Overview

Dataset statistics

Number of variables7
Number of observations922
Missing cells0
Missing cells (%)0.0%
Duplicate rows141
Duplicate rows (%)15.3%
Total size in memory52.3 KiB
Average record size in memory58.1 B

Variable types

Text4
Numeric2
Categorical1

Dataset

Description전북특별자치도 전주시 내 사업장폐기물배출자를 제공하며 상호, 폐기물종류, 사업장도로명주소 등을 제공합니다.항목 : 상호, 폐기물종류, 사업장도로명주소, 사업장지번주소, 위도, 경도제공부서: 자원순환과
Author전북특별자치도 전주시
URLhttps://www.data.go.kr/data/15081437/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
Dataset has 141 (15.3%) duplicate rowsDuplicates

Reproduction

Analysis started2024-03-15 01:43:03.713609
Analysis finished2024-03-15 01:43:06.261320
Duration2.55 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

상호
Text

Distinct246
Distinct (%)26.7%
Missing0
Missing (%)0.0%
Memory size7.3 KiB
2024-03-15T10:43:06.890194image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length18
Mean length8.7071584
Min length2

Characters and Unicode

Total characters8028
Distinct characters293
Distinct categories9 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique122 ?
Unique (%)13.2%

Sample

1st row(사법)전북자동차검사정비사업조합
2nd row(사법)전북자동차검사정비사업조합
3rd row(사법)전북자동차검사정비사업조합
4th row(사법)전북자동차정비사업조합
5th row(유)공동체나눔환경
ValueCountFrequency (%)
주)전주페이퍼 80
 
7.6%
주)휴비스 65
 
6.2%
주식회사 39
 
3.7%
효성첨단소재(주)전주공장 27
 
2.6%
전주리싸이클링에너지(주 27
 
2.6%
천일제지(주 24
 
2.3%
주)전주원파워 22
 
2.1%
전주파워 21
 
2.0%
유)풍성산업 15
 
1.4%
케이씨환경서비스(주)전주사업부 14
 
1.3%
Other values (258) 712
68.1%
2024-03-15T10:43:07.971093image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
920
 
11.5%
( 660
 
8.2%
) 660
 
8.2%
422
 
5.3%
233
 
2.9%
146
 
1.8%
129
 
1.6%
125
 
1.6%
125
 
1.6%
124
 
1.5%
Other values (283) 4484
55.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 6541
81.5%
Open Punctuation 660
 
8.2%
Close Punctuation 660
 
8.2%
Space Separator 124
 
1.5%
Uppercase Letter 24
 
0.3%
Other Punctuation 6
 
0.1%
Connector Punctuation 6
 
0.1%
Decimal Number 6
 
0.1%
Dash Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
920
 
14.1%
422
 
6.5%
233
 
3.6%
146
 
2.2%
129
 
2.0%
125
 
1.9%
125
 
1.9%
119
 
1.8%
115
 
1.8%
97
 
1.5%
Other values (270) 4110
62.8%
Uppercase Letter
ValueCountFrequency (%)
Y 10
41.7%
D 6
25.0%
B 4
 
16.7%
C 4
 
16.7%
Decimal Number
ValueCountFrequency (%)
1 3
50.0%
8 2
33.3%
2 1
 
16.7%
Open Punctuation
ValueCountFrequency (%)
( 660
100.0%
Close Punctuation
ValueCountFrequency (%)
) 660
100.0%
Space Separator
ValueCountFrequency (%)
124
100.0%
Other Punctuation
ValueCountFrequency (%)
. 6
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 6
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 6541
81.5%
Common 1463
 
18.2%
Latin 24
 
0.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
920
 
14.1%
422
 
6.5%
233
 
3.6%
146
 
2.2%
129
 
2.0%
125
 
1.9%
125
 
1.9%
119
 
1.8%
115
 
1.8%
97
 
1.5%
Other values (270) 4110
62.8%
Common
ValueCountFrequency (%)
( 660
45.1%
) 660
45.1%
124
 
