Overview

Dataset statistics

Number of variables12
Number of observations10000
Missing cells30253
Missing cells (%)25.2%
Duplicate rows1066
Duplicate rows (%)10.7%
Total size in memory1.0 MiB
Average record size in memory107.0 B

Variable types

Categorical1
Text7
Numeric3
DateTime1

Dataset

Description사업장 폐기물 배출 신고 현황
Author가평군
URLhttps://data.gg.go.kr/portal/data/service/selectServicePage.do?&infId=GD0H9M3WQZLPG2CC9HDB30394421&infSeq=1

Alerts

Dataset has 1066 (10.7%) duplicate rowsDuplicates
위도 is highly overall correlated with 우편번호High correlation
경도 is highly overall correlated with 시군명High correlation
우편번호 is highly overall correlated with 위도High correlation
시군명 is highly overall correlated with 경도High correlation
사업장전화번호 has 5937 (59.4%) missing valuesMissing
소재지도로명주소 has 1608 (16.1%) missing valuesMissing
소재지지번주소 has 1380 (13.8%) missing valuesMissing
위도 has 1385 (13.9%) missing valuesMissing
경도 has 1384 (13.8%) missing valuesMissing
인허가관리번호 has 5310 (53.1%) missing valuesMissing
인허가등록일자 has 5430 (54.3%) missing valuesMissing
배출폐기물코드 has 6393 (63.9%) missing valuesMissing
우편번호 has 1416 (14.2%) missing valuesMissing

Reproduction

Analysis started2024-03-23 01:37:15.492529
Analysis finished2024-03-23 01:37:29.193303
Duration13.7 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시군명
Categorical

HIGH CORRELATION 

Distinct28
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size156.2 KiB
화성시
2304 
포천시
1366 
용인시
1345 
안산시
906 
안양시
815 
Other values (23)
3264 

Length

Max length4
Median length3
Mean length3.0886
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row안산시
2nd row파주시
3rd row용인시
4th row포천시
5th row화성시

Common Values

ValueCountFrequency (%)
화성시 2304
23.0%
포천시 1366
13.7%
용인시 1345
13.5%
안산시 906
 
9.1%
안양시 815
 
8.2%
남양주시 776
 
7.8%
파주시 323
 
3.2%
의왕시 295
 
2.9%
여주시 225
 
2.2%
평택시 211
 
2.1%
Other values (18) 1434
14.3%

Length

2024-03-23T01:37:29.487506image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
화성시 2304
23.0%
포천시 1366
13.7%
용인시 1345
13.5%
안산시 906
 
9.1%
안양시 815
 
8.2%
남양주시 776
 
7.8%
파주시 323
 
3.2%
의왕시 295
 
2.9%
여주시 225
 
2.2%
평택시 211
 
2.1%
Other values (18) 1434
14.3%

상호명
Text

Distinct5710
Distinct (%)57.1%
Missing1
Missing (%)< 0.1%
Memory size156.2 KiB
2024-03-23T01:37:30.036645image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length38
Median length27
Mean length8.4380438
Min length2

Characters and Unicode

Total characters84372
Distinct characters715
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

Unique4154 ?
Unique (%)41.5%

Sample

1st row(주)한길전자
2nd row(주)포모스트(지점)
3rd row코레드무역주식회사
4th row세종산업
5th row(주)신원에프아이
ValueCountFrequency (%)
주식회사 728
 
6.0%
주)에코비트워터 116
 
1.0%
주)노루페인트 81
 
0.7%
농업회사법인 59
 
0.5%
진접 49
 
0.4%
신대한정유산업(주 48
 
0.4%
주)원보 43
 
0.4%
주)수도권서부자원순환센터 40
 
0.3%
진건바이오텍(주 39
 
0.3%
주)이마트 37
 
0.3%
Other values (5988) 10803
89.7%
2024-03-23T01:37:31.185246image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 6374
 
7.6%
( 5762
 
6.8%
) 5760
 
6.8%
2044
 
2.4%
사 1677
 
2.0%
이 1643
 
1.9%
업 1532
 
1.8%
스 1487
 
1.8%
산 1225
 
1.5%
에 1217
 
1.4%
Other values (705) 55651
66.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 68501
81.2%
Open Punctuation 5786
 
6.9%
Close Punctuation 5784
 
6.9%
Space Separator 2044
 
2.4%
Other Symbol 1055
 
1.3%
Uppercase Letter 601
 
0.7%
Decimal Number 317
 
0.4%
Lowercase Letter 181
 
0.2%
Other Punctuation 68
 
0.1%
Connector Punctuation 21
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 6374
 
9.3%
사 1677
 
2.4%
이 1643
 
2.4%
업 1532
 
2.2%
스 1487
 
2.2%
산 1225
 
1.8%
에 1217
 
1.8%
원 1146
 
1.7%
회 1070
 
1.6%
식 1045
 
1.5%
Other values (644) 50085
73.1%
Uppercase Letter
ValueCountFrequency (%)
S 59
 
9.8%
C 58
 
9.7%
K 53
 
8.8%
G 38
 
6.3%
E 37
 
6.2%
N 35
 
5.8%
A 33
 
5.5%
F 32
 
5.3%
I 29
 
4.8%
R 28
 
4.7%
Other values (13) 199
33.1%
Lowercase Letter
ValueCountFrequency (%)
n 24
13.3%
a 22
12.2%
c 18
9.9%
o 17
9.4%
l 15
8.3%
t 15
8.3%
i 15
8.3%
d 14
7.7%
v 14
7.7%
r 8
 
4.4%
Other values (7) 19
10.5%
Decimal Number
ValueCountFrequency (%)
2 121
38.2%
3 59
18.6%
1 55
17.4%
6 20
 
6.3%
5 15
 
4.7%
4 12
 
3.8%
8 12
 
3.8%
7 9
 
2.8%
9 9
 
2.8%
0 5
 
1.6%
Other Punctuation
ValueCountFrequency (%)
. 38
55.9%
& 17
25.0%
/ 13
 
19.1%
Open Punctuation
ValueCountFrequency (%)
( 5762
99.6%
[ 24
 
0.4%
Close Punctuation
ValueCountFrequency (%)
) 5760
99.6%
] 24
 
0.4%
Space Separator
ValueCountFrequency (%)
2044
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 1055
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 21
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 14
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 69556
82.4%
Common 14034
 
