Overview

Dataset statistics

Number of variables6
Number of observations42
Missing cells9
Missing cells (%)3.6%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory2.1 KiB
Average record size in memory51.1 B

Variable types

Categorical2
DateTime1
Text3

Dataset

Description제주특별자치도 서귀포시 관내 폐기물처리업 현황에 관한 데이터로 상호, 연락처, 소재지, 위도, 경도 등 정보를 제공합니다.
Author제주특별자치도 서귀포시
URLhttps://www.data.go.kr/data/15056473/fileData.do

Alerts

데이터기준일자 has constant value ""Constant
전화번호 has 9 (21.4%) missing valuesMissing
인허가일자 has unique valuesUnique

Reproduction

Analysis started2023-12-12 07:05:22.707209
Analysis finished2023-12-12 07:05:23.084488
Duration0.38 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

구분
Categorical

Distinct4
Distinct (%)9.5%
Missing0
Missing (%)0.0%
Memory size468.0 B
건설폐기물처리업 수집운반업
22 
건설폐기물처리업 중간처분업
17 
건설폐기물처리업
 
2
건설폐기물처리업
 
1

Length

Max length14
Median length14
Mean length13.595238
Min length8

Unique

Unique1 ?
Unique (%)2.4%

Sample

1st row건설폐기물처리업 중간처분업
2nd row건설폐기물처리업 수집운반업
3rd row건설폐기물처리업 중간처분업
4th row건설폐기물처리업 중간처분업
5th row건설폐기물처리업 중간처분업

Common Values

ValueCountFrequency (%)
건설폐기물처리업 수집운반업 22
52.4%
건설폐기물처리업 중간처분업 17
40.5%
건설폐기물처리업 2
 
4.8%
건설폐기물처리업 1
 
2.4%

Length

2023-12-12T16:05:23.153673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T16:05:23.261080image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
건설폐기물처리업 42
51.9%
수집운반업 22
27.2%
중간처분업 17
21.0%

인허가일자
Date

UNIQUE 

Distinct42
Distinct (%)100.0%
Missing0
Missing (%)0.0%
Memory size468.0 B
Minimum2006-06-09 00:00:00
Maximum2022-05-13 00:00:00
2023-12-12T16:05:23.365911image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-12T16:05:23.487980image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=42)

사업장명
Text

Distinct36
Distinct (%)85.7%
Missing0
Missing (%)0.0%
Memory size468.0 B
2023-12-12T16:05:23.687473image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length9
Mean length6.9285714
Min length4

Characters and Unicode

Total characters291
Distinct characters69
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

Unique31 ?
Unique (%)73.8%

Sample

1st row서귀포산업㈜
2nd row(주)산남산업개발
3rd row보성산업(가칭)
4th row보성산업(가칭)
5th row서귀포산업 주식회사
ValueCountFrequency (%)
주식회사 4
 
8.7%
보성산업(가칭 3
 
6.5%
주)동화산업 2
 
4.3%
동남산업(주 2
 
4.3%
서귀포산업 2
 
4.3%
일승산업(주 2
 
4.3%
주)한라진산업개발 1
 
2.2%
제일미니중기 1
 
2.2%
탐라개발 1
 
2.2%
주)조앤씨 1
 
2.2%
Other values (27) 27
58.7%
2023-12-12T16:05:24.087790image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
산 27
 
