Overview

Dataset statistics

Number of variables7
Number of observations4311
Missing cells959
Missing cells (%)3.2%
Duplicate rows43
Duplicate rows (%)1.0%
Total size in memory240.1 KiB
Average record size in memory57.0 B

Variable types

Categorical2
Text4
Numeric1

Dataset

Description연도별 건설폐기물 배출 사업장 정보현황(시도, 시군구, 현장명, 발주자, 발주자연락처, 폐기물명, 발생량 등)
Author한국환경공단
URLhttps://www.data.go.kr/data/15048020/fileData.do

Alerts

Dataset has 43 (1.0%) duplicate rowsDuplicates
시·군·구 has 60 (1.4%) missing valuesMissing
발주자연락처 has 300 (7.0%) missing valuesMissing
발생량(톤) has 599 (13.9%) missing valuesMissing

Reproduction

Analysis started2023-12-12 05:26:48.758047
Analysis finished2023-12-12 05:26:50.427192
Duration1.67 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

시도
Categorical

Distinct18
Distinct (%)0.4%
Missing0
Missing (%)0.0%
Memory size33.8 KiB
서울특별시
1007 
경기도
865 
경상북도
349 
전라남도
291 
대구광역시
232 
Other values (13)
1567 

Length

Max length7
Median length5
Mean length4.3266064
Min length3

Unique

Unique1 ?
Unique (%)< 0.1%

Sample

1st row경기도
2nd row경기도
3rd row서울특별시
4th row서울특별시
5th row경기도

Common Values

ValueCountFrequency (%)
서울특별시 1007
23.4%
경기도 865
20.1%
경상북도 349
 
8.1%
전라남도 291
 
6.8%
대구광역시 232
 
5.4%
부산광역시 207
 
4.8%
강원도 180
 
4.2%
인천광역시 176
 
4.1%
대전광역시 151
 
3.5%
충청남도 146
 
3.4%
Other values (8) 707
16.4%

Length

2023-12-12T14:26:50.532872image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
서울특별시 1007
23.4%
경기도 865
20.1%
경상북도 349
 
8.1%
전라남도 291
 
6.8%
대구광역시 232
 
5.4%
부산광역시 207
 
4.8%
강원도 180
 
4.2%
인천광역시 176
 
4.1%
대전광역시 151
 
3.5%
경상남도 146
 
3.4%
Other values (8) 707
16.4%

시·군·구
Text

MISSING 

Distinct225
Distinct (%)5.3%
Missing60
Missing (%)1.4%
Memory size33.8 KiB
2023-12-12T14:26:50.966940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length9
Median length3
Mean length3.4398965
Min length2

Characters and Unicode

Total characters14623
Distinct characters138
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique16 ?
Unique (%)0.4%

Sample

1st row이천시
2nd row이천시
3rd row종로구
4th row종로구
5th row화성시
ValueCountFrequency (%)
종로구 235
 
4.9%
서초구 201
 
4.2%
중구 154
 
3.2%
남구 138
 
2.9%
동구 133
 
2.8%
서구 119
 
2.5%
성남시 110
 
2.3%
화성시 103
 
2.1%
강남구 99
 
2.1%
북구 91
 
1.9%
Other values (221) 3444
71.3%
2023-12-12T14:26:51.541053image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
구 2479
 
17.0%
시 1806
 
12.4%
군 656
 
4.5%
577
 
3.9%
서 515
 
3.5%
남 488
 
3.3%
주 467
 
3.2%
성 420
 
2.9%
동 391
 
2.7%
산 313
 
2.1%
Other values (128) 6511
44.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 14046
96.1%
Space Separator 577
 
3.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 2479
 
17.6%
시 1806
 
12.9%
군 656
 
4.7%
서 515
 
3.7%
남 488
 
3.5%
주 467
 
3.3%
성 420
 
3.0%
동 391
 
2.8%
산 313
 
2.2%
천 285
 
2.0%
Other values (127) 6226
44.3%
Space Separator
ValueCountFrequency (%)
577
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 14046
96.1%
Common 577
 
