Overview

Dataset statistics

Number of variables13
Number of observations108
Missing cells454
Missing cells (%)32.3%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory11.1 KiB
Average record size in memory105.2 B

Variable types

Text11
Unsupported2

Dataset

Description인천광역시 건설폐기물처리업체 현황에 관한 데이터로 수집운반과 중간처리 업체가 있습니다. 연번, 시도, 시군구, 업체명, 대표자, 소재지, 영업대상 건설폐기물, 보유차량대수(대), 전화번호, 2021년 수집 운반량, 허가승인일, 반납 신고일, 비고의 목록을 제공합니다.
Author인천광역시
URLhttps://data.incheon.go.kr/findData/publicDataDetail?dataId=15121820&srcSe=7661IVAWM27C61E190

Alerts

Unnamed: 11 has constant value ""Constant
Unnamed: 12 has constant value ""Constant
Unnamed: 1 has 106 (98.1%) missing valuesMissing
Unnamed: 2 has 96 (88.9%) missing valuesMissing
Unnamed: 3 has 3 (2.8%) missing valuesMissing
Unnamed: 4 has 3 (2.8%) missing valuesMissing
Unnamed: 5 has 3 (2.8%) missing valuesMissing
Unnamed: 6 has 3 (2.8%) missing valuesMissing
Unnamed: 7 has 2 (1.9%) missing valuesMissing
Unnamed: 8 has 18 (16.7%) missing valuesMissing
Unnamed: 9 has 2 (1.9%) missing valuesMissing
Unnamed: 10 has 3 (2.8%) missing valuesMissing
Unnamed: 11 has 107 (99.1%) missing valuesMissing
Unnamed: 12 has 107 (99.1%) missing valuesMissing
Unnamed: 7 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 9 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-01-28 08:43:54.753862
Analysis finished2024-01-28 08:43:55.667158
Duration0.91 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

3. 폐기물 수집·운반업체 현황
Text

Distinct107
Distinct (%)100.0%
Missing1
Missing (%)0.9%
Memory size996.0 B
2024-01-28T17:43:56.122757image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length19
Median length2
Mean length2.1495327
Min length1

Characters and Unicode

Total characters230
Distinct characters31
Distinct categories4 ?
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 (%)100.0%

Sample

1st row나. 건설폐기물 수집·운반업체 현황
2nd row연번
3rd row104개소
4th row1
5th row2
ValueCountFrequency (%)
나 1
 
0.9%
63 1
 
0.9%
75 1
 
0.9%
74 1
 
0.9%
73 1
 
0.9%
72 1
 
0.9%
71 1
 
0.9%
70 1
 
0.9%
69 1
 
0.9%
68 1
 
0.9%
Other values (100) 100
90.9%
2024-01-28T17:43:56.490836image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
1 27
11.7%
4 22
9.6%
3 21
9.1%
2 21
9.1%
9 20
8.7%
8 20
8.7%
7 20
8.7%
6 20
8.7%
5 20
8.7%
0 16
7.0%
Other values (21) 23
10.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 207
90.0%
Other Letter 18
 
7.8%
Space Separator 3
 
1.3%
Other Punctuation 2
 
0.9%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
황 1
 
5.6%
소 1
 
5.6%
개 1
 
5.6%
번 1
 
5.6%
연 1
 
5.6%
나 1
 
5.6%
체 1
 
5.6%
업 1
 
5.6%
반 1
 
5.6%
운 1
 
5.6%
Other values (8) 8
44.4%
Decimal Number
ValueCountFrequency (%)
1 27
13.0%
4 22
10.6%
3 21
10.1%
2 21
10.1%
9 20
9.7%
8 20
9.7%
7 20
9.7%
6 20
9.7%
5 20
9.7%
0 16
7.7%
Other Punctuation
ValueCountFrequency (%)
. 1
50.0%
· 1
50.0%
Space Separator
ValueCountFrequency (%)
3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 212
92.2%
Hangul 18
 
7.8%

Most frequent character per script

Hangul
ValueCountFrequency (%)
황 1
 
5.6%
소 1
 
5.6%
개 1
 
5.6%
번 1
 
5.6%
연 1
 
5.6%
나 1
 
5.6%
체 1
 
5.6%
업 1
 
5.6%
반 1
 
5.6%
운 1
 
5.6%
Other values (8) 8
44.4%
Common
ValueCountFrequency (%)
1 27
12.7%
4 22
10.4%
3 21
9.9%
2 21
9.9%
9 20
9.4%
8 20
9.4%
7 20
9.4%
6 20
9.4%
5 20
9.4%
0 16
7.5%
Other values (3) 5
 
2.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 211
91.7%
Hangul 18
 
7.8%
None 1
 
0.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
1 27
12.8%
4 22
10.4%
3 21
10.0%
2 21
10.0%
9 20
9.5%
8 20
9.5%
7 20
9.5%
6 20
9.5%
5 20
9.5%
0 16
7.6%
Other values (2) 4
 
