Overview

Dataset statistics

Number of variables9
Number of observations927
Missing cells128
Missing cells (%)1.5%
Duplicate rows42
Duplicate rows (%)4.5%
Total size in memory67.1 KiB
Average record size in memory74.1 B

Variable types

Categorical2
Text5
Numeric2

Dataset

Description영천시의 사업장폐기물배출자 신고현황으로 배출자 상호, 소재지, 배출폐기물, 처리업체명 등의 데이터를 제공합니다.
Author경상북도 영천시
URLhttps://www.data.go.kr/data/15060236/fileData.do

Alerts

배출구분 has constant value ""Constant
등록기준일 has constant value ""Constant
Dataset has 42 (4.5%) duplicate rowsDuplicates
위도 has 64 (6.9%) missing valuesMissing
경도 has 64 (6.9%) missing valuesMissing

Reproduction

Analysis started2023-12-12 12:56:58.529879
Analysis finished2023-12-12 12:56:59.783963
Duration1.25 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

배출구분
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size7.4 KiB
일반
927 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
일반 927
100.0%

Length

2023-12-12T21:56:59.837295image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:56:59.917974image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
일반 927
100.0%

상호
Text

Distinct325
Distinct (%)35.1%
Missing0
Missing (%)0.0%
Memory size7.4 KiB
2023-12-12T21:57:00.178673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length23
Median length16
Mean length8.0733549
Min length2

Characters and Unicode

Total characters7484
Distinct characters290
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

Unique128 ?
Unique (%)13.8%

Sample

1st row(주)제일윈도텍스
2nd row삼일특장
3rd row(주)도투락
4th row(주)에이치인더스트리
5th row(주)에코비트
ValueCountFrequency (%)
주식회사 36
 
3.5%
녹색자원(주)동영천지점 24
 
2.3%
영천공장 21
 
2.1%
주)영천알씨 21
 
2.1%
주)화신 19
 
1.9%
주)에스피환경 17
 
1.7%
이앤알컴퍼니 17
 
1.7%
주)에니스환경건설 14
 
1.4%
주)다이엑스 13
 
1.3%
주)덕성 13
 
1.3%
Other values (325) 829
81.0%
2023-12-12T21:57:00.630531image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
687
 
9.2%
( 668
 
8.9%
) 668
 
8.9%
202
 
2.7%
161
 
2.2%
158
 
2.1%
154
 
2.1%
153
 
2.0%
131
 
1.8%
122
 
1.6%
Other values (280) 4380
58.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5895
78.8%
Open Punctuation 669
 
8.9%
Close Punctuation 669
 
8.9%
Space Separator 97
 
1.3%
Uppercase Letter 64
 
0.9%
Decimal Number 42
 
0.6%
Lowercase Letter 28
 
0.4%
Other Punctuation 17
 
0.2%
Connector Punctuation 3
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
687
 
11.7%
202
 
3.4%
161
 
2.7%
158
 
2.7%
154
 
2.6%
153
 
2.6%
131
 
2.2%
122
 
2.1%
111
 
1.9%
110
 
1.9%
Other values (242) 3906
66.3%
Uppercase Letter
ValueCountFrequency (%)
S 15
23.4%
R 9
14.1%
F 6
 
9.4%
M 4
 
6.2%
G 4
 
6.2%
N 4
 
6.2%
T 4
 
6.2%
P 3
 
4.7%
L 3
 
4.7%
E 3
 
4.7%
Other values (3) 9
14.1%
Lowercase Letter
ValueCountFrequency (%)
o 6
21.4%
a 4
14.3%
d 4
14.3%
t 3
10.7%
n 2
 
7.1%
e 2
 
7.1%
r 1
 
3.6%
i 1
 
3.6%
f 1
 
3.6%
g 1
 
3.6%
Other values (3) 3
10.7%
Decimal Number
ValueCountFrequency (%)
2 14
33.3%
8 12
28.6%
3 9
21.4%
7 6
14.3%
1 1
 
2.4%
Open Punctuation
ValueCountFrequency (%)
( 668
99.9%
[ 1
 
0.1%
Close Punctuation
ValueCountFrequency (%)
) 668
99.9%
] 1
 
0.1%
Space Separator
ValueCountFrequency (%)
97
100.0%
Other Punctuation
ValueCountFrequency (%)
. 17
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5895
78.8%
Common 1497
 
