Overview

Dataset statistics

Number of variables4
Number of observations814
Missing cells0
Missing cells (%)0.0%
Duplicate rows65
Duplicate rows (%)8.0%
Total size in memory26.4 KiB
Average record size in memory33.2 B

Variable types

Text3
Numeric1

Dataset

Description전라남도 영암군 사업장폐기물배출자의 신고현황에 대한 데이터로 상호, 도로명주소, 폐기물 종류, 배출량등의 항목을 제공합니다.
Author전라남도 영암군
URLhttps://www.data.go.kr/data/15081025/fileData.do

Alerts

Dataset has 65 (8.0%) duplicate rowsDuplicates

Reproduction

Analysis started2023-12-12 02:48:02.182464
Analysis finished2023-12-12 02:48:02.844310
Duration0.66 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

상호
Text

Distinct287
Distinct (%)35.3%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
2023-12-12T11:48:03.025990image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length15
Mean length8.6265356
Min length2

Characters and Unicode

Total characters7022
Distinct characters263
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique114 ?
Unique (%)14.0%

Sample

1st row계성중공업(주)
2nd row계성중공업(주)
3rd row신우산업(주)제2공장
4th row신우산업(주)제2공장
5th row신우산업(주)
ValueCountFrequency (%)
현대삼호중공업(주 35
 
4.0%
보워터코리아(유 27
 
3.1%
케이씨(주 25
 
2.9%
유)미래환경 24
 
2.8%
현대힘스(주)대불1공장 15
 
1.7%
해군제3함대사령부 13
 
1.5%
주)삼호로커스 12
 
1.4%
주)엘케이스틸 10
 
1.1%
현대힘스(주)대불2공장 10
 
1.1%
대한조선(주)내업2공장지점 10
 
1.1%
Other values (294) 689
79.2%
2023-12-12T11:48:03.446585image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
( 728
 
10.4%
) 728
 
10.4%
573
 
8.2%
278
 
4.0%
251
 
3.6%
235
 
3.3%
199
 
2.8%
153
 
2.2%
144
 
2.1%
134
 
1.9%
Other values (253) 3599
51.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5366
76.4%
Open Punctuation 728
 
10.4%
Close Punctuation 728
 
10.4%
Decimal Number 103
 
1.5%
Space Separator 56
 
0.8%
Uppercase Letter 33
 
0.5%
Other Punctuation 4
 
0.1%
Lowercase Letter 4
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
573
 
10.7%
278
 
5.2%
251
 
4.7%
235
 
4.4%
199
 
3.7%
153
 
2.9%
144
 
2.7%
134
 
2.5%
120
 
2.2%
109
 
2.0%
Other values (234) 3170
59.1%
Uppercase Letter
ValueCountFrequency (%)
K 7
21.2%
S 7
21.2%
G 5
15.2%
C 3
9.1%
M 3
9.1%
E 2
 
6.1%
N 2
 
6.1%
D 2
 
6.1%
Y 2
 
6.1%
Decimal Number
ValueCountFrequency (%)
1 45
43.7%
2 31
30.1%
3 27
26.2%
Other Punctuation
ValueCountFrequency (%)
. 2
50.0%
& 2
50.0%
Lowercase Letter
ValueCountFrequency (%)
p 2
50.0%
s 2
50.0%
Open Punctuation
ValueCountFrequency (%)
( 728
100.0%
Close Punctuation
ValueCountFrequency (%)
) 728
100.0%
Space Separator
ValueCountFrequency (%)
56
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5366
76.4%
Common 1619
 
23.1%
Latin 37
 
0.5%

Most frequent character per script

Hangul
ValueCountFrequency (%)
573
 
10.7%
278
 
5.2%
251
 
4.7%
235
 
4.4%
199
 
3.7%
153
 
2.9%
144
 
2.7%
134
 
2.5%
120
 
2.2%
109
 
2.0%
Other values (234) 3170
59.1%
Latin
ValueCountFrequency (%)
K 7
18.9%
S 7
18.9%
G 5
13.5%
C 3
8.1%
M 3
8.1%
E 2
 