8.5%
. 6
 
0.4%
_ 6
 
0.4%
1 3
 
0.2%
8 2
 
0.1%
2 1
 
0.1%
- 1
 
0.1%
Latin
ValueCountFrequency (%)
Y 10
41.7%
D 6
25.0%
B 4
 
16.7%
C 4
 
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 6541
81.5%
ASCII 1487
 
18.5%

Most frequent character per block

Hangul
ValueCountFrequency (%)
920
 
14.1%
422
 
6.5%
233
 
3.6%
146
 
2.2%
129
 
2.0%
125
 
1.9%
125
 
1.9%
119
 
1.8%
115
 
1.8%
97
 
1.5%
Other values (270) 4110
62.8%
ASCII
ValueCountFrequency (%)
( 660
44.4%
) 660
44.4%
124
 
8.3%
Y 10
 
0.7%
. 6
 
0.4%
D 6
 
0.4%
_ 6
 
0.4%
B 4
 
0.3%
C 4
 
0.3%
1 3
 
0.2%
Other values (3) 4
 
0.3%
Distinct104
Distinct (%)11.3%
Missing0
Missing (%)0.0%
Memory size7.3 KiB
2024-03-15T10:43:09.126751image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length84
Median length57
Mean length15.530369
Min length1

Characters and Unicode

Total characters14319
Distinct characters196
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks4 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique41 ?
Unique (%)4.4%

Sample

1st row폐합성수지류(폐염화비닐수지류는 제외한다)
2nd row폐합성수지류(폐염화비닐수지류는 제외한다)
3rd row폐합성수지류(폐염화비닐수지류는 제외한다)
4th row
5th row폐합성수지류
ValueCountFrequency (%)
제외한다 228
 
9.3%
225
 
9.1%
밖의 225
 
9.1%
폐합성수지류(폐염화비닐수지류는 220
 
8.9%
말한다 99
 
4.0%
사업장폐기물 93
 
3.8%
소각시설 89
 
3.6%
비산재가 65
 
2.6%
소각재(바닥재와 63
 
2.6%
혼합된 63
 
2.6%
Other values (179) 1091
44.3%
2024-03-15T10:43:10.562253image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1566
 
10.9%
1096
 
7.7%
611
 
4.3%
603
 
4.2%
558
 
3.9%
384
 
2.7%
382
 
2.7%
357
 
2.5%
348
 
2.4%
337
 
2.4%
Other values (186) 8077
56.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 11974
83.6%
Space Separator 1575
 
11.0%
Open Punctuation 342
 
2.4%
Close Punctuation 342
 
2.4%
Connector Punctuation 67
 
0.5%
Decimal Number 18
 
0.1%
Other Punctuation 1
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1096
 
9.2%
611
 
5.1%
603
 
5.0%
558
 
4.7%
384
 
3.2%
382
 
3.2%
357
 
3.0%
348
 
2.9%
337
 
2.8%
336
 
2.8%
Other values (174) 6962
58.1%
Decimal Number
ValueCountFrequency (%)
1 11
61.1%
8 5
27.8%
4 1
 
5.6%
3 1
 
5.6%
Space Separator
ValueCountFrequency (%)
1566
99.4%
  9
 
0.6%
Open Punctuation
ValueCountFrequency (%)
( 337
98.5%
5
 
1.5%
Close Punctuation
ValueCountFrequency (%)
) 337
98.5%
5
 
1.5%
Connector Punctuation
ValueCountFrequency (%)
_ 67
100.0%
Other Punctuation
ValueCountFrequency (%)
. 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 11974
83.6%
Common 2345
 
16.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1096
 
9.2%
611
 
5.1%
603
 
5.0%
558
 
4.7%
384
 
3.2%
382
 
3.2%
357
 
3.0%
348
 
2.9%
337
 
2.8%
336
 
2.8%
Other values (174) 6962
58.1%
Common
ValueCountFrequency (%)
1566
66.8%
( 337
 
14.4%
) 337
 
14.4%
_ 67
 
2.9%
1 11
 
0.5%
  9
 
0.4%
8 5
 
0.2%
5
 
0.2%
5
 
0.2%
4 1
 
< 0.1%
Other values (2) 2
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 11900
83.1%
ASCII 2326
 