20.0%
Latin 92
 
1.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
687
 
11.7%
202
 
3.4%
161
 
2.7%
158
 
2.7%
154
 
2.6%
153
 
2.6%
131
 
2.2%
122
 
2.1%
111
 
1.9%
110
 
1.9%
Other values (242) 3906
66.3%
Latin
ValueCountFrequency (%)
S 15
16.3%
R 9
 
9.8%
o 6
 
6.5%
F 6
 
6.5%
M 4
 
4.3%
G 4
 
4.3%
N 4
 
4.3%
a 4
 
4.3%
d 4
 
4.3%
T 4
 
4.3%
Other values (16) 32
34.8%
Common
ValueCountFrequency (%)
( 668
44.6%
) 668
44.6%
97
 
6.5%
. 17
 
1.1%
2 14
 
0.9%
8 12
 
0.8%
3 9
 
0.6%
7 6
 
0.4%
_ 3
 
0.2%
[ 1
 
0.1%
Other values (2) 2
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5895
78.8%
ASCII 1589
 
21.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
687
 
11.7%
202
 
3.4%
161
 
2.7%
158
 
2.7%
154
 
2.6%
153
 
2.6%
131
 
2.2%
122
 
2.1%
111
 
1.9%
110
 
1.9%
Other values (242) 3906
66.3%
ASCII
ValueCountFrequency (%)
( 668
42.0%
) 668
42.0%
97
 
6.1%
. 17
 
1.1%
S 15
 
0.9%
2 14
 
0.9%
8 12
 
0.8%
R 9
 
0.6%
3 9
 
0.6%
o 6
 
0.4%
Other values (28) 74
 
4.7%
Distinct96
Distinct (%)10.4%
Missing0
Missing (%)0.0%
Memory size7.4 KiB
2023-12-12T21:57:00.977886image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length84
Median length54
Mean length14.357066
Min length1

Characters and Unicode

Total characters13309
Distinct characters182
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

Unique19 ?
Unique (%)2.0%

Sample

1st row폐합성수지류(폐염화비닐수지류는 제외한다)
2nd row폐합성수지류(폐염화비닐수지류는 제외한다)
3rd row폐합성수지류(폐염화비닐수지류는 제외한다)
4th row목재가공공장 부산물(접착제_ 페인트_ 기름_ 콘크리트 등의 물질이 사용된 목재부산물 및 분진을 말한다)
5th row그 밖의 공정오니
ValueCountFrequency (%)
제외한다 324
15.6%
폐합성수지류(폐염화비닐수지류는 312
 
15.0%
199
 
9.6%
밖의 199
 
9.6%
폐수처리오니 66
 
3.2%
폐합성수지류 51
 
2.5%
분진 38
 
1.8%
공정오니 36
 
1.7%
폐토사 30
 
1.4%
광재류 29
 
1.4%
Other values (158) 790
38.1%
2023-12-12T21:57:01.481138image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1186
 
8.9%
1068
 
8.0%
787
 
5.9%
770
 
5.8%
712
 
5.3%
454
 
3.4%
399
 
3.0%
383
 
2.9%
( 365
 
2.7%
) 365
 
2.7%
Other values (172) 6820
51.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 11326
85.1%
Space Separator 1186
 
8.9%
Open Punctuation 365
 
2.7%
Close Punctuation 365
 
2.7%
Connector Punctuation 57
 
0.4%
Decimal Number 6
 
< 0.1%
Other Punctuation 4
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1068
 
9.4%
787
 
6.9%
770
 
6.8%
712
 
6.3%
454
 
4.0%
399
 
3.5%
383
 
3.4%
362
 
3.2%
360
 
3.2%
355
 
3.1%
Other values (165) 5676
50.1%
Decimal Number
ValueCountFrequency (%)
1 3
50.0%
2 3
50.0%
Space Separator
ValueCountFrequency (%)
1186
100.0%
Open Punctuation
ValueCountFrequency (%)
( 365
100.0%
Close Punctuation
ValueCountFrequency (%)
) 365
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 57
100.0%
Other Punctuation
ValueCountFrequency (%)
. 4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 11326
85.1%
Common 1983
 
14.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1068
 
9.4%
787
 
6.9%
770
 
6.8%
712
 
6.3%
454
 
4.0%
399
 
3.5%
383
 
3.4%
362
 
3.2%
360
 
3.2%
355
 
3.1%
Other values (165) 5676
50.1%
Common
ValueCountFrequency (%)
1186
59.8%
( 365
 
