Overview

Dataset statistics

Number of variables13
Number of observations57
Missing cells111
Missing cells (%)15.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory6.1 KiB
Average record size in memory109.3 B

Variable types

Text5
DateTime2
Categorical4
Numeric2

Dataset

Description경상남도 김해시 폐기물 중간처리업 현황에 대한 데이터로 사업장명,전화번호,지번주소,도로명주소,위도,경도 등의 항목을 제공합니다.
Author경상남도 김해시
URLhttps://www.data.go.kr/data/15033434/fileData.do

Alerts

폐기물처리업별처리구분명 has constant value ""Constant
상세영업상태명 is highly overall correlated with 폐기물구분명 and 1 other fieldsHigh correlation
허용보관량 is highly overall correlated with 위도 and 3 other fieldsHigh correlation
폐기물구분명 is highly overall correlated with 위도 and 3 other fieldsHigh correlation
폐기물처리업구분명 is highly overall correlated with 폐기물구분명 and 1 other fieldsHigh correlation
위도 is highly overall correlated with 폐기물구분명 and 1 other fieldsHigh correlation
경도 is highly overall correlated with 폐기물구분명 and 1 other fieldsHigh correlation
허용보관량 is highly imbalanced (78.2%)Imbalance
폐업일자 has 42 (73.7%) missing valuesMissing
전화번호 has 11 (19.3%) missing valuesMissing
도로명주소 has 2 (3.5%) missing valuesMissing
폐기물처리업별처리구분명 has 56 (98.2%) missing valuesMissing
인허가일자 has unique valuesUnique

Reproduction

Analysis started2023-12-12 11:58:28.490640
Analysis finished2023-12-12 11:58:30.222656
Duration1.73 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

사업장명
Text

Distinct49
Distinct (%)86.0%
Missing0
Missing (%)0.0%
Memory size588.0 B
2023-12-12T20:58:30.457685image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length14
Median length12
Mean length7.2807018
Min length4

Characters and Unicode

Total characters415
Distinct characters86
Distinct categories5 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique41 ?
Unique (%)71.9%

Sample

1st row세영개발 주식회사
2nd row제이케이산업
3rd row민영기업
4th row(주)태영환경
5th row(주)이헌환경
ValueCountFrequency (%)
주식회사 3
 
4.7%
주)그린자원 2
 
3.1%
덕산 2
 
3.1%
주)태영환경 2
 
3.1%
주촌지점 2
 
3.1%
동헌산업(주 2
 
3.1%
주)경부이엔티 2
 
3.1%
한통아스콘(주 2
 
3.1%
주)명송 2
 
3.1%
주)현주개발 2
 
3.1%
Other values (43) 43
67.2%
2023-12-12T20:58:30.958558image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
주 51
 
12.3%
( 43
 
10.4%
) 43
 
10.4%
산 21
 
5.1%
업 20
 
4.8%
경 15
 
3.6%
개 13
 
3.1%
발 13
 
3.1%
환 12
 
2.9%
원 8
 
1.9%
Other values (76) 176
42.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 321
77.3%
Open Punctuation 43
 
10.4%
Close Punctuation 43
 
10.4%
Space Separator 7
 
1.7%
Other Symbol 1
 
0.2%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 51
 
15.9%
산 21
 
6.5%
업 20
 
6.2%
경 15
 
4.7%
개 13
 
4.0%
발 13
 
4.0%
환 12
 
3.7%
원 8
 
2.5%
이 7
 
2.2%
기 6
 
1.9%
Other values (72) 155
48.3%
Open Punctuation
ValueCountFrequency (%)
( 43
100.0%
Close Punctuation
ValueCountFrequency (%)
) 43
100.0%
Space Separator
ValueCountFrequency (%)
7
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 322
77.6%
Common 93
 