9.3%
업 25
 
8.6%
주 24
 
8.2%
( 23
 
7.9%
) 23
 
7.9%
개 11
 
3.8%
발 11
 
3.8%
성 7
 
2.4%
라 6
 
2.1%
서 5
 
1.7%
Other values (59) 129
44.3%

Most occurring categories

ValueCountFrequency (%)
Other Letter 240
82.5%
Open Punctuation 23
 
7.9%
Close Punctuation 23
 
7.9%
Space Separator 4
 
1.4%
Other Symbol 1
 
0.3%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
산 27
 
11.2%
업 25
 
10.4%
주 24
 
10.0%
개 11
 
4.6%
발 11
 
4.6%
성 7
 
2.9%
라 6
 
2.5%
서 5
 
2.1%
가 5
 
2.1%
일 5
 
2.1%
Other values (55) 114
47.5%
Open Punctuation
ValueCountFrequency (%)
( 23
100.0%
Close Punctuation
ValueCountFrequency (%)
) 23
100.0%
Space Separator
ValueCountFrequency (%)
4
100.0%
Other Symbol
ValueCountFrequency (%)
㈜ 1
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 241
82.8%
Common 50
 
17.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
산 27
 
11.2%
업 25
 
10.4%
주 24
 
10.0%
개 11
 
4.6%
발 11
 
4.6%
성 7
 
2.9%
라 6
 
2.5%
서 5
 
2.1%
가 5
 
2.1%
일 5
 
2.1%
Other values (56) 115
47.7%
Common
ValueCountFrequency (%)
( 23
46.0%
) 23
46.0%
4
 
8.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 240
82.5%
ASCII 50
 
17.2%
None 1
 
0.3%

Most frequent character per block

Hangul
ValueCountFrequency (%)
산 27
 
11.2%
업 25
 
10.4%
주 24
 
10.0%
개 11
 
4.6%
발 11
 
4.6%
성 7
 
2.9%
라 6
 
2.5%
서 5
 
2.1%
가 5
 
2.1%
일 5
 
2.1%
Other values (55) 114
47.5%
ASCII
ValueCountFrequency (%)
( 23
46.0%
) 23
46.0%
4
 
8.0%
None
ValueCountFrequency (%)
㈜ 1
100.0%

도로명전체주소
Text

Distinct37
Distinct (%)88.1%
Missing0
Missing (%)0.0%
Memory size468.0 B
2023-12-12T16:05:24.358174image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length31
Median length27.5
Mean length25.714286
Min length20

Characters and Unicode

Total characters1080
Distinct characters79
Distinct categories4 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique32 ?
Unique (%)76.2%

Sample

1st row제주특별자치도 서귀포시 산록남로1241번길 168
2nd row제주특별자치도 서귀포시 안덕면 감천로 6-5
3rd row제주특별자치도 서귀포시 성산읍 삼달리 1253-1번지
4th row제주특별자치도 서귀포시 성산읍 삼달리 1253-1번지
5th row제주특별자치도 서귀포시 산록남로1241번길 168
ValueCountFrequency (%)
제주특별자치도 42
22.1%
서귀포시 42
22.1%
표선면 6
 
3.2%
성산읍 6
 
3.2%
일주동로 4
 
2.1%
삼달리 4
 
2.1%
중산간동로 3
 
1.6%
세성로 3
 
1.6%
안덕면 3
 
1.6%
산록남로1241번길 3
 
1.6%
Other values (64) 74
38.9%
2023-12-12T16:05:24.782850image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
178
 
16.5%
주 46
 
4.3%
서 46
 
4.3%
귀 44
 
4.1%
포 43
 
4.0%
제 42
 
3.9%
특 42
 
3.9%
별 42
 
3.9%
자 42
 
3.9%
치 42
 
3.9%
Other values (69) 513
47.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 720
66.7%
Space Separator 178
 
16.5%
Decimal Number 166
 
15.4%
Dash Punctuation 16
 
1.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
주 46
 
6.4%
서 46
 
6.4%
귀 44
 
6.1%
포 43
 
6.0%
제 42
 
5.8%
특 42
 
5.8%
별 42
 
5.8%
자 42
 
5.8%
치 42
 
5.8%
도 42
 
5.8%
Other values (57) 289
40.1%
Decimal Number
ValueCountFrequency (%)
1 34
20.5%
2 24
14.5%
6 21
12.7%
4 19
11.4%
0 17
10.2%
8 17
10.2%
3 16
9.6%
5 10
 
