Overview

Dataset statistics

Number of variables31
Number of observations565
Missing cells5312
Missing cells (%)30.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory144.1 KiB
Average record size in memory261.2 B

Variable types

Numeric5
DateTime5
Unsupported5
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,폐기물처리업구분명,폐기물처리업별처리구분명,폐기물구분명,허용보관량,허용보관량내용
Author서울특별시
URLhttps://data.seoul.go.kr/dataList/OA-16120/S/1/datasetView.do

Alerts

영업상태코드 is highly imbalanced (50.4%)Imbalance
영업상태명 is highly imbalanced (50.4%)Imbalance
상세영업상태코드 is highly imbalanced (59.7%)Imbalance
상세영업상태명 is highly imbalanced (59.7%)Imbalance
휴업종료일자 is highly imbalanced (98.1%)Imbalance
재개업일자 is highly imbalanced (98.1%)Imbalance
폐기물구분명 is highly imbalanced (88.2%)Imbalance
인허가취소일자 has 565 (100.0%) missing valuesMissing
폐업일자 has 464 (82.1%) missing valuesMissing
휴업시작일자 has 556 (98.4%) missing valuesMissing
전화번호 has 262 (46.4%) missing valuesMissing
소재지면적 has 565 (100.0%) missing valuesMissing
소재지우편번호 has 180 (31.9%) missing valuesMissing
지번주소 has 20 (3.5%) missing valuesMissing
도로명주소 has 130 (23.0%) missing valuesMissing
도로명우편번호 has 263 (46.5%) missing valuesMissing
업태구분명 has 565 (100.0%) missing valuesMissing
좌표정보(X) has 76 (13.5%) missing valuesMissing
좌표정보(Y) has 76 (13.5%) missing valuesMissing
폐기물처리업별처리구분명 has 565 (100.0%) missing valuesMissing
허용보관량 has 460 (81.4%) missing valuesMissing
허용보관량내용 has 565 (100.0%) missing valuesMissing
관리번호 has unique valuesUnique
인허가취소일자 is an unsupported type, check if it needs cleaning or further analysisUnsupported
소재지면적 is an unsupported type, check if it needs cleaning or further analysisUnsupported
업태구분명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
폐기물처리업별처리구분명 is an unsupported type, check if it needs cleaning or further analysisUnsupported
허용보관량내용 is an unsupported type, check if it needs cleaning or further analysisUnsupported
허용보관량 has 86 (15.2%) zerosZeros

Reproduction

Analysis started2024-05-11 05:52:21.292083
Analysis finished2024-05-11 05:52:22.551649
Duration1.26 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

개방자치단체코드
Real number (ℝ)

Distinct25
Distinct (%)4.4%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3122831.9
Minimum3000000
Maximum3240000
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.1 KiB
2024-05-11T14:52:22.650949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3000000
5-th percentile3030000
Q13060000
median3130000
Q33170000
95-th percentile3230000
Maximum3240000
Range240000
Interquartile range (IQR)110000

Descriptive statistics

Standard deviation62731.402
Coefficient of variation (CV)0.020087986
Kurtosis-1.0408119
Mean3122831.9
Median Absolute Deviation (MAD)50000
Skewness-0.042688494
Sum1.7644 × 109
Variance3.9352288 × 109
MonotonicityNot monotonic
2024-05-11T14:52:22.870961image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=25)
ValueCountFrequency (%)
3030000 72
 
12.7%
3160000 46
 
8.1%
3150000 45
 
8.0%
3120000 41
 
7.3%
3100000 37
 
6.5%
3180000 33
 
5.8%
3130000 29
 
5.1%
3060000 26
 
4.6%
3050000 24
 
4.2%
3210000 24
 
4.2%
Other values (15) 188
33.3%
ValueCountFrequency (%)
3000000 3
 
0.5%
3010000 2
 
0.4%
3020000 4
 
0.7%
3030000 72
12.7%
3040000 12
 
2.1%
3050000 24
 
4.2%
3060000 26
 
4.6%
3070000 15
 
2.7%
3080000 7
 
1.2%
3090000 20
 
3.5%
ValueCountFrequency (%)
3240000 12
 
2.1%
3230000 21
3.7%
3220000 5
 
0.9%
3210000 24
4.2%
3200000 21
3.7%
3190000 14
 
2.5%
3180000 33
5.8%
3170000 18
 
3.2%
3160000 46
8.1%
3150000 45
8.0%

관리번호
Real number (ℝ)

UNIQUE 

Distinct565
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean3.1245319 × 1017
Minimum3.0000009 × 1017
Maximum4.0900009 × 1017
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.1 KiB
2024-05-11T14:52:23.457386image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum3.0000009 × 1017
5-th percentile3.0300009 × 1017
Q13.0600009 × 1017
median3.1300009 × 1017
Q33.1700009 × 1017
95-th percentile3.2300009 × 1017
Maximum4.0900009 × 1017
Range1.09 × 1017
Interquartile range (IQR)1.1 × 1016

Descriptive statistics

Standard deviation7.4771528 × 1015
Coefficient of variation (CV)0.023930474
Kurtosis47.780868
Mean3.1245319 × 1017
Median Absolute Deviation (MAD)5 × 1015
Skewness3.7572266
Sum-7.9313886 × 1018
Variance5.5907814 × 1031
MonotonicityNot monotonic
2024-05-11T14:52:23.707174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
306000092202300001 1
 
0.2%
315000092201000003 1
 
0.2%
315000092200900001 1
 
0.2%
315000092200100003 1
 
0.2%
314000092201800001 1
 
0.2%
322000092202200002 1
 
0.2%
315000092200900004 1
 
0.2%
315000092200900005 1
 
0.2%
315000092200900002 1
 
0.2%
315000092200800007 1
 
0.2%
Other values (555) 555
98.2%
ValueCountFrequency (%)
300000092200700001 1
0.2%
300000092200800001 1
0.2%
300000092202000001 1
0.2%
301000092200700001 1
0.2%
301000092201700001 1
0.2%
302000092200100001 1
0.2%
302000092200800001 1
0.2%
302000092202000001 1
0.2%
302000092202200001 1
0.2%
303000092200600001 1
0.2%
ValueCountFrequency (%)
409000092200700001 1
0.2%
324000092201900001 1
0.2%
324000092201700001 1
0.2%
324000092201600001 1
0.2%
324000092201300002 1
0.2%
324000092201300001 1
0.2%
324000092201100001 1
0.2%
324000092200800002 1
0.2%
324000092200800001 1
0.2%
324000092200700002 1
0.2%