22.4%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 51
 
15.8%
산 21
 
6.5%
업 20
 
6.2%
경 15
 
4.7%
개 13
 
4.0%
발 13
 
4.0%
환 12
 
3.7%
원 8
 
2.5%
이 7
 
2.2%
기 6
 
1.9%
Other values (73) 156
48.4%
Common
ValueCountFrequency (%)
( 43
46.2%
) 43
46.2%
7
 
7.5%

Most occurring blocks

ValueCountFrequency (%)
Hangul 321
77.3%
ASCII 93
 
22.4%
None 1
 
0.2%

Most frequent character per block

Hangul
ValueCountFrequency (%)
주 51
 
15.9%
산 21
 
6.5%
업 20
 
6.2%
경 15
 
4.7%
개 13
 
4.0%
발 13
 
4.0%
환 12
 
3.7%
원 8
 
2.5%
이 7
 
2.2%
기 6
 
1.9%
Other values (72) 155
48.3%
ASCII
ValueCountFrequency (%)
( 43
46.2%
) 43
46.2%
7
 
7.5%
None
ValueCountFrequency (%)
㈜ 1
100.0%

인허가일자
Date

UNIQUE 

Distinct57
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size588.0 B
Minimum2005-07-26 00:00:00
Maximum2020-12-03 00:00:00
2023-12-12T20:58:31.201663image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:58:31.419593image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)

상세영업상태명
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)3.5%
Missing0
Missing (%)0.0%
Memory size588.0 B
영업
42 
폐업
15 

Length

Max length2
Median length2
Mean length2
Min length2

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
영업 42
73.7%
폐업 15
 
26.3%

Length

2023-12-12T20:58:31.589467image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T20:58:31.702940image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
영업 42
73.7%
폐업 15
 
26.3%

폐업일자
Date

MISSING 

Distinct15
Distinct (%)100.0%
Missing42
Missing (%)73.7%
Memory size588.0 B
Minimum2008-07-30 00:00:00
Maximum2020-01-17 00:00:00
2023-12-12T20:58:31.826120image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:58:31.970679image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=15)

전화번호
Text

MISSING 

Distinct39
Distinct (%)84.8%
Missing11
Missing (%)19.3%
Memory size588.0 B
2023-12-12T20:58:32.233588image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters552
Distinct characters11
Distinct categories2 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique32 ?
Unique (%)69.6%

Sample

1st row055-338-3890
2nd row055-332-3007
3rd row055-331-6549
4th row055-311-5179
5th row055-345-8464
ValueCountFrequency (%)
055-346-1100 2
 
4.3%
055-345-6565 2
 
4.3%
055-346-4986 2
 
4.3%
055-336-2925 2
 
4.3%
055-311-5179 2
 
4.3%
055-346-4932 2
 
4.3%
055-326-9123 2
 
4.3%
055-345-5141 1
 
2.2%
055-343-0059 1
 
2.2%
055-338-3376 1
 
2.2%
Other values (29) 29
63.0%
2023-12-12T20:58:32.613363image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
5 122
22.1%
- 92
16.7%
3 78
14.1%
0 68
12.3%
4 40
 
7.2%
6 36
 
6.5%
1 31
 
5.6%
2 27
 
4.9%
9 23
 
4.2%
8 19
 
3.4%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 460
83.3%
Dash Punctuation 92
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
5 122
26.5%
3 78
17.0%
0 68
14.8%
4 40
 
8.7%
6 36
 
7.8%
1 31
 
6.7%
2 27
 
5.9%
9 23
 
5.0%
8 19
 
4.1%
7 16
 
3.5%
Dash Punctuation
ValueCountFrequency (%)
- 92
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 552
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
5 122
22.1%
- 92
16.7%
3 78
14.1%
0 68
12.3%
4 40
 
7.2%
6 36
 
6.5%
1 31
 
5.6%
2 27
 
4.9%
9 23
 
4.2%
8 19
 
3.4%

Most occurring blocks

ValueCountFrequency (%)
ASCII 552
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
5 122
22.1%
- 92
16.7%
3 78
14.1%
0 68
12.3%
4 40
 