1.9%
Hangul
ValueCountFrequency (%)
황 1
 
5.6%
소 1
 
5.6%
개 1
 
5.6%
번 1
 
5.6%
연 1
 
5.6%
나 1
 
5.6%
체 1
 
5.6%
업 1
 
5.6%
반 1
 
5.6%
운 1
 
5.6%
Other values (8) 8
44.4%
None
ValueCountFrequency (%)
· 1
100.0%

Unnamed: 1
Text

MISSING 

Distinct2
Distinct (%)100.0%
Missing106
Missing (%)98.1%
Memory size996.0 B
2024-01-28T17:43:56.614321image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters4
Distinct characters4
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique2 ?
Unique (%)100.0%

Sample

1st row시도
2nd row인천
ValueCountFrequency (%)
시도 1
50.0%
인천 1
50.0%
2024-01-28T17:43:56.812325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
시 1
25.0%
도 1
25.0%
인 1
25.0%
천 1
25.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
시 1
25.0%
도 1
25.0%
인 1
25.0%
천 1
25.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
시 1
25.0%
도 1
25.0%
인 1
25.0%
천 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
시 1
25.0%
도 1
25.0%
인 1
25.0%
천 1
25.0%

Unnamed: 2
Text

MISSING 

Distinct12
Distinct (%)100.0%
Missing96
Missing (%)88.9%
Memory size996.0 B
2024-01-28T17:43:56.953701image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length4
Median length3
Mean length2.75
Min length2

Characters and Unicode

Total characters33
Distinct characters21
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique12 ?
Unique (%)100.0%

Sample

1st row시군구
2nd row소계
3rd row중구
4th row동구
5th row미추홀구
ValueCountFrequency (%)
시군구 1
8.3%
소계 1
8.3%
중구 1
8.3%
동구 1
8.3%
미추홀구 1
8.3%
연수구 1
8.3%
남동구 1
8.3%
부평구 1
8.3%
계양구 1
8.3%
서구 1
8.3%
Other values (2) 2
16.7%
2024-01-28T17:43:57.209773image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
구 9
27.3%
군 3
 
9.1%
계 2
 
6.1%
동 2
 
6.1%
시 1
 
3.0%
부 1
 
3.0%
옹 1
 
3.0%
화 1
 
3.0%
강 1
 
3.0%
서 1
 
3.0%
Other values (11) 11
33.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 33
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
구 9
27.3%
군 3
 
9.1%
계 2
 
6.1%
동 2
 
6.1%
시 1
 
3.0%
부 1
 
3.0%
옹 1
 
3.0%
화 1
 
3.0%
강 1
 
3.0%
서 1
 
3.0%
Other values (11) 11
33.3%

Most occurring scripts

ValueCountFrequency (%)
Hangul 33
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
구 9
27.3%
군 3
 
9.1%
계 2
 
6.1%
동 2
 
6.1%
시 1
 
3.0%
부 1
 
3.0%
옹 1
 
3.0%
화 1
 
3.0%
강 1
 
3.0%
서 1
 
3.0%
Other values (11) 11
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 33
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
구 9
27.3%
군 3
 
9.1%
계 2
 
6.1%
동 2
 
6.1%
시 1
 
3.0%
부 1
 
3.0%
옹 1
 
3.0%
화 1
 
3.0%
강 1
 
3.0%
서 1
 
3.0%
Other values (11) 11
33.3%

Unnamed: 3
Text

MISSING 

Distinct105
Distinct (%)100.0%
Missing3
Missing (%)2.8%
Memory size996.0 B
2024-01-28T17:43:57.431894image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length27
Median length21
Mean length8.5904762
Min length3

Characters and Unicode

Total characters902
Distinct characters179
Distinct categories10 ?
Distinct scripts3 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique105 ?
Unique (%)100.0%

Sample

1st row업체명
2nd row(주)고려환경
3rd row주식회사 동운
4th row인성코퍼레이션(주)
5th row길튼개발주식회사
ValueCountFrequency (%)
주식회사 11
 
8.7%
정진이엔씨(주 1
 
0.8%
주)화승산업개발 1
 
0.8%
한국포장건설주식회사 1
 
0.8%
주)청화공영(지점 1
 
0.8%
ltd 1
 
0.8%
co 1
 
0.8%
yido 1
 
0.8%
주)이도 1
 
0.8%
주)정암건설 1
 
0.8%
Other values (107) 107
84.3%
2024-01-28T17:43:57.772006image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 90
 
10.0%
( 82
 
9.1%
) 82
 
9.1%
경 29
 
3.2%
환 29
 
3.2%
업 22
 
2.4%
22
 
2.4%
이 22
 
2.4%
발 20
 
2.2%
개 20
 
2.2%
Other values (169) 484
53.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 682
75.6%
Open Punctuation 82
 
9.1%
Close Punctuation 82
 
9.1%
Space Separator 22
 
2.4%
Decimal Number 11
 
1.2%
Lowercase Letter 8
 
0.9%
Uppercase Letter 7
 
0.8%
Dash Punctuation 3
 
0.3%
Connector Punctuation 3
 
0.3%
Other Punctuation 2
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 90
 
