.0 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-05 00:03:00
2024-05-11T08:51:27.432686image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T08:51:28.008454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Categorical

IMBALANCE 

Distinct27
Distinct (%)4.3%
Missing0
Missing (%)0.0%
Memory size5.0 KiB
<NA>
409 
하수, 분뇨 및 축산폐기물 처리업
61 
분뇨 처리업
48 
폐기물 처리 및 오염방지시설 건설업
 
24
분뇨 및 축산폐기물 처리업
 
22
Other values (22)
60 

Length

Max length23
Median length4
Mean length7.3830128
Min length2

Unique

Unique15 ?
Unique (%)2.4%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 409
65.5%
하수, 분뇨 및 축산폐기물 처리업 61
 
9.8%
분뇨 처리업 48
 
7.7%
폐기물 처리 및 오염방지시설 건설업 24
 
3.8%
분뇨 및 축산폐기물 처리업 22
 
3.5%
하수처리, 폐기물처리 및 청소관련 서비스업 14
 
2.2%
종합 건설업 11
 
1.8%
환경상담 및 관련 엔지니어링 서비스업 9
 
1.4%
하수 처리업 4
 
0.6%
기타 건물건설관련 전문 공사업 3
 
0.5%
Other values (17) 19
 
3.0%

Length

2024-05-11T08:51:28.599044image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 409
33.3%
처리업 135
 
11.0%
및 132
 
10.8%
분뇨 131
 
10.7%
축산폐기물 83
 
6.8%
하수 65
 
5.3%
건설업 40
 
3.3%
폐기물 24
 
2.0%
처리 24
 
2.0%
오염방지시설 24
 
2.0%
Other values (39) 160
 
13.0%

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct342
Distinct (%)71.5%
Missing146
Missing (%)23.4%
Infinite0
Infinite (%)0.0%
Mean199046.5
Minimum183914.94
Maximum217137.52
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.6 KiB
2024-05-11T08:51:29.004766image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum183914.94
5-th percentile189127.98
Q1193483.08
median199915.98
Q3203477.19
95-th percentile208268.72
Maximum217137.52
Range33222.581
Interquartile range (IQR)9994.1121

Descriptive statistics

Standard deviation6144.5209
Coefficient of variation (CV)0.030869776
Kurtosis-0.54085773
Mean199046.5
Median Absolute Deviation (MAD)3949.727
Skewness-0.26782031
Sum95144226
Variance37755137
MonotonicityNot monotonic
2024-05-11T08:51:29.569246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
199371.371382654 13
 
2.1%
203908.342097327 8
 
1.3%
198513.33078735 8
 
1.3%
206460.340838133 7
 
1.1%
199971.14619007 6
 
1.0%
201293.26005564 6
 
1.0%
203865.709970943 5
 
0.8%
200214.828933969 5
 
0.8%
201643.645893671 4
 
0.6%
200833.751922277 4
 
0.6%
Other values (332) 412
66.0%
(Missing) 146
 
23.4%
ValueCountFrequency (%)
183914.938310002 3
0.5%
184229.740132067 1
 
0.2%
185099.7875285 1
 
0.2%
185368.413894206 1
 
0.2%
185914.514475763 1
 
0.2%
186301.875540288 1
 
0.2%
186317.207037672 1
 
0.2%
186617.653704143 1
 
0.2%
186712.11224869 1
 
0.2%
187307.924980657 1
 
0.2%
ValueCountFrequency (%)
217137.519410187 1
0.2%
212239.908968756 1
0.2%
211682.464581191 1
0.2%
211573.770265043 1
0.2%
211330.148489184 1
0.2%
211314.789502725 1
0.2%
210758.119119654 2
0.3%
210736.904409143 2
0.3%
210530.220720417 1
0.2%
210231.822848068 2
0.3%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct342
Distinct (%)71.5%
Missing146
Missing (%)23.4%
Infinite0
Infinite (%)0.0%
Mean446893.76
Minimum437280.57
Maximum463940.98
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.6 KiB
2024-05-11T08:51:30.070750image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum437280.57
5-th percentile441124.36
Q1442612.36
median445366.69
Q3450127.28
95-th percentile459106.96
Maximum463940.98
Range26660.403
Interquartile range (IQR)7514.9154