6.0%
7 6
 
3.6%
9 2
 
1.2%
Space Separator
ValueCountFrequency (%)
178
100.0%
Dash Punctuation
ValueCountFrequency (%)
- 16
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 720
66.7%
Common 360
33.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
주 46
 
6.4%
서 46
 
6.4%
귀 44
 
6.1%
포 43
 
6.0%
제 42
 
5.8%
특 42
 
5.8%
별 42
 
5.8%
자 42
 
5.8%
치 42
 
5.8%
도 42
 
5.8%
Other values (57) 289
40.1%
Common
ValueCountFrequency (%)
178
49.4%
1 34
 
9.4%
2 24
 
6.7%
6 21
 
5.8%
4 19
 
5.3%
0 17
 
4.7%
8 17
 
4.7%
3 16
 
4.4%
- 16
 
4.4%
5 10
 
2.8%
Other values (2) 8
 
2.2%

Most occurring blocks

ValueCountFrequency (%)
Hangul 720
66.7%
ASCII 360
33.3%

Most frequent character per block

ASCII
ValueCountFrequency (%)
178
49.4%
1 34
 
9.4%
2 24
 
6.7%
6 21
 
5.8%
4 19
 
5.3%
0 17
 
4.7%
8 17
 
4.7%
3 16
 
4.4%
- 16
 
4.4%
5 10
 
2.8%
Other values (2) 8
 
2.2%
Hangul
ValueCountFrequency (%)
주 46
 
6.4%
서 46
 
6.4%
귀 44
 
6.1%
포 43
 
6.0%
제 42
 
5.8%
특 42
 
5.8%
별 42
 
5.8%
자 42
 
5.8%
치 42
 
5.8%
도 42
 
5.8%
Other values (57) 289
40.1%

전화번호
Text

MISSING 

Distinct26
Distinct (%)78.8%
Missing9
Missing (%)21.4%
Memory size468.0 B
2023-12-12T16:05:24.998337image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length12
Median length12
Mean length12
Min length12

Characters and Unicode

Total characters396
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

Unique20 ?
Unique (%)60.6%

Sample

1st row064-738-8882
2nd row064-792-7398
3rd row064-738-8882
4th row064-733-0166
5th row064-763-5413
ValueCountFrequency (%)
064-738-8882 3
 
9.1%
064-744-8891 2
 
6.1%
064-732-3653 2
 
6.1%
064-762-9500 2
 
6.1%
064-739-2648 2
 
6.1%
064-763-5413 2
 
6.1%
064-787-3470 1
 
3.0%
064-732-7338 1
 
3.0%
064-738-0588 1
 
3.0%
064-738-7335 1
 
3.0%
Other values (16) 16
48.5%
2023-12-12T16:05:25.442147image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
- 66
16.7%
0 51
12.9%
6 50
12.6%
4 50
12.6%
7 45
11.4%
3 38
9.6%
8 38
9.6%
9 18
 
4.5%
2 16
 
4.0%
5 14
 
3.5%

Most occurring categories

ValueCountFrequency (%)
Decimal Number 330
83.3%
Dash Punctuation 66
 
16.7%

Most frequent character per category

Decimal Number
ValueCountFrequency (%)
0 51
15.5%
6 50
15.2%
4 50
15.2%
7 45
13.6%
3 38
11.5%
8 38
11.5%
9 18
 
5.5%
2 16
 
4.8%
5 14
 
4.2%
1 10
 
3.0%
Dash Punctuation
ValueCountFrequency (%)
- 66
100.0%

Most occurring scripts

ValueCountFrequency (%)
Common 396
100.0%

Most frequent character per script

Common
ValueCountFrequency (%)
- 66
16.7%
0 51
12.9%
6 50
12.6%
4 50
12.6%
7 45
11.4%
3 38
9.6%
8 38
9.6%
9 18
 