18.4%
) 365
 
18.4%
_ 57
 
2.9%
. 4
 
0.2%
1 3
 
0.2%
2 3
 
0.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 11291
84.8%
ASCII 1983
 
14.9%
Compat Jamo 35
 
0.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1186
59.8%
( 365
 
18.4%
) 365
 
18.4%
_ 57
 
2.9%
. 4
 
0.2%
1 3
 
0.2%
2 3
 
0.2%
Hangul
ValueCountFrequency (%)
1068
 
9.5%
787
 
7.0%
770
 
6.8%
712
 
6.3%
454
 
4.0%
399
 
3.5%
383
 
3.4%
362
 
3.2%
360
 
3.2%
355
 
3.1%
Other values (164) 5641
50.0%
Compat Jamo
ValueCountFrequency (%)
35
100.0%
Distinct406
Distinct (%)43.8%
Missing0
Missing (%)0.0%
Memory size7.4 KiB
2023-12-12T21:57:01.729543image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length41
Median length32
Mean length8.1294498
Min length1

Characters and Unicode

Total characters7536
Distinct characters274
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

Unique265 ?
Unique (%)28.6%

Sample

1st row이앤알컴퍼니
2nd row주식회사 대호리텍
3rd row(주)에코비트 에너지정세
4th row(주)삼명환경
5th row쌍용씨앤이(주)영월공장
ValueCountFrequency (%)
동양에코(주 38
 
3.8%
주)대풍환경 35
 
3.5%
주)경주산업개발 31
 
3.1%
주)네비엔 21
 
2.1%
영천사업소 20
 
2.0%
주)성호기업 17
 
1.7%
주)네비엔영천사업소 16
 
1.6%
한국에너지(주 15
 
1.5%
주)대호리텍 14
 
1.4%
주식회사 13
 
1.3%
Other values (402) 776
77.9%
2023-12-12T21:57:02.204326image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
847
 
11.2%
( 769
 
10.2%
) 768
 
10.2%
223
 
3.0%
215
 
2.9%
208
 
2.8%
194
 
2.6%
181
 
2.4%
144
 
1.9%
130
 
1.7%
Other values (264) 3857
51.2%

Most occurring categories

ValueCountFrequency (%)
Other Letter 5796
76.9%
Open Punctuation 769
 
10.2%
Close Punctuation 768
 
10.2%
Space Separator 108
 
1.4%
Uppercase Letter 43
 
0.6%
Connector Punctuation 38
 
0.5%
Math Symbol 4
 
0.1%
Other Punctuation 4
 
0.1%
Decimal Number 3
 
< 0.1%
Dash Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
847
 
14.6%
223
 
3.8%
215
 
3.7%
208
 
3.6%
194
 
3.3%
181
 
3.1%
144
 
2.5%
130
 
2.2%
114
 
2.0%
103
 
1.8%
Other values (241) 3437
59.3%
Uppercase Letter
ValueCountFrequency (%)
R 10
23.3%
S 8
18.6%
F 7
16.3%
N 5
11.6%
P 4
 
9.3%
G 2
 
4.7%
E 2
 
4.7%
C 1
 
2.3%
M 1
 
2.3%
K 1
 
2.3%
Other values (2) 2
 
4.7%
Other Punctuation
ValueCountFrequency (%)
/ 3
75.0%
? 1
 
25.0%
Decimal Number
ValueCountFrequency (%)
2 2
66.7%
0 1
33.3%
Open Punctuation
ValueCountFrequency (%)
( 769
100.0%
Close Punctuation
ValueCountFrequency (%)
) 768
100.0%
Space Separator
ValueCountFrequency (%)
108
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 38
100.0%
Math Symbol
ValueCountFrequency (%)
+ 4
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 2
100.0%
Other Symbol
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 5797
76.9%
Common 1696
 
22.5%
Latin 43
 
0.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
847
 
14.6%
223
 
3.8%
215
 
3.7%
208
 
3.6%
194
 
3.3%
181
 
3.1%
144
 
2.5%
130
 
2.2%
114
 
2.0%
103
 
1.8%
Other values (242) 3438
59.3%
Latin
ValueCountFrequency (%)
R 10
23.3%
S 8
18.6%
F 7
16.3%
N 5
11.6%
P 4
 