3.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 2479
 
17.6%
시 1806
 
12.9%
군 656
 
4.7%
서 515
 
3.7%
남 488
 
3.5%
주 467
 
3.3%
성 420
 
3.0%
동 391
 
2.8%
산 313
 
2.2%
천 285
 
2.0%
Other values (127) 6226
44.3%
Common
ValueCountFrequency (%)
577
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 14046
96.1%
ASCII 577
 
3.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
구 2479
 
17.6%
시 1806
 
12.9%
군 656
 
4.7%
서 515
 
3.7%
남 488
 
3.5%
주 467
 
3.3%
성 420
 
3.0%
동 391
 
2.8%
산 313
 
2.2%
천 285
 
2.0%
Other values (127) 6226
44.3%
ASCII
ValueCountFrequency (%)
577
100.0%

현장명
Text

Distinct1954
Distinct (%)45.3%
Missing0
Missing (%)0.0%
Memory size33.8 KiB
2023-12-12T14:26:51.865126image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length51
Median length42
Mean length22.345627
Min length1

Characters and Unicode

Total characters96332
Distinct characters654
Distinct categories14 ?
Distinct scripts3 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1071 ?
Unique (%)24.8%

Sample

1st row동산리 농어촌도로 확포장공사(3공구) 폐기물처리용역
2nd row동산리 농어촌도로 확포장공사(3공구) 폐기물처리용역
3rd row여주천연가스발전소 공급배관 건설공사
4th row여주천연가스발전소 공급배관 건설공사
5th row대보건설 화성동탄2 A-81BL 아파트 건설공사 16공구
ValueCountFrequency (%)
신축공사 1043
 
6.5%
폐기물처리용역 261
 
1.6%
아파트 188
 
1.2%
및 178
 
1.1%
처리용역 134
 
0.8%
공동주택 129
 
0.8%
건설공사 122
 
0.8%
2019년 111
 
0.7%
건설폐기물 108
 
0.7%
정비사업 107
 
0.7%
Other values (4247) 13608
85.1%
2023-12-12T14:26:52.361778image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
11722
 
12.2%
사 4134
 
4.3%
공 3816
 
4.0%
주 2251
 
2.3%
) 1807
 
1.9%
( 1802
 
1.9%
설 1768
 
1.8%
축 1707
 
1.8%
신 1696
 
1.8%
건 1614
 
1.7%
Other values (644) 64015
66.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 72519
75.3%
Space Separator 11722
 
12.2%
Decimal Number 4542
 
4.7%
Uppercase Letter 1847
 
1.9%
Close Punctuation 1832
 
1.9%
Open Punctuation 1827
 
1.9%
Dash Punctuation 1176
 
1.2%
Lowercase Letter 443
 
0.5%
Other Punctuation 214
 
0.2%
Math Symbol 127
 
0.1%
Other values (4) 83
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
사 4134
 
5.7%
공 3816
 
5.3%
주 2251
 
3.1%
설 1768
 
2.4%
축 1707
 
2.4%
신 1696
 
2.3%
건 1614
 
2.2%
동 1447
 
2.0%
리 1421
 
2.0%
구 1368
 
1.9%
Other values (567) 51297
70.7%
Uppercase Letter
ValueCountFrequency (%)
B 355
19.2%
L 312
16.9%
A 237
12.8%
P 134
 
7.3%
C 109
 
5.9%
T 103
 
5.6%
S 78
 
4.2%
M 60
 
3.2%
I 57
 
3.1%
E 49
 
2.7%
Other values (15) 353
19.1%
Lowercase Letter
ValueCountFrequency (%)
e 73
16.5%
c 43
9.7%
r 39
8.8%
a 36
8.1%
t 35
7.9%
o 33
 
7.4%
n 31
 
7.0%
j 23
 
5.2%
h 23
 
5.2%
i 20
 
4.5%
Other values (13) 87
19.6%
Decimal Number
ValueCountFrequency (%)
1 1109
24.4%
2 988
21.8%
3 512
11.3%
0 414
 