16.2%
Compat Jamo 74
 
0.5%
None 19
 
0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1566
67.3%
( 337
 
14.5%
) 337
 
14.5%
_ 67
 
2.9%
1 11
 
0.5%
8 5
 
0.2%
4 1
 
< 0.1%
. 1
 
< 0.1%
3 1
 
< 0.1%
Hangul
ValueCountFrequency (%)
1096
 
9.2%
611
 
5.1%
603
 
5.1%
558
 
4.7%
384
 
3.2%
382
 
3.2%
357
 
3.0%
348
 
2.9%
337
 
2.8%
336
 
2.8%
Other values (173) 6888
57.9%
Compat Jamo
ValueCountFrequency (%)
74
100.0%
None
ValueCountFrequency (%)
  9
47.4%
5
26.3%
5
26.3%
Distinct228
Distinct (%)24.7%
Missing0
Missing (%)0.0%
Memory size7.3 KiB
2024-03-15T10:43:11.560927image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length46
Median length44
Mean length32.280911
Min length1

Characters and Unicode

Total characters29763
Distinct characters207
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique107 ?
Unique (%)11.6%

Sample

1st row전북특별자치도 전주시 덕진구 서귀로 23 (팔복동2가)
2nd row전북특별자치도 전주시 덕진구 서귀로 23 (팔복동2가)
3rd row전북특별자치도 전주시 덕진구 서귀로 23 (팔복동2가)
4th row전북특별자치도 전주시 덕진구 서귀로 23 (팔복동3가)
5th row전북특별자치도 전주시 덕진구 고내천변로 388-23 (전미동2가)
ValueCountFrequency (%)
전북특별자치도 902
16.3%
전주시 900
16.3%
덕진구 753
 
13.6%
팔복동2가 167
 
3.0%
팔복로 157
 
2.8%
완산구 147
 
2.7%
59 123
 
2.2%
기린대로 112
 
2.0%
팔복동3가 105
 
1.9%
팔복동2가_(주)전주페이퍼 80
 
1.4%
Other values (351) 2075
37.6%
2024-03-15T10:43:13.036255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4665
 
15.7%
1965
 
6.6%
1142
 
3.8%
) 1014
 
3.4%
( 1014
 
3.4%
960
 
3.2%
944
 
3.2%
934
 
3.1%
911
 
3.1%
909
 
3.1%
Other values (197) 15305
51.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 19275
64.8%
Space Separator 4665
 
15.7%
Decimal Number 3411
 
11.5%
Close Punctuation 1014
 
3.4%
Open Punctuation 1014
 
3.4%
Dash Punctuation 221
 
0.7%
Connector Punctuation 163
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1965
 
10.2%
1142
 
5.9%
960
 
5.0%
944
 
4.9%
934
 
4.8%
911
 
4.7%
909
 
4.7%
908
 
4.7%
904
 
4.7%
902
 
4.7%
Other values (182) 8796
45.6%
Decimal Number
ValueCountFrequency (%)
1 626
18.4%
2 618
18.1%
3 415
12.2%
5 399
11.7%
7 313
9.2%
4 308
9.0%
8 244
 
7.2%
9 172
 
5.0%
0 164
 
4.8%
6 152
 
4.5%
Space Separator
ValueCountFrequency (%)
4665
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1014
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1014
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 221
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 163
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 19275
64.8%
Common 10488
35.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1965
 
10.2%
1142
 
5.9%
960
 
5.0%
944
 
4.9%
934
 
4.8%
911
 
4.7%
909
 
4.7%
908
 
4.7%
904
 
4.7%
902
 
4.7%
Other values (182) 8796
45.6%
Common
ValueCountFrequency (%)
4665
44.5%
) 1014
 
9.7%
( 1014
 
9.7%
1 626
 
6.0%
2 618
 
5.9%
3 415
 
4.0%
5 399
 
3.8%
7 313
 
3.0%
4 308
 
2.9%
8 244
 
2.3%
Other values (5) 872
 
8.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 19275
64.8%
ASCII 10488
35.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4665
44.5%
) 1014
 
9.7%
( 1014
 
9.7%
1 626
 
6.0%
2 618
 
5.9%
3 415
 
4.0%
5 399
 
3.8%
7 313
 
3.0%
4 308
 
2.9%
8 244
 
2.3%
Other values (5) 872
 
8.3%
Hangul
ValueCountFrequency (%)
1965
 
10.2%
1142
 
5.9%
960
 
5.0%
944
 
4.9%
934
 
4.8%
911
 
4.7%
909
 
4.7%
908
 
4.7%
904
 
4.7%
902
 
4.7%
Other values (182) 8796
45.6%
Distinct203
Distinct (%)22.0%
Missing0
Missing (%)0.0%
Memory size7.3 KiB
2024-03-15T10:43:14.285998image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length48
Median length39
Mean length26.694143
Min length1