13.2%
경 29
 
4.3%
환 29
 
4.3%
업 22
 
3.2%
이 22
 
3.2%
발 20
 
2.9%
개 20
 
2.9%
사 19
 
2.8%
건 17
 
2.5%
식 16
 
2.3%
Other values (145) 398
58.4%
Uppercase Letter
ValueCountFrequency (%)
S 2
28.6%
D 1
14.3%
L 1
14.3%
C 1
14.3%
Y 1
14.3%
E 1
14.3%
Lowercase Letter
ValueCountFrequency (%)
o 2
25.0%
d 2
25.0%
t 1
12.5%
i 1
12.5%
m 1
12.5%
c 1
12.5%
Decimal Number
ValueCountFrequency (%)
2 5
45.5%
0 3
27.3%
3 1
 
9.1%
1 1
 
9.1%
6 1
 
9.1%
Other Punctuation
ValueCountFrequency (%)
, 1
50.0%
. 1
50.0%
Open Punctuation
ValueCountFrequency (%)
( 82
100.0%
Close Punctuation
ValueCountFrequency (%)
) 82
100.0%
Space Separator
ValueCountFrequency (%)
22
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 3
100.0%
Connector Punctuation
ValueCountFrequency (%)
_ 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 682
75.6%
Common 205
 
22.7%
Latin 15
 
1.7%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 90
 
13.2%
경 29
 
4.3%
환 29
 
4.3%
업 22
 
3.2%
이 22
 
3.2%
발 20
 
2.9%
개 20
 
2.9%
사 19
 
2.8%
건 17
 
2.5%
식 16
 
2.3%
Other values (145) 398
58.4%
Common
ValueCountFrequency (%)
( 82
40.0%
) 82
40.0%
22
 
10.7%
2 5
 
2.4%
- 3
 
1.5%
0 3
 
1.5%
_ 3
 
1.5%
3 1
 
0.5%
, 1
 
0.5%
. 1
 
0.5%
Other values (2) 2
 
1.0%
Latin
ValueCountFrequency (%)
S 2
13.3%
o 2
13.3%
d 2
13.3%
D 1
6.7%
t 1
6.7%
L 1
6.7%
C 1
6.7%
i 1
6.7%
Y 1
6.7%
E 1
6.7%
Other values (2) 2
13.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 682
75.6%
ASCII 220
 
24.4%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 90
 
13.2%
경 29
 
4.3%
환 29
 
4.3%
업 22
 
3.2%
이 22
 
3.2%
발 20
 
2.9%
개 20
 
2.9%
사 19
 
2.8%
건 17
 
2.5%
식 16
 
2.3%
Other values (145) 398
58.4%
ASCII
ValueCountFrequency (%)
( 82
37.3%
) 82
37.3%
22
 
10.0%
2 5
 
2.3%
- 3
 
1.4%
0 3
 
1.4%
_ 3
 
1.4%
S 2
 
0.9%
o 2
 
0.9%
d 2
 
0.9%
Other values (14) 14
 
6.4%

Unnamed: 4
Text

MISSING 

Distinct104
Distinct (%)99.0%
Missing3
Missing (%)2.8%
Memory size996.0 B
2024-01-28T17:43:58.022449image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length3
Mean length3.0666667
Min length2

Characters and Unicode

Total characters322
Distinct characters113
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique103 ?
Unique (%)98.1%

Sample

1st row대표자
2nd row한순일
3rd row양우용
4th row추성호
5th row김혜경
ValueCountFrequency (%)
대표이사 2
 
1.9%
김갑환 1
 
0.9%
금기동 1
 
0.9%
최일영 1
 
0.9%
남기현 1
 
0.9%
강석봉 1
 
0.9%
신명학 1
 
0.9%
임희곤 1
 
0.9%
최경용 1
 
0.9%
한민구 1
 
0.9%
Other values (96) 96
89.7%
2024-01-28T17:43:58.390363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
이 23
 
7.1%
김 21
 
6.5%
영 12
 
3.7%
최 10
 
3.1%
진 9
 
2.8%
경 9
 
2.8%
성 8
 
2.5%
용 7
 
2.2%
재 7
 
2.2%
현 7
 
2.2%
Other values (103) 209
64.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 319
99.1%
Space Separator 2
 
0.6%
Other Punctuation 1
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
이 23
 
7.2%
김 21
 
6.6%
영 12
 
3.8%
최 10
 
3.1%
진 9
 
2.8%
경 9
 
2.8%
성 8
 
2.5%
용 7
 
2.2%
재 7
 
2.2%
현 7
 
2.2%
Other values (101) 206
64.6%
Space Separator
ValueCountFrequency (%)
2
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 319
99.1%
Common 3
 
0.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
이 23
 
7.2%
김 21
 
6.6%
영 12
 
3.8%
최 10
 
3.1%
진 9
 
2.8%
경 9
 
2.8%
성 8
 
2.5%
용 7
 
2.2%
재 7
 
2.2%
현 7
 
2.2%
Other values (101) 206
64.6%
Common
ValueCountFrequency (%)
2
66.7%
, 1
33.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 319
99.1%
ASCII 3
 
