Overview

Dataset statistics

Number of variables17
Number of observations22
Missing cells46
Missing cells (%)12.3%
Duplicate rows1
Duplicate rows (%)4.5%
Total size in memory3.1 KiB
Average record size in memory142.0 B

Variable types

Text1
Unsupported16

Dataset

Description부산광역시_쓰레기발생량현황_20221231
Author부산광역시
URLhttp://data.busan.go.kr/dataSet/detail.nm?contentId=10&publicdatapk=3075849

Alerts

Dataset has 1 (4.5%) duplicate rowsDuplicates
1. 생활폐기물 관리 구역 현황 has 2 (9.1%) missing valuesMissing
Unnamed: 1 has 2 (9.1%) missing valuesMissing
Unnamed: 2 has 3 (13.6%) missing valuesMissing
Unnamed: 3 has 3 (13.6%) missing valuesMissing
Unnamed: 4 has 3 (13.6%) missing valuesMissing
Unnamed: 5 has 2 (9.1%) missing valuesMissing
Unnamed: 6 has 3 (13.6%) missing valuesMissing
Unnamed: 7 has 3 (13.6%) missing valuesMissing
Unnamed: 8 has 3 (13.6%) missing valuesMissing
Unnamed: 9 has 2 (9.1%) missing valuesMissing
Unnamed: 10 has 3 (13.6%) missing valuesMissing
Unnamed: 11 has 3 (13.6%) missing valuesMissing
Unnamed: 12 has 3 (13.6%) missing valuesMissing
Unnamed: 13 has 2 (9.1%) missing valuesMissing
Unnamed: 14 has 3 (13.6%) missing valuesMissing
Unnamed: 15 has 3 (13.6%) missing valuesMissing
Unnamed: 16 has 3 (13.6%) missing valuesMissing
Unnamed: 1 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 2 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 3 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 4 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 5 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 6 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 7 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 8 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
Unnamed: 10 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 11 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 12 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 13 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 14 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 15 is an unsupported type, check if it needs cleaning or further analysisUnsupported
Unnamed: 16 is an unsupported type, check if it needs cleaning or further analysisUnsupported

Reproduction

Analysis started2024-03-13 13:18:51.985962
Analysis finished2024-03-13 13:18:53.120396
Duration1.13 second
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

1. 생활폐기물 관리 구역 현황
Text

MISSING 

Distinct20
Distinct (%)100.0%
Missing2
Missing (%)9.1%
Memory size308.0 B
2024-03-13T22:18:53.247903image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length20
Median length2
Mean length2.9
Min length2

Characters and Unicode

Total characters58
Distinct characters37
Distinct categories3 ?
Distinct scripts2 ?
Distinct blocks3 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique20 ?
Unique (%)100.0%

Sample

1st row가. 시·도 생활폐기물 관리구역 현황
2nd row시도
3rd row전국
4th row서울
5th row부산
ValueCountFrequency (%)
울산 1
 
4.2%
시도 1
 
4.2%
세종 1
 
4.2%
경남 1
 
4.2%
경북 1
 
4.2%
전남 1
 
4.2%
전북 1
 
4.2%
충남 1
 
4.2%
충북 1
 
4.2%
강원 1
 
4.2%
Other values (14) 14
58.3%
2024-03-13T22:18:53.573740image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
4
 
6.9%
전 4
 
6.9%
남 3
 
5.2%
북 3
 
5.2%
경 3
 
5.2%
주 2
 
3.4%
충 2
 
3.4%
산 2
 
3.4%
기 2
 
3.4%
울 2
 
3.4%
Other values (27) 31
53.4%

Most occurring categories

ValueCountFrequency (%)
Other Letter 52
89.7%
Space Separator 4
 
6.9%
Other Punctuation 2
 
3.4%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
전 4
 
7.7%
남 3
 
5.8%
북 3
 
5.8%
경 3
 
5.8%
주 2
 
3.8%
충 2
 
3.8%
산 2
 
3.8%
기 2
 
3.8%
울 2
 
3.8%
구 2
 
3.8%
Other values (24) 27
51.9%
Other Punctuation
ValueCountFrequency (%)
· 1
50.0%
. 1
50.0%
Space Separator
ValueCountFrequency (%)
4
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 52
89.7%
Common 6
 
10.3%

Most frequent character per script

Hangul
ValueCountFrequency (%)
전 4
 
7.7%
남 3
 
5.8%
북 3
 
5.8%
경 3
 
5.8%
주 2
 
3.8%
충 2
 
3.8%
산 2
 
3.8%
기 2
 
3.8%
울 2
 
3.8%
구 2
 
3.8%
Other values (24) 27
51.9%
Common
ValueCountFrequency (%)
4
66.7%
· 1
 
16.7%
. 1
 
16.7%

Most occurring blocks

ValueCountFrequency (%)
Hangul 52
89.7%
ASCII 5
 
8.6%
None 1
 
1.7%

Most frequent character per block

ASCII
ValueCountFrequency (%)
4
80.0%
. 1
 
20.0%
Hangul
ValueCountFrequency (%)
전 4
 
7.7%
남 3
 
5.8%
북 3
 
5.8%
경 3
 
5.8%
주 2
 
3.8%
충 2
 
3.8%
산 2
 
3.8%
기 2
 
3.8%
울 2
 
3.8%
구 2
 
3.8%
Other values (24) 27
51.9%
None
ValueCountFrequency (%)
· 1
100.0%

Unnamed: 1
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2
Missing (%)9.1%
Memory size308.0 B

Unnamed: 2
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3
Missing (%)13.6%
Memory size308.0 B

Unnamed: 3
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3
Missing (%)13.6%
Memory size308.0 B

Unnamed: 4
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3
Missing (%)13.6%
Memory size308.0 B

Unnamed: 5
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2
Missing (%)9.1%
Memory size308.0 B

Unnamed: 6
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3
Missing (%)13.6%
Memory size308.0 B

Unnamed: 7
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3
Missing (%)13.6%
Memory size308.0 B

Unnamed: 8
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3
Missing (%)13.6%
Memory size308.0 B

Unnamed: 9
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2
Missing (%)9.1%
Memory size308.0 B

Unnamed: 10
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3