Characters and Unicode

Total characters24612
Distinct characters121
Distinct categories7 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique94 ?
Unique (%)10.2%

Sample

1st row전북특별자치도 전주시 덕진구 팔복동2가 417-13
2nd row전북특별자치도 전주시 덕진구 팔복동2가 417-13
3rd row전북특별자치도 전주시 덕진구 팔복동2가 417-13
4th row전북특별자치도 전주시 덕진구 팔복동3가 222-2
5th row전북특별자치도 전주시 덕진구 전미동2가 115-1
ValueCountFrequency (%)
전북특별자치도 845
18.9%
전주시 843
18.8%
덕진구 700
15.6%
팔복동2가 237
 
5.3%
완산구 144
 
3.2%
180 123
 
2.7%
주)전주페이퍼 101
 
2.3%
팔복동3가 99
 
2.2%
여의동 87
 
1.9%
팔복동4가 78
 
1.7%
Other values (266) 1217
27.2%
2024-03-15T10:43:15.834761image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4545
18.5%
1817
 
7.4%
1127
 
4.6%
865
 
3.5%
856
 
3.5%
852
 
3.5%
851
 
3.5%
851
 
3.5%
851
 
3.5%
850
 
3.5%
Other values (111) 11147
45.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 15318
62.2%
Space Separator 4545
 
18.5%
Decimal Number 3895
 
15.8%
Dash Punctuation 491
 
2.0%
Open Punctuation 170
 
0.7%
Close Punctuation 170
 
0.7%
Connector Punctuation 23
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1817
 
11.9%
1127
 
7.4%
865
 
5.6%
856
 
5.6%
852
 
5.6%
851
 
5.6%
851
 
5.6%
851
 
5.6%
850
 
5.5%
846
 
5.5%
Other values (96) 5552
36.2%
Decimal Number
ValueCountFrequency (%)
1 666
17.1%
2 594
15.3%
3 592
15.2%
4 387
9.9%
8 368
9.4%
0 363
9.3%
5 293
7.5%
7 236
 
6.1%
9 203
 
5.2%
6 193
 
5.0%
Space Separator
ValueCountFrequency (%)
4545
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 491
100.0%
Open Punctuation
ValueCountFrequency (%)
( 170
100.0%
Close Punctuation
ValueCountFrequency (%)
) 170
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 23
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 15318
62.2%
Common 9294
37.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1817
 
11.9%
1127
 
7.4%
865
 
5.6%
856
 
5.6%
852
 
5.6%
851
 
5.6%
851
 
5.6%
851
 
5.6%
850
 
5.5%
846
 
5.5%
Other values (96) 5552
36.2%
Common
ValueCountFrequency (%)
4545
48.9%
1 666
 
7.2%
2 594
 
6.4%
3 592
 
6.4%
- 491
 
5.3%
4 387
 
4.2%
8 368
 
4.0%
0 363
 
3.9%
5 293
 
3.2%
7 236
 
2.5%
Other values (5) 759
 
8.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 15318
62.2%
ASCII 9294
37.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4545
48.9%
1 666
 
7.2%
2 594
 
6.4%
3 592
 
6.4%
- 491
 
5.3%
4 387
 
4.2%
8 368
 
4.0%
0 363
 
3.9%
5 293
 
3.2%
7 236
 
2.5%
Other values (5) 759
 
8.2%
Hangul
ValueCountFrequency (%)
1817
 
11.9%
1127
 
7.4%
865
 
5.6%
856
 
5.6%
852
 
5.6%
851
 
5.6%
851
 
5.6%
851
 
5.6%
850
 
5.5%
846
 
5.5%
Other values (96) 5552
36.2%

위도
Real number (ℝ)

Distinct221
Distinct (%)24.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.860155
Minimum35.751611
Maximum37.517641
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size8.2 KiB
2024-03-15T10:43:16.288487image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.751611
5-th percentile35.799827
Q135.845129
median35.854315
Q335.858773
95-th percentile35.870009
Maximum37.517641
Range1.7660303
Interquartile range (IQR)0.01364329