9.1%
9 327
 
7.2%
4 323
 
7.1%
6 265
 
5.8%
5 233
 
5.1%
8 191
 
4.2%
7 180
 
4.0%
Other Punctuation
ValueCountFrequency (%)
, 125
58.4%
/ 60
28.0%
. 20
 
9.3%
· 8
 
3.7%
: 1
 
0.5%
Math Symbol
ValueCountFrequency (%)
~ 119
93.7%
< 4
 
3.1%
> 4
 
3.1%
Close Punctuation
ValueCountFrequency (%)
) 1807
98.6%
] 25
 
1.4%
Open Punctuation
ValueCountFrequency (%)
( 1802
98.6%
[ 25
 
1.4%
Letter Number
ValueCountFrequency (%)
Ⅱ 2
50.0%
Ⅵ 2
50.0%
Space Separator
ValueCountFrequency (%)
11722
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1176
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 76
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 2
100.0%
Modifier Symbol
ValueCountFrequency (%)
` 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 72521
75.3%
Common 21517
 
22.3%
Latin 2294
 
2.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
사 4134
 
5.7%
공 3816
 
5.3%
주 2251
 
3.1%
설 1768
 
2.4%
축 1707
 
2.4%
신 1696
 
2.3%
건 1614
 
2.2%
동 1447
 
2.0%
리 1421
 
2.0%
구 1368
 
1.9%
Other values (568) 51299
70.7%
Latin
ValueCountFrequency (%)
B 355
15.5%
L 312
13.6%
A 237
 
10.3%
P 134
 
5.8%
C 109
 
4.8%
T 103
 
4.5%
S 78
 
3.4%
e 73
 
3.2%
M 60
 
2.6%
I 57
 
2.5%
Other values (40) 776
33.8%
Common
ValueCountFrequency (%)
11722
54.5%
) 1807
 
8.4%
( 1802
 
8.4%
- 1176
 
5.5%
1 1109
 
5.2%
2 988
 
4.6%
3 512
 
2.4%
0 414
 
1.9%
9 327
 
1.5%
4 323
 
1.5%
Other values (16) 1337
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 72519
75.3%
ASCII 23799
 
24.7%
None 10
 
< 0.1%
Number Forms 4
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
11722
49.3%
) 1807
 
7.6%
( 1802
 
7.6%
- 1176
 
4.9%
1 1109
 
4.7%
2 988
 
4.2%
3 512
 
2.2%
0 414
 
1.7%
B 355
 
1.5%
9 327
 
1.4%
Other values (63) 3587
 
15.1%
Hangul
ValueCountFrequency (%)
사 4134
 
5.7%
공 3816
 
5.3%
주 2251
 
3.1%
설 1768
 
2.4%
축 1707
 
2.4%
신 1696
 
2.3%
건 1614
 
2.2%
동 1447
 
2.0%
리 1421
 
2.0%
구 1368
 
1.9%
Other values (567) 51297
70.7%
None
ValueCountFrequency (%)
· 8
80.0%
㈜ 2
 
20.0%
Number Forms
ValueCountFrequency (%)
Ⅱ 2
50.0%
Ⅵ 2
50.0%

발주자
Text

Distinct1244
Distinct (%)28.9%
Missing0
Missing (%)0.0%
Memory size33.8 KiB
2023-12-12T14:26:52.695313image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length47
Median length43
Mean length11.057991
Min length1

Characters and Unicode

Total characters47671
Distinct characters473
Distinct categories11 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique565 ?
Unique (%)13.1%

Sample

1st row이천시청 지역개발국 건설과
2nd row이천시청 지역개발국 건설과
3rd row에스케이건설(주)
4th row에스케이건설(주)
5th row대보건설 화성동탄2 A-81BL 아파트 건설공사 16공구
ValueCountFrequency (%)
주식회사 142
 
2.2%
롯데건설(주 116
 
1.8%
현대건설(주 113
 
1.7%
한국토지주택공사 66
 
1.0%
신축공사 61
 
0.9%
경상북도 56
 
0.9%
주)포스코건설 53
 
0.8%
아파트 47
 
0.7%
동신아파트주택재건축정비사업조합 42
 
0.6%
주)대우건설 41
 
0.6%
Other values (1656) 5760
88.7%
2023-12-12T14:26:53.223254image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 3275
 