Descriptive statistics

Standard deviation5478.7144
Coefficient of variation (CV)0.012259545
Kurtosis1.0729294
Mean446893.76
Median Absolute Deviation (MAD)3099.3649
Skewness1.1941879
Sum2.1361522 × 108
Variance30016311
MonotonicityNot monotonic
2024-05-11T08:51:30.484637image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
443987.021242832 13
 
2.1%
440422.094963963 8
 
1.3%
442267.326128184 8
 
1.3%
461782.719034388 7
 
1.1%
441431.482365654 6
 
1.0%
446179.309516814 6
 
1.0%
441674.893877771 5
 
0.8%
442206.118999192 5
 
0.8%
445764.161880369 4
 
0.6%
443142.889069935 4
 
0.6%
Other values (332) 412
66.0%
(Missing) 146
 
23.4%
ValueCountFrequency (%)
437280.574150819 1
 
0.2%
437914.06299827 2
 
0.3%
438641.653485665 1
 
0.2%
440256.501465873 1
 
0.2%
440295.618804889 1
 
0.2%
440422.094963963 8
1.3%
440521.85524888 1
 
0.2%
440569.259053553 1
 
0.2%
440771.039835881 1
 
0.2%
440963.790624982 2
 
0.3%
ValueCountFrequency (%)
463940.976727043 1
 
0.2%
463887.942604325 2
 
0.3%
463533.259200639 3
0.5%
463000.651595126 2
 
0.3%
462714.188504333 1
 
0.2%
462708.495728674 1
 
0.2%
462215.331325654 1
 
0.2%
461782.719034388 7
1.1%
461582.803734992 2
 
0.3%
460896.983072795 2
 
0.3%

환경업무구분명
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size5.0 KiB
분뇨등설계시공업관리
562 
<NA>
61 
분뇨등관련영업관리
 
1

Length

Max length10
Median length10
Mean length9.411859
Min length4

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
분뇨등설계시공업관리 562
90.1%
<NA> 61
 
9.8%
분뇨등관련영업관리 1
 
0.2%

Length

2024-05-11T08:51:31.156324image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:51:31.577656image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
분뇨등설계시공업관리 562
90.1%
na 61
 
9.8%
분뇨등관련영업관리 1
 
0.2%

업종구분명
Categorical

IMBALANCE 

Distinct22
Distinct (%)3.5%
Missing0
Missing (%)0.0%
Memory size5.0 KiB
<NA>
434 
하수, 분뇨 및 축산폐기물 처리업
59 
분뇨 처리업
 
43
폐기물 처리 및 오염방지시설 건설업
 
24
분뇨 및 축산폐기물 처리업
 
18
Other values (17)
46 

Length

Max length23
Median length4
Mean length7.2099359
Min length2

Unique

Unique10 ?
Unique (%)1.6%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 434
69.6%
하수, 분뇨 및 축산폐기물 처리업 59
 
9.5%
분뇨 처리업 43
 
6.9%
폐기물 처리 및 오염방지시설 건설업 24
 
3.8%
분뇨 및 축산폐기물 처리업 18
 
2.9%
하수처리, 폐기물처리 및 청소관련 서비스업 14
 
2.2%
환경상담 및 관련 엔지니어링 서비스업 9
 
1.4%
종합 건설업 4
 
0.6%
기타 건물건설관련 전문 공사업 3
 
0.5%
토목 건설업 2
 
0.3%
Other values (12) 14
 
2.2%

Length

2024-05-11T08:51:32.146602image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
na 434
36.5%
및 125
 
10.5%
처리업 122
 
10.3%
분뇨 120
 
10.1%
축산폐기물 77
 
6.5%
하수 61
 
5.1%
건설업 32
 
2.7%
처리 24
 
2.0%
오염방지시설 24
 
2.0%
폐기물 24
 
2.0%
Other values (31) 145
 
12.2%

종별명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing624
Missing (%)100.0%
Memory size5.6 KiB

주생산품명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing624
Missing (%)100.0%
Memory size5.6 KiB

배출시설조업시간
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing624
Missing (%)100.0%
Memory size5.6 KiB