0.9%

Most frequent character per block

Hangul
ValueCountFrequency (%)
이 23
 
7.2%
김 21
 
6.6%
영 12
 
3.8%
최 10
 
3.1%
진 9
 
2.8%
경 9
 
2.8%
성 8
 
2.5%
용 7
 
2.2%
재 7
 
2.2%
현 7
 
2.2%
Other values (101) 206
64.6%
ASCII
ValueCountFrequency (%)
2
66.7%
, 1
33.3%

Unnamed: 5
Text

MISSING 

Distinct105
Distinct (%)100.0%
Missing3
Missing (%)2.8%
Memory size996.0 B
2024-01-28T17:43:58.695375image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length47
Median length37
Mean length30.742857
Min length3

Characters and Unicode

Total characters3228
Distinct characters222
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

Unique105 ?
Unique (%)100.0%

Sample

1st row소재지
2nd row인천광역시 중구 도원로 61 (유동)
3rd row인천광역시 중구 서해대로262번길 4 삼신빌딩202호 (신흥동3가)
4th row인천광역시 중구 서해대로93번길 14-1 , 3층 (항동7가)
5th row인천광역시 중구 자유공원로 22 (전동) 3층
ValueCountFrequency (%)
인천광역시 104
 
17.1%
서구 31
 
5.1%
계양구 16
 
2.6%
중구 13
 
2.1%
남동구 12
 
2.0%
부평구 11
 
1.8%
8
 
1.3%
동구 6
 
1.0%
오류동 6
 
1.0%
3층 6
 
1.0%
Other values (308) 396
65.0%
2024-01-28T17:43:59.114139image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
604
 
18.7%
동 133
 
4.1%
천 114
 
3.5%
인 109
 
3.4%
시 107
 
3.3%
역 105
 
3.3%
광 104
 
3.2%
구 103
 
3.2%
1 90
 
2.8%
2 84
 
2.6%
Other values (212) 1675
51.9%

Most occurring categories

ValueCountFrequency (%)
Other Letter 1811
56.1%
Space Separator 604
 
18.7%
Decimal Number 565
 
17.5%
Close Punctuation 79
 
2.4%
Open Punctuation 79
 
2.4%
Other Punctuation 47
 
1.5%
Dash Punctuation 38
 
1.2%
Uppercase Letter 5
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 133
 
7.3%
천 114
 
6.3%
인 109
 
6.0%
시 107
 
5.9%
역 105
 
5.8%
광 104
 
5.7%
구 103
 
5.7%
로 81
 
4.5%
호 42
 
2.3%
서 41
 
2.3%
Other values (190) 872
48.2%
Decimal Number
ValueCountFrequency (%)
1 90
15.9%
2 84
14.9%
0 75
13.3%
3 74
13.1%
4 50
8.8%
5 46
8.1%
7 46
8.1%
6 36
 
6.4%
8 35
 
6.2%
9 29
 
5.1%
Uppercase Letter
ValueCountFrequency (%)
D 1
20.0%
M 1
20.0%
A 1
20.0%
B 1
20.0%
F 1
20.0%
Other Punctuation
ValueCountFrequency (%)
, 44
93.6%
. 2
 
4.3%
/ 1
 
2.1%
Space Separator
ValueCountFrequency (%)
604
100.0%
Close Punctuation
ValueCountFrequency (%)
) 79
100.0%
Open Punctuation
ValueCountFrequency (%)
( 79
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 38
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 1811
56.1%
Common 1412
43.7%
Latin 5
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 133
 
7.3%
천 114
 
6.3%
인 109
 
6.0%
시 107
 
5.9%
역 105
 
5.8%
광 104
 
5.7%
구 103
 
5.7%
로 81
 
4.5%
호 42
 
2.3%
서 41
 
2.3%
Other values (190) 872
48.2%
Common
ValueCountFrequency (%)
604
42.8%
1 90
 
6.4%
2 84
 
5.9%
) 79
 
5.6%
( 79
 
5.6%
0 75
 
5.3%
3 74
 
5.2%
4 50
 
3.5%
5 46
 
3.3%
7 46
 
3.3%
Other values (7) 185
 
13.1%
Latin
ValueCountFrequency (%)
D 1
20.0%
M 1
20.0%
A 1
20.0%
B 1
20.0%
F 1
20.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 1811
56.1%
ASCII 1417
43.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
604
42.6%
1 90
 
6.4%
2 84
 
5.9%
) 79
 
5.6%
( 79
 
5.6%
0 75
 
5.3%
3 74
 
5.2%
4 50
 
3.5%
5 46
 
3.2%
7 46
 
3.2%
Other values (12) 190
 
13.4%
Hangul
ValueCountFrequency (%)
동 133
 
7.3%
천 114
 
6.3%
인 109
 
6.0%
시 107
 
5.9%
역 105
 
5.8%
광 104
 
5.7%
구 103
 
5.7%
로 81
 
4.5%
호 42
 
2.3%
서 41
 
2.3%
Other values (190) 872
48.2%

Unnamed: 6
Text

MISSING 

Distinct58
Distinct (%)55.2%
Missing3
Missing (%)2.8%
Memory size996.0 B
2024-01-28T17:43:59.287727image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length134
Median length106
Mean length59.095238
Min length1