16.6%
Latin 782
 
0.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 6374
 
9.2%
사 1677
 
2.4%
이 1643
 
2.4%
업 1532
 
2.2%
스 1487
 
2.1%
산 1225
 
1.8%
에 1217
 
1.7%
원 1146
 
1.6%
회 1070
 
1.5%
㈜ 1055
 
1.5%
Other values (645) 51130
73.5%
Latin
ValueCountFrequency (%)
S 59
 
7.5%
C 58
 
7.4%
K 53
 
6.8%
G 38
 
4.9%
E 37
 
4.7%
N 35
 
4.5%
A 33
 
4.2%
F 32
 
4.1%
I 29
 
3.7%
R 28
 
3.6%
Other values (30) 380
48.6%
Common
ValueCountFrequency (%)
( 5762
41.1%
) 5760
41.0%
2044
 
14.6%
2 121
 
0.9%
3 59
 
0.4%
1 55
 
0.4%
. 38
 
0.3%
[ 24
 
0.2%
] 24
 
0.2%
_ 21
 
0.1%
Other values (10) 126
 
0.9%

Most occurring blocks

ValueCountFrequency (%)
Hangul 68501
81.2%
ASCII 14816
 
17.6%
None 1055
 
1.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 6374
 
9.3%
사 1677
 
2.4%
이 1643
 
2.4%
업 1532
 
2.2%
스 1487
 
2.2%
산 1225
 
1.8%
에 1217
 
1.8%
원 1146
 
1.7%
회 1070
 
1.6%
식 1045
 
1.5%
Other values (644) 50085
73.1%
ASCII
ValueCountFrequency (%)
( 5762
38.9%
) 5760
38.9%
2044
 
13.8%
2 121
 
0.8%
3 59
 
0.4%
S 59
 
0.4%
C 58
 
0.4%
1 55
 
0.4%
K 53
 
0.4%
G 38
 
0.3%
Other values (50) 807
 
5.4%
None
ValueCountFrequency (%)
㈜ 1055
100.0%

사업장전화번호
Text

MISSING 

Distinct2389
Distinct (%)58.8%
Missing5937
Missing (%)59.4%
Memory size156.2 KiB
2024-03-23T01:37:31.824948image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length11.07236
Min length8

Characters and Unicode

Total characters44987
Distinct characters14
Distinct categories5 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1746 ?
Unique (%)43.0%

Sample

1st row031-495-2452
2nd row031-954-3800
3rd row313510221
4th row031-8040-0000
5th row***-****-****
ValueCountFrequency (%)
031-352-3831 44
 
1.1%
313542861 40
 
1.0%
38
 
0.9%
312081792 36
 
0.9%
031-355-0022 27
 
0.7%
031-354-6527 26
 
0.6%
313686106 18
 
0.4%
031-489-6917 15
 
0.4%
313661548 14
 
0.3%
313576451 14
 
0.3%
Other values (2381) 3805
93.3%
2024-03-23T01:37:32.919672image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3 7691
17.1%
1 6422
14.3%
0 5885
13.1%
- 5341
11.9%
5 3541
7.9%
4 2966
 
6.6%
2 2723
 
6.1%
6 2705
 
6.0%
9 2654
 
5.9%
8 2463
 
5.5%
Other values (4) 2596
 
5.8%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 39214
87.2%
Dash Punctuation 5341
 
11.9%
Other Punctuation 417
 
0.9%
Space Separator 14
 
< 0.1%
Math Symbol 1
 
< 0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
3 7691
19.6%
1 6422
16.4%
0 5885
15.0%
5 3541
9.0%
4 2966
 
7.6%
2 2723
 
6.9%
6 2705
 
6.9%
9 2654
 
6.8%
8 2463
 
6.3%
7 2164
 
5.5%
Dash Punctuation
ValueCountFrequency (%)
- 5341
100.0%
Other Punctuation
ValueCountFrequency (%)
* 417
100.0%
Space Separator
ValueCountFrequency (%)
14
100.0%
Math Symbol
ValueCountFrequency (%)
~ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 44987
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
3 7691
17.1%
1 6422
14.3%
0 5885
13.1%
- 5341
11.9%
5 3541
7.9%
4 2966
 
6.6%
2 2723
 
6.1%
6 2705
 
6.0%
9 2654
 
5.9%
8 2463
 
5.5%
Other values (4) 2596
 
5.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 44987
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3 7691
17.1%
1 6422
14.3%
0 5885
13.1%
- 5341
11.9%
5 3541
7.9%
4 2966
 
6.6%
2 2723
 
6.1%
6 2705
 
6.0%
9 2654
 
5.9%
8 2463
 
5.5%
Other values (4) 2596
 
5.8%

소재지도로명주소
Text

MISSING 

Distinct4262
Distinct (%)50.8%
Missing1608
Missing (%)16.1%
Memory size156.2 KiB
2024-03-23T01:37:33.735091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length81
Median length42
Mean length21.14919
Min length13

Characters and Unicode

Total characters177484
Distinct characters449
Distinct categories12 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2822 ?
Unique (%)33.6%

Sample

1st row경기도 안산시 단원구 만해로169번길 28
2nd row경기도 파주시 파주읍 아랫도장길 8
3rd row경기도 포천시 가산면 정금로 122
4th row경기도 화성시 장안면 수정로299번길 18
5th row경기도 의왕시 포일세거리로 3
ValueCountFrequency (%)
경기도 8334
 
20.4%
화성시 2306
 
5.6%
포천시 1219
 
3.0%
안산시 913
 
2.2%
단원구 890
 
2.2%
안양시 796
 
1.9%
남양주시 756
 
1.9%
만안구 485
 
1.2%
파주시 325
 
0.8%
향남읍 314
 
0.8%
Other values (4488) 24506
60.0%
2024-03-23T01:37:34.831171image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
32455
 