인허가일자
Date

Distinct492
Distinct (%)87.1%
Missing0
Missing (%)0.0%
Memory size4.5 KiB
Minimum1993-04-02 00:00:00
Maximum2024-05-08 00:00:00
2024-05-11T14:52:23.939352image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:52:24.162274image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

인허가취소일자
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing565
Missing (%)100.0%
Memory size5.1 KiB

영업상태코드
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size4.5 KiB
1
456 
3
100 
2
 
9

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row1
2nd row1
3rd row1
4th row3
5th row1

Common Values

ValueCountFrequency (%)
1 456
80.7%
3 100
 
17.7%
2 9
 
1.6%

Length

2024-05-11T14:52:24.369329image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:52:24.533367image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
1 456
80.7%
3 100
 
17.7%
2 9
 
1.6%

영업상태명
Categorical

IMBALANCE 

Distinct3
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size4.5 KiB
영업/정상
456 
폐업
100 
휴업
 
9

Length

Max length5
Median length5
Mean length4.4212389
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업/정상 456
80.7%
폐업 100
 
17.7%
휴업 9
 
1.6%

Length

2024-05-11T14:52:24.719667image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:52:24.903891image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업/정상 456
80.7%
폐업 100
 
17.7%
휴업 9
 
1.6%

상세영업상태코드
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size4.5 KiB
BBBB
455 
2
100 
1
 
9
3
 
1

Length

Max length4
Median length4
Mean length3.4159292
Min length1

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
BBBB 455
80.5%
2 100
 
17.7%
1 9
 
1.6%
3 1
 
0.2%

Length

2024-05-11T14:52:25.084251image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:52:25.292956image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
bbbb 455
80.5%
2 100
 
17.7%
1 9
 
1.6%
3 1
 
0.2%

상세영업상태명
Categorical

IMBALANCE 

Distinct4
Distinct (%)0.7%
Missing0
Missing (%)0.0%
Memory size4.5 KiB
영업
455 
폐업
100 
휴업
 
9
재개업
 
1

Length

Max length3
Median length2
Mean length2.0017699
Min length2

Unique

Unique1 ?
Unique (%)0.2%

Sample

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

Common Values

ValueCountFrequency (%)
영업 455
80.5%
폐업 100
 
17.7%
휴업 9
 
1.6%
재개업 1
 
0.2%

Length

2024-05-11T14:52:25.480928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:52:25.684165image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업 455
80.5%
폐업 100
 
17.7%
휴업 9
 
1.6%
재개업 1
 
0.2%

폐업일자
Date

MISSING 

Distinct92
Distinct (%)91.1%
Missing464
Missing (%)82.1%
Memory size4.5 KiB
Minimum2004-02-23 00:00:00
Maximum2024-02-23 00:00:00
2024-05-11T14:52:25.890783image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:52:26.104221image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

휴업시작일자
Date

MISSING 

Distinct9
Distinct (%)100.0%
Missing556
Missing (%)98.4%
Memory size4.5 KiB
Minimum2007-08-08 00:00:00
Maximum2023-12-14 00:00:00
2024-05-11T14:52:26.277687image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:52:26.460393image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)

휴업종료일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.5 KiB
<NA>
564 
20221027
 
1

Length

Max length8
Median length4
Mean length4.0070796
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 (%)
<NA> 564
99.8%
20221027 1
 
0.2%

Length

2024-05-11T14:52:26.675168image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:52:26.881828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 564
99.8%
20221027 1
 
0.2%

재개업일자
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.5 KiB
<NA>
564 
20221027
 
1

Length

Max length8
Median length4
Mean length4.0070796
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 (%)
<NA> 564
99.8%
20221027 1
 
0.2%

Length

2024-05-11T14:52:27.085327image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:52:27.256180image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 564
99.8%
20221027 1
 
0.2%

전화번호
Text

MISSING 

Distinct264
Distinct (%)87.1%
Missing262
Missing (%)46.4%
Memory size4.5 KiB
2024-05-11T14:52:27.716767image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length11
Mean length9.9042904
Min length7

Characters and Unicode

Total characters3001
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

Unique239 ?
Unique (%)78.9%

Sample

1st row02-433-1927
2nd row029803646
3rd row029036661
4th row02-6403-7895
5th row02-995-6661
ValueCountFrequency (%)
3030065 8
 
2.6%
028877520 6
 
1.9%
02-2614-8400 5
 
1.6%
02 4
 
1.3%
302-5573 3
 
1.0%
02-2631-0100 2
 
0.6%
02-2248-8122 2
 
0.6%
26618460 2
 
0.6%
2665-6266 2
 
0.6%
031-422-6624 2
 
0.6%
Other values (256) 272
88.3%
2024-05-11T14:52:28.489964image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 544
18.1%
2 483
16.1%
- 294
9.8%
6 262
8.7%
4 235
7.8%
3 232
7.7%
7 204
 
6.8%
5 203
 
6.8%
1 189
 
6.3%
8 176
 
5.9%
Other values (3) 179
 
6.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2699
89.9%
Dash Punctuation 294
 
9.8%
Space Separator 7
 
0.2%
Close Punctuation 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 544
20.2%
2 483
17.9%
6 262
9.7%
4 235
8.7%
3 232
8.6%
7 204
 
7.6%
5 203
 
7.5%
1 189
 
7.0%
8 176
 
6.5%
9 171
 
6.3%
Dash Punctuation
ValueCountFrequency (%)
- 294
100.0%
Space Separator
ValueCountFrequency (%)
7
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 3001
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 544
18.1%
2 483
16.1%
- 294
9.8%
6 262
8.7%
4 235
7.8%
3 232
7.7%
7 204
 
6.8%
5 203
 
6.8%
1 189
 
6.3%
8 176
 
5.9%
Other values (3) 179
 
6.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 3001
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 544
18.1%
2 483
16.1%
- 294
9.8%
6 262
8.7%
4 235
7.8%
3 232
7.7%
7 204
 
6.8%
5 203
 
6.8%
1 189
 
6.3%
8 176
 
5.9%
Other values (3) 179
 
6.0%

소재지면적
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing565
Missing (%)100.0%
Memory size5.1 KiB