Characters and Unicode

Total characters6205
Distinct characters67
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

Unique44 ?
Unique (%)41.9%

Sample

1st row영업대상 건설폐기물
2nd row-
3rd row폐콘크리트, 혼합건설폐기물
4th row폐콘크리트, 폐아스팔트콘크리트, 폐벽돌, 폐블록, 폐기와, 폐목재, 폐합성수지, 폐섬유, 폐벽지, 건설오니, 폐금속류, 폐유리, 폐타일 및 폐도자기, 폐보드류, 폐판넬, 건설폐토석, 혼합건설폐기물, 건설공사로 인하여 발생되는 그 밖의 폐기물
5th row폐콘크리트, 폐아스팔트콘크리트, 폐벽돌, 폐기와, 폐목재, 폐합성수지, 폐섬유, 폐벽지, 건설오니, 폐금속류, 폐유리, 폐타일 및 폐도자기, 폐보드류, 폐판넬, 건설폐토석, 혼합건설폐기물
ValueCountFrequency (%)
혼합건설폐기물 81
 
7.5%
폐콘크리트 79
 
7.4%
폐아스팔트콘크리트 71
 
6.6%
건설폐토석 65
 
6.1%
폐벽돌 53
 
4.9%
폐합성수지 53
 
4.9%
폐목재 51
 
4.7%
폐블록 45
 
4.2%
건설오니 45
 
4.2%
폐기와 41
 
3.8%
Other values (22) 490
45.6%
2024-01-28T17:43:59.595814image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
969
15.6%
폐 839
 
13.5%
, 754
 
12.2%
설 233
 
3.8%
건 233
 
3.8%
트 221
 
3.6%
기 193
 
3.1%
리 185
 
3.0%
크 150
 
2.4%
콘 150
 
2.4%
Other values (57) 2278
36.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 4473
72.1%
Space Separator 969
 
15.6%
Other Punctuation 754
 
12.2%
Dash Punctuation 5
 
0.1%
Open Punctuation 2
 
< 0.1%
Close Punctuation 2
 
< 0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
폐 839
18.8%
설 233
 
5.2%
건 233
 
5.2%
트 221
 
4.9%
기 193
 
4.3%
리 185
 
4.1%
크 150
 
3.4%
콘 150
 
3.4%
합 134
 
3.0%
물 118
 
2.6%
Other values (52) 2017
45.1%
Space Separator
ValueCountFrequency (%)
969
100.0%
Other Punctuation
ValueCountFrequency (%)
, 754
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 5
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 4473
72.1%
Common 1732
 
27.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
폐 839
18.8%
설 233
 
5.2%
건 233
 
5.2%
트 221
 
4.9%
기 193
 
4.3%
리 185
 
4.1%
크 150
 
3.4%
콘 150
 
3.4%
합 134
 
3.0%
물 118
 
2.6%
Other values (52) 2017
45.1%
Common
ValueCountFrequency (%)
969
55.9%
, 754
43.5%
- 5
 
0.3%
( 2
 
0.1%
) 2
 
0.1%

Most occurring blocks

ValueCountFrequency (%)
Hangul 4473
72.1%
ASCII 1732
 
27.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
969
55.9%
, 754
43.5%
- 5
 
0.3%
( 2
 
0.1%
) 2
 
0.1%
Hangul
ValueCountFrequency (%)
폐 839
18.8%
설 233
 
5.2%
건 233
 
5.2%
트 221
 
4.9%
기 193
 
4.3%
리 185
 
4.1%
크 150
 
3.4%
콘 150
 
3.4%
합 134
 
3.0%
물 118
 
2.6%
Other values (52) 2017
45.1%

Unnamed: 7
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2
Missing (%)1.9%
Memory size996.0 B

Unnamed: 8
Text

MISSING 

Distinct90
Distinct (%)100.0%
Missing18
Missing (%)16.7%
Memory size996.0 B
2024-01-28T17:43:59.831074image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length13
Median length12
Mean length11.722222
Min length4

Characters and Unicode

Total characters1055
Distinct characters15
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique90 ?
Unique (%)100.0%

Sample

1st row전화번호
2nd row032-887-8026
3rd row032-833-4760
4th row032-555-7971
5th row032-882-7070
ValueCountFrequency (%)
032-875-7757 1
 
1.1%
032-581-0034 1
 
1.1%
032-579-1052 1
 
1.1%
032-567-5257 1
 
1.1%
032-567-2315 1
 
1.1%
032-562-1770 1
 
1.1%
032-552-6247 1
 
1.1%
032-569-5210 1
 
1.1%
032-562-3605 1
 
1.1%
032-553-2255 1
 
1.1%
Other values (80) 80
88.9%
2024-01-28T17:44:00.151320image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 166
15.7%
0 144
13.6%
3 142
13.5%
2 135
12.8%
5 105
10.0%
6 76
7.2%
8 69
6.5%
1 65
 
6.2%
7 63
 
6.0%
4 43
 
4.1%
Other values (5) 47
 
4.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 885
83.9%
Dash Punctuation 166
 
