Overview

Dataset statistics

Number of variables5
Number of observations82
Missing cells0
Missing cells (%)0.0%
Duplicate rows2
Duplicate rows (%)2.4%
Total size in memory3.3 KiB
Average record size in memory41.6 B

Variable types

DateTime1
Text1
Categorical3

Dataset

Description부산광역시사상구_대형폐기물수거현황_20221102
Author부산광역시 사상구
URLhttp://data.busan.go.kr/dataSet/detail.nm?contentId=10&publicdatapk=15093984

Alerts

수거일자 has constant value ""Constant
관리기관 has constant value ""Constant
전화번호 has constant value ""Constant
Dataset has 2 (2.4%) duplicate rowsDuplicates

Reproduction

Analysis started2023-12-10 16:15:46.918215
Analysis finished2023-12-10 16:15:47.433368
Duration0.52 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

수거일자
Date

CONSTANT 

Distinct1
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size788.0 B
Minimum2021-10-27 00:00:00
Maximum2021-10-27 00:00:00
2023-12-11T01:15:47.505838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
2023-12-11T01:15:47.651758image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram with fixed size bins (bins=1)

폐기물 명
Text

Distinct70
Distinct (%)85.4%
Missing0
Missing (%)0.0%
Memory size788.0 B
2023-12-11T01:15:47.950838image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length28
Median length18
Mean length6.8902439
Min length1

Characters and Unicode

Total characters565
Distinct characters123
Distinct categories6 ?
Distinct scripts3 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique62 ?
Unique (%)75.6%

Sample

1st row병풍, 상, 목재류 조금
2nd row책장
3rd row유모차
4th row상, 골프가방
5th row장식장, 3인쇼파, 1인쇼파2, 의자, 탁자
ValueCountFrequency (%)
의자 8
 
7.5%
전기매트 5
 
4.7%
5단서랍장 4
 
3.7%
상 3
 
2.8%
책상 3
 
2.8%
책장 3
 
2.8%
3인쇼파 3
 
2.8%
매트리스 2
 
1.9%
의자2 2
 
1.9%
1인쇼파2 2
 
1.9%
Other values (64) 72
67.3%
2023-12-11T01:15:48.522768image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
, 68
 
12.0%
장 29
 
5.1%
27
 
4.8%
자 23
 
4.1%
트 22
 
3.9%
매 20
 
3.5%
의 19
 
3.4%
2 19
 
3.4%
상 15
 
2.7%
기 14
 
2.5%
Other values (113) 309
54.7%

Most occurring categories

ValueCountFrequency (%)
Other Letter 421
74.5%
Other Punctuation 68
 
12.0%
Decimal Number 43
 
7.6%
Space Separator 27
 
4.8%
Open Punctuation 3
 
0.5%
Close Punctuation 3
 
0.5%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
장 29
 
6.9%
자 23
 
5.5%
트 22
 
5.2%
매 20
 
4.8%
의 19
 
4.5%
상 15
 
3.6%
기 14
 
3.3%
책 13
 
3.1%
리 12
 
2.9%
파 12
 
2.9%
Other values (103) 242
57.5%
Decimal Number
ValueCountFrequency (%)
2 19
44.2%
3 12
27.9%
5 5
 
11.6%
4 4
 
9.3%
1 2
 
4.7%
8 1
 
2.3%
Other Punctuation
ValueCountFrequency (%)
, 68
100.0%
Space Separator
ValueCountFrequency (%)
27
100.0%
Open Punctuation
ValueCountFrequency (%)
( 3
100.0%
Close Punctuation
ValueCountFrequency (%)
) 3
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 420
74.3%
Common 144
 
25.5%
Han 1
 
0.2%

Most frequent character per script

Hangul
ValueCountFrequency (%)
장 29
 
6.9%
자 23
 
5.5%
트 22
 
5.2%
매 20
 
4.8%
의 19
 
4.5%
상 15
 
3.6%
기 14
 
3.3%
책 13
 
3.1%
리 12
 
2.9%
파 12
 
2.9%
Other values (102) 241
57.4%
Common
ValueCountFrequency (%)
, 68
47.2%
27
 
18.8%
2 19
 
13.2%
3 12
 
8.3%
5 5
 
3.5%
4 4
 
2.8%
( 3
 
2.1%
) 3
 
2.1%
1 2
 
1.4%
8 1
 
0.7%
Han
ValueCountFrequency (%)
大 1
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 420
74.3%
ASCII 144
 