7.2%
6 36
 
6.5%
1 31
 
5.6%
2 27
 
4.9%
9 23
 
4.2%
8 19
 
3.4%

지번주소
Text

Distinct52
Distinct (%)91.2%
Missing0
Missing (%)0.0%
Memory size588.0 B
2023-12-12T20:58:32.935244image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length35
Median length30
Mean length22.77193
Min length18

Characters and Unicode

Total characters1298
Distinct characters84
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

Unique47 ?
Unique (%)82.5%

Sample

1st row경상남도 김해시 삼계동 429-2
2nd row경상남도 김해시 안동 333-1번지
3rd row경상남도 김해시 내동 1110-5번지
4th row경상남도 김해시 주촌면 선지리 30-32번지
5th row경상남도 김해시 주촌면 976-2번지
ValueCountFrequency (%)
경상남도 57
20.7%
김해시 57
20.7%
한림면 16
 
5.8%
주촌면 9
 
3.3%
생림면 5
 
1.8%
내동 5
 
1.8%
내삼리 4
 
1.4%
삼계동 4
 
1.4%
부원동 4
 
1.4%
명동리 4
 
1.4%
Other values (92) 111
40.2%
2023-12-12T20:58:33.405469image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
219
 
16.9%
상 60
 
4.6%
남 58
 
4.5%
경 57
 
4.4%
도 57
 
4.4%
김 57
 
4.4%
해 57
 
4.4%
시 57
 
4.4%
1 54
 
4.2%
지 44
 
3.4%
Other values (74) 578
44.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 778
59.9%
Decimal Number 256
 
19.7%
Space Separator 219
 
16.9%
Dash Punctuation 44
 
3.4%
Other Punctuation 1
 
0.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
상 60
 
7.7%
남 58
 
7.5%
경 57
 
7.3%
도 57
 
7.3%
김 57
 
7.3%
해 57
 
7.3%
시 57
 
7.3%
지 44
 
5.7%
번 40
 
5.1%
동 35
 
4.5%
Other values (61) 256
32.9%
Decimal Number
ValueCountFrequency (%)
1 54
21.1%
2 36
14.1%
3 33
12.9%
0 26
10.2%
4 24
9.4%
6 18
 
7.0%
5 17
 
6.6%
7 17
 
6.6%
9 16
 
6.2%
8 15
 
5.9%
Space Separator
ValueCountFrequency (%)
219
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 44
100.0%
Other Punctuation
ValueCountFrequency (%)
, 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 778
59.9%
Common 520
40.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
상 60
 
7.7%
남 58
 
7.5%
경 57
 
7.3%
도 57
 
7.3%
김 57
 
7.3%
해 57
 
7.3%
시 57
 
7.3%
지 44
 
5.7%
번 40
 
5.1%
동 35
 
4.5%
Other values (61) 256
32.9%
Common
ValueCountFrequency (%)
219
42.1%
1 54
 
10.4%
- 44
 
8.5%
2 36
 
6.9%
3 33
 
6.3%
0 26
 
5.0%
4 24
 
4.6%
6 18
 
3.5%
5 17
 
3.3%
7 17
 
3.3%
Other values (3) 32
 
6.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 778
59.9%
ASCII 520
40.1%

Most frequent character per block

ASCII
ValueCountFrequency (%)
219
42.1%
1 54
 
10.4%
- 44
 
8.5%
2 36
 
6.9%
3 33
 
6.3%
0 26
 
5.0%
4 24
 
4.6%
6 18
 
3.5%
5 17
 
3.3%
7 17
 
3.3%
Other values (3) 32
 
6.2%
Hangul
ValueCountFrequency (%)
상 60
 
7.7%
남 58
 
7.5%
경 57
 
7.3%
도 57
 
7.3%
김 57
 
7.3%
해 57
 
7.3%
시 57
 
7.3%
지 44
 
5.7%
번 40
 
5.1%
동 35
 
4.5%
Other values (61) 256
32.9%

도로명주소
Text

MISSING 

Distinct48
Distinct (%)87.3%
Missing2
Missing (%)3.5%
Memory size588.0 B
2023-12-12T20:58:33.781086image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length39
Median length32
Mean length26.036364
Min length19