15.7%
Other Letter 4
 
0.4%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 144
16.3%
3 142
16.0%
2 135
15.3%
5 105
11.9%
6 76
8.6%
8 69
7.8%
1 65
7.3%
7 63
7.1%
4 43
 
4.9%
9 43
 
4.9%
Other Letter
ValueCountFrequency (%)
전 1
25.0%
화 1
25.0%
번 1
25.0%
호 1
25.0%
Dash Punctuation
ValueCountFrequency (%)
- 166
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1051
99.6%
Hangul 4
 
0.4%

Most frequent character per script

Common
ValueCountFrequency (%)
- 166
15.8%
0 144
13.7%
3 142
13.5%
2 135
12.8%
5 105
10.0%
6 76
7.2%
8 69
6.6%
1 65
 
6.2%
7 63
 
6.0%
4 43
 
4.1%
Hangul
ValueCountFrequency (%)
전 1
25.0%
화 1
25.0%
번 1
25.0%
호 1
25.0%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1051
99.6%
Hangul 4
 
0.4%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 166
15.8%
0 144
13.7%
3 142
13.5%
2 135
12.8%
5 105
10.0%
6 76
7.2%
8 69
6.6%
1 65
 
6.2%
7 63
 
6.0%
4 43
 
4.1%
Hangul
ValueCountFrequency (%)
전 1
25.0%
화 1
25.0%
번 1
25.0%
호 1
25.0%

Unnamed: 9
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2
Missing (%)1.9%
Memory size996.0 B

Unnamed: 10
Text

MISSING 

Distinct101
Distinct (%)96.2%
Missing3
Missing (%)2.8%
Memory size996.0 B
2024-01-28T17:44:00.441669image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length15
Median length10
Mean length10.047619
Min length10

Characters and Unicode

Total characters1055
Distinct characters21
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

Unique97 ?
Unique (%)92.4%

Sample

1st row허가(승인)일 (년.월.일)
2nd row1999.10.21
3rd row2018.01.15
4th row2009.07.29
5th row2018.12.31
ValueCountFrequency (%)
2020.11.20 2
 
1.9%
2019.10.07 2
 
1.9%
2019.08.16 2
 
1.9%
1999.10.21 2
 
1.9%
1999.11.06 1
 
0.9%
2021.06.23 1
 
0.9%
2013.05.28 1
 
0.9%
2019.07.30 1
 
0.9%
2005.11.08 1
 
0.9%
2010.02.26 1
 
0.9%
Other values (92) 92
86.8%
2024-01-28T17:44:00.819068image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
0 257
24.4%
. 210
19.9%
2 190
18.0%
1 171
16.2%
9 47
 
4.5%
7 37
 
3.5%
3 37
 
3.5%
6 28
 
2.7%
8 27
 
2.6%
4 19
 
1.8%
Other values (11) 32
 
3.0%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 832
78.9%
Other Punctuation 210
 
19.9%
Other Letter 8
 
0.8%
Open Punctuation 2
 
0.2%
Close Punctuation 2
 
0.2%
Control 1
 
0.1%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 257
30.9%
2 190
22.8%
1 171
20.6%
9 47
 
5.6%
7 37
 
4.4%
3 37
 
4.4%
6 28
 
3.4%
8 27
 
3.2%
4 19
 
2.3%
5 19
 
2.3%
Other Letter
ValueCountFrequency (%)
일 2
25.0%
허 1
12.5%
가 1
12.5%
승 1
12.5%
인 1
12.5%
년 1
12.5%
월 1
12.5%
Other Punctuation
ValueCountFrequency (%)
. 210
100.0%
Open Punctuation
ValueCountFrequency (%)
( 2
100.0%
Close Punctuation
ValueCountFrequency (%)
) 2
100.0%
Control
ValueCountFrequency (%)
1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 1047
99.2%
Hangul 8
 
0.8%

Most frequent character per script

Common
ValueCountFrequency (%)
0 257
24.5%
. 210
20.1%
2 190
18.1%
1 171
16.3%
9 47
 
4.5%
7 37
 
3.5%
3 37
 
3.5%
6 28
 
2.7%
8 27
 
2.6%
4 19
 
1.8%
Other values (4) 24
 
2.3%
Hangul
ValueCountFrequency (%)
일 2
25.0%
허 1
12.5%
가 1
12.5%
승 1
12.5%
인 1
12.5%
년 1
12.5%
월 1
12.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 1047
99.2%
Hangul 8
 
0.8%

Most frequent character per block

ASCII
ValueCountFrequency (%)
0 257
24.5%
. 210
20.1%
2 190
18.1%
1 171
16.3%
9 47
 
4.5%
7 37
 
3.5%
3 37
 
3.5%
6 28
 
2.7%
8 27
 
2.6%
4 19
 
1.8%
Other values (4) 24
 
2.3%
Hangul
ValueCountFrequency (%)
일 2
25.0%
허 1
12.5%
가 1
12.5%
승 1
12.5%
인 1
12.5%
년 1
12.5%
월 1
12.5%