9.3%
G 2
 
4.7%
E 2
 
4.7%
C 1
 
2.3%
M 1
 
2.3%
K 1
 
2.3%
Other values (2) 2
 
4.7%
Common
ValueCountFrequency (%)
( 769
45.3%
) 768
45.3%
108
 
6.4%
_ 38
 
2.2%
+ 4
 
0.2%
/ 3
 
0.2%
2 2
 
0.1%
- 2
 
0.1%
? 1
 
0.1%
0 1
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 5796
76.9%
ASCII 1739
 
23.1%
None 1
 
< 0.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
847
 
14.6%
223
 
3.8%
215
 
3.7%
208
 
3.6%
194
 
3.3%
181
 
3.1%
144
 
2.5%
130
 
2.2%
114
 
2.0%
103
 
1.8%
Other values (241) 3437
59.3%
ASCII
ValueCountFrequency (%)
( 769
44.2%
) 768
44.2%
108
 
6.2%
_ 38
 
2.2%
R 10
 
0.6%
S 8
 
0.5%
F 7
 
0.4%
N 5
 
0.3%
P 4
 
0.2%
+ 4
 
0.2%
Other values (12) 18
 
1.0%
None
ValueCountFrequency (%)
1
100.0%
Distinct277
Distinct (%)29.9%
Missing0
Missing (%)0.0%
Memory size7.4 KiB
2023-12-12T21:57:02.572174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length35
Median length32
Mean length21.503776
Min length1

Characters and Unicode

Total characters19934
Distinct characters185
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique107 ?
Unique (%)11.5%

Sample

1st row경상북도 영천시 대창면 선진길 202
2nd row경상북도 영천시 한방로 188-10 (작산동)
3rd row경상북도 영천시 화산면 유성길 77
4th row경상북도 영천시 대창면 신당길 25-21
5th row경기도 성남시 수정구 위례서일로 18_ 2층 204호 (창곡동)
ValueCountFrequency (%)
경상북도 854
19.3%
영천시 854
19.3%
대창면 133
 
3.0%
금호읍 119
 
2.7%
북안면 97
 
2.2%
고경면 80
 
1.8%
임고면 69
 
1.6%
도남동 66
 
1.5%
오계공단길 47
 
1.1%
선진길 46
 
1.0%
Other values (401) 2066
46.6%
2023-12-12T21:57:03.025038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
3643
18.3%
1046
 
5.2%
977
 
4.9%
965
 
4.8%
904
 
4.5%
875
 
4.4%
874
 
4.4%
864
 
4.3%
1 630
 
3.2%
560
 
2.8%
Other values (175) 8596
43.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 12232
61.4%
Space Separator 3643
 
18.3%
Decimal Number 3000
 
15.0%
Dash Punctuation 368
 
1.8%
Close Punctuation 319
 
1.6%
Open Punctuation 319
 
1.6%
Connector Punctuation 48
 
0.2%
Other Symbol 5
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1046
 
8.6%
977
 
8.0%
965
 
7.9%
904
 
7.4%
875
 
7.2%
874
 
7.1%
864
 
7.1%
560
 
4.6%
487
 
4.0%
305
 
2.5%
Other values (159) 4375
35.8%
Decimal Number
ValueCountFrequency (%)
1 630
21.0%
2 422
14.1%
4 323
10.8%
3 323
10.8%
5 258
8.6%
6 247
 
8.2%
8 228
 
7.6%
7 190
 
6.3%
9 190
 
6.3%
0 189
 
6.3%
Space Separator
ValueCountFrequency (%)
3643
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 368
100.0%
Close Punctuation
ValueCountFrequency (%)
) 319
100.0%
Open Punctuation
ValueCountFrequency (%)
( 319
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 48
100.0%
Other Symbol
ValueCountFrequency (%)
5
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 12237
61.4%
Common 7697
38.6%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1046
 
8.5%
977
 
8.0%
965
 
7.9%
904
 
7.4%
875
 
7.2%
874
 
7.1%
864
 
7.1%
560
 
4.6%
487
 
4.0%
305
 
2.5%
Other values (160) 4380
35.8%
Common
ValueCountFrequency (%)
3643
47.3%
1 630
 
8.2%
2 422
 
5.5%
- 368
 
4.8%
4 323
 
4.2%
3 323
 
4.2%
) 319
 
4.1%
( 319
 
4.1%
5 258
 
3.4%
6 247
 
3.2%
Other values (5) 845
 
11.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 12232
61.4%
ASCII 7697
38.6%
None 5
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
3643
47.3%
1 630
 