Characters and Unicode

Total characters1432
Distinct characters92
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

Unique42 ?
Unique (%)76.4%

Sample

1st row경상남도 김해시 김해대로 1816, 2층 (삼계동)
2nd row경상남도 김해시 삼안로 108(안동)
3rd row경상남도 김해시 우암로63번길 7 (내동)
4th row경상남도 김해시 주촌면 서부로1701번안길 58-202
5th row경상남도 김해시 주촌면 서부로1499번안길 28
ValueCountFrequency (%)
경상남도 55
19.2%
김해시 55
19.2%
한림면 15
 
5.2%
주촌면 10
 
3.5%
김해대로1538번길 5
 
1.7%
내동 4
 
1.4%
2층 4
 
1.4%
김해대로 4
 
1.4%
부원동 4
 
1.4%
생림면 4
 
1.4%
Other values (103) 126
44.1%
2023-12-12T20:58:34.432523image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
236
 
16.5%
김 69
 
4.8%
해 69
 
4.8%
1 67
 
4.7%
상 59
 
4.1%
경 57
 
4.0%
남 56
 
3.9%
도 55
 
3.8%
시 55
 
3.8%
로 55
 
3.8%
Other values (82) 654
45.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 840
58.7%
Decimal Number 282
 
19.7%
Space Separator 236
 
16.5%
Close Punctuation 22
 
1.5%
Open Punctuation 22
 
1.5%
Dash Punctuation 19
 
1.3%
Other Punctuation 11
 
0.8%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
김 69
 
8.2%
해 69
 
8.2%
상 59
 
7.0%
경 57
 
6.8%
남 56
 
6.7%
도 55
 
6.5%
시 55
 
6.5%
로 55
 
6.5%
면 32
 
3.8%
번 32
 
3.8%
Other values (67) 301
35.8%
Decimal Number
ValueCountFrequency (%)
1 67
23.8%
2 42
14.9%
3 36
12.8%
5 32
11.3%
0 25
 
8.9%
4 24
 
8.5%
8 19
 
6.7%
7 18
 
6.4%
6 12
 
4.3%
9 7
 
2.5%
Space Separator
ValueCountFrequency (%)
236
100.0%
Close Punctuation
ValueCountFrequency (%)
) 22
100.0%
Open Punctuation
ValueCountFrequency (%)
( 22
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 19
100.0%
Other Punctuation
ValueCountFrequency (%)
, 11
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 840
58.7%
Common 592
41.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
김 69
 
8.2%
해 69
 
8.2%
상 59
 
7.0%
경 57
 
6.8%
남 56
 
6.7%
도 55
 
6.5%
시 55
 
6.5%
로 55
 
6.5%
면 32
 
3.8%
번 32
 
3.8%
Other values (67) 301
35.8%
Common
ValueCountFrequency (%)
236
39.9%
1 67
 
11.3%
2 42
 
7.1%
3 36
 
6.1%
5 32
 
5.4%
0 25
 
4.2%
4 24
 
4.1%
) 22
 
3.7%
( 22
 
3.7%
- 19
 
3.2%
Other values (5) 67
 
11.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 840
58.7%
ASCII 592
41.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
236
39.9%
1 67
 
11.3%
2 42
 
7.1%
3 36
 
6.1%
5 32
 
5.4%
0 25
 
4.2%
4 24
 
4.1%
) 22
 
3.7%
( 22
 
3.7%
- 19
 
3.2%
Other values (5) 67
 
11.3%
Hangul
ValueCountFrequency (%)
김 69
 
8.2%
해 69
 
8.2%
상 59
 
7.0%
경 57
 
6.8%
남 56
 
6.7%
도 55
 
6.5%
시 55
 
6.5%
로 55
 
6.5%
면 32
 
3.8%
번 32
 
3.8%
Other values (67) 301
35.8%

폐기물처리업구분명
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)3.5%
Missing0
Missing (%)0.0%
Memory size588.0 B
수집운반업(건설폐기물)
42 
중간처분업(건설폐기물)
15 