Unnamed: 11
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing107
Missing (%)99.1%
Memory size996.0 B
2024-01-28T17:44:00.961091image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length14
Mean length14
Min length14

Characters and Unicode

Total characters14
Distinct characters11
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row반납 신고일 (년.월.일)
ValueCountFrequency (%)
반납 1
33.3%
신고일 1
33.3%
년.월.일 1
33.3%
2024-01-28T17:44:01.208604image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
2
14.3%
일 2
14.3%
. 2
14.3%
반 1
7.1%
납 1
7.1%
신 1
7.1%
고 1
7.1%
( 1
7.1%
년 1
7.1%
월 1
7.1%

Most occurring categories

ValueCountFrequency (%)
Other Letter 8
57.1%
Control 2
 
14.3%
Other Punctuation 2
 
14.3%
Open Punctuation 1
 
7.1%
Close Punctuation 1
 
7.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
일 2
25.0%
반 1
12.5%
납 1
12.5%
신 1
12.5%
고 1
12.5%
년 1
12.5%
월 1
12.5%
Control
ValueCountFrequency (%)
2
100.0%
Other Punctuation
ValueCountFrequency (%)
. 2
100.0%
Open Punctuation
ValueCountFrequency (%)
( 1
100.0%
Close Punctuation
ValueCountFrequency (%)
) 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 8
57.1%
Common 6
42.9%

Most frequent character per script

Hangul
ValueCountFrequency (%)
일 2
25.0%
반 1
12.5%
납 1
12.5%
신 1
12.5%
고 1
12.5%
년 1
12.5%
월 1
12.5%
Common
ValueCountFrequency (%)
2
33.3%
. 2
33.3%
( 1
16.7%
) 1
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 8
57.1%
ASCII 6
42.9%

Most frequent character per block

ASCII
ValueCountFrequency (%)
2
33.3%
. 2
33.3%
( 1
16.7%
) 1
16.7%
Hangul
ValueCountFrequency (%)
일 2
25.0%
반 1
12.5%
납 1
12.5%
신 1
12.5%
고 1
12.5%
년 1
12.5%
월 1
12.5%

Unnamed: 12
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing107
Missing (%)99.1%
Memory size996.0 B
2024-01-28T17:44:01.286363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length2
Median length2
Mean length2
Min length2

Characters and Unicode

Total characters2
Distinct characters2
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique1 ?
Unique (%)100.0%

Sample

1st row비고
ValueCountFrequency (%)
비고 1
100.0%
2024-01-28T17:44:01.450476image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
비 1
50.0%
고 1
50.0%

Most occurring categories

ValueCountFrequency (%)
Other Letter 2
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
비 1
50.0%
고 1
50.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 2
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
비 1
50.0%
고 1
50.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 2
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
비 1
50.0%
고 1
50.0%

Correlations

2024-01-28T17:44:01.524738image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Unnamed: 1Unnamed: 2Unnamed: 6Unnamed: 8
Unnamed: 11.0000.000NaNNaN
Unnamed: 20.0001.0001.0001.000
Unnamed: 6NaN1.0001.0001.000
Unnamed: 8NaN1.0001.0001.000

Missing values

2024-01-28T17:43:55.253829image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-01-28T17:43:55.409506image/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.
2024-01-28T17:43:55.551061image/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