Descriptive statistics

Standard deviation0.14619476
Coefficient of variation (CV)0.0040768023
Kurtosis121.99966
Mean35.860155
Median Absolute Deviation (MAD)0.00901704
Skewness10.997068
Sum33063.063
Variance0.021372909
MonotonicityNot monotonic
2024-03-15T10:43:16.859826image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35.84512928 123
 
13.3%
35.85431528 65
 
7.0%
35.79982653 27
 
2.9%
35.86555298 27
 
2.9%
35.86618505 24
 
2.6%
35.85877257 15
 
1.6%
35.85568447 14
 
1.5%
35.85423212 13
 
1.4%
35.8143857 13
 
1.4%
35.84696451 13
 
1.4%
Other values (211) 588
63.8%
ValueCountFrequency (%)
35.75161091 2
0.2%
35.75852406 1
 
0.1%
35.76707707 3
0.3%
35.7794632 1
 
0.1%
35.77960185 3
0.3%
35.78504933 4
0.4%
35.78686647 1
 
0.1%
35.79041886 3
0.3%
35.79056737 3
0.3%
35.79142817 1
 
0.1%
ValueCountFrequency (%)
37.51764123 6
0.7%
37.48469666 1
 
0.1%
35.89102396 4
0.4%
35.89077305 1
 
0.1%
35.89060094 6
0.7%
35.88659396 1
 
0.1%
35.88493988 4
0.4%
35.88263254 2
 
0.2%
35.8811435 6
0.7%
35.88021639 1
 
0.1%

경도
Real number (ℝ)

Distinct221
Distinct (%)24.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean127.09816
Minimum127.0175
Maximum127.22743
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size8.2 KiB
2024-03-15T10:43:17.322936image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum127.0175
5-th percentile127.06858
Q1127.08595
median127.0967
Q3127.10407
95-th percentile127.14799
Maximum127.22743
Range0.2099308
Interquartile range (IQR)0.0181175

Descriptive statistics

Standard deviation0.023831783
Coefficient of variation (CV)0.00018750691
Kurtosis3.1334969
Mean127.09816
Median Absolute Deviation (MAD)0.0086608
Skewness0.85788311
Sum117184.51
Variance0.0005679539
MonotonicityNot monotonic
2024-03-15T10:43:17.800735image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
127.0967046 123
 
13.3%
127.0964265 65
 
7.0%
127.0736913 27
 
2.9%
127.088396 27
 
2.9%
127.1044258 24
 
2.6%
127.058647 15
 
1.6%
127.0766483 14
 
1.5%
127.0859478 13
 
1.4%
127.1443569 13
 
1.4%
127.0897308 13
 
1.4%
Other values (211) 588
63.8%
ValueCountFrequency (%)
127.017497 1
 
0.1%
127.0294118 1
 
0.1%
127.0329587 4
 
0.4%
127.0334506 6
 
0.7%
127.0337834 2
 
0.2%
127.0416732 6
 
0.7%
127.0580791 1
 
0.1%
127.058647 15
1.6%
127.0602097 1
 
0.1%
127.063341 5
 
0.5%
ValueCountFrequency (%)
127.2274278 2
0.2%
127.1853828 2
0.2%
127.1734749 1
 
0.1%
127.1703365 1
 
0.1%
127.1682973 1
 
0.1%
127.1673251 3
0.3%
127.1673162 1
 
0.1%
127.1663689 1
 
0.1%
127.1599928 3
0.3%
127.1596459 1
 
0.1%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size7.3 KiB
2024-01-18
922 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2024-01-18
2nd row2024-01-18
3rd row2024-01-18
4th row2024-01-18
5th row2024-01-18

Common Values

ValueCountFrequency (%)
2024-01-18 922
100.0%

Length

2024-03-15T10:43:18.225146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-03-15T10:43:18.524415image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2024-01-18 922
100.0%

Interactions

2024-03-15T10:43:05.107431image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:43:04.567457image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:43:05.332669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2024-03-15T10:43:04.860303image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2024-03-15T10:43:18.707991image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도
위도1.0000.480
경도0.4801.000
2024-03-15T10:43:18.961530image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도
위도1.000-0.106
경도-0.1061.000