6.9%
) 3137
 
6.6%
( 3133
 
6.6%
건 2460
 
5.2%
설 2282
 
4.8%
2195
 
4.6%
사 1348
 
2.8%
공 794
 
1.7%
대 688
 
1.4%
지 655
 
1.4%
Other values (463) 27704
58.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 37556
78.8%
Close Punctuation 3137
 
6.6%
Open Punctuation 3133
 
6.6%
Space Separator 2195
 
4.6%
Decimal Number 676
 
1.4%
Dash Punctuation 567
 
1.2%
Uppercase Letter 248
 
0.5%
Lowercase Letter 77
 
0.2%
Connector Punctuation 39
 
0.1%
Other Punctuation 39
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 3275
 
8.7%
건 2460
 
6.6%
설 2282
 
6.1%
사 1348
 
3.6%
공 794
 
2.1%
대 688
 
1.8%
지 655
 
1.7%
시 625
 
1.7%
청 589
 
1.6%
도 573
 
1.5%
Other values (415) 24267
64.6%
Uppercase Letter
ValueCountFrequency (%)
A 66
26.6%
B 64
25.8%
L 59
23.8%
S 10
 
4.0%
P 9
 
3.6%
D 8
 
3.2%
O 8
 
3.2%
H 5
 
2.0%
C 4
 
1.6%
K 3
 
1.2%
Other values (7) 12
 
4.8%
Lowercase Letter
ValueCountFrequency (%)
c 19
24.7%
b 11
14.3%
o 9
11.7%
r 8
10.4%
j 8
10.4%
e 8
10.4%
t 8
10.4%
l 2
 
2.6%
a 1
 
1.3%
g 1
 
1.3%
Other values (2) 2
 
2.6%
Decimal Number
ValueCountFrequency (%)
1 156
23.1%
2 141
20.9%
3 119
17.6%
0 50
 
7.4%
4 47
 
7.0%
9 46
 
6.8%
5 37
 
5.5%
6 36
 
5.3%
7 22
 
3.3%
8 22
 
3.3%
Other Punctuation
ValueCountFrequency (%)
, 15
38.5%
/ 13
33.3%
. 11
28.2%
Close Punctuation
ValueCountFrequency (%)
) 3137
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3133
100.0%
Space Separator
ValueCountFrequency (%)
2195
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 567
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 39
100.0%
Math Symbol
ValueCountFrequency (%)
~ 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 37556
78.8%
Common 9790
 
20.5%
Latin 325
 
0.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 3275
 
8.7%
건 2460
 
6.6%
설 2282
 
6.1%
사 1348
 
3.6%
공 794
 
2.1%
대 688
 
1.8%
지 655
 
1.7%
시 625
 
1.7%
청 589
 
1.6%
도 573
 
1.5%
Other values (415) 24267
64.6%
Latin
ValueCountFrequency (%)
A 66
20.3%
B 64
19.7%
L 59
18.2%
c 19
 
5.8%
b 11
 
3.4%
S 10
 
3.1%
o 9
 
2.8%
P 9
 
2.8%
r 8
 
2.5%
j 8
 
2.5%
Other values (19) 62
19.1%
Common
ValueCountFrequency (%)
) 3137
32.0%
( 3133
32.0%
2195
22.4%
- 567
 
5.8%
1 156
 
1.6%
2 141
 
1.4%
3 119
 
1.2%
0 50
 
0.5%
4 47
 
0.5%
9 46
 
0.5%
Other values (9) 199
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 37556
78.8%
ASCII 10115
 
21.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 3275
 
8.7%
건 2460
 
6.6%
설 2282
 
6.1%
사 1348
 
3.6%
공 794
 
2.1%
대 688
 
1.8%
지 655
 
1.7%
시 625
 
1.7%
청 589
 
1.6%
도 573
 
1.5%
Other values (415) 24267
64.6%
ASCII
ValueCountFrequency (%)
) 3137
31.0%
( 3133
31.0%
2195
21.7%
- 567
 