Length

Max length12
Median length12
Mean length12
Min length12

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row수집운반업(건설폐기물)
2nd row수집운반업(건설폐기물)
3rd row수집운반업(건설폐기물)
4th row수집운반업(건설폐기물)
5th row수집운반업(건설폐기물)

Common Values

ValueCountFrequency (%)
수집운반업(건설폐기물) 42
73.7%
중간처분업(건설폐기물) 15
 
26.3%

Length

2023-12-12T20:58:34.591630image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T20:58:34.717518image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
수집운반업(건설폐기물 42
73.7%
중간처분업(건설폐기물 15
 
26.3%

폐기물처리업별처리구분명
Text

CONSTANT  MISSING 

Distinct1
Distinct (%)100.0%
Missing56
Missing (%)98.2%
Memory size588.0 B
2023-12-12T20:58:34.894325image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length7
Median length7
Mean length7
Min length7

Characters and Unicode

Total characters7
Distinct characters7
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 row폐기물처리업자
ValueCountFrequency (%)
폐기물처리업자 1
100.0%
2023-12-12T20:58:35.243833image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
폐 1
14.3%
기 1
14.3%
물 1
14.3%
처 1
14.3%
리 1
14.3%
업 1
14.3%
자 1
14.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 7
100.0%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
폐 1
14.3%
기 1
14.3%
물 1
14.3%
처 1
14.3%
리 1
14.3%
업 1
14.3%
자 1
14.3%

Most occurring scripts

ValueCountFrequency (%)
Hangul 7
100.0%

Most frequent character per script

Hangul
ValueCountFrequency (%)
폐 1
14.3%
기 1
14.3%
물 1
14.3%
처 1
14.3%
리 1
14.3%
업 1
14.3%
자 1
14.3%

Most occurring blocks

ValueCountFrequency (%)
Hangul 7
100.0%

Most frequent character per block

Hangul
ValueCountFrequency (%)
폐 1
14.3%
기 1
14.3%
물 1
14.3%
처 1
14.3%
리 1
14.3%
업 1
14.3%
자 1
14.3%

폐기물구분명
Categorical

HIGH CORRELATION 

Distinct2
Distinct (%)3.5%
Missing0
Missing (%)0.0%
Memory size588.0 B
<NA>
50 
건설폐기물
7 

Length

Max length5
Median length4
Mean length4.122807
Min length4

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row<NA>
2nd row건설폐기물
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 50
87.7%
건설폐기물 7
 
12.3%

Length

2023-12-12T20:58:35.737732image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T20:58:35.872151image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 50
87.7%
건설폐기물 7
 
12.3%

허용보관량
Categorical

HIGH CORRELATION  IMBALANCE 

Distinct5
Distinct (%)8.8%
Missing0
Missing (%)0.0%
Memory size588.0 B
<NA>
53 
13047.93
 
1
25238.4
 
1
5727.15
 
1
19067.2
 
1

Length

Max length8
Median length4
Mean length4.2280702
Min length4

Unique

Unique4 ?
Unique (%)7.0%

Sample

1st row<NA>
2nd row<NA>
3rd row<NA>
4th row<NA>
5th row<NA>

Common Values

ValueCountFrequency (%)
<NA> 53
93.0%
13047.93 1
 
1.8%
25238.4 1
 
1.8%
5727.15 1
 
1.8%
19067.2 1
 
1.8%

Length

2023-12-12T20:58:36.032196image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T20:58:36.212527image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
na 53
93.0%
13047.93 1
 
1.8%
25238.4 1
 
1.8%
5727.15 1
 
1.8%
19067.2 1
 
1.8%

위도
Real number (ℝ)