8.2%
2 422
 
5.5%
- 368
 
4.8%
4 323
 
4.2%
3 323
 
4.2%
) 319
 
4.1%
( 319
 
4.1%
5 258
 
3.4%
6 247
 
3.2%
Other values (5) 845
 
11.0%
Hangul
ValueCountFrequency (%)
1046
 
8.6%
977
 
8.0%
965
 
7.9%
904
 
7.4%
875
 
7.2%
874
 
7.1%
864
 
7.1%
560
 
4.6%
487
 
4.0%
305
 
2.5%
Other values (159) 4375
35.8%
None
ValueCountFrequency (%)
5
100.0%
Distinct297
Distinct (%)32.0%
Missing0
Missing (%)0.0%
Memory size7.4 KiB
2023-12-12T21:57:03.385858image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length49
Median length31
Mean length20.389428
Min length1

Characters and Unicode

Total characters18901
Distinct characters142
Distinct categories8 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique118 ?
Unique (%)12.7%

Sample

1st row경상북도 영천시 대창면 사리리 490-1
2nd row경상북도 영천시 작산동 238
3rd row경상북도 영천시 화산면 유성리 808
4th row경상북도 영천시 대창면 대창리 680-6
5th row경기도 성남시 수정구 창곡동
ValueCountFrequency (%)
경상북도 871
20.4%
영천시 871
20.4%
대창면 133
 
3.1%
금호읍 125
 
2.9%
북안면 89
 
2.1%
도남동 76
 
1.8%
고경면 73
 
1.7%
사리리 73
 
1.7%
임고면 64
 
1.5%
화산면 48
 
1.1%
Other values (415) 1842
43.2%
2023-12-12T21:57:03.877702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4312
22.8%
1000
 
5.3%
969
 
5.1%
963
 
5.1%
911
 
4.8%
887
 
4.7%
881
 
4.7%
874
 
4.6%
713
 
3.8%
1 585
 
3.1%
Other values (132) 6806
36.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 10884
57.6%
Space Separator 4312
 
22.8%
Decimal Number 3097
 
16.4%
Dash Punctuation 529
 
2.8%
Connector Punctuation 33
 
0.2%
Close Punctuation 22
 
0.1%
Open Punctuation 22
 
0.1%
Other Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
1000
 
9.2%
969
 
8.9%
963
 
8.8%
911
 
8.4%
887
 
8.1%
881
 
8.1%
874
 
8.0%
713
 
6.6%
472
 
4.3%
285
 
2.6%
Other values (116) 2929
26.9%
Decimal Number
ValueCountFrequency (%)
1 585
18.9%
4 435
14.0%
2 388
12.5%
6 343
11.1%
3 255
8.2%
5 252
8.1%
0 245
7.9%
7 218
 
7.0%
8 196
 
6.3%
9 180
 
5.8%
Space Separator
ValueCountFrequency (%)
4312
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 529
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 33
100.0%
Close Punctuation
ValueCountFrequency (%)
) 22
100.0%
Open Punctuation
ValueCountFrequency (%)
( 22
100.0%
Other Punctuation
ValueCountFrequency (%)
· 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 10884
57.6%
Common 8017
42.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
1000
 
9.2%
969
 
8.9%
963
 
8.8%
911
 
8.4%
887
 
8.1%
881
 
8.1%
874
 
8.0%
713
 
6.6%
472
 
4.3%
285
 
2.6%
Other values (116) 2929
26.9%
Common
ValueCountFrequency (%)
4312
53.8%
1 585
 
7.3%
- 529
 
6.6%
4 435
 
5.4%
2 388
 
4.8%
6 343
 
4.3%
3 255
 
3.2%
5 252
 
3.1%
0 245
 
3.1%
7 218
 
2.7%
Other values (6) 455
 
5.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 10884
57.6%
ASCII 8015
42.4%
None 2
 