5.6%
1 156
 
1.5%
2 141
 
1.4%
3 119
 
1.2%
A 66
 
0.7%
B 64
 
0.6%
L 59
 
0.6%
Other values (38) 478
 
4.7%

발주자연락처
Text

MISSING 

Distinct1136
Distinct (%)28.3%
Missing300
Missing (%)7.0%
Memory size33.8 KiB
2023-12-12T14:26:53.559816image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length11.939417
Min length11

Characters and Unicode

Total characters47889
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

Unique493 ?
Unique (%)12.3%

Sample

1st row031-644-2541
2nd row031-644-2541
3rd row02-3499-1665
4th row02-3499-1665
5th row031-378-4581
ValueCountFrequency (%)
02-3480-9114 113
 
2.8%
02-746-3925 76
 
1.9%
02-6177-0326 49
 
1.2%
032-341-2344 42
 
1.0%
02-2154-1114 41
 
1.0%
02-3499-1665 41
 
1.0%
054-280-3478 40
 
1.0%
02-2288-3114 36
 
0.9%
02-746-2547 32
 
0.8%
02-3484-2315 31
 
0.8%
Other values (1126) 3510
87.5%
2023-12-12T14:26:54.117845image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 8022
16.8%
0 7671
16.0%
2 5038
10.5%
3 4753
9.9%
4 4159
8.7%
1 4031
8.4%
5 3742
7.8%
6 3251
6.8%
7 2739
 
5.7%
8 2449
 
5.1%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 39867
83.2%
Dash Punctuation 8022
 
16.8%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 7671
19.2%
2 5038
12.6%
3 4753
11.9%
4 4159
10.4%
1 4031
10.1%
5 3742
9.4%
6 3251
8.2%
7 2739
 
6.9%
8 2449
 
6.1%
9 2034
 
5.1%
Dash Punctuation
ValueCountFrequency (%)
- 8022
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 47889
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 8022
16.8%
0 7671
16.0%
2 5038
10.5%
3 4753
9.9%
4 4159
8.7%
1 4031
8.4%
5 3742
7.8%
6 3251
6.8%
7 2739
 
5.7%
8 2449
 
5.1%

Most occurring blocks

ValueCountFrequency (%)
ASCII 47889
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 8022
16.8%
0 7671
16.0%
2 5038
10.5%
3 4753
9.9%
4 4159
8.7%
1 4031
8.4%
5 3742
7.8%
6 3251
6.8%
7 2739
 
5.7%
8 2449
 
5.1%

폐기물명
Categorical

Distinct15
Distinct (%)0.3%
Missing0
Missing (%)0.0%
Memory size33.8 KiB
폐콘크리트(건설)
1394 
혼합건설폐기물
822 
실적없음
599 
폐아스팔트콘크리트(건설)
409 
폐합성수지(건설)
399 
Other values (10)
688 

Length

Max length13
Median length10
Mean length7.7921596
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row폐콘크리트(건설)
2nd row폐아스팔트콘크리트(건설)
3rd row폐콘크리트(건설)
4th row폐아스팔트콘크리트(건설)
5th row폐목재(건설)

Common Values

ValueCountFrequency (%)
폐콘크리트(건설) 1394
32.3%
혼합건설폐기물 822
19.1%
실적없음 599
13.9%
폐아스팔트콘크리트(건설) 409
 
9.5%
폐합성수지(건설) 399
 
9.3%
폐목재(건설) 290
 
6.7%
건설폐토석 167
 
3.9%
건설오니 86
 
2.0%
폐보드류 80
 
1.9%
폐벽돌(건설) 37
 
0.9%
Other values (5) 28
 
0.6%

Length

2023-12-12T14:26:54.283500image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category
ValueCountFrequency (%)
폐콘크리트(건설 1394
32.3%
혼합건설폐기물 822
19.0%
실적없음 599
13.9%
폐아스팔트콘크리트(건설 409
 
9.5%
폐합성수지(건설 399
 
9.2%
폐목재(건설 290
 
6.7%
건설폐토석 167
 
3.9%
건설오니 86
 
2.0%
폐보드류 80
 
1.9%
폐벽돌(건설 37
 
0.9%
Other values (7) 36
 
0.8%

발생량(톤)
Real number (ℝ)