Missing values

2024-03-15T10:43:05.727668image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-15T10:43:06.104229image/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

상호폐기물 종류사업장도로명주소사업장지번주소위도경도데이터기준일자
0(사법)전북자동차검사정비사업조합폐합성수지류(폐염화비닐수지류는 제외한다)전북특별자치도 전주시 덕진구 서귀로 23 (팔복동2가)전북특별자치도 전주시 덕진구 팔복동2가 417-1335.849911127.0947072024-01-18
1(사법)전북자동차검사정비사업조합폐합성수지류(폐염화비닐수지류는 제외한다)전북특별자치도 전주시 덕진구 서귀로 23 (팔복동2가)전북특별자치도 전주시 덕진구 팔복동2가 417-1335.849911127.0947072024-01-18
2(사법)전북자동차검사정비사업조합폐합성수지류(폐염화비닐수지류는 제외한다)전북특별자치도 전주시 덕진구 서귀로 23 (팔복동2가)전북특별자치도 전주시 덕진구 팔복동2가 417-1335.849911127.0947072024-01-18
3(사법)전북자동차정비사업조합전북특별자치도 전주시 덕진구 서귀로 23 (팔복동3가)전북특별자치도 전주시 덕진구 팔복동3가 222-235.849911127.0947072024-01-18
4(유)공동체나눔환경폐합성수지류전북특별자치도 전주시 덕진구 고내천변로 388-23 (전미동2가)전북특별자치도 전주시 덕진구 전미동2가 115-135.891024127.0972792024-01-18
5(유)공동체나눔환경폐합성수지류전북특별자치도 전주시 덕진구 고내천변로 388-23 (전미동2가)전북특별자치도 전주시 덕진구 전미동2가 115-135.891024127.0972792024-01-18
6(유)그린종합폐차장폐합성수지류(폐염화비닐수지류는 제외한다)전북특별자치도 전주시 덕진구 감수길 10-40 (팔복동4가)전북특별자치도 전주시 덕진구 팔복동4가 184-235.866408127.1032172024-01-18
7(유)그린종합폐차장그 밖의 폐촉매전북특별자치도 전주시 덕진구 감수길 10-40 (팔복동4가)전북특별자치도 전주시 덕진구 팔복동4가 184-235.866408127.1032172024-01-18
8(유)그린종합폐차장자동차 폐타이어전북특별자치도 전주시 덕진구 감수길 10-40 (팔복동4가)전북특별자치도 전주시 덕진구 팔복동4가 184-235.866408127.1032172024-01-18
9(유)그린종합폐차장그 밖의 폐촉매전북특별자치도 전주시 덕진구 감수길 10-40 (팔복동4가)전북특별자치도 전주시 덕진구 팔복동4가 184-235.866408127.1032172024-01-18
상호폐기물 종류사업장도로명주소사업장지번주소위도경도데이터기준일자
912효성첨단소재(주)전주공장폐활성탄전북특별자치도 전주시 덕진구 기린대로 886 (동산동)전북특별자치도 전주시 덕진구 여의동2가 74835.865553127.0883962024-01-18
913효성첨단소재(주)전주공장폐합성섬유전북특별자치도 전주시 덕진구 기린대로 886 (동산동)전북특별자치도 전주시 덕진구 여의동2가 74835.865553127.0883962024-01-18
914효성첨단소재(주)전주공장폐합성수지류(폐염화비닐수지류는 제외한다)전북특별자치도 전주시 덕진구 기린대로 886 (동산동)전북특별자치도 전주시 덕진구 여의동2가 74835.865553127.0883962024-01-18
915훼미리식품(주)폐식용유전북특별자치도 전주시 덕진구 팔과정로 216 (팔복동4가)전북특별자치도 전주시 덕진구 팔복동4가 249-335.864458127.0983262024-01-18
916훼미리식품(주)그 밖의 식물성잔재물전북특별자치도 전주시 덕진구 팔과정로 216 (팔복동4가)전북특별자치도 전주시 덕진구 팔복동4가 249-335.864458127.0983262024-01-18
917훼미리식품(주)폐합성수지류(폐염화비닐수지류는 제외한다)전북특별자치도 전주시 덕진구 팔과정로 216 (팔복동4가)전북특별자치도 전주시 덕진구 팔복동4가 249-335.864458127.0983262024-01-18
918훼미리식품(주)폐합성수지류(폐염화비닐수지류는 제외한다)전북특별자치도 전주시 덕진구 팔과정로 216 (팔복동4가)전북특별자치도 전주시 덕진구 팔복동4가 249-335.864458127.0983262024-01-18
919훼미리식품(주)그 밖의 폐수처리오니전북특별자치도 전주시 덕진구 팔과정로 216 (팔복동4가)전북특별자치도 전주시 덕진구 팔복동4가 249-335.864458127.0983262024-01-18
920훼미리식품(주)그 밖의 폐수처리오니전북특별자치도 전주시 덕진구 팔과정로 216 (팔복동4가)전북특별자치도 전주시 덕진구 팔복동4가 249-335.864458127.0983262024-01-18
921훼미리식품(주)음식물류폐기물전북특별자치도 전주시 덕진구 팔과정로 216 (팔복동4가)전북특별자치도 전주시 덕진구 팔복동4가 249-335.864458127.0983262024-01-18