4.5%
2 16
 
4.0%
5 14
 
3.5%

Most occurring blocks

ValueCountFrequency (%)
ASCII 396
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
- 66
16.7%
0 51
12.9%
6 50
12.6%
4 50
12.6%
7 45
11.4%
3 38
9.6%
8 38
9.6%
9 18
 
4.5%
2 16
 
4.0%
5 14
 
3.5%

데이터기준일자
Categorical

CONSTANT 

Distinct1
Distinct (%)2.4%
Missing0
Missing (%)0.0%
Memory size468.0 B
2022-08-23
42 

Length

Max length10
Median length10
Mean length10
Min length10

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row2022-08-23
2nd row2022-08-23
3rd row2022-08-23
4th row2022-08-23
5th row2022-08-23

Common Values

ValueCountFrequency (%)
2022-08-23 42
100.0%

Length

2023-12-12T16:05:25.726017image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-12T16:05:25.844942image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
2022-08-23 42
100.0%

Correlations

2023-12-12T16:05:25.928264image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
구분인허가일자사업장명도로명전체주소전화번호
구분1.0001.0000.9760.9440.000
인허가일자1.0001.0001.0001.0001.000
사업장명0.9761.0001.0001.0001.000
도로명전체주소0.9441.0001.0001.0001.000
전화번호0.0001.0001.0001.0001.000

Missing values

2023-12-12T16:05:22.914385image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-12T16:05:23.005443image/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

구분인허가일자사업장명도로명전체주소전화번호데이터기준일자
0건설폐기물처리업 중간처분업2020-07-16서귀포산업㈜제주특별자치도 서귀포시 산록남로1241번길 168064-738-88822022-08-23
1건설폐기물처리업 수집운반업2017-08-09(주)산남산업개발제주특별자치도 서귀포시 안덕면 감천로 6-5064-792-73982022-08-23
2건설폐기물처리업 중간처분업2009-10-25보성산업(가칭)제주특별자치도 서귀포시 성산읍 삼달리 1253-1번지<NA>2022-08-23
3건설폐기물처리업 중간처분업2009-12-31보성산업(가칭)제주특별자치도 서귀포시 성산읍 삼달리 1253-1번지<NA>2022-08-23
4건설폐기물처리업 중간처분업2010-06-01서귀포산업 주식회사제주특별자치도 서귀포시 산록남로1241번길 168064-738-88822022-08-23
5건설폐기물처리업 수집운반업2011-08-01혁신환경제주특별자치도 서귀포시 동홍동로26번길 8064-733-01662022-08-23
6건설폐기물처리업 중간처분업2011-01-18일승산업(주)제주특별자치도 서귀포시 성산읍 중산간동로 4364-64064-763-54132022-08-23
7건설폐기물처리업 중간처분업2014-02-28(주)동화산업제주특별자치도 서귀포시 표선면 세성로 650064-744-88912022-08-23
8건설폐기물처리업 수집운반업2007-08-06두원개발제주특별자치도 서귀포시 서귀동 324-2번지064-763-07882022-08-23
9건설폐기물처리업 중간처분업2012-02-23동남산업(주)제주특별자치도 서귀포시 토평공단로106번길 18064-732-36532022-08-23
구분인허가일자사업장명도로명전체주소전화번호데이터기준일자
32건설폐기물처리업 중간처분업2020-11-13한라환경산업(주)제주특별자치도 서귀포시 인정오름로86번길 63064-733-95032022-08-23
33건설폐기물처리업 수집운반업2020-08-05(주)동화산업제주특별자치도 서귀포시 표선면 세성로 650064-744-88912022-08-23
34건설폐기물처리업 수집운반업2013-12-23동남산업(주)제주특별자치도 서귀포시 토평공단로106번길 18064-732-36532022-08-23
35건설폐기물처리업 수집운반업2021-05-21(주)승인자원제주특별자치도 서귀포시 대정읍 암반수마농로 275064-792-42832022-08-23
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