< 0.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4312
53.8%
1 585
 
7.3%
- 529
 
6.6%
4 435
 
5.4%
2 388
 
4.8%
6 343
 
4.3%
3 255
 
3.2%
5 252
 
3.1%
0 245
 
3.1%
7 218
 
2.7%
Other values (5) 453
 
5.7%
Hangul
ValueCountFrequency (%)
1000
 
9.2%
969
 
8.9%
963
 
8.8%
911
 
8.4%
887
 
8.1%
881
 
8.1%
874
 
8.0%
713
 
6.6%
472
 
4.3%
285
 
2.6%
Other values (116) 2929
26.9%
None
ValueCountFrequency (%)
· 2
100.0%

위도
Real number (ℝ)

MISSING 

Distinct268
Distinct (%)31.1%
Missing64
Missing (%)6.9%
Infinite0
Infinite (%)0.0%
Mean35.963425
Minimum35.859309
Maximum37.573506
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size8.3 KiB
2023-12-12T21:57:04.006876image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.859309
5-th percentile35.872565
Q135.913038
median35.931286
Q335.995076
95-th percentile36.047942
Maximum37.573506
Range1.7141977
Interquartile range (IQR)0.08203796

Descriptive statistics

Standard deviation0.16467905
Coefficient of variation (CV)0.0045790703
Kurtosis72.309672
Mean35.963425
Median Absolute Deviation (MAD)0.04793256
Skewness8.1227006
Sum31036.436
Variance0.027119191
MonotonicityNot monotonic
2023-12-12T21:57:04.142116image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35.88335354 28
 
3.0%
36.00533383 25
 
2.7%
35.86756485 20
 
2.2%
35.92854087 17
 
1.8%
35.93662888 16
 
1.7%
35.9312861 13
 
1.4%
35.91731 13
 
1.4%
35.91479931 13
 
1.4%
35.91833234 11
 
1.2%
35.91575968 11
 
1.2%
Other values (258) 696
75.1%
(Missing) 64
 
6.9%
ValueCountFrequency (%)
35.85930879 1
 
0.1%
35.86173707 2
 
0.2%
35.86296876 3
 
0.3%
35.8642166 3
 
0.3%
35.86698737 5
 
0.5%
35.86756485 20
2.2%
35.86958446 7
 
0.8%
35.87250534 3
 
0.3%
35.87310621 3
 
0.3%
35.87314592 3
 
0.3%
ValueCountFrequency (%)
37.57350645 1
 
0.1%
37.46510361 8
0.9%
36.11063493 2
 
0.2%
36.08278579 1
 
0.1%
36.08166963 1
 
0.1%
36.0756484 5
0.5%
36.07179487 2
 
0.2%
36.05736672 3
 
0.3%
36.05664229 1
 
0.1%
36.05656424 1
 
0.1%

경도
Real number (ℝ)

MISSING 

Distinct268
Distinct (%)31.1%
Missing64
Missing (%)6.9%
Infinite0
Infinite (%)0.0%
Mean128.91512
Minimum126.97899
Maximum129.11002
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size8.3 KiB
2023-12-12T21:57:04.297476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum126.97899
5-th percentile128.83533
Q1128.88487
median128.93305
Q3128.9663
95-th percentile129.03508
Maximum129.11002
Range2.1310256
Interquartile range (IQR)0.0814236

Descriptive statistics

Standard deviation0.19515761
Coefficient of variation (CV)0.0015138457
Kurtosis72.634086
Mean128.91512
Median Absolute Deviation (MAD)0.0436715
Skewness-8.1171239
Sum111253.75
Variance0.038086491
MonotonicityNot monotonic
2023-12-12T21:57:04.447702image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
129.0232178 28
 
3.0%
128.963343 25
 
2.7%
128.8907918 20
 
2.2%
128.9376531 17
 
1.8%
128.9767264 16
 
1.7%
129.0292882 13
 
1.4%
128.8794834 13
 
1.4%
128.9509856 13
 
1.4%
128.8911621 11
 
1.2%
128.892906 11
 
1.2%
Other values (258) 696
75.1%
(Missing) 64
 
6.9%
ValueCountFrequency (%)
126.9789896 1
 
0.1%
127.1378315 8
0.9%
128.7735519 1
 
0.1%
128.7902903 1
 
0.1%
128.7909484 2
 
0.2%
128.7937488 2
 
0.2%
128.7953098 6
0.6%
128.7988761 1
 
0.1%
128.8023189 3
 
0.3%
128.8110269 2
 
0.2%
ValueCountFrequency (%)
129.1100152 2
 
0.2%
129.1099842 1
 
0.1%
129.1090562 3
 
0.3%
129.0970617 9
1.0%
129.0919497 1
 
0.1%
129.0865082 1
 
0.1%
129.0847121 10
1.1%
129.0578009 2
 
0.2%
129.0526649 1
 
0.1%
129.0519496 3
 
0.3%

등록기준일
Categorical

CONSTANT 

Distinct1
Distinct (%)0.1%
Missing0
Missing (%)0.0%
Memory size7.4 KiB
2023-10-11
927 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2023-10-11
2nd row2023-10-11
3rd row2023-10-11
4th row2023-10-11
5th row2023-10-11