5.4%
N 2
 
5.4%
D 2
 
5.4%
p 2
 
5.4%
Y 2
 
5.4%
Common
ValueCountFrequency (%)
( 728
45.0%
) 728
45.0%
56
 
3.5%
1 45
 
2.8%
2 31
 
1.9%
3 27
 
1.7%
. 2
 
0.1%
& 2
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5366
76.4%
ASCII 1656
 
23.6%

Most frequent character per block

ASCII
ValueCountFrequency (%)
( 728
44.0%
) 728
44.0%
56
 
3.4%
1 45
 
2.7%
2 31
 
1.9%
3 27
 
1.6%
K 7
 
0.4%
S 7
 
0.4%
G 5
 
0.3%
C 3
 
0.2%
Other values (9) 19
 
1.1%
Hangul
ValueCountFrequency (%)
573
 
10.7%
278
 
5.2%
251
 
4.7%
235
 
4.4%
199
 
3.7%
153
 
2.9%
144
 
2.7%
134
 
2.5%
120
 
2.2%
109
 
2.0%
Other values (234) 3170
59.1%
Distinct253
Distinct (%)31.1%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
2023-12-12T11:48:03.790936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length37
Median length35
Mean length22.769042
Min length1

Characters and Unicode

Total characters18534
Distinct characters181
Distinct categories8 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique101 ?
Unique (%)12.4%

Sample

1st row전라남도 영암군 삼호읍 대불산단2로 170
2nd row전라남도 영암군 삼호읍 대불산단2로 170
3rd row전라남도 영암군 삼호읍 대불산단7로 72_ 신우산업
4th row전라남도 영암군 삼호읍 대불산단7로 72_ 신우산업
5th row전라남도 영암군 삼호읍 나불로1길 38_ 신우산업(주)
ValueCountFrequency (%)
전라남도 812
19.3%
영암군 812
19.3%
삼호읍 720
17.1%
대불산단6로 78
 
1.9%
나불로 77
 
1.8%
대불산단3로 64
 
1.5%
용앙로 56
 
1.3%
산단서부로 49
 
1.2%
대불로 46
 
1.1%
93 37
 
0.9%
Other values (319) 1456
34.6%
2023-12-12T11:48:04.247962image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3518
19.0%
831
 
4.5%
830
 
4.5%
824
 
4.4%
823
 
4.4%
816
 
4.4%
816
 
4.4%
813
 
4.4%
755
 
4.1%
735
 
4.0%
Other values (171) 7773
41.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 11983
64.7%
Space Separator 3518
 
19.0%
Decimal Number 2576
 
13.9%
Close Punctuation 129
 
0.7%
Open Punctuation 124
 
0.7%
Dash Punctuation 103
 
0.6%
Uppercase Letter 51
 
0.3%
Connector Punctuation 50
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
831
 
6.9%
830
 
6.9%
824
 
6.9%
823
 
6.9%
816
 
6.8%
816
 
6.8%
813
 
6.8%
755
 
6.3%
735
 
6.1%
728
 
6.1%
Other values (153) 4012
33.5%
Decimal Number
ValueCountFrequency (%)
1 450
17.5%
3 427
16.6%
2 354
13.7%
0 299
11.6%
5 225
8.7%
6 215
8.3%
7 173
 
6.7%
9 164
 
6.4%
8 154
 
6.0%
4 115
 
4.5%
Uppercase Letter
ValueCountFrequency (%)
K 25
49.0%
C 25
49.0%
A 1
 
2.0%
Space Separator
ValueCountFrequency (%)
3518
100.0%
Close Punctuation
ValueCountFrequency (%)
) 129
100.0%
Open Punctuation
ValueCountFrequency (%)
( 124
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 103
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 50
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 11983
64.7%
Common 6500
35.1%
Latin 51
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
831
 