18.3%
도 8825
 
5.0%
시 8608
 
4.9%
경 8577
 
4.8%
기 8543
 
4.8%
로 6856
 
3.9%
1 6234
 
3.5%
2 4752
 
2.7%
3 4079
 
2.3%
길 3949
 
2.2%
Other values (439) 84606
47.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 108263
61.0%
Decimal Number 33209
 
18.7%
Space Separator 32455
 
18.3%
Dash Punctuation 2832
 
1.6%
Connector Punctuation 275
 
0.2%
Open Punctuation 195
 
0.1%
Close Punctuation 195
 
0.1%
Other Punctuation 37
 
< 0.1%
Uppercase Letter 16
 
< 0.1%
Math Symbol 5
 
< 0.1%
Other values (2) 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 8825
 
8.2%
시 8608
 
8.0%
경 8577
 
7.9%
기 8543
 
7.9%
로 6856
 
6.3%
길 3949
 
3.6%
안 3553
 
3.3%
면 2959
 
2.7%
성 2813
 
2.6%
화 2779
 
2.6%
Other values (411) 50801
46.9%
Decimal Number
ValueCountFrequency (%)
1 6234
18.8%
2 4752
14.3%
3 4079
12.3%
4 2893
8.7%
5 2880
8.7%
6 2650
8.0%
0 2560
7.7%
7 2537
7.6%
8 2327
 
7.0%
9 2297
 
6.9%
Uppercase Letter
ValueCountFrequency (%)
I 5
31.2%
B 3
18.8%
K 2
 
12.5%
C 2
 
12.5%
S 1
 
6.2%
L 1
 
6.2%
G 1
 
6.2%
T 1
 
6.2%
Other Punctuation
ValueCountFrequency (%)
. 35
94.6%
, 2
 
5.4%
Space Separator
ValueCountFrequency (%)
32455
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2832
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 275
100.0%
Open Punctuation
ValueCountFrequency (%)
( 195
100.0%
Close Punctuation
ValueCountFrequency (%)
) 195
100.0%
Math Symbol
ValueCountFrequency (%)
~ 5
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 1
100.0%
Lowercase Letter
ValueCountFrequency (%)
n 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 108263
61.0%
Common 69203
39.0%
Latin 18
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 8825
 
8.2%
시 8608
 
8.0%
경 8577
 
7.9%
기 8543
 
7.9%
로 6856
 
6.3%
길 3949
 
3.6%
안 3553
 
3.3%
면 2959
 
2.7%
성 2813
 
2.6%
화 2779
 
2.6%
Other values (411) 50801
46.9%
Common
ValueCountFrequency (%)
32455
46.9%
1 6234
 
9.0%
2 4752
 
6.9%
3 4079
 
5.9%
4 2893
 
4.2%
5 2880
 
4.2%
- 2832
 
4.1%
6 2650
 
3.8%
0 2560
 
3.7%
7 2537
 
3.7%
Other values (8) 5331
 
7.7%
Latin
ValueCountFrequency (%)
I 5
27.8%
B 3
16.7%
K 2
 
11.1%
C 2
 
11.1%
Ⅱ 1
 
5.6%
S 1
 
5.6%
n 1
 
5.6%
L 1
 
5.6%
G 1
 
5.6%
T 1
 
5.6%

Most occurring blocks

ValueCountFrequency (%)
Hangul 108263
61.0%
ASCII 69220
39.0%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
32455
46.9%
1 6234
 
9.0%
2 4752
 
6.9%
3 4079
 
5.9%
4 2893
 
4.2%
5 2880
 
4.2%
- 2832
 
4.1%
6 2650
 
3.8%
0 2560
 
3.7%
7 2537
 
3.7%
Other values (17) 5348
 
7.7%
Hangul
ValueCountFrequency (%)
도 8825
 
8.2%
시 8608
 
8.0%
경 8577
 
7.9%
기 8543
 
7.9%
로 6856
 
6.3%
길 3949
 
3.6%
안 3553
 
3.3%
면 2959
 
2.7%
성 2813
 
2.6%
화 2779
 
2.6%
Other values (411) 50801
46.9%
Number Forms
ValueCountFrequency (%)
Ⅱ 1
100.0%

소재지지번주소
Text

MISSING 

Distinct4462
Distinct (%)51.8%
Missing1380
Missing (%)13.8%
Memory size156.2 KiB
2024-03-23T01:37:35.493195image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length81
Median length45
Mean length22.490139
Min length11

Characters and Unicode

Total characters193865
Distinct characters456
Distinct categories12 ?
Distinct scripts4 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique3004 ?
Unique (%)34.8%

Sample

1st row경기도 안산시 단원구 신길동 1054-10번지
2nd row경기도 파주시 파주읍 백석리 416-3번지
3rd row경기도 포천시 가산면 정교리 334-4번지
4th row경기도 화성시 장안면 수촌리 263번지
5th row경기도 의왕시 포일동 662번지
ValueCountFrequency (%)
경기도 8562
 
20.2%
화성시 2309
 
5.4%
포천시 1367
 
3.2%
안산시 913
 
2.2%
단원구 890
 
2.1%
안양시 808
 
1.9%
남양주시 779
 
1.8%
만안구 491
 
1.2%
성곡동 378
 
0.9%
파주시 325
 
0.8%
Other values (5285) 25574
60.3%
2024-03-23T01:37:36.616390image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
33776
 
17.4%
도 8973
 
4.6%
시 8767
 
4.5%
기 8640
 
4.5%
경 8588
 
4.4%
지 8346
 
4.3%
번 7992
 
4.1%
1 6620
 
3.4%
- 6245
 
3.2%
리 5038
 
2.6%
Other values (446) 90880
46.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 119384
61.6%
Decimal Number 33844
 
17.5%
Space Separator 33776
 
17.4%
Dash Punctuation 6245
 
3.2%
Connector Punctuation 238
 
0.1%
Close Punctuation 127
 
0.1%
Open Punctuation 127
 
0.1%
Uppercase Letter 103
 
0.1%
Lowercase Letter 14
 
< 0.1%
Math Symbol 4
 
< 0.1%
Other values (2) 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
도 8973
 