Common Values

ValueCountFrequency (%)
2023-10-11 927
100.0%

Length

2023-12-12T21:57:04.568038image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T21:57:04.655288image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2023-10-11 927
100.0%

Interactions

2023-12-12T21:56:59.348973image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:56:59.170758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:56:59.435075image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T21:56:59.262895image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T21:57:04.738255image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
폐기물 종류위도경도
폐기물 종류1.0000.5530.531
위도0.5531.0000.943
경도0.5310.9431.000
2023-12-12T21:57:04.859420image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도
위도1.0000.148
경도0.1481.000

Missing values

2023-12-12T21:56:59.540067image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T21:56:59.650078image/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.
2023-12-12T21:56:59.740190image/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

배출구분상호폐기물 종류처리업소명사업장도로명주소사업장지번주소위도경도등록기준일
0일반(주)제일윈도텍스폐합성수지류(폐염화비닐수지류는 제외한다)이앤알컴퍼니경상북도 영천시 대창면 선진길 202경상북도 영천시 대창면 사리리 490-135.88224128.8708992023-10-11
1일반삼일특장폐합성수지류(폐염화비닐수지류는 제외한다)주식회사 대호리텍경상북도 영천시 한방로 188-10 (작산동)경상북도 영천시 작산동 23835.940041128.9490942023-10-11
2일반(주)도투락폐합성수지류(폐염화비닐수지류는 제외한다)(주)에코비트 에너지정세경상북도 영천시 화산면 유성길 77경상북도 영천시 화산면 유성리 80836.024455128.8571532023-10-11
3일반(주)에이치인더스트리목재가공공장 부산물(접착제_ 페인트_ 기름_ 콘크리트 등의 물질이 사용된 목재부산물 및 분진을 말한다)(주)삼명환경경상북도 영천시 대창면 신당길 25-21경상북도 영천시 대창면 대창리 680-635.879426128.8919772023-10-11
4일반(주)에코비트그 밖의 공정오니쌍용씨앤이(주)영월공장경기도 성남시 수정구 위례서일로 18_ 2층 204호 (창곡동)경기도 성남시 수정구 창곡동37.465104127.1378322023-10-11
5일반(주)에코비트그 밖의 공정오니쌍용씨앤이(주)영월공장경기도 성남시 수정구 위례서일로 18_ 2층 204호 (창곡동)경기도 성남시 수정구 창곡동37.465104127.1378322023-10-11
6일반(주)에코비트그 밖의 공정오니쌍용씨앤이(주)영월공장경기도 성남시 수정구 위례서일로 18_ 2층 204호 (창곡동)경기도 성남시 수정구 창곡동37.465104127.1378322023-10-11
7일반(주)에코비트그 밖의 공정오니쌍용씨앤이(주)영월공장경기도 성남시 수정구 위례서일로 18_ 2층 204호 (창곡동)경기도 성남시 수정구 창곡동37.465104127.1378322023-10-11
8일반(주)에코비트그 밖의 공정오니쌍용씨앤이(주)동해공장경기도 성남시 수정구 위례서일로 18_ 2층 204호 (창곡동)경기도 성남시 수정구 창곡동37.465104127.1378322023-10-11
9일반(주)에코비트그 밖의 공정오니쌍용씨앤이(주)동해공장경기도 성남시 수정구 위례서일로 18_ 2층 204호 (창곡동)경기도 성남시 수정구 창곡동37.465104127.1378322023-10-11
배출구분상호폐기물 종류처리업소명사업장도로명주소사업장지번주소위도경도등록기준일
917일반(주)신명특수강화학점결폐주물사(주)케이엠그린구미지점경상북도 영천시 대창면 금박로 908경상북도 영천시 대창면 사리리 200-435.873425128.880782023-10-11
918일반(주)신명특수강화학점결폐주물사(주)대풍환경경상북도 영천시 대창면 금박로 908경상북도 영천시 대창면 사리리 200-435.873425128.880782023-10-11
919일반평산금속폐수처리오니(주)동양에코경상북도 영천시 도남동 210-2<NA><NA>2023-10-11
920일반평산금속폐합성고무류(주)네비엔영천사업소경상북도 영천시 도남동 210-2<NA><NA>2023-10-11
921일반평산금속그 밖의 공정오니화진금속공업(주)경상북도 영천시 도남동 210-2<NA><NA>2023-10-11
922일반(주)대열레미콘폐콘크리트하림개발경상북도 영천시 북안면 유하큰길 48경상북도 영천시 북안면 유하리 56-135.935141128.9756552023-10-11
923일반육군제3887부대폐가구류_ 폐도장목_ 폐목재포장재_ 폐전선드럼(원목상태의 깨끗한 목재를 말한다)지씨테크(주)경산공장경상북도 영천시 주남3길 61 (금노동_사서함 2호)경상북도 영천시 금노동 456 사서함 2호35.953049128.9362472023-10-11
924일반육군제3887부대폐가구류_ 폐도장목_ 폐목재포장재_ 폐전선드럼(원목상태의 깨끗한 목재를 말한다)미래자원(주)경상북도 영천시 주남3길 61 (금노동_사서함 2호)경상북도 영천시 금노동 456 사서함 2호35.953049128.9362472023-10-11
925일반육군제3887부대그 밖의 폐기물(주)네비엔영천사업소경상북도 영천시 주남3길 61 (금노동_사서함 2호)경상북도 영천시 금노동 456 사서함 2호35.953049128.9362472023-10-11
926일반육군제3887부대폐합성수지류(폐염화비닐수지류는 제외한다)(주)에코파크경상북도 영천시 주남3길 61 (금노동_사서함 2호)경상북도 영천시 금노동 456 사서함 2호35.953049128.9362472023-10-11