6.9%
830
 
6.9%
824
 
6.9%
823
 
6.9%
816
 
6.8%
816
 
6.8%
813
 
6.8%
755
 
6.3%
735
 
6.1%
728
 
6.1%
Other values (153) 4012
33.5%
Common
ValueCountFrequency (%)
3518
54.1%
1 450
 
6.9%
3 427
 
6.6%
2 354
 
5.4%
0 299
 
4.6%
5 225
 
3.5%
6 215
 
3.3%
7 173
 
2.7%
9 164
 
2.5%
8 154
 
2.4%
Other values (5) 521
 
8.0%
Latin
ValueCountFrequency (%)
K 25
49.0%
C 25
49.0%
A 1
 
2.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 11983
64.7%
ASCII 6551
35.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3518
53.7%
1 450
 
6.9%
3 427
 
6.5%
2 354
 
5.4%
0 299
 
4.6%
5 225
 
3.4%
6 215
 
3.3%
7 173
 
2.6%
9 164
 
2.5%
8 154
 
2.4%
Other values (8) 572
 
8.7%
Hangul
ValueCountFrequency (%)
831
 
6.9%
830
 
6.9%
824
 
6.9%
823
 
6.9%
816
 
6.8%
816
 
6.8%
813
 
6.8%
755
 
6.3%
735
 
6.1%
728
 
6.1%
Other values (153) 4012
33.5%
Distinct84
Distinct (%)10.3%
Missing0
Missing (%)0.0%
Memory size6.5 KiB
2023-12-12T11:48:04.506065image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length88
Median length54
Mean length15.04914
Min length2

Characters and Unicode

Total characters12250
Distinct characters169
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique35 ?
Unique (%)4.3%

Sample

1st row그 밖의 폐금속류
2nd row폐합성수지류(폐염화비닐수지류는 제외한다)
3rd row폐합성수지류(폐염화비닐수지류는 제외한다)
4th row폐가구류_ 폐도장목_ 폐목재포장재_ 폐전선드럼(원목상태의 깨끗한 목재를 말한다)
5th row폐합성수지류(폐염화비닐수지류는 제외한다)
ValueCountFrequency (%)
제외한다 244
 
11.6%
219
 
10.4%
밖의 219
 
10.4%
폐합성수지류(폐염화비닐수지류는 204
 
9.7%
폐합성수지류 105
 
5.0%
폐금속류 69
 
3.3%
분진 65
 
3.1%
발생되는 38
 
1.8%
소각시설에서 37
 
1.8%
것은 37
 
1.8%
Other values (144) 868
41.2%
2023-12-12T11:48:04.941740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1317
 
10.8%
922
 
7.5%
707
 
5.8%
583
 
4.8%
565
 
4.6%
365
 
3.0%
365
 
3.0%
365
 
3.0%
( 300
 
2.4%
) 300
 
2.4%
Other values (159) 6461
52.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 10198
83.2%
Space Separator 1317
 
10.8%
Open Punctuation 300
 
2.4%
Close Punctuation 300
 
2.4%
Connector Punctuation 126
 
1.0%
Decimal Number 8
 
0.1%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
922
 
9.0%
707
 
6.9%
583
 
5.7%
565
 
5.5%
365
 
3.6%
365
 
3.6%
365
 
3.6%
294
 
2.9%
261
 
2.6%
250
 
2.5%
Other values (151) 5521
54.1%
Decimal Number
ValueCountFrequency (%)
2 3
37.5%
3 3
37.5%
1 2
25.0%
Space Separator
ValueCountFrequency (%)
1317
100.0%
Open Punctuation
ValueCountFrequency (%)
( 300
100.0%
Close Punctuation
ValueCountFrequency (%)
) 300
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 126
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 10198
83.2%
Common 2052
 
16.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
922
 
9.0%
707
 
6.9%
583
 
5.7%
565
 
5.5%
365
 
3.6%
365
 
3.6%
365
 
3.6%
294
 
2.9%
261
 
2.6%
250
 
2.5%
Other values (151) 5521
54.1%
Common
ValueCountFrequency (%)
1317
64.2%
( 300
 