HIGH CORRELATION 

Distinct51
Distinct (%)89.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean35.26376
Minimum35.171069
Maximum35.372867
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size645.0 B
2023-12-12T20:58:36.389768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum35.171069
5-th percentile35.222622
Q135.236158
median35.260158
Q335.292972
95-th percentile35.317176
Maximum35.372867
Range0.20179871
Interquartile range (IQR)0.05681474

Descriptive statistics

Standard deviation0.037078121
Coefficient of variation (CV)0.0010514512
Kurtosis0.25932762
Mean35.26376
Median Absolute Deviation (MAD)0.02506418
Skewness0.37073421
Sum2010.0343
Variance0.0013747871
MonotonicityNot monotonic
2023-12-12T20:58:36.593322image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
35.23709918 2
 
3.5%
35.22742981 2
 
3.5%
35.24591421 2
 
3.5%
35.23615776 2
 
3.5%
35.28522257 2
 
3.5%
35.2692803 2
 
3.5%
35.26458923 1
 
1.8%
35.23545513 1
 
1.8%
35.28506337 1
 
1.8%
35.32501688 1
 
1.8%
Other values (41) 41
71.9%
ValueCountFrequency (%)
35.17106852 1
1.8%
35.20465453 1
1.8%
35.21252418 1
1.8%
35.22514673 1
1.8%
35.22742981 2
3.5%
35.22792838 1
1.8%
35.22805478 1
1.8%
35.22872809 1
1.8%
35.22921107 1
1.8%
35.22926641 1
1.8%
ValueCountFrequency (%)
35.37286723 1
1.8%
35.32522603 1
1.8%
35.32501688 1
1.8%
35.31521586 1
1.8%
35.31464897 1
1.8%
35.3138015 1
1.8%
35.31374121 1
1.8%
35.31309899 1
1.8%
35.30337494 1
1.8%
35.30261685 1
1.8%

경도
Real number (ℝ)

HIGH CORRELATION 

Distinct51
Distinct (%)89.5%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean128.84608
Minimum128.74711
Maximum128.96815
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size645.0 B
2023-12-12T20:58:36.817443image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Quantile statistics

Minimum128.74711
5-th percentile128.77055
Q1128.81996
median128.84518
Q3128.86794
95-th percentile128.90028
Maximum128.96815
Range0.2210407
Interquartile range (IQR)0.0479743

Descriptive statistics

Standard deviation0.040185225
Coefficient of variation (CV)0.00031188551
Kurtosis0.83919989
Mean128.84608
Median Absolute Deviation (MAD)0.0252149
Skewness0.0086738037
Sum7344.2264
Variance0.0016148523
MonotonicityNot monotonic
2023-12-12T20:58:37.021694image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
128.8679371 2
 
3.5%
128.8163535 2
 
3.5%
128.8441012 2
 
3.5%
128.8607066 2
 
3.5%
128.8505044 2
 
3.5%
128.8418043 2
 
3.5%
128.8435703 1
 
1.8%
128.8092826 1
 
1.8%
128.8413512 1
 
1.8%
128.7703837 1
 
1.8%
Other values (41) 41
71.9%
ValueCountFrequency (%)
128.747106 1
1.8%
128.7698706 1
1.8%
128.7703837 1
1.8%
128.7705908 1
1.8%
128.7852318 1
1.8%
128.7895098 1
1.8%
128.8032668 1
1.8%
128.8057969 1
1.8%
128.8092826 1
1.8%
128.8106556 1
1.8%
ValueCountFrequency (%)
128.9681467 1
1.8%
128.9173459 1
1.8%
128.9038097 1
1.8%
128.899397 1
1.8%
128.895089 1
1.8%
128.8924425 1
1.8%
128.8873013 1
1.8%
128.8872591 1
1.8%
128.8870507 1
1.8%
128.8847038 1
1.8%

Interactions

2023-12-12T20:58:29.450146image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:58:29.212673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:58:29.567554image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T20:58:29.350753image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Correlations