7.5%
시 8767
 
7.3%
기 8640
 
7.2%
경 8588
 
7.2%
지 8346
 
7.0%
번 7992
 
6.7%
리 5038
 
4.2%
동 4604
 
3.9%
안 3329
 
2.8%
면 3080
 
2.6%
Other values (403) 52027
43.6%
Uppercase Letter
ValueCountFrequency (%)
B 24
23.3%
L 15
14.6%
C 11
10.7%
I 10
9.7%
K 8
 
7.8%
T 8
 
7.8%
S 7
 
6.8%
G 3
 
2.9%
N 3
 
2.9%
D 3
 
2.9%
Other values (7) 11
10.7%
Decimal Number
ValueCountFrequency (%)
1 6620
19.6%
2 3936
11.6%
6 3280
9.7%
3 3250
9.6%
4 3243
9.6%
5 3123
9.2%
7 2958
8.7%
0 2605
 
7.7%
8 2522
 
7.5%
9 2307
 
6.8%
Lowercase Letter
ValueCountFrequency (%)
e 4
28.6%
h 3
21.4%
c 3
21.4%
r 1
 
7.1%
w 1
 
7.1%
o 1
 
7.1%
n 1
 
7.1%
Other Punctuation
ValueCountFrequency (%)
, 1
50.0%
. 1
50.0%
Space Separator
ValueCountFrequency (%)
33776
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 6245
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 238
100.0%
Close Punctuation
ValueCountFrequency (%)
) 127
100.0%
Open Punctuation
ValueCountFrequency (%)
( 127
100.0%
Math Symbol
ValueCountFrequency (%)
~ 4
100.0%
Letter Number
ValueCountFrequency (%)
Ⅱ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 119382
61.6%
Common 74363
38.4%
Latin 118
 
0.1%
Han 2
 
< 0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
도 8973
 
7.5%
시 8767
 
7.3%
기 8640
 
7.2%
경 8588
 
7.2%
지 8346
 
7.0%
번 7992
 
6.7%
리 5038
 
4.2%
동 4604
 
3.9%
안 3329
 
2.8%
면 3080
 
2.6%
Other values (401) 52025
43.6%
Latin
ValueCountFrequency (%)
B 24
20.3%
L 15
12.7%
C 11
9.3%
I 10
 
8.5%
K 8
 
6.8%
T 8
 
6.8%
S 7
 
5.9%
e 4
 
3.4%
G 3
 
2.5%
N 3
 
2.5%
Other values (15) 25
21.2%
Common
ValueCountFrequency (%)
33776
45.4%
1 6620
 
8.9%
- 6245
 
8.4%
2 3936
 
5.3%
6 3280
 
4.4%
3 3250
 
4.4%
4 3243
 
4.4%
5 3123
 
4.2%
7 2958
 
4.0%
0 2605
 
3.5%
Other values (8) 5327
 
7.2%
Han
ValueCountFrequency (%)
家 1
50.0%
休 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 119382
61.6%
ASCII 74480
38.4%
CJK 2
 
< 0.1%
Number Forms 1
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
33776
45.3%
1 6620
 
8.9%
- 6245
 
8.4%
2 3936
 
5.3%
6 3280
 
4.4%
3 3250
 
4.4%
4 3243
 
4.4%
5 3123
 
4.2%
7 2958
 
4.0%
0 2605
 
3.5%
Other values (32) 5444
 
7.3%
Hangul
ValueCountFrequency (%)
도 8973
 
7.5%
시 8767
 
7.3%
기 8640
 
7.2%
경 8588
 
7.2%
지 8346
 
7.0%
번 7992
 
6.7%
리 5038
 
4.2%
동 4604
 
3.9%
안 3329
 
2.8%
면 3080
 
2.6%
Other values (401) 52025
43.6%
Number Forms
ValueCountFrequency (%)
Ⅱ 1
100.0%
CJK
ValueCountFrequency (%)
家 1
50.0%
休 1
50.0%

위도
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct4494
Distinct (%)52.2%
Missing1385
Missing (%)13.9%
Infinite0
Infinite (%)0.0%
Mean37.429537
Minimum34.604743
Maximum38.198
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-23T01:37:37.104068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum34.604743
5-th percentile37.075813
Q137.188691
median37.358066
Q337.686829
95-th percentile37.941423
Maximum38.198
Range3.5932565
Interquartile range (IQR)0.49813802

Descriptive statistics

Standard deviation0.29575326
Coefficient of variation (CV)0.0079016007
Kurtosis2.9294747
Mean37.429537
Median Absolute Deviation (MAD)0.20818846
Skewness-0.043067385
Sum322455.46
Variance0.087469989
MonotonicityNot monotonic
2024-03-23T01:37:37.588136image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
37.63541371 79
 
0.8%
37.71130402 49
 
0.5%
37.407501 48
 
0.5%
37.1610569731 44
 
0.4%
37.1347464028 40
 
0.4%
37.67348828 37
 
0.4%
37.2234666446 36
 
0.4%
37.58571147 35
 
0.4%
37.59700255 35
 
0.4%
37.40750113 33
 
0.3%
Other values (4484) 8179
81.8%
(Missing) 1385
 
13.9%
ValueCountFrequency (%)
34.6047432747 1
 
< 0.1%
35.0164768339 1
 
< 0.1%
35.0851745699 1
 
< 0.1%
35.1992315615 1
 
< 0.1%
35.2362280855 4
< 0.1%
35.2460457524 1
 
< 0.1%
35.9626997025 1
 
< 0.1%
36.32588625 1
 
< 0.1%
36.8270222107 1
 
< 0.1%
36.8316022769 1
 
< 0.1%
ValueCountFrequency (%)
38.19799973 1
 
< 0.1%
38.1977694 1
 
< 0.1%
38.18462738 1
 
< 0.1%
38.143373 1
 
< 0.1%
38.139702 3
< 0.1%
38.1061118 1
 
< 0.1%
38.10471837 1
 
< 0.1%
38.1014787727 1
 
< 0.1%
38.100652 1
 
< 0.1%
38.092686 2
< 0.1%

경도
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct4483
Distinct (%)52.0%
Missing1384
Missing (%)13.8%
Infinite0
Infinite (%)0.0%
Mean127.01684
Minimum126.52141
Maximum129.09229
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-23T01:37:38.166642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.52141
5-th percentile126.75194
Q1126.84175
median126.96576
Q3127.18322
95-th percentile127.40858
Maximum129.09229
Range2.5708787
Interquartile range (IQR)0.34147444