Duplicate rows

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배출구분상호폐기물 종류처리업소명사업장도로명주소사업장지번주소위도경도등록기준일# duplicates
15일반녹색자원(주)동영천지점폐합성수지류(폐염화비닐수지류는 제외한다)(주)삼표시멘트삼척공장경상북도 영천시 임고면 매호운천길 108경상북도 영천시 임고면 매호리 86436.005334128.9633432023-10-115
8일반(주)에코비트그 밖의 공정오니쌍용씨앤이(주)동해공장경기도 성남시 수정구 위례서일로 18_ 2층 204호 (창곡동)경기도 성남시 수정구 창곡동37.465104127.1378322023-10-114
9일반(주)에코비트그 밖의 공정오니쌍용씨앤이(주)영월공장경기도 성남시 수정구 위례서일로 18_ 2층 204호 (창곡동)경기도 성남시 수정구 창곡동37.465104127.1378322023-10-114
18일반녹색자원(주)동영천지점폐합성수지류(폐염화비닐수지류는 제외한다)모다스경상북도 영천시 임고면 매호운천길 108경상북도 영천시 임고면 매호리 86436.005334128.9633432023-10-114
25일반이앤알컴퍼니건설폐토석정도개발(주)경상북도 영천시 대창면 용대로 954경상북도 영천시 대창면 구지리 167-735.867565128.8907922023-10-114
27일반이앤알컴퍼니폐토사구슬(주)경상북도 영천시 대창면 용대로 954경상북도 영천시 대창면 구지리 167-735.867565128.8907922023-10-114
17일반녹색자원(주)동영천지점폐합성수지류(폐염화비닐수지류는 제외한다)디엠이티에스(주)경상북도 영천시 임고면 매호운천길 108경상북도 영천시 임고면 매호리 86436.005334128.9633432023-10-113
36일반주식회사 오엠시스템그 밖의 폐목재류강철환경경상북도 영천시 대창면 선진길 121-20경상북도 영천시 대창면 사리리 320-735.879143128.8766132023-10-113
41일반한남환경(주)폐합성수지류(폐염화비닐수지류는 제외한다)모다스경상북도 영천시 금호읍 금창로 204-48경상북도 영천시 금호읍 삼호리 201-235.91731128.8794832023-10-113
0일반(주)다이엑스그 밖의 분진(주)서진인바이러테크경상북도 영천시 북안면 돌할매로 284-14경상북도 영천시 북안면 자포리 2735.931286129.0292882023-10-112