14.6%
) 300
 
14.6%
_ 126
 
6.1%
2 3
 
0.1%
3 3
 
0.1%
1 2
 
0.1%
. 1
 
< 0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 10187
83.2%
ASCII 2052
 
16.8%
Compat Jamo 11
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1317
64.2%
( 300
 
14.6%
) 300
 
14.6%
_ 126
 
6.1%
2 3
 
0.1%
3 3
 
0.1%
1 2
 
0.1%
. 1
 
< 0.1%
Hangul
ValueCountFrequency (%)
922
 
9.1%
707
 
6.9%
583
 
5.7%
565
 
5.5%
365
 
3.6%
365
 
3.6%
365
 
3.6%
294
 
2.9%
261
 
2.6%
250
 
2.5%
Other values (150) 5510
54.1%
Compat Jamo
ValueCountFrequency (%)
11
100.0%

배출량(톤)
Real number (ℝ)

Distinct153
Distinct (%)18.8%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean1158.9017
Minimum0
Maximum219000
Zeros1
Zeros (%)0.1%
Negative0
Negative (%)0.0%
Memory size7.3 KiB
2023-12-12T11:48:05.124138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum0
5-th percentile10
Q148
median100
Q3250
95-th percentile1894
Maximum219000
Range219000
Interquartile range (IQR)202

Descriptive statistics

Standard deviation9840.0049
Coefficient of variation (CV)8.4908017
Kurtosis322.37094
Mean1158.9017
Median Absolute Deviation (MAD)76
Skewness16.509467
Sum943346.02
Variance96825696
MonotonicityNot monotonic
2023-12-12T11:48:05.289828image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
60.0 85
 
10.4%
120.0 73
 
9.0%
24.0 35
 
4.3%
100.0 34
 
4.2%
30.0 34
 
4.2%
300.0 34
 
4.2%
36.0 29
 
3.6%
240.0 27
 
3.3%
50.0 27
 
3.3%
200.0 23
 
2.8%
Other values (143) 413
50.7%
ValueCountFrequency (%)
0.0 1
 
0.1%
0.24 1
 
0.1%
0.264 1
 
0.1%
0.3 1
 
0.1%
1.0 3
0.4%
2.1 1
 
0.1%
3.0 2
 
0.2%
3.6 3
0.4%
4.8 1
 
0.1%
5.0 7
0.9%
ValueCountFrequency (%)
219000.0 1
0.1%
100000.0 1
0.1%
94400.0 1
0.1%
71175.0 1
0.1%
60000.0 1
0.1%
36000.0 1
0.1%
30000.0 1
0.1%
25000.0 2
0.2%
12240.0 1
0.1%
10470.0 1
0.1%

Interactions

2023-12-12T11:48:02.557650image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T11:48:05.379454image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
폐기물 종류배출량(톤)
폐기물 종류1.0000.549
배출량(톤)0.5491.000

Missing values

2023-12-12T11:48:02.708410image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T11:48:02.801073image/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.