소재지우편번호
Text

MISSING 

Distinct189
Distinct (%)49.1%
Missing180
Missing (%)31.9%
Memory size4.5 KiB
2024-05-11T14:52:29.010756image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length6
Mean length6.2025974
Min length6

Characters and Unicode

Total characters2388
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

Unique132 ?
Unique (%)34.3%

Sample

1st row152-080
2nd row142-061
3rd row142-070
4th row139-241
5th row110012
ValueCountFrequency (%)
133170 48
 
12.5%
120130 15
 
3.9%
120759 13
 
3.4%
152-080 12
 
3.1%
152050 9
 
2.3%
137070 8
 
2.1%
133160 8
 
2.1%
139200 7
 
1.8%
150032 7
 
1.8%
152-100 5
 
1.3%
Other values (179) 253
65.7%
2024-05-11T14:52:29.762050image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 585
24.5%
0 511
21.4%
3 343
14.4%
2 234
 
9.8%
5 187
 
7.8%
7 151
 
6.3%
8 108
 
4.5%
- 78
 
3.3%
9 75
 
3.1%
4 56
 
2.3%
Other values (5) 60
 
2.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 2304
96.5%
Dash Punctuation 78
 
3.3%
Lowercase Letter 4
 
0.2%
Space Separator 2
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 585
25.4%
0 511
22.2%
3 343
14.9%
2 234
 
10.2%
5 187
 
8.1%
7 151
 
6.6%
8 108
 
4.7%
9 75
 
3.3%
4 56
 
2.4%
6 54
 
2.3%
Lowercase Letter
ValueCountFrequency (%)
l 2
50.0%
n 1
25.0%
u 1
25.0%
Dash Punctuation
ValueCountFrequency (%)
- 78
100.0%
Space Separator
ValueCountFrequency (%)
2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 2384
99.8%
Latin 4
 
0.2%

Most frequent character per script

Common
ValueCountFrequency (%)
1 585
24.5%
0 511
21.4%
3 343
14.4%
2 234
 
9.8%
5 187
 
7.8%
7 151
 
6.3%
8 108
 
4.5%
- 78
 
3.3%
9 75
 
3.1%
4 56
 
2.3%
Other values (2) 56
 
2.3%
Latin
ValueCountFrequency (%)
l 2
50.0%
n 1
25.0%
u 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 2388
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 585
24.5%
0 511
21.4%
3 343
14.4%
2 234
 
9.8%
5 187
 
7.8%
7 151
 
6.3%
8 108
 
4.5%
- 78
 
3.3%
9 75
 
3.1%
4 56
 
2.3%
Other values (5) 60
 
2.5%

지번주소
Text

MISSING 

Distinct411
Distinct (%)75.4%
Missing20
Missing (%)3.5%
Memory size4.5 KiB
2024-05-11T14:52:30.316684image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length42
Median length36
Mean length26.306422
Min length16

Characters and Unicode

Total characters14337
Distinct characters296
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique352 ?
Unique (%)64.6%

Sample

1st row서울특별시 중랑구 신내동 493-84 202호
2nd row서울특별시 구로구 항동 산 51-4
3rd row서울특별시 용산구 용산동3가 1
4th row서울특별시 강북구 번동 204
5th row서울특별시 강북구 수유동 391-197
ValueCountFrequency (%)
서울특별시 542
 
19.6%
성동구 72
 
2.6%
번지 56
 
2.0%
용답동 53
 
1.9%
구로구 42
 
1.5%
강서구 42
 
1.5%
서대문구 41
 
1.5%
노원구 36
 
1.3%
영등포구 32
 
1.2%
중랑구 26
 
0.9%
Other values (818) 1818
65.9%
2024-05-11T14:52:31.053949image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2588
 
18.1%
동 713
 
5.0%
서 668
 
4.7%
구 603
 
4.2%
시 570
 
4.0%
울 549
 
3.8%
특 542
 
3.8%
별 542
 
3.8%
1 501
 
3.5%
- 438
 
3.1%
Other values (286) 6623
46.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8392
58.5%
Decimal Number 2856
 
19.9%
Space Separator 2588
 
18.1%
Dash Punctuation 438
 
3.1%
Uppercase Letter 34
 
0.2%
Open Punctuation 8
 
0.1%
Close Punctuation 8
 
0.1%
Lowercase Letter 7
 
< 0.1%
Other Punctuation 6
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 713
 
8.5%
서 668
 
8.0%
구 603
 
7.2%
시 570
 
6.8%
울 549
 
6.5%
특 542
 
6.5%
별 542
 
6.5%
지 307
 
3.7%
번 285
 
3.4%
호 156
 
1.9%
Other values (248) 3457
41.2%
Uppercase Letter
ValueCountFrequency (%)
B 7
20.6%
K 5
14.7%
T 4
11.8%
S 4
11.8%
G 3
8.8%
A 2
 
5.9%
C 1
 
2.9%
M 1
 
2.9%
R 1
 
2.9%
E 1
 
2.9%
Other values (5) 5
14.7%
Decimal Number
ValueCountFrequency (%)
1 501
17.5%
2 390
13.7%
3 366
12.8%
5 295
10.3%
0 294
10.3%
4 272
9.5%
7 229
8.0%
9 189
 
6.6%
6 184
 
6.4%
8 136
 
4.8%
Lowercase Letter
ValueCountFrequency (%)
c 2
28.6%
k 1
14.3%
r 1
14.3%
e 1
14.3%
w 1
14.3%
o 1
14.3%
Other Punctuation
ValueCountFrequency (%)
, 2
33.3%
& 2
33.3%
? 2
33.3%
Space Separator
ValueCountFrequency (%)
2588
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 438
100.0%
Open Punctuation
ValueCountFrequency (%)
( 8
100.0%
Close Punctuation
ValueCountFrequency (%)
) 8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 8392
58.5%
Common 5904
41.2%
Latin 41
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 713
 
8.5%
서 668
 
8.0%
구 603
 
7.2%
시 570
 
6.8%
울 549
 
6.5%
특 542
 
6.5%
별 542
 
6.5%
지 307
 
3.7%
번 285
 
3.4%
호 156
 
1.9%
Other values (248) 3457
41.2%
Latin
ValueCountFrequency (%)
B 7
17.1%
K 5
12.2%
T 4
 