Descriptive statistics

Standard deviation0.21938466
Coefficient of variation (CV)0.0017272093
Kurtosis2.2319298
Mean127.01684
Median Absolute Deviation (MAD)0.17270575
Skewness0.98710339
Sum1094377.1
Variance0.048129629
MonotonicityNot monotonic
2024-03-23T01:37:38.669070image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.1507551 79
 
0.8%
127.1885882 49
 
0.5%
126.891601 48
 
0.5%
127.0155895718 44
 
0.4%
126.8025511578 40
 
0.4%
127.2006643 37
 
0.4%
127.0633444875 36
 
0.4%
127.1656098 35
 
0.4%
127.1620332 35
 
0.4%
126.8916006 33
 
0.3%
Other values (4473) 8180
81.8%
(Missing) 1384
 
13.8%
ValueCountFrequency (%)
126.5214101628 1
< 0.1%
126.5629882 1
< 0.1%
126.564627 1
< 0.1%
126.5848889 1
< 0.1%
126.6023958345 1
< 0.1%
126.6063859 1
< 0.1%
126.6138857801 1
< 0.1%
126.621185 1
< 0.1%
126.6295714643 1
< 0.1%
126.6509564 1
< 0.1%
ValueCountFrequency (%)
129.0922888941 1
 
< 0.1%
128.5802563107 4
< 0.1%
128.2635672859 1
 
< 0.1%
128.1228895 1
 
< 0.1%
128.0847459656 1
 
< 0.1%
127.788241 2
< 0.1%
127.7434123 1
 
< 0.1%
127.739319 1
 
< 0.1%
127.7339648 1
 
< 0.1%
127.726306 1
 
< 0.1%

인허가관리번호
Text

MISSING 

Distinct2989
Distinct (%)63.7%
Missing5310
Missing (%)53.1%
Memory size156.2 KiB
2024-03-23T01:37:39.428967image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length22
Median length21
Mean length21
Min length20

Characters and Unicode

Total characters98490
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

Unique2428 ?
Unique (%)51.8%

Sample

1st row3930000-31-2008-00008
2nd row4060000-31-2013-00018
3rd row3930000-31-2008-00020
4th row3990000-31-2018-00006
5th row3860000-31-2022-00013
ValueCountFrequency (%)
3990000-31-2010-00020 49
 
1.0%
3830000-31-2007-00019 45
 
1.0%
3990000-31-2021-00018 35
 
0.7%
3990000-31-2013-00008 35
 
0.7%
3830000-31-1992-00007 34
 
0.7%
3830000-31-1997-00074 29
 
0.6%
3990000-31-2012-00028 25
 
0.5%
3830000-31-2008-00024 24
 
0.5%
3830000-31-2007-00023 24
 
0.5%
3990000-31-2020-00031 24
 
0.5%
Other values (2979) 4366
93.1%
2024-03-23T01:37:40.521614image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 40359
41.0%
- 14070
 
14.3%
3 11500
 
11.7%
1 9706
 
9.9%
2 8039
 
8.2%
9 5264
 
5.3%
8 2383
 
2.4%
4 2339
 
2.4%
7 1913
 
1.9%
6 1639
 
1.7%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 84420
85.7%
Dash Punctuation 14070
 
14.3%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 40359
47.8%
3 11500
 
13.6%
1 9706
 
11.5%
2 8039
 
9.5%
9 5264
 
6.2%
8 2383
 
2.8%
4 2339
 
2.8%
7 1913
 
2.3%
6 1639
 
1.9%
5 1278
 
1.5%
Dash Punctuation
ValueCountFrequency (%)
- 14070
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 98490
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
0 40359
41.0%
- 14070
 
14.3%
3 11500
 
11.7%
1 9706
 
9.9%
2 8039
 
8.2%
9 5264
 
5.3%
8 2383
 
2.4%
4 2339
 
2.4%
7 1913
 
1.9%
6 1639
 
1.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 98490
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 40359
41.0%
- 14070
 
14.3%
3 11500
 
11.7%
1 9706
 
9.9%
2 8039
 
8.2%
9 5264
 
5.3%
8 2383
 
2.4%
4 2339
 
2.4%
7 1913
 
1.9%
6 1639
 
1.7%

인허가등록일자
Date

MISSING 

Distinct1992
Distinct (%)43.6%
Missing5430
Missing (%)54.3%
Memory size156.2 KiB
Minimum1994-04-23 00:00:00
Maximum2077-07-22 00:00:00
2024-03-23T01:37:40.947992image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T01:37:41.414259image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

배출폐기물코드
Text

MISSING 

Distinct387
Distinct (%)10.7%
Missing6393
Missing (%)63.9%
Memory size156.2 KiB
2024-03-23T01:37:42.090919image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length197
Median length152
Mean length9.3376767
Min length3

Characters and Unicode

Total characters33681
Distinct characters24
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

Unique236 ?
Unique (%)6.5%

Sample

1st row1951-02-01
2nd row비공개
3rd row1951-01-06
4th row51-05-99
5th row51-03-01+51-17-29
ValueCountFrequency (%)
배출시설계 852
23.1%
1951-03-01 412
 
11.2%
비공개 323
 
8.8%
51-20-01 169
 
4.6%
51-03-01 155
 
4.2%
1951-02-01 130
 
3.5%
1951-11-03 124
 
3.4%
51-99-00 82
 
2.2%
51-20-21 69
 
1.9%
비배출시설계 68
 
1.8%
Other values (366) 1307
35.4%
2024-03-23T01:37:43.249328image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 6671
19.8%
- 6325
18.8%
0 5019
14.9%
5 3240
9.6%
9 2010
 