배출시설연간가동일수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.0 KiB
<NA>
612 
0
 
12

Length

Max length4
Median length4
Mean length3.9423077
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 612
98.1%
0 12
 
1.9%

Length

2024-05-11T08:51:32.960475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:51:33.391058image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 612
98.1%
0 12
 
1.9%

방지시설조업시간
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing624
Missing (%)100.0%
Memory size5.6 KiB

방지시설연간가동일수
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size5.0 KiB
<NA>
612 
0
 
12

Length

Max length4
Median length4
Mean length3.9423077
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 612
98.1%
0 12
 
1.9%

Length

2024-05-11T08:51:33.720718image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T08:51:34.027568image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 612
98.1%
0 12
 
1.9%

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)환경업무구분명업종구분명종별명주생산품명배출시설조업시간배출시설연간가동일수방지시설조업시간방지시설연간가동일수
030400003040000541996000031996-09-17<NA>1영업/정상11영업<NA><NA><NA><NA>024559281<NA><NA>서울특별시 광진구 구의동 592-36서울특별시 광진구 뚝섬로67길 5, 디와이즈빌딩 3층 (구의동)05049누리환경(주)2023-07-14 09:01:22U2022-12-06 23:06:00.0<NA>207959.495345448045.166176<NA><NA><NA><NA><NA><NA><NA><NA>
130500003050000541998000051998-01-12<NA>1영업/정상11영업<NA><NA><NA><NA>02-2247-5678<NA><NA>서울특별시 동대문구 휘경동 268-3서울특별시 동대문구 망우로 62 (휘경동)02496동양종합건업2023-03-23 09:58:22U2022-12-02 22:05:00.0<NA>205243.536682454114.757493<NA><NA><NA><NA><NA><NA><NA><NA>
232100003210000542023000022023-03-24<NA>1영업/정상11영업<NA><NA><NA><NA>02-489-8419<NA><NA>서울특별시 서초구 염곡동 300-4서울특별시 서초구 양재대로 246 (염곡동)06792에스지씨이테크건설 주식회사2023-03-24 15:29:47I2022-12-02 22:06:00.0종합 건설업203908.342097440422.094964<NA><NA><NA><NA><NA><NA><NA><NA>
331800003180000542018000012018-05-15<NA>1영업/정상11영업<NA><NA><NA><NA>02-6150-7433<NA><NA>서울특별시 영등포구 여의도동 23-10 삼성생명(주)여의도빌딩 4층서울특별시 영등포구 국제금융로2길 24, 삼성생명(주)여의도빌딩 4층 (여의도동)07325(주)동양2023-04-03 15:34:15U2022-12-04 00:05:00.0<NA>193289.927062446893.487525<NA><NA><NA><NA><NA><NA><NA><NA>
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932000003200000541996000042006-02-01<NA>5제외/삭제/전출5제외사항<NA><NA><NA><NA><NA><NA>151-060서울특별시 관악구 봉천동 874-17<NA><NA>(주)장성엔지니어링2023-09-12 15:32:36U2022-12-08 23:04:00.0하수, 분뇨 및 축산폐기물 처리업<NA><NA><NA><NA><NA><NA><NA><NA><NA><NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)환경업무구분명업종구분명종별명주생산품명배출시설조업시간배출시설연간가동일수방지시설조업시간방지시설연간가동일수
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620321000032100005420220000420220928<NA>1영업/정상11영업<NA><NA><NA><NA>5906554<NA><NA>서울특별시 서초구 반포동 112-4서울특별시 서초구 사평대로 84 (반포동)137714이수건설(주)2022-09-28 17:23:28I2021-12-08 21:00:00.0<NA>199371.371383443987.021243<NA><NA><NA><NA><NA><NA><NA><NA>
621310000031000005420220000120220928<NA>1영업/정상11영업<NA><NA><NA><NA><NA><NA>139200서울특별시 노원구 상계동 136-4서울특별시 노원구 수락산로 55 (상계동)<NA>(주)한배엔지니어링2022-09-28 15:02:47I2021-12-08 21:00:00.0<NA>206180.465649462714.188504<NA><NA><NA><NA><NA><NA><NA><NA>
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