9.8%
S 4
 
9.8%
G 3
 
7.3%
c 2
 
4.9%
A 2
 
4.9%
k 1
 
2.4%
C 1
 
2.4%
M 1
 
2.4%
Other values (11) 11
26.8%
Common
ValueCountFrequency (%)
2588
43.8%
1 501
 
8.5%
- 438
 
7.4%
2 390
 
6.6%
3 366
 
6.2%
5 295
 
5.0%
0 294
 
5.0%
4 272
 
4.6%
7 229
 
3.9%
9 189
 
3.2%
Other values (7) 342
 
5.8%

Most occurring blocks

ValueCountFrequency (%)
Hangul 8391
58.5%
ASCII 5945
41.5%
Compat Jamo 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2588
43.5%
1 501
 
8.4%
- 438
 
7.4%
2 390
 
6.6%
3 366
 
6.2%
5 295
 
5.0%
0 294
 
4.9%
4 272
 
4.6%
7 229
 
3.9%
9 189
 
3.2%
Other values (28) 383
 
6.4%
Hangul
ValueCountFrequency (%)
동 713
 
8.5%
서 668
 
8.0%
구 603
 
7.2%
시 570
 
6.8%
울 549
 
6.5%
특 542
 
6.5%
별 542
 
6.5%
지 307
 
3.7%
번 285
 
3.4%
호 156
 
1.9%
Other values (247) 3456
41.2%
Compat Jamo
ValueCountFrequency (%)
ㄹ 1
100.0%

도로명주소
Text

MISSING 

Distinct360
Distinct (%)82.8%
Missing130
Missing (%)23.0%
Memory size4.5 KiB
2024-05-11T14:52:31.481892image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length53
Median length43
Mean length33.331034
Min length21

Characters and Unicode

Total characters14499
Distinct characters339
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique327 ?
Unique (%)75.2%

Sample

1st row서울특별시 중랑구 송림길 46-4, 202호 (신내동)
2nd row서울특별시 구로구 부광로 88, 7층 에이701호 (항동)
3rd row서울특별시 용산구 이태원로 22, 지하1층 (용산동3가)
4th row서울특별시 강북구 월계로37길 87-5 (번동)
5th row서울특별시 강북구 삼각산로 94 (수유동)
ValueCountFrequency (%)
서울특별시 431
 
15.7%
구로구 36
 
1.3%
서대문구 35
 
1.3%
강서구 30
 
1.1%
노원구 29
 
1.1%
2층 28
 
1.0%
성동구 28
 
1.0%
천호대로 27
 
1.0%
마포구 25
 
0.9%
서초구 23
 
0.8%
Other values (934) 2057
74.8%
2024-05-11T14:52:32.064482image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2411
 
16.6%
동 583
 
4.0%
서 549
 
3.8%
1 495
 
3.4%
구 486
 
3.4%
로 479
 
3.3%
시 472
 
3.3%
) 442
 
3.0%
( 442
 
3.0%
울 440
 
3.0%
Other values (329) 7700
53.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8352
57.6%
Space Separator 2411
 
16.6%
Decimal Number 2350
 
16.2%
Close Punctuation 442
 
3.0%
Open Punctuation 442
 
3.0%
Other Punctuation 391
 
2.7%
Dash Punctuation 63
 
0.4%
Uppercase Letter 38
 
0.3%
Lowercase Letter 8
 
0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 583
 
7.0%
서 549
 
6.6%
구 486
 
5.8%
로 479
 
5.7%
시 472
 
5.7%
울 440
 
5.3%
별 431
 
5.2%
특 431
 
5.2%
호 256
 
3.1%
길 171
 
2.0%
Other values (289) 4054
48.5%
Uppercase Letter
ValueCountFrequency (%)
B 7
18.4%
S 4
10.5%
A 4
10.5%
O 3
7.9%
N 3
7.9%
E 3
7.9%
C 2
 
5.3%
G 2
 
5.3%
T 2
 
5.3%
L 2
 
5.3%
Other values (6) 6
15.8%
Decimal Number
ValueCountFrequency (%)
1 495
21.1%
2 377
16.0%
0 311
13.2%
3 236
10.0%
4 214
9.1%
7 171
 
7.3%
5 171
 
7.3%
8 154
 
6.6%
6 112
 
4.8%
9 109
 
4.6%
Lowercase Letter
ValueCountFrequency (%)
c 2
25.0%
o 1
12.5%
w 1
12.5%
k 1
12.5%
r 1
12.5%
e 1
12.5%
a 1
12.5%
Space Separator
ValueCountFrequency (%)
2411
100.0%
Close Punctuation
ValueCountFrequency (%)
) 442
100.0%
Open Punctuation
ValueCountFrequency (%)
( 442
100.0%
Other Punctuation
ValueCountFrequency (%)
, 391
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 63
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 8352
57.6%
Common 6100
42.1%
Latin 47
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 583
 
7.0%
서 549
 
6.6%
구 486
 
5.8%
로 479
 
5.7%
시 472
 
5.7%
울 440
 
5.3%
별 431
 
5.2%
특 431
 
5.2%
호 256
 
3.1%
길 171
 
2.0%
Other values (289) 4054
48.5%
Latin
ValueCountFrequency (%)
B 7
14.9%
S 4
 
8.5%
A 4
 
8.5%
O 3
 
6.4%
N 3
 
6.4%
E 3
 
6.4%
C 2
 
4.3%
G 2
 
4.3%
T 2
 
4.3%
c 2
 
4.3%
Other values (14) 15
31.9%
Common
ValueCountFrequency (%)
2411
39.5%
1 495
 
8.1%
) 442
 
7.2%
( 442
 
7.2%
, 391
 
6.4%
2 377
 
6.2%
0 311
 
5.1%
3 236
 
3.9%
4 214
 
3.5%
7 171
 
2.8%
Other values (6) 610
 
10.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 8352
57.6%
ASCII 6146
42.4%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2411
39.2%
1 495
 
8.1%
) 442
 
7.2%
( 442
 
7.2%
, 391
 
6.4%
2 377
 
6.1%
0 311
 
5.1%
3 236
 
3.8%
4 214
 
3.5%
7 171
 
2.8%
Other values (29) 656
 
10.7%
Hangul
ValueCountFrequency (%)
동 583
 
7.0%
서 549
 
6.6%
구 486
 
5.8%
로 479
 
5.7%
시 472
 
5.7%
울 440
 
5.3%
별 431
 
5.2%
특 431
 
5.2%
호 256
 
3.1%
길 171
 
2.0%
Other values (289) 4054
48.5%
Number Forms
ValueCountFrequency (%)
Ⅱ 1
100.0%