2023-12-12T20:58:37.156392image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
사업장명인허가일자상세영업상태명폐업일자전화번호지번주소도로명주소폐기물처리업구분명허용보관량위도경도
사업장명1.0001.0000.4491.0001.0001.0000.9990.4491.0000.9941.000
인허가일자1.0001.0001.0001.0001.0001.0001.0001.0001.0001.0001.000
상세영업상태명0.4491.0001.000NaN0.6550.4690.7420.433NaN0.1830.360
폐업일자1.0001.000NaN1.0001.0001.0001.000NaNNaN1.0001.000
전화번호1.0001.0000.6551.0001.0001.0000.9970.3261.0000.9911.000
지번주소1.0001.0000.4691.0001.0001.0001.0000.8851.0001.0001.000
도로명주소0.9991.0000.7421.0000.9971.0001.0000.5461.0001.0001.000
폐기물처리업구분명0.4491.0000.433NaN0.3260.8850.5461.0001.0000.3700.165
허용보관량1.0001.000NaNNaN1.0001.0001.0001.0001.0001.0001.000
위도0.9941.0000.1831.0000.9911.0001.0000.3701.0001.0000.601
경도1.0001.0000.3601.0001.0001.0001.0000.1651.0000.6011.000
2023-12-12T20:58:37.337153image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
상세영업상태명허용보관량폐기물구분명폐기물처리업구분명
상세영업상태명1.0001.0001.0000.284
허용보관량1.0001.000NaN1.000
폐기물구분명1.000NaN1.0001.000
폐기물처리업구분명0.2841.0001.0001.000
2023-12-12T20:58:37.487072image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
위도경도상세영업상태명폐기물처리업구분명폐기물구분명허용보관량
위도1.000-0.2690.1630.3421.0001.000
경도-0.2691.0000.2970.0331.0001.000
상세영업상태명0.1630.2971.0000.2841.0001.000
폐기물처리업구분명0.3420.0330.2841.0001.0001.000
폐기물구분명1.0001.0001.0001.0001.0000.000
허용보관량1.0001.0001.0001.0000.0001.000

Missing values

2023-12-12T20:58:29.732918image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T20:58:29.950885image/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.
2023-12-12T20:58:30.127210image/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