25.5%
CJK 1
 
0.2%

Most frequent character per block

ASCII
ValueCountFrequency (%)
, 68
47.2%
27
 
18.8%
2 19
 
13.2%
3 12
 
8.3%
5 5
 
3.5%
4 4
 
2.8%
( 3
 
2.1%
) 3
 
2.1%
1 2
 
1.4%
8 1
 
0.7%
Hangul
ValueCountFrequency (%)
장 29
 
6.9%
자 23
 
5.5%
트 22
 
5.2%
매 20
 
4.8%
의 19
 
4.5%
상 15
 
3.6%
기 14
 
3.3%
책 13
 
3.1%
리 12
 
2.9%
파 12
 
2.9%
Other values (102) 241
57.4%
CJK
ValueCountFrequency (%)
大 1
100.0%

수거동
Categorical

Distinct8
Distinct (%)9.8%
Missing0
Missing (%)0.0%
Memory size788.0 B
주례동
21 
모라동
14 
덕포동
13 
학장동
11 
괘법동
8 
Other values (3)
15 

Length

Max length3
Median length3
Mean length3
Min length3

Unique

Unique1 ?
Unique (%)1.2%

Sample

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

Common Values

ValueCountFrequency (%)
주례동 21
25.6%
모라동 14
17.1%
덕포동 13
15.9%
학장동 11
13.4%
괘법동 8
 
9.8%
엄궁동 8
 
9.8%
감전동 6
 
7.3%
삼락동 1
 
1.2%

Length

2023-12-11T01:15:48.746412image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:15:48.932673image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
주례동 21
25.6%
모라동 14
17.1%
덕포동 13
15.9%
학장동 11
13.4%
괘법동 8
 
9.8%
엄궁동 8
 
9.8%
감전동 6
 
7.3%
삼락동 1
 
1.2%

관리기관
Categorical

CONSTANT 

Distinct1
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size788.0 B
청소행정과
82 

Length

Max length5
Median length5
Mean length5
Min length5

Unique

Unique0 ?
Unique (%)0.0%

Sample

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

Common Values

ValueCountFrequency (%)
청소행정과 82
100.0%

Length

2023-12-11T01:15:49.159012image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:15:49.389997image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
청소행정과 82
100.0%

전화번호
Categorical

CONSTANT 

Distinct1
Distinct (%)1.2%
Missing0
Missing (%)0.0%
Memory size788.0 B
051-310-4332
82 

Length

Max length12
Median length12
Mean length12
Min length12

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st row051-310-4332
2nd row051-310-4332
3rd row051-310-4332
4th row051-310-4332
5th row051-310-4332

Common Values

ValueCountFrequency (%)
051-310-4332 82
100.0%

Length

2023-12-11T01:15:49.524475image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2023-12-11T01:15:49.661734image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
ValueCountFrequency (%)
051-310-4332 82
100.0%

Correlations

2023-12-11T01:15:49.753798image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
폐기물 명수거동
폐기물 명1.0000.000
수거동0.0001.000

Missing values

2023-12-11T01:15:47.204226image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2023-12-11T01:15:47.355823image/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

수거일자폐기물 명수거동관리기관전화번호
02021-10-27병풍, 상, 목재류 조금모라동청소행정과051-310-4332
12021-10-27책장모라동청소행정과051-310-4332
22021-10-27유모차모라동청소행정과051-310-4332
32021-10-27상, 골프가방모라동청소행정과051-310-4332
42021-10-27장식장, 3인쇼파, 1인쇼파2, 의자, 탁자모라동청소행정과051-310-4332
52021-10-27비데모라동청소행정과051-310-4332
62021-10-273단서랍장, 스펀지매트모라동청소행정과051-310-4332
72021-10-27책장모라동청소행정과051-310-4332
82021-10-27전기매트모라동청소행정과051-310-4332
92021-10-27온수매트모라동청소행정과051-310-4332
수거일자폐기물 명수거동관리기관전화번호
722021-10-27의자4주례동청소행정과051-310-4332
732021-10-27상2, 전기매트주례동청소행정과051-310-4332
742021-10-27의자주례동청소행정과051-310-4332
752021-10-27농, 쇼파주례동청소행정과051-310-4332
762021-10-27농주례동청소행정과051-310-4332
772021-10-27화장대,나무계단,옷걸이주례동청소행정과051-310-4332
782021-10-27옥매트주례동청소행정과051-310-4332
792021-10-27매트리스,작은가구주례동청소행정과051-310-4332
802021-10-27카펫,블라인드2,상주례동청소행정과051-310-4332
812021-10-27협탁,렌지대주례동청소행정과051-310-4332

Duplicate rows

Most frequently occurring

수거일자폐기물 명수거동관리기관전화번호# duplicates
02021-10-27쇼파패드2괘법동청소행정과051-310-43322
12021-10-27책장모라동청소행정과051-310-43322