도로명우편번호
Text

MISSING 

Distinct229
Distinct (%)75.8%
Missing263
Missing (%)46.5%
Memory size4.5 KiB
2024-05-11T14:52:32.562380image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length5
Mean length5.4172185
Min length5

Characters and Unicode

Total characters1636
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

Unique195 ?
Unique (%)64.6%

Sample

1st row02072
2nd row08362
3rd row04383
4th row142-061
5th row142-884
ValueCountFrequency (%)
08362 13
 
4.3%
120759 13
 
4.3%
07802 5
 
1.7%
03938 5
 
1.7%
08265 5
 
1.7%
03925 4
 
1.3%
08639 4
 
1.3%
07249 3
 
1.0%
120132 3
 
1.0%
07285 3
 
1.0%
Other values (219) 244
80.8%
2024-05-11T14:52:33.295499image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 342
20.9%
1 206
12.6%
3 179
10.9%
2 173
10.6%
8 167
10.2%
5 137
8.4%
7 120
 
7.3%
6 104
 
6.4%
4 93
 
5.7%
9 84
 
5.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 1605
98.1%
Dash Punctuation 31
 
1.9%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 342
21.3%
1 206
12.8%
3 179
11.2%
2 173
10.8%
8 167
10.4%
5 137
8.5%
7 120
 
7.5%
6 104
 
6.5%
4 93
 
5.8%
9 84
 
5.2%
Dash Punctuation
ValueCountFrequency (%)
- 31
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1636
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 342
20.9%
1 206
12.6%
3 179
10.9%
2 173
10.6%
8 167
10.2%
5 137
8.4%
7 120
 
7.3%
6 104
 
6.4%
4 93
 
5.7%
9 84
 
5.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1636
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 342
20.9%
1 206
12.6%
3 179
10.9%
2 173
10.6%
8 167
10.2%
5 137
8.4%
7 120
 
7.3%
6 104
 
6.4%
4 93
 
5.7%
9 84
 
5.1%

사업장명
Text

Distinct392
Distinct (%)69.4%
Missing0
Missing (%)0.0%
Memory size4.5 KiB
2024-05-11T14:52:33.661032image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length17
Median length15
Mean length7.3893805
Min length2

Characters and Unicode

Total characters4175
Distinct characters268
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

Unique327 ?
Unique (%)57.9%

Sample

1st row(주)와이제이환경
2nd row영특수츄레라(주)
3rd row단디아이오티(iot)
4th row영화덤프
5th row(주)씨와이환경
ValueCountFrequency (%)
주식회사 36
 
5.8%
만강건설(주 27
 
4.4%
주)도성개발 23
 
3.7%
거리개발(주 15
 
2.4%
영특수츄레라(주 12
 
1.9%
건부산업(주 8
 
1.3%
주)대아 7
 
1.1%
이디아이 7
 
1.1%
성원이앤아이(주 6
 
1.0%
마이건설중기 6
 
1.0%
Other values (387) 470
76.2%
2024-05-11T14:52:34.248505image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 403
 
9.7%
) 365
 
8.7%
( 362
 
8.7%
건 133
 
3.2%
이 131
 
3.1%
경 115
 
2.8%
개 108
 
2.6%
환 106
 
2.5%
발 105
 
2.5%
기 94
 
2.3%
Other values (258) 2253
54.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 3359
80.5%
Close Punctuation 365
 
8.7%
Open Punctuation 362
 
8.7%
Space Separator 52
 
1.2%
Uppercase Letter 15
 
0.4%
Other Punctuation 13
 
0.3%
Decimal Number 3
 
0.1%
Lowercase Letter 3
 
0.1%
Dash Punctuation 2
 
< 0.1%
Other Symbol 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 403
 
12.0%
건 133
 
4.0%
이 131
 
3.9%
경 115
 
3.4%
개 108
 
3.2%
환 106
 
3.2%
발 105
 
3.1%
기 94
 
2.8%
설 91
 
2.7%
산 71
 
2.1%
Other values (240) 2002
59.6%
Uppercase Letter
ValueCountFrequency (%)
T 6
40.0%
E 4
26.7%
N 4
26.7%
C 1
 
6.7%
Other Punctuation
ValueCountFrequency (%)
. 9
69.2%
? 3
 
23.1%
, 1
 
7.7%
Decimal Number
ValueCountFrequency (%)
7 1
33.3%
4 1
33.3%
2 1
33.3%
Lowercase Letter
ValueCountFrequency (%)
t 1
33.3%
o 1
33.3%
i 1
33.3%
Close Punctuation
ValueCountFrequency (%)
) 365
100.0%
Open Punctuation
ValueCountFrequency (%)
( 362
100.0%
Space Separator
ValueCountFrequency (%)
52
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 3360
80.5%
Common 797
 
19.1%
Latin 18
 
0.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 403
 
12.0%
건 133
 
4.0%
이 131
 
3.9%
경 115
 
3.4%
개 108
 
3.2%
환 106
 
3.2%
발 105
 
3.1%
기 94
 
2.8%
설 91
 
2.7%
산 71
 
2.1%
Other values (241) 2003
59.6%
Common
ValueCountFrequency (%)
) 365
45.8%
( 362
45.4%
52
 
6.5%
. 9
 
1.1%
? 3
 
0.4%
- 2
 
0.3%
7 1
 
0.1%
4 1
 
0.1%
2 1
 
0.1%
, 1
 
0.1%
Latin
ValueCountFrequency (%)
T 6
33.3%
E 4
22.2%
N 4
22.2%
C 1
 
5.6%
t 1
 
5.6%
o 1
 
5.6%
i 1
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 3359
80.5%
ASCII 815
 
19.5%
None 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 403
 
12.0%
건 133
 
4.0%
이 131
 
3.9%
경 115
 
3.4%
개 108
 
3.2%
환 106
 
3.2%
발 105
 
3.1%
기 94
 
2.8%
설 91
 
2.7%
산 71
 
2.1%
Other values (240) 2002
59.6%
ASCII
ValueCountFrequency (%)
) 365
44.8%
( 362
44.4%
52
 