MISSING 

Distinct3395
Distinct (%)91.5%
Missing599
Missing (%)13.9%
Infinite0
Infinite (%)0.0%
Mean1318.1256
Minimum0
Maximum141984.2
Zeros12
Zeros (%)0.3%
Negative0
Negative (%)0.0%
Memory size38.0 KiB
2023-12-12T14:26:54.426662image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile4.171
Q125.8025
median109.205
Q3506.235
95-th percentile4684.6
Maximum141984.2
Range141984.2
Interquartile range (IQR)480.4325

Descriptive statistics

Standard deviation6482.8567
Coefficient of variation (CV)4.9182392
Kurtosis209.40358
Mean1318.1256
Median Absolute Deviation (MAD)98.36
Skewness12.910675
Sum4892882
Variance42027431
MonotonicityNot monotonic
2023-12-12T14:26:54.612266image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0.0 12
 
0.3%
50.0 8
 
0.2%
17.0 6
 
0.1%
23.0 5
 
0.1%
49.0 5
 
0.1%
2.0 4
 
0.1%
1.0 4
 
0.1%
3.1 4
 
0.1%
20.4 3
 
0.1%
19.35 3
 
0.1%
Other values (3385) 3658
84.9%
(Missing) 599
 
13.9%
ValueCountFrequency (%)
0.0 12
0.3%
0.08 1
 
< 0.1%
0.1 2
 
< 0.1%
0.11 1
 
< 0.1%
0.12 1
 
< 0.1%
0.15 1
 
< 0.1%
0.16 1
 
< 0.1%
0.18 1
 
< 0.1%
0.27 2
 
< 0.1%
0.31 1
 
< 0.1%
ValueCountFrequency (%)
141984.2 1
< 0.1%
120876.28 1
< 0.1%
119101.17 1
< 0.1%
112041.78 1
< 0.1%
111173.35 1
< 0.1%
104540.38 1
< 0.1%
88710.45 1
< 0.1%
85986.81 1
< 0.1%
68789.25 1
< 0.1%
59745.27 1
< 0.1%

Interactions

2023-12-12T14:26:49.676338image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T14:26:54.737890image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
시도폐기물명발생량(톤)
시도1.0000.2770.000
폐기물명0.2771.0000.000
발생량(톤)0.0000.0001.000
2023-12-12T14:26:54.869642image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
폐기물명시도
폐기물명1.0000.096
시도0.0961.000
2023-12-12T14:26:54.982284image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
발생량(톤)시도폐기물명
발생량(톤)1.0000.0000.000
시도0.0001.0000.096
폐기물명0.0000.0961.000

Missing values

2023-12-12T14:26:49.813056image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T14:26:50.240902image/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.
2023-12-12T14:26:50.344696image/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