Duplicate rows

Most frequently occurring

상호폐기물 종류사업장도로명주소사업장지번주소위도경도데이터기준일자# duplicates
51(주)전주페이퍼사업장폐기물 소각시설 소각재(바닥재와 비산재가 혼합된 경우를 말한다)전북특별자치도 전주시 덕진구 팔복로 59 (팔복동2가_(주)전주페이퍼)전북특별자치도 전주시 덕진구 팔복동2가 180 (주)전주페이퍼35.845129127.0967052024-01-1828
68(주)휴비스폐합성수지류(폐염화비닐수지류는 제외한다)전북특별자치도 전주시 덕진구 기린대로 787 (팔복동2가)전북특별자치도 전주시 덕진구 팔복동2가 339 (주)휴비스35.854315127.0964272024-01-1827
55(주)전주페이퍼폐합성수지류(폐염화비닐수지류는 제외한다)전북특별자치도 전주시 덕진구 팔복로 59 (팔복동2가_(주)전주페이퍼)전북특별자치도 전주시 덕진구 팔복동2가 180 (주)전주페이퍼35.845129127.0967052024-01-1822
117천일제지(주)펄프ㆍ제지폐수처리오니전북특별자치도 전주시 덕진구 야전1길 27 (팔복동4가)전북특별자치도 전주시 덕진구 팔복동4가 215-3335.866185127.1044262024-01-1818
45(주)전주원파워사업장폐기물 소각시설 소각재(바닥재와 비산재가 혼합된 경우를 말한다)전북특별자치도 전주시 덕진구 팔복로 59 (팔복동2가)전북특별자치도 전주시 덕진구 팔복동2가 18035.845129127.0967052024-01-1815
65(주)휴비스석탄재전북특별자치도 전주시 덕진구 기린대로 787 (팔복동2가)전북특별자치도 전주시 덕진구 팔복동2가 339 (주)휴비스35.854315127.0964272024-01-1815
53(주)전주페이퍼펄프ㆍ제지폐수처리오니전북특별자치도 전주시 덕진구 팔복로 59 (팔복동2가_(주)전주페이퍼)전북특별자치도 전주시 덕진구 팔복동2가 180 (주)전주페이퍼35.845129127.0967052024-01-1814
112주식회사 전주파워사업장폐기물 소각시설 소각재(바닥재와 비산재가 혼합된 경우를 말한다)전북특별자치도 전주시 덕진구 팔복로 59 (주)전주페이퍼 (팔복동2가)전북특별자치도 전주시 덕진구 팔복동2가 180 (주)전주페이퍼35.845129127.0967052024-01-1813
94이도에코전주(주)사업장폐기물 소각시설 바닥재전북특별자치도 전주시 덕진구 원만성로 55 (팔복동3가)전북특별자치도 전주시 덕진구 팔복동3가 478-135.854232127.0859482024-01-189
104전주리싸이클링에너지(주)폐합성수지류(폐염화비닐수지류는 제외한다)전북특별자치도 전주시 완산구 삼산길 51-24 (삼천동3가)전북특별자치도 전주시 완산구 삼천동3가 749-535.799827127.0736912024-01-189