6.4%
. 9
 
1.1%
T 6
 
0.7%
E 4
 
0.5%
N 4
 
0.5%
? 3
 
0.4%
- 2
 
0.2%
C 1
 
0.1%
Other values (7) 7
 
0.9%
None
ValueCountFrequency (%)
㈜ 1
100.0%

최종수정일자
Date

Distinct451
Distinct (%)79.8%
Missing0
Missing (%)0.0%
Memory size4.5 KiB
Minimum2007-06-30 10:13:37
Maximum2024-05-08 15:04:54
2024-05-11T14:52:34.445480image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:52:34.656491image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

데이터갱신구분
Categorical

Distinct3
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size4.5 KiB
I
284 
U
275 
D
 
6

Length

Max length1
Median length1
Mean length1
Min length1

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
I 284
50.3%
U 275
48.7%
D 6
 
1.1%

Length

2024-05-11T14:52:34.869054image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:52:35.018245image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
i 284
50.3%
u 275
48.7%
d 6
 
1.1%

데이터갱신일자
Date

Distinct195
Distinct (%)34.5%
Missing0
Missing (%)0.0%
Memory size4.5 KiB
Minimum2018-08-31 23:59:59
Maximum2023-12-05 00:09:00
2024-05-11T14:52:35.181958image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-05-11T14:52:35.370303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

업태구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing565
Missing (%)100.0%
Memory size5.1 KiB

좌표정보(X)
Real number (ℝ)

MISSING 

Distinct330
Distinct (%)67.5%
Missing76
Missing (%)13.5%
Infinite0
Infinite (%)0.0%
Mean197449.27
Minimum180656.61
Maximum238485.92
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.1 KiB
2024-05-11T14:52:35.549780image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum180656.61
5-th percentile183746.69
Q1191082.57
median195582.35
Q3205486.3
95-th percentile210761.5
Maximum238485.92
Range57829.311
Interquartile range (IQR)14403.732

Descriptive statistics

Standard deviation8854.9421
Coefficient of variation (CV)0.044846669
Kurtosis-0.46364164
Mean197449.27
Median Absolute Deviation (MAD)8401.7881
Skewness0.1793558
Sum96552692
Variance78409999
MonotonicityNot monotonic
2024-05-11T14:52:35.734706image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
194297.832937369 15
 
2.7%
183746.686550444 13
 
2.3%
205895.022955723 9
 
1.6%
192079.366557621 8
 
1.4%
191094.016051179 6
 
1.1%
191957.888065159 6
 
1.1%
205921.703469803 5
 
0.9%
185351.345378075 5
 
0.9%
209668.90120464 5
 
0.9%
191226.287379467 5
 
0.9%
Other values (320) 412
72.9%
(Missing) 76
 
13.5%
ValueCountFrequency (%)
180656.613514685 1
0.2%
181565.668668 1
0.2%
182876.367858149 1
0.2%
183015.932951822 1
0.2%
183338.583360203 1
0.2%
183366.283511118 1
0.2%
183371.245085015 1
0.2%
183438.673656262 1
0.2%
183467.033171994 1
0.2%
183479.955247008 2
0.4%
ValueCountFrequency (%)
238485.924020194 1
0.2%
215661.222623 1
0.2%
215383.034106 1
0.2%
215203.880915796 1
0.2%
213030.20852974 1
0.2%
212863.644690982 1
0.2%
212343.69364512 1
0.2%
211834.079335928 1
0.2%
211650.564418133 1
0.2%
211542.314116941 1
0.2%

좌표정보(Y)
Real number (ℝ)

MISSING 

Distinct330
Distinct (%)67.5%
Missing76
Missing (%)13.5%
Infinite0
Infinite (%)0.0%
Mean450027.31
Minimum419942.03
Maximum481901.66
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size5.1 KiB
2024-05-11T14:52:35.937060image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum419942.03
5-th percentile440763.36
Q1444251.1
median450936.73
Q3453615.64
95-th percentile462110.85
Maximum481901.66
Range61959.639
Interquartile range (IQR)9364.5399

Descriptive statistics

Standard deviation6712.3925
Coefficient of variation (CV)0.014915522
Kurtosis0.97456571
Mean450027.31
Median Absolute Deviation (MAD)4717.3123
Skewness0.24087782
Sum2.2006336 × 108
Variance45056213
MonotonicityNot monotonic
2024-05-11T14:52:36.148682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
452570.312592501 15
 
2.7%
441744.40616131 13
 
2.3%
450936.729727466 9
 
1.6%
453483.787496388 8
 
1.4%
443570.443536531 6
 
1.1%
453095.63265739 6
 
1.1%
450931.561948791 5
 
0.9%
443405.408553756 5
 
0.9%
449767.964721034 5
 
0.9%
437914.06299827 5
 
0.9%
Other values (320) 412
72.9%
(Missing) 76
 
13.5%
ValueCountFrequency (%)
419942.025053434 1
 
0.2%
437190.641074911 1
 
0.2%
437197.38817881 1
 
0.2%
437244.861159969 1
 
0.2%
437405.747882418 1
 
0.2%
437676.252420606 1
 
0.2%
437914.06299827 5
0.9%
438756.148563584 1
 
0.2%
439328.50476394 2
 
0.4%
439569.401459017 1
 
0.2%
ValueCountFrequency (%)
481901.663868288 1
 
0.2%
468065.941237462 1
 
0.2%
464922.213107238 1
 
0.2%
464779.326449954 1
 
0.2%
464363.69607831 1
 
0.2%
464212.297931928 1
 
0.2%
464208.305428933 1
 
0.2%
464199.048415229 3
0.5%
464092.187505065 2
0.4%
463781.320660902 1
 
0.2%

환경업무구분명
Categorical

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.5 KiB
건설폐기물처리업사업계획(허가)신청
333 
<NA>
232 

Length

Max length18
Median length18
Mean length12.251327
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
건설폐기물처리업사업계획(허가)신청 333
58.9%
<NA> 232
41.1%

Length

2024-05-11T14:52:36.659379image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:52:36.820682image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
건설폐기물처리업사업계획(허가)신청 333
58.9%
na 232
41.1%

폐기물처리업구분명
Categorical

Distinct3
Distinct (%)0.5%
Missing0
Missing (%)0.0%
Memory size4.5 KiB
<NA>
359 
수집운반업(건설폐기물)
204 
중간처분업(건설폐기물)
 