Sample

상호사업장도로명주소폐기물 종류배출량(톤)
0계성중공업(주)전라남도 영암군 삼호읍 대불산단2로 170그 밖의 폐금속류240.0
1계성중공업(주)전라남도 영암군 삼호읍 대불산단2로 170폐합성수지류(폐염화비닐수지류는 제외한다)120.0
2신우산업(주)제2공장전라남도 영암군 삼호읍 대불산단7로 72_ 신우산업폐합성수지류(폐염화비닐수지류는 제외한다)50.0
3신우산업(주)제2공장전라남도 영암군 삼호읍 대불산단7로 72_ 신우산업폐가구류_ 폐도장목_ 폐목재포장재_ 폐전선드럼(원목상태의 깨끗한 목재를 말한다)50.0
4신우산업(주)전라남도 영암군 삼호읍 나불로1길 38_ 신우산업(주)폐합성수지류(폐염화비닐수지류는 제외한다)50.0
5신우산업(주)전라남도 영암군 삼호읍 나불로1길 38_ 신우산업(주)폐가구류_ 폐도장목_ 폐목재포장재_ 폐전선드럼(원목상태의 깨끗한 목재를 말한다)50.0
6(주)우리조선전라남도 영암군 삼호읍 산단서부로 18 (주)우리조선폐합성수지류(폐염화비닐수지류는 제외한다)30.0
7(주)빈센전라남도 영암군 삼호읍 대불주거3로 55폐합성수지류(폐염화비닐수지류는 제외한다)30.0
8코스틸산업(주)전라남도 영암군 삼호읍 대불주거1로 192_ 코스틸산업그 밖의 광재류20.0
9현대인프라솔루션주식회사전라남도 영암군 삼호읍 용앙로 520_ 지팸중공업(주)폐합성수지류(폐염화비닐수지류는 제외한다)36.0
상호사업장도로명주소폐기물 종류배출량(톤)
804케이씨(주)전라남도 영암군 삼호읍 산단서부로 85_ KC(주)폐합성수지류(폐염화비닐수지류는 제외한다)200.0
805케이씨(주)전라남도 영암군 삼호읍 산단서부로 85_ KC(주)그 밖의 광재류5.0
806케이씨(주)전라남도 영암군 삼호읍 산단서부로 85_ KC(주)그 밖의 분진120.0
807케이씨(주)전라남도 영암군 삼호읍 산단서부로 85_ KC(주)보크사이트잔재물60000.0
808케이씨(주)전라남도 영암군 삼호읍 산단서부로 85_ KC(주)금속성폐촉매25.0
809케이씨(주)전라남도 영암군 삼호읍 산단서부로 85_ KC(주)폐합성수지류(폐염화비닐수지류는 제외한다)100.0
810케이씨(주)전라남도 영암군 삼호읍 산단서부로 85_ KC(주)보크사이트잔재물30000.0
811케이씨(주)전라남도 영암군 삼호읍 산단서부로 85_ KC(주)폐합성수지류(폐염화비닐수지류는 제외한다)100.0
812케이씨(주)전라남도 영암군 삼호읍 산단서부로 85_ KC(주)보크사이트잔재물71175.0
813케이씨(주)전라남도 영암군 삼호읍 산단서부로 85_ KC(주)폐수처리오니2500.0

Duplicate rows

Most frequently occurring

상호사업장도로명주소폐기물 종류배출량(톤)# duplicates
6(유)미래환경전라남도 영암군 학산면 녹색로 3030폐합성수지류(폐염화비닐수지류는 제외한다)250.04
10(유)천하환경전라남도 영암군 삼호읍 백야길 29-215폐합성수지류(폐염화비닐수지류는 제외한다)360.04
61현대힘스(주)대불1공장전라남도 영암군 삼호읍 대불산단3로 20그 밖의 광재류250.04
5(유)미래환경전라남도 영암군 학산면 녹색로 3030폐합성수지류(폐염화비닐수지류는 제외한다)175.03
13(유)현성산업전라남도 영암군 삼호읍 난전리 1685-5폐사(샌드블라스트 폐사)200.03
14(주)미주산업전라남도 영암군 삼호읍 대불산단7로 38폐합성수지류(폐염화비닐수지류는 제외한다)60.03
15(주)보석산업전라남도 영암군 삼호읍 대불산단6로 37-21폐합성수지류(폐염화비닐수지류는 제외한다)60.03
40보워터코리아(유)전라남도 영암군 삼호읍 나불로 230그 밖의 소각시설 중 바닥재와 비산재가 분리ㆍ배출되지 아니하는 시설에서 발생하는 소각재6000.03
46영암그린에너지(주)전라남도 영암군 삼호읍 대불산단6로 31폐합성수지류(폐염화비닐수지류는 제외한다)1000.03
64현대힘스(주)대불2공장전라남도 영암군 삼호읍 대불산단6로 155폐합성수지류(폐염화비닐수지류는 제외한다)300.03