3. 폐기물 수집·운반업체 현황Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7Unnamed: 8Unnamed: 9Unnamed: 10Unnamed: 11Unnamed: 12
0나. 건설폐기물 수집·운반업체 현황<NA><NA><NA><NA><NA><NA>NaN<NA>NaN<NA><NA><NA>
1<NA><NA><NA><NA><NA><NA><NA>NaN<NA>NaN<NA><NA><NA>
2연번시도시군구업체명대표자소재지영업대상 건설폐기물보유차량대수(대)전화번호2021년 수집·운반량허가(승인)일 (년.월.일)반납 신고일 (년.월.일)비고
3104개소인천소계<NA><NA><NA><NA>1752<NA>9572679<NA><NA><NA>
41<NA>중구(주)고려환경한순일인천광역시 중구 도원로 61 (유동)-31032-887-80261148151999.10.21<NA><NA>
52<NA><NA>주식회사 동운양우용인천광역시 중구 서해대로262번길 4 삼신빌딩202호 (신흥동3가)폐콘크리트, 혼합건설폐기물4032-833-476015792018.01.15<NA><NA>
63<NA><NA>인성코퍼레이션(주)추성호인천광역시 중구 서해대로93번길 14-1 , 3층 (항동7가)폐콘크리트, 폐아스팔트콘크리트, 폐벽돌, 폐블록, 폐기와, 폐목재, 폐합성수지, 폐섬유, 폐벽지, 건설오니, 폐금속류, 폐유리, 폐타일 및 폐도자기, 폐보드류, 폐판넬, 건설폐토석, 혼합건설폐기물, 건설공사로 인하여 발생되는 그 밖의 폐기물4032-555-7971337362009.07.29<NA><NA>
74<NA><NA>길튼개발주식회사김혜경인천광역시 중구 자유공원로 22 (전동) 3층폐콘크리트, 폐아스팔트콘크리트, 폐벽돌, 폐기와, 폐목재, 폐합성수지, 폐섬유, 폐벽지, 건설오니, 폐금속류, 폐유리, 폐타일 및 폐도자기, 폐보드류, 폐판넬, 건설폐토석, 혼합건설폐기물6032-882-707002018.12.31<NA><NA>
85<NA><NA>지피건설김민희인천광역시 중구 제물량로 176 3층 (신생동)폐콘크리트3<NA>02021.09.23<NA><NA>
96<NA><NA>티에스산업주식회사김성현인천광역시 중구 축항대로 245 (항동7가) 2층폐콘크리트, 폐아스팔트콘크리트, 폐벽돌, 폐블록, 폐기와, 건설폐토석, 혼합건설폐기물9032-889-1510595022016.08.09<NA><NA>
3. 폐기물 수집·운반업체 현황Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7Unnamed: 8Unnamed: 9Unnamed: 10Unnamed: 11Unnamed: 12
9895<NA><NA>에스지이(주)석남지점박창호인천광역시 서구 석남동 223-640 (봉수대로300번길 9) 2동 1층폐아스팔트콘크리트11032-584-5353188552012.07.17<NA><NA>
9996<NA><NA>(주)엔케이산업남궁균인천광역시 서구 심곡동 승학로 198 1-207폐콘크리트, 폐아스팔트콘크리트, 폐벽돌, 폐블록, 폐기와, 폐목재, 폐합성수지, 폐섬유, 폐벽지, 건설오니, 폐금속류, 폐유리, 폐타일 및 폐도자기, 폐보드류, 폐판넬, 건설폐토석, 혼합건설폐기물11032-263-5114291842012.04.05<NA><NA>
10097<NA><NA>(주)아이케이이상진인천광역시 서구 오류동 1536번지폐콘크리트, 폐아스팔트콘크리트, 폐벽돌, 폐블록, 폐합성수지, 건설오니, 건설폐토석, 혼합건설폐기물48032-565-711415376981997.08.29<NA><NA>
10198<NA><NA>(주)장형기업홍제태인천광역시 서구 오류동 검단천로 203 (오류동, 장형기업)폐콘크리트, 폐아스팔트콘크리트, 폐벽돌, 폐목재, 폐합성수지, 건설오니, 건설폐토석, 혼합건설폐기물451032-562-165810040771995.02.18<NA><NA>
10299<NA><NA>한밭미래자원(주)심상열인천광역시 서구 왕길동 (거월로 51)폐콘크리트, 폐아스팔트콘크리트, 폐벽돌, 폐블록, 폐기와, 폐목재, 폐합성수지, 폐섬유, 폐벽지, 건설오니, 폐유리, 폐타일 및 폐도자기, 폐보드류, 폐판넬, 건설폐토석, 혼합건설폐기물, 건설공사로 인하여 발생되는 그 밖의 폐기물9032-562-99734252852012.03.12<NA><NA>
103100<NA>강화군송우환경(주)최흥곤인천광역시 강화군 길상면 초지로 148 (M.D마린모타보트) 2층 208호폐콘크리트, 폐아스팔트콘크리트, 폐벽돌, 폐목재, 폐합성수지, 혼합건설폐기물7032-934-0775353121997.07.01<NA><NA>
104101<NA><NA>(주)케이제이와이건설김진영인천광역시 강화군 길상면 해안동로 75 2층 (초지리, 초지주유소)폐콘크리트, 폐아스팔트콘크리트, 폐벽돌, 폐블록, 폐기와, 폐목재, 폐합성수지, 폐섬유, 폐벽지, 건설오니, 폐금속류, 폐유리, 폐타일 및 폐도자기, 폐보드류, 폐판넬, 건설폐토석, 혼합건설폐기물, 건설공사로 인하여 발생되는 그 밖의 폐기물4<NA>11582020.06.23<NA><NA>
105102<NA><NA>(주)한강건설환경최병관인천광역시 강화군 불은면 신현리 1-4폐콘크리트, 폐아스팔트콘크리트, 폐벽돌, 폐블록, 폐기와, 폐목재, 폐합성수지, 건설오니, 폐타일 및 폐도자기, 건설폐토석, 혼합건설폐기물8032-937-41171446181999.11.06<NA><NA>
106103<NA>옹진군황해환경(주)조민경인천광역시 옹진군 백령면 백령로 461-20 , 2층폐콘크리트, 폐아스팔트콘크리트, 폐벽돌, 폐블록, 폐기와, 폐목재, 폐합성수지, 폐섬유, 폐벽지, 건설오니, 폐금속류, 폐유리, 폐타일 및 폐도자기, 폐보드류, 폐판넬, 건설폐토석, 혼합건설폐기물, 건설공사로 인하여 발생되는 그 밖의 폐기물13<NA>123272021.08.31<NA><NA>
107104<NA><NA>(주)옹진환경변 영 현인천광역시 옹진군 백령면 백령로297번길 44 .폐콘크리트, 폐아스팔트콘크리트, 혼합건설폐기물3032-836-99974892018.02.23<NA><NA>