2

Length

Max length12
Median length4
Mean length6.9168142
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 359
63.5%
수집운반업(건설폐기물) 204
36.1%
중간처분업(건설폐기물) 2
 
0.4%

Length

2024-05-11T14:52:37.018928image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:52:37.181557image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 359
63.5%
수집운반업(건설폐기물 204
36.1%
중간처분업(건설폐기물 2
 
0.4%

폐기물처리업별처리구분명
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing565
Missing (%)100.0%
Memory size5.1 KiB

폐기물구분명
Categorical

IMBALANCE 

Distinct2
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size4.5 KiB
<NA>
556 
건설폐기물
 
9

Length

Max length5
Median length4
Mean length4.0159292
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
<NA> 556
98.4%
건설폐기물 9
 
1.6%

Length

2024-05-11T14:52:37.305203image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-05-11T14:52:37.418088image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 556
98.4%
건설폐기물 9
 
1.6%

허용보관량
Real number (ℝ)

MISSING  ZEROS 

Distinct9
Distinct (%)8.6%
Missing460
Missing (%)81.4%
Infinite0
Infinite (%)0.0%
Mean293.00914
Minimum0
Maximum18000.96
Zeros86
Zeros (%)15.2%
Negative0
Negative (%)0.0%
Memory size5.1 KiB
2024-05-11T14:52:37.523975image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile0
Q10
median0
Q30
95-th percentile1050
Maximum18000.96
Range18000.96
Interquartile range (IQR)0

Descriptive statistics

Standard deviation1789.7477
Coefficient of variation (CV)6.1081634
Kurtosis94.585901
Mean293.00914
Median Absolute Deviation (MAD)0
Skewness9.5294091
Sum30765.96
Variance3203196.9
MonotonicityNot monotonic
2024-05-11T14:52:37.650736image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=9)
ValueCountFrequency (%)
0.0 86
 
15.2%
1050.0 7
 
1.2%
1.0 4
 
0.7%
450.0 2
 
0.4%
700.0 2
 
0.4%
11.0 1
 
0.2%
3000.0 1
 
0.2%
100.0 1
 
0.2%
18000.96 1
 
0.2%
(Missing) 460
81.4%
ValueCountFrequency (%)
0.0 86
15.2%
1.0 4
 
0.7%
11.0 1
 
0.2%
100.0 1
 
0.2%
450.0 2
 
0.4%
700.0 2
 
0.4%
1050.0 7
 
1.2%
3000.0 1
 
0.2%
18000.96 1
 
0.2%
ValueCountFrequency (%)
18000.96 1
 
0.2%
3000.0 1
 
0.2%
1050.0 7
 
1.2%
700.0 2
 
0.4%
450.0 2
 
0.4%
100.0 1
 
0.2%
11.0 1
 
0.2%
1.0 4
 
0.7%
0.0 86
15.2%

허용보관량내용
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing565
Missing (%)100.0%
Memory size5.1 KiB