6.0%
2 1511
 
4.5%
3 1363
 
4.0%
배 920
 
2.7%
시 920
 
2.7%
설 920
 
2.7%
Other values (14) 4782
14.2%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 20808
61.8%
Dash Punctuation 6325
 
18.8%
Other Letter 5637
 
16.7%
Math Symbol 802
 
2.4%
Space Separator 84
 
0.2%
Other Punctuation 25
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
1 6671
32.1%
0 5019
24.1%
5 3240
15.6%
9 2010
 
9.7%
2 1511
 
7.3%
3 1363
 
6.6%
7 312
 
1.5%
8 283
 
1.4%
4 225
 
1.1%
6 174
 
0.8%
Other Letter
ValueCountFrequency (%)
배 920
16.3%
시 920
16.3%
설 920
16.3%
계 920
16.3%
출 920
16.3%
비 391
6.9%
공 323
 
5.7%
개 323
 
5.7%
Other Punctuation
ValueCountFrequency (%)
. 21
84.0%
; 2
 
8.0%
, 2
 
8.0%
Dash Punctuation
ValueCountFrequency (%)
- 6325
100.0%
Math Symbol
ValueCountFrequency (%)
+ 802
100.0%
Space Separator
ValueCountFrequency (%)
84
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 28044
83.3%
Hangul 5637
 
16.7%

Most frequent character per script

Common
ValueCountFrequency (%)
1 6671
23.8%
- 6325
22.6%
0 5019
17.9%
5 3240
11.6%
9 2010
 
7.2%
2 1511
 
5.4%
3 1363
 
4.9%
+ 802
 
2.9%
7 312
 
1.1%
8 283
 
1.0%
Other values (6) 508
 
1.8%
Hangul
ValueCountFrequency (%)
배 920
16.3%
시 920
16.3%
설 920
16.3%
계 920
16.3%
출 920
16.3%
비 391
6.9%
공 323
 
5.7%
개 323
 
5.7%

Most occurring blocks

ValueCountFrequency (%)
ASCII 28044
83.3%
Hangul 5637
 
16.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 6671
23.8%
- 6325
22.6%
0 5019
17.9%
5 3240
11.6%
9 2010
 
7.2%
2 1511
 
5.4%
3 1363
 
4.9%
+ 802
 
2.9%
7 312
 
1.1%
8 283
 
1.0%
Other values (6) 508
 
1.8%
Hangul
ValueCountFrequency (%)
배 920
16.3%
시 920
16.3%
설 920
16.3%
계 920
16.3%
출 920
16.3%
비 391
6.9%
공 323
 
5.7%
개 323
 
5.7%

배출폐기물종류
Text

Distinct594
Distinct (%)5.9%
Missing9
Missing (%)0.1%
Memory size156.2 KiB
2024-03-23T01:37:44.041968image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length207
Median length157
Mean length15.682514
Min length2

Characters and Unicode

Total characters156684
Distinct characters306
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique337 ?
Unique (%)3.4%

Sample

1st row폐수처리오니
2nd row비공개
3rd row사업장폐기물배출자
4th row목재가공공장 부산물(접착제_ 페인트_ 기름_ 콘크리트 등의 물질이 사용된 목재부산물 및 분진을 말한다)
5th row축산물가공잔재물(동물성 유지류는 제외한다)
ValueCountFrequency (%)
제외한다 2594
 
10.8%
폐합성수지류(폐염화비닐수지류는 2506
 
10.4%
밖의 1599
 
6.7%
그 1407
 
5.9%
건설폐기물배출자 749
 
3.1%
말한다 570
 
2.4%
폐수처리오니 525
 
2.2%
등의 461
 
1.9%
과정에서 402
 
1.7%
사업장폐기물배출자 376
 
1.6%
Other values (779) 12832
53.4%
2024-03-23T01:37:45.309987image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
14031
 
9.0%
폐 12070
 
7.7%
수 7169
 
4.6%
류 6992
 
4.5%
지 6589
 
4.2%
물 4539
 
2.9%
성 4321
 
2.8%
한 3895
 
2.5%
합 3635
 
2.3%
) 3554
 
2.3%
Other values (296) 89889
57.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 132571
84.6%
Space Separator 14031
 
9.0%
Close Punctuation 3578
 
2.3%
Open Punctuation 3578
 
2.3%
Connector Punctuation 1543
 
1.0%
Math Symbol 1021
 
0.7%
Lowercase Letter 144
 
0.1%
Decimal Number 119
 
0.1%
Other Punctuation 87
 
0.1%
Uppercase Letter 12
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
폐 12070
 
9.1%
수 7169
 
5.4%
류 6992
 
5.3%
지 6589
 
5.0%
물 4539
 
3.4%
성 4321
 
3.3%
한 3895
 
2.9%
합 3635
 
2.7%
다 3507
 
2.6%
제 3211
 
2.4%
Other values (268) 76643
57.8%
Lowercase Letter
ValueCountFrequency (%)
e 48
33.3%
a 24
16.7%
g 12
 
8.3%
r 12
 
8.3%
s 12
 
8.3%
h 12
 
8.3%
l 12
 
8.3%
t 12
 
8.3%
Decimal Number
ValueCountFrequency (%)
2 67
56.3%
1 22
 
18.5%
0 12
 
10.1%
8 10
 
8.4%
3 3
 
2.5%
7 3
 
2.5%
4 2
 
1.7%
Close Punctuation
ValueCountFrequency (%)
) 3554
99.3%
] 12
 
0.3%
」 12
 
0.3%
Open Punctuation
ValueCountFrequency (%)
( 3554
99.3%
[ 12
 
0.3%
「 12
 
0.3%
Other Punctuation
ValueCountFrequency (%)
, 66
75.9%
. 13
 
14.9%
· 8
 
9.2%
Space Separator
ValueCountFrequency (%)
14031
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 1543
100.0%
Math Symbol
ValueCountFrequency (%)
+ 1021
100.0%
Uppercase Letter
ValueCountFrequency (%)
C 12
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 132571
84.6%
Common 23957
 