사업장명인허가일자상세영업상태명폐업일자전화번호지번주소도로명주소폐기물처리업구분명폐기물처리업별처리구분명폐기물구분명허용보관량위도경도
0세영개발 주식회사2020-01-19폐업2020-01-17<NA>경상남도 김해시 삼계동 429-2경상남도 김해시 김해대로 1816, 2층 (삼계동)수집운반업(건설폐기물)<NA><NA><NA>35.264112128.863847
1제이케이산업2011-11-28폐업2011-11-25<NA>경상남도 김해시 안동 333-1번지경상남도 김해시 삼안로 108(안동)수집운반업(건설폐기물)<NA>건설폐기물<NA>35.238659128.917346
2민영기업2006-12-18폐업2008-08-29<NA>경상남도 김해시 내동 1110-5번지경상남도 김해시 우암로63번길 7 (내동)수집운반업(건설폐기물)<NA><NA><NA>35.236472128.860345
3(주)태영환경2006-08-30폐업2008-07-30055-338-3890경상남도 김해시 주촌면 선지리 30-32번지경상남도 김해시 주촌면 서부로1701번안길 58-202수집운반업(건설폐기물)<NA><NA><NA>35.245914128.844101
4(주)이헌환경2019-12-17폐업2019-12-17055-332-3007경상남도 김해시 주촌면 976-2번지경상남도 김해시 주촌면 서부로1499번안길 28수집운반업(건설폐기물)<NA><NA><NA>35.253989128.82403
5(주)상동토건중기2016-07-11폐업2016-07-11055-331-6549경상남도 김해시 상동면 매리 95-2번지경상남도 김해시 상동면 동북로 475수집운반업(건설폐기물)<NA><NA><NA>35.315216128.968147
6(주)현주개발2012-10-26폐업2012-10-26055-311-5179경상남도 김해시 내동 1114-2번지경상남도 김해시 우암로63번길 3-5 (내동)수집운반업(건설폐기물)<NA><NA><NA>35.236158128.860707
7(주)무창2013-07-08폐업2013-07-08055-345-8464경상남도 김해시 한림면 퇴래리 465-2번지경상남도 김해시 한림면 김해대로835번길 146수집운반업(건설폐기물)<NA><NA><NA>35.303375128.785232
8건풍자원2013-01-21폐업2013-01-21055-313-7165경상남도 김해시 어방동 680번지 동원아파트 507동 1503호경상남도 김해시 활천로 181(어방동, 어방동원아파트)수집운반업(건설폐기물)<NA><NA><NA>35.241884128.899397
9태영환경2011-04-28폐업2011-04-25<NA>경상남도 김해시 구산동 274-13번지 102호경상남도 김해시 구산로30번길 4-4, 102호 (구산동)수집운반업(건설폐기물)<NA><NA><NA>35.248505128.871661
사업장명인허가일자상세영업상태명폐업일자전화번호지번주소도로명주소폐기물처리업구분명폐기물처리업별처리구분명폐기물구분명허용보관량위도경도
47동헌산업(주) 주촌지점2010-05-19영업<NA>055-336-2925경상남도 김해시 주촌면 내삼리 887번지경상남도 김해시 주촌면 서부로1403번길 48중간처분업(건설폐기물)<NA><NA><NA>35.22743128.816353
48주식회사 덕산2020-10-12영업<NA>055-345-6565경상남도 김해시 한림면 가동리 502-2경상남도 김해시 한림면 장방로 157-7중간처분업(건설폐기물)<NA><NA>19067.235.325226128.769871
49태산개발2015-02-10영업<NA><NA>경상남도 김해시 부원동 627-15경상남도 김해시 활천로15번길 13, 2층 (부원동)수집운반업(건설폐기물)<NA><NA><NA>35.228728128.892442
50성원이엔티(주)2013-09-04영업<NA>055-346-1283경상남도 김해시 한림면 신천리 434-9번지경상남도 김해시 한림면 김해대로1538번길 101중간처분업(건설폐기물)<NA><NA><NA>35.268767128.84136
51㈜석원산업 원지지점2013-05-30영업<NA>055-346-4544경상남도 김해시 한림면 명동리 287-8경상남도 김해시 한림면 한림로 78-42수집운반업(건설폐기물)<NA><NA><NA>35.301092128.811144
52미래환경2009-01-16영업<NA>055-322-0772경상남도 김해시 한림면 퇴래리 703경상남도 김해시 주촌면 서부로1430번길 4-1, 2층 2호수집운반업(건설폐기물)<NA><NA><NA>35.302617128.78951
53대양산업2008-04-22영업<NA>055-338-3376경상남도 김해시 생림면 안양리 699-1번지경상남도 김해시 생림면 안양로 309-55수집운반업(건설폐기물)<NA><NA><NA>35.372867128.845178
54덕흥건설(주)2007-11-19영업<NA>055-322-3668경상남도 김해시 내동 1141-4번지 성하빌딩 301호경상남도 김해시 경원로73번길 1 (내동,성하빌딩 301호)수집운반업(건설폐기물)<NA><NA><NA>35.237099128.867937
55(주)경부이엔티2007-10-19영업<NA>055-326-9123경상남도 김해시 생림면 나전리 1090-10번지경상남도 김해시 생림면 나전로 76수집운반업(건설폐기물)<NA><NA><NA>35.292972128.872358
56(주)중앙환경2005-07-26영업<NA>055-343-7755경상남도 김해시 한림면 안하리 226-6번지 ,-4경상남도 김해시 한림면 안하로 156중간처분업(건설폐기물)<NA><NA><NA>35.313099128.823887