Sample

개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)환경업무구분명폐기물처리업구분명폐기물처리업별처리구분명폐기물구분명허용보관량허용보관량내용
030600003060000922023000012023-11-22<NA>1영업/정상BBBB영업<NA><NA><NA><NA>02-433-1927<NA><NA>서울특별시 중랑구 신내동 493-84 202호서울특별시 중랑구 송림길 46-4, 202호 (신내동)02072(주)와이제이환경2023-11-22 18:30:17U2022-10-31 22:04:00.0<NA>208640.339443455474.251589<NA><NA><NA><NA><NA><NA>
131600003160000922006000052006-03-24<NA>1영업/정상BBBB영업<NA><NA><NA><NA><NA><NA>152-080서울특별시 구로구 항동 산 51-4서울특별시 구로구 부광로 88, 7층 에이701호 (항동)08362영특수츄레라(주)2024-04-18 16:37:44U2023-12-03 22:00:00.0<NA>183746.68655441744.406161<NA><NA><NA><NA><NA><NA>
230200003020000922020000012020-05-07<NA>1영업/정상BBBB영업<NA><NA><NA><NA><NA><NA><NA>서울특별시 용산구 용산동3가 1서울특별시 용산구 이태원로 22, 지하1층 (용산동3가)04383단디아이오티(iot)2023-11-23 17:53:06U2022-10-31 22:05:00.0<NA>197948.317862447933.587473<NA><NA><NA><NA><NA><NA>
330800003080000922014000022023-03-13<NA>3폐업2폐업2023-03-13<NA><NA><NA>029803646<NA>142-061서울특별시 강북구 번동 204서울특별시 강북구 월계로37길 87-5 (번동)142-061영화덤프2023-03-13 15:43:02U2022-12-02 23:05:00.0<NA>203742.886286458165.113951<NA><NA><NA><NA><NA><NA>
430800003080000922022000012022-03-08<NA>1영업/정상BBBB영업<NA><NA><NA><NA>029036661<NA>142-070서울특별시 강북구 수유동 391-197서울특별시 강북구 삼각산로 94 (수유동)142-884(주)씨와이환경2024-02-19 15:19:43U2023-12-01 22:01:00.0<NA>201230.729055459778.596434<NA><NA><NA><NA><NA><NA>
531500003150000922020000012020-10-05<NA>1영업/정상BBBB영업<NA><NA><NA><NA><NA><NA><NA>서울특별시 강서구 등촌동 697-1 그랜드종합상가서울특별시 강서구 공항대로41길 65, 그랜드종합상가 지하1층 131호 (등촌동)07586주식회사 건양환경2023-03-23 16:17:48U2022-12-02 22:05:00.0<NA>186336.003797450960.614576<NA><NA><NA><NA><NA><NA>
631000003100000922012000022012-05-29<NA>1영업/정상BBBB영업<NA><NA><NA><NA>02-6403-7895<NA>139-241서울특별시 노원구 공릉동 610-19서울특별시 노원구 동일로173가길 2 (공릉동)139-241(주)창현엘씨엠2023-08-10 14:38:06U2022-12-07 23:02:00.0<NA>206456.249867457349.726164<NA><NA><NA><NA><NA><NA>
730900003090000922015000032015-11-03<NA>1영업/정상BBBB영업<NA><NA><NA><NA>02-995-6661<NA><NA>서울특별시 도봉구 도봉동 595 럭키아파트상가 307-4호서울특별시 도봉구 도봉로 851, 307-4호 (도봉동, 럭키아파트상가)01306(주)진흥이엔티2023-06-05 09:36:05U2022-12-06 00:08:00.0<NA>203848.772423464092.187505<NA><NA><NA><NA><NA><NA>
831500003150000922019000032019-07-01<NA>1영업/정상BBBB영업<NA><NA><NA><NA>02-2663-2413<NA><NA>서울특별시 강서구 방화동 35<NA><NA>(주)에이치더블유철강2023-09-25 09:40:28U2022-12-08 22:08:00.0<NA>183559.440536453503.340943<NA><NA><NA><NA><NA><NA>
9300000030000009220080000120080102<NA>1영업/정상BBBB영업<NA><NA><NA><NA>023790618<NA>110012서울특별시 종로구 평창동 81-3서울특별시 종로구 평창문화로 127 (평창동)<NA>(주)새재공영2020-09-15 16:41:19U2020-09-17 02:40:00.0<NA>197617.321768456364.152894건설폐기물처리업사업계획(허가)신청수집운반업(건설폐기물)<NA><NA>1050.0<NA>
개방자치단체코드관리번호인허가일자인허가취소일자영업상태코드영업상태명상세영업상태코드상세영업상태명폐업일자휴업시작일자휴업종료일자재개업일자전화번호소재지면적소재지우편번호지번주소도로명주소도로명우편번호사업장명최종수정일자데이터갱신구분데이터갱신일자업태구분명좌표정보(X)좌표정보(Y)환경업무구분명폐기물처리업구분명폐기물처리업별처리구분명폐기물구분명허용보관량허용보관량내용
55531600003160000922007000022007-02-15<NA>1영업/정상BBBB영업<NA><NA><NA><NA><NA><NA>152-080서울특별시 구로구 항동 산 51-4서울특별시 구로구 부광로 88, 7층 에이701호 (항동)08362영특수츄레라(주)2024-04-18 16:37:44U2023-12-03 22:00:00.0<NA>183746.68655441744.406161<NA><NA><NA><NA><NA><NA>
55630500003050000922018000012018-09-14<NA>1영업/정상BBBB영업<NA><NA><NA><NA><NA><NA><NA>서울특별시 동대문구 장안동 374-1 장안현대벤처빌 225호서울특별시 동대문구 장한로 85, 장안현대벤처빌 225호 (장안동)02625(주)태산환경2024-02-28 14:55:02U2023-12-03 00:01:00.0<NA>206009.495098451806.846263<NA><NA><NA><NA><NA><NA>
55731300003130000922015000022022-05-27<NA>1영업/정상BBBB영업<NA><NA><NA><NA>02-304-0720<NA><NA>서울특별시 마포구 상암동 1734 상암 한화 오벨리스크서울특별시 마포구 구룡길 19, 상암 한화 오벨리스크 9층 B939호 (상암동)03918(주)청우이앤디2024-01-03 17:43:05U2023-12-01 00:05:00.0<NA>189624.675469453872.399332<NA><NA><NA><NA><NA><NA>
55831400003140000922022000012022-05-12<NA>1영업/정상BBBB영업<NA><NA><NA><NA><NA><NA><NA>서울특별시 양천구 신월동 607-1 동방아파트 상가서울특별시 양천구 신월로 220, 상가 103호 (신월동, 동방아파트)08062주식회사 모스트씨앤디2023-09-14 17:26:10U2022-12-08 23:06:00.0<NA>186357.98476446590.916613<NA><NA><NA><NA><NA><NA>
55931600003160000922013000012013-02-01<NA>1영업/정상BBBB영업<NA><NA><NA><NA>02-2686-1484<NA><NA><NA>서울특별시 구로구 중앙로1길 42, 2층 6호 (고척동, 일이삼전자타운1동)152-826디더블유기업(주)2024-02-28 08:03:10U2023-12-03 00:01:00.0<NA>187756.91945443962.832747<NA><NA><NA><NA><NA><NA>
56031800003180000922001000012023-04-21<NA>3폐업2폐업2023-04-21<NA><NA><NA>2631-0451<NA>150-032서울특별시 영등포구 영등포동2가 94-24 카보드동우빌딩 405호서울특별시 영등포구 버드나루로7길 7, 405호 (영등포동2가)07249창조중기2023-04-21 14:43:11U2022-12-03 22:03:00.0<NA>191979.460401446740.301257<NA><NA><NA><NA><NA><NA>
56131700003170000922021000012021-07-27<NA>1영업/정상BBBB영업<NA><NA><NA><NA><NA><NA><NA>서울특별시 금천구 시흥동 109-1 무지개상가 16호서울특별시 금천구 시흥대로73길 11, 2층 16호 (시흥동, 무지개아파트)08613주식회사 에코그리니치2024-05-04 13:57:02U2023-12-05 00:06:00.0<NA>190932.07604439328.504764<NA><NA><NA><NA><NA><NA>
56231600003160000922006000262006-11-24<NA>1영업/정상BBBB영업<NA><NA><NA><NA><NA><NA>152-080서울특별시 구로구 항동 산 51-4서울특별시 구로구 부광로 88, 7층 에이701호 (항동)08362영특수츄레라(주)2024-04-18 16:37:44U2023-12-03 22:00:00.0<NA>183746.68655441744.406161<NA><NA><NA><NA><NA><NA>
56331600003160000922006000232006-10-18<NA>1영업/정상BBBB영업<NA><NA><NA><NA><NA><NA>152-080서울특별시 구로구 항동 산 51-4서울특별시 구로구 부광로 88, 7층 에이701호 (항동)08362영특수츄레라(주)2024-04-18 16:37:44U2023-12-03 22:00:00.0<NA>183746.68655441744.406161<NA><NA><NA><NA><NA><NA>
56430600003060000922007000052000-11-30<NA>1영업/정상BBBB영업<NA><NA><NA><NA>0222087474<NA><NA>서울특별시 중랑구 면목동 1342-8 용마산타워 201호서울특별시 중랑구 용마산로 194, 201호 (면목동, 용마산타워)02256(공동대표)용마산건설2024-04-19 13:48:50U2023-12-03 22:01:00.0<NA>207564.34181452077.782812<NA><NA><NA><NA><NA><NA>