15.3%
Latin 156
 
0.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
폐 12070
 
9.1%
수 7169
 
5.4%
류 6992
 
5.3%
지 6589
 
5.0%
물 4539
 
3.4%
성 4321
 
3.3%
한 3895
 
2.9%
합 3635
 
2.7%
다 3507
 
2.6%
제 3211
 
2.4%
Other values (268) 76643
57.8%
Common
ValueCountFrequency (%)
14031
58.6%
) 3554
 
14.8%
( 3554
 
14.8%
_ 1543
 
6.4%
+ 1021
 
4.3%
2 67
 
0.3%
, 66
 
0.3%
1 22
 
0.1%
. 13
 
0.1%
] 12
 
0.1%
Other values (9) 74
 
0.3%
Latin
ValueCountFrequency (%)
e 48
30.8%
a 24
15.4%
g 12
 
7.7%
r 12
 
7.7%
s 12
 
7.7%
h 12
 
7.7%
l 12
 
7.7%
t 12
 
7.7%
C 12
 
7.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 132035
84.3%
ASCII 24081
 
15.4%
Compat Jamo 536
 
0.3%
None 32
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
14031
58.3%
) 3554
 
14.8%
( 3554
 
14.8%
_ 1543
 
6.4%
+ 1021
 
4.2%
2 67
 
0.3%
, 66
 
0.3%
e 48
 
0.2%
a 24
 
0.1%
1 22
 
0.1%
Other values (15) 151
 
0.6%
Hangul
ValueCountFrequency (%)
폐 12070
 
9.1%
수 7169
 
5.4%
류 6992
 
5.3%
지 6589
 
5.0%
물 4539
 
3.4%
성 4321
 
3.3%
한 3895
 
2.9%
합 3635
 
2.8%
다 3507
 
2.7%
제 3211
 
2.4%
Other values (267) 76107
57.6%
Compat Jamo
ValueCountFrequency (%)
ㆍ 536
100.0%
None
ValueCountFrequency (%)
「 12
37.5%
」 12
37.5%
· 8
25.0%

우편번호
Real number (ℝ)

HIGH CORRELATION  MISSING 

Distinct1371
Distinct (%)16.0%
Missing1416
Missing (%)14.2%
Infinite0
Infinite (%)0.0%
Mean14819.439
Minimum2633
Maximum59543
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size166.0 KiB
2024-03-23T01:37:45.761660image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum2633
5-th percentile10952
Q112032
median14547
Q318280
95-th percentile18619.1
Maximum59543
Range56910
Interquartile range (IQR)6248

Descriptive statistics

Standard deviation3285.2956
Coefficient of variation (CV)0.22168825
Kurtosis21.922448
Mean14819.439
Median Absolute Deviation (MAD)3355
Skewness1.9187265
Sum1.2721007 × 108
Variance10793167
MonotonicityNot monotonic
2024-03-23T01:37:46.222590image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
11167 153
 
1.5%
11138 115
 
1.1%
18559 99
 
1.0%
18574 94
 
0.9%
18622 91
 
0.9%
14014 91
 
0.9%
13977 86
 
0.9%
12247 79
 
0.8%
11168 79
 
0.8%
18623 75
 
0.8%
Other values (1361) 7622
76.2%
(Missing) 1416
 
14.2%
ValueCountFrequency (%)
2633 1
 
< 0.1%
3149 3
< 0.1%
3157 1
 
< 0.1%
3159 1
 
< 0.1%
3188 1
 
< 0.1%
3961 1
 
< 0.1%
4323 1
 
< 0.1%
4334 1
 
< 0.1%
4780 1
 
< 0.1%
4969 2
< 0.1%
ValueCountFrequency (%)
59543 1
 
< 0.1%
58263 1
 
< 0.1%
57121 1
 
< 0.1%
54139 1
 
< 0.1%
52519 1
 
< 0.1%
51302 4
< 0.1%
46273 1
 
< 0.1%
37257 1
 
< 0.1%
31099 1
 
< 0.1%
31090 1
 
< 0.1%

Interactions

2024-03-23T01:37:26.426031image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T01:37:24.140607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T01:37:25.387550image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T01:37:26.734177image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T01:37:24.596116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T01:37:25.715699image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T01:37:27.068669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T01:37:24.965147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-23T01:37:26.090202image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-23T01:37:46.540002image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시군명위도경도우편번호
시군명1.0000.8150.8720.684
위도0.8151.0000.8620.864
경도0.8720.8621.0000.864
우편번호0.6840.8640.8641.000
2024-03-23T01:37:46.822078image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도우편번호시군명
위도1.0000.397-0.9350.498
경도0.3971.000-0.4280.589
우편번호-0.935-0.4281.0000.325
시군명0.4980.5890.3251.000

Missing values

2024-03-23T01:37:27.520260image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-23T01:37:28.119635image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.
2024-03-23T01:37:28.628896image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
The correlation heatmap measures nullity correlation: how strongly the presence or absence of one variable affects the presence of another.