시도시·군·구현장명발주자발주자연락처폐기물명발생량(톤)
0경기도이천시동산리 농어촌도로 확포장공사(3공구) 폐기물처리용역이천시청 지역개발국 건설과031-644-2541폐콘크리트(건설)90.43
1경기도이천시동산리 농어촌도로 확포장공사(3공구) 폐기물처리용역이천시청 지역개발국 건설과031-644-2541폐아스팔트콘크리트(건설)60.65
2서울특별시종로구여주천연가스발전소 공급배관 건설공사에스케이건설(주)02-3499-1665폐콘크리트(건설)23.96
3서울특별시종로구여주천연가스발전소 공급배관 건설공사에스케이건설(주)02-3499-1665폐아스팔트콘크리트(건설)491.83
4경기도화성시대보건설 화성동탄2 A-81BL 아파트 건설공사 16공구대보건설 화성동탄2 A-81BL 아파트 건설공사 16공구031-378-4581폐목재(건설)39.97
5경기도화성시대보건설 화성동탄2 A-81BL 아파트 건설공사 16공구대보건설 화성동탄2 A-81BL 아파트 건설공사 16공구031-378-4581폐목재(건설)81.01
6경기도화성시대보건설 화성동탄2 A-81BL 아파트 건설공사 16공구대보건설 화성동탄2 A-81BL 아파트 건설공사 16공구031-378-4581폐목재(건설)49.93
7경기도화성시대보건설 화성동탄2 A-81BL 아파트 건설공사 16공구대보건설 화성동탄2 A-81BL 아파트 건설공사 16공구031-378-4581폐콘크리트(건설)1596.4
8경기도화성시대보건설 화성동탄2 A-81BL 아파트 건설공사 16공구대보건설 화성동탄2 A-81BL 아파트 건설공사 16공구031-378-4581폐합성수지(건설)192.25
9경기도화성시대보건설 화성동탄2 A-81BL 아파트 건설공사 16공구대보건설 화성동탄2 A-81BL 아파트 건설공사 16공구031-378-4581혼합건설폐기물48.51
시도시·군·구현장명발주자발주자연락처폐기물명발생량(톤)
4301경기도평택시현촌초 교실 증축공사경기도평택교육청031-650-1296실적없음<NA>
4302경상북도청도군관하2 신천마을 진입로 확포장공사경상북도 청도군청054-370-2183실적없음<NA>
4303충청북도충주시지방도 520호 충주 노은도로 긴급보수공사유성토건(주)043-851-5402실적없음<NA>
4304경상북도상주시모동 용신세천 수해복구공사대륙건설(주)054-533-4048실적없음<NA>
4305경상북도문경시주민숙원사업 건설폐기물처리 용역(1차)문경시 영순면사무소054-550-6643실적없음<NA>
4306경기도이천시(주)삼성종합건설-부발읍 가좌리 223-20 외 건축공사(2차분)(주)삼성종합건설-부발읍 가좌리 223-20 외 건축공사(2차분)031-635-2190실적없음<NA>
4307강원도화천군하남미사 2단계산업 2-1블럭 도시형공장 신축공사장위종합건설(주)033-441-0224실적없음<NA>
4308전라남도담양군안산선부지역주택조합 조합주택 신축공사(주)태원종합건설-그룹062-681-6657실적없음<NA>
4309광주광역시서구우산 빛여울채 발코니 창호 교체공사광주광역시도시공사-그룹062-600-6753실적없음<NA>
4310강원도춘천시홍천군 내면 창촌로 지중화 통신 관로시설공사(합)동서정보통신033-242-3488실적없음<NA>

Duplicate rows

Most frequently occurring

시도시·군·구현장명발주자발주자연락처폐기물명발생량(톤)# duplicates
2경기도부천시 소사구동신아파트주택재건축정비사업조합동신아파트주택재건축정비사업조합032-341-2344건설폐토석42.963
3경기도부천시 소사구동신아파트주택재건축정비사업조합동신아파트주택재건축정비사업조합032-341-2344건설폐토석103.823
4경기도부천시 소사구동신아파트주택재건축정비사업조합동신아파트주택재건축정비사업조합032-341-2344실적없음<NA>3
5경기도부천시 소사구동신아파트주택재건축정비사업조합동신아파트주택재건축정비사업조합032-341-2344폐목재(건설)91.013
6경기도부천시 소사구동신아파트주택재건축정비사업조합동신아파트주택재건축정비사업조합032-341-2344폐보드류179.143
7경기도부천시 소사구동신아파트주택재건축정비사업조합동신아파트주택재건축정비사업조합032-341-2344폐아스팔트콘크리트(건설)222.463
8경기도부천시 소사구동신아파트주택재건축정비사업조합동신아파트주택재건축정비사업조합032-341-2344폐콘크리트(건설)24.513
9경기도부천시 소사구동신아파트주택재건축정비사업조합동신아파트주택재건축정비사업조합032-341-2344폐콘크리트(건설)1386.773
10경기도부천시 소사구동신아파트주택재건축정비사업조합동신아파트주택재건축정비사업조합032-341-2344폐콘크리트(건설)4095.153
11경기도부천시 소사구동신아파트주택재건축정비사업조합동신아파트주택재건축정비사업조합032-341-2344폐합성수지(건설)19.633