Sample

시군명상호명사업장전화번호소재지도로명주소소재지지번주소위도경도인허가관리번호인허가등록일자배출폐기물코드배출폐기물종류우편번호
5155안산시(주)한길전자031-495-2452경기도 안산시 단원구 만해로169번길 28경기도 안산시 단원구 신길동 1054-10번지37.325971126.758633930000-31-2008-000082008-02-211951-02-01폐수처리오니15405
13054파주시(주)포모스트(지점)031-954-3800경기도 파주시 파주읍 아랫도장길 8경기도 파주시 파주읍 백석리 416-3번지37.803068126.8031754060000-31-2013-000182013-07-09비공개비공개10839
8811용인시코레드무역주식회사<NA><NA><NA><NA><NA><NA><NA><NA>사업장폐기물배출자<NA>
15900포천시세종산업<NA>경기도 포천시 가산면 정금로 122경기도 포천시 가산면 정교리 334-4번지37.813914127.174253<NA><NA><NA>목재가공공장 부산물(접착제_ 페인트_ 기름_ 콘크리트 등의 물질이 사용된 목재부산물 및 분진을 말한다)11167
21985화성시(주)신원에프아이313510221경기도 화성시 장안면 수정로299번길 18경기도 화성시 장안면 수촌리 263번지37.092355126.860462<NA><NA><NA>축산물가공잔재물(동물성 유지류는 제외한다)18581
11836의왕시영내과<NA>경기도 의왕시 포일세거리로 3경기도 의왕시 포일동 662번지37.396011126.984741<NA><NA><NA>생물ㆍ화학폐기물16004
5175안산시(주)모다이노칩031-8040-0000경기도 안산시 단원구 동산로27번길 42-7경기도 안산시 단원구 원시동 769-12번지37.316647126.7919243930000-31-2008-000202008-04-041951-01-06그 밖의 공정오니15433
2054남양주시(주)부민보드<NA>경기도 남양주시 수동면 남가로 1532경기도 남양주시 수동면 운수리 178-5번지37.698926127.3278943990000-31-2018-000062018-03-08<NA>목재가공공장 부산물(할로겐족 유기화합물 또는 방부제가 사용된 폐목재_ 목재부산물 및 분진을 말한다)12031
9209용인시그린이엔씨(주)***-****-****<NA><NA><NA><NA><NA><NA><NA>사업장폐기물배출자<NA>
2832부천시(주)케이엠하이테크032-674-2867경기도 부천시 삼작로133번길 41-18경기도 부천시 내동 77-2번지37.521958126.7768843860000-31-2022-000132022-12-2151-05-99그 밖의 분진14452
시군명상호명사업장전화번호소재지도로명주소소재지지번주소위도경도인허가관리번호인허가등록일자배출폐기물코드배출폐기물종류우편번호
12608이천시㈜석예<NA>경기도 이천시 설성면 설가로 177경기도 이천시 설성면 상봉리 604-5번지37.15232127.5104774070000-31-2014-000062014-03-2051-14-02+51-02-06폐석재+석재·골재폐수처리오니17409
15583포천시신궁전통한과<NA><NA>경기도 포천시 소흘읍 고모리 859-237.811463127.170305<NA><NA><NA>그 밖의 폐수처리오니11185
10332용인시서천건설(주)<NA><NA><NA><NA><NA><NA><NA><NA>건설폐기물배출자<NA>
19114화성시(주)에스엔에스<NA>경기도 화성시 서신면 해운로458번길 94-14경기도 화성시 서신면 홍법리 250-57번지37.161974126.744625<NA><NA><NA>폐합성수지류(폐염화비닐수지류는 제외한다)18556
10684용인시(주)현승종합건설<NA><NA><NA><NA><NA><NA><NA><NA>건설폐기물배출자<NA>
6648안양시GS파워주식회사 안양열병합발전처<NA>경기도 안양시 동안구 부림로 100경기도 안양시 동안구 평촌동 897-2번지37.394083126.9670843830000-31-1997-000102007-01-29<NA>그 밖의 폐기물14065
16578포천시㈜지에스포천그린에너지<NA><NA>경기도 포천시 신북면 신평리 661-337.957641127.235236<NA><NA>배출시설계석탄재11138
13901평택시(주)평택종합개발<NA>경기도 평택시 죽백5로 23경기도 평택시 죽백동 770-1번지 301호37.003872127.118343910000-32-2023-000752023-04-0551-20-21임목폐목재(건설공사_ 산지개간 등의 과정에서 발생된 나무뿌리_ 가지_ 줄기 등을 말한다)17860
1230남양주시(주)에코비트워터<NA>경기도 남양주시 별내2로 88경기도 남양주시 별내동 927번지37.647273127.1275923990000-31-2012-000282012-09-03<NA>그 밖의 공정오니12114
20000화성시(주)하이콘코리아313587515경기도 화성시 팔탄면 버들로 1261경기도 화성시 팔탄면 서근리 52-5번지37.130128126.846218<NA><NA><NA>폐합성수지류(폐염화비닐수지류는 제외한다)18575

Duplicate rows

Most frequently occurring

시군명상호명사업장전화번호소재지도로명주소소재지지번주소위도경도인허가관리번호인허가등록일자배출폐기물코드배출폐기물종류우편번호# duplicates
40남양주시(주)에코비트워터 진접<NA>경기도 남양주시 진접읍 해밀예당1로 30-31경기도 남양주시 진접읍 금곡리 1085번지37.711304127.1885883990000-31-2010-000202010-08-10<NA>하수처리오니1206640
42남양주시(주)에코비트워터(지금)<NA>경기도 남양주시 강변북로651번길 50경기도 남양주시 수석동 400번지37.585711127.165613990000-31-2021-000182021-06-01<NA>하수처리오니1226830
34남양주시(주)에코비트워터<NA>경기도 남양주시 가운로 108경기도 남양주시 다산동 689번지37.597003127.1620333990000-31-2013-000082013-02-08<NA>하수처리오니1226629
461용인시처인구청<NA><NA><NA><NA><NA><NA><NA><NA>건설폐기물배출자<NA>27
32남양주시(주)알엔텍<NA>경기도 남양주시 와부읍 수레로661번안길 33경기도 남양주시 와부읍 월문리 108-4번지37.620187127.2755763990000-31-2014-000082014-08-13<NA>폐합성수지류(폐염화비닐수지류는 제외한다)1220220
108남양주시진건바이오텍(주)진건사업소<NA>경기도 남양주시 진건읍 금강로380번길 67경기도 남양주시 진건읍 진관리 875번지37.635414127.1507553990000-31-2020-000312020-06-29<NA>하수처리오니1224718
38남양주시(주)에코비트워터<NA>경기도 남양주시 별내2로 88경기도 남양주시 별내동 927번지37.647273127.1275923990000-31-2012-000282012-09-03<NA>하수처리오니1211417
465용인시태영건설(주)<NA><NA><NA><NA><NA><NA><NA><NA>건설폐기물배출자<NA>17
208안양시공공하수처리시설(안양)<NA>경기도 안양시 만안구 석천로 1경기도 안양시 만안구 박달동 655번지37.416997126.8906993830000-31-1997-000742007-04-26<NA>하수처리오니1390116
545포천시㈜씨아이에코텍<NA><NA>경기도 포천시 소흘읍 송우리 61437.836267127.128936<NA><NA>배출시설계폐합성수지류(폐염화비닐수지류는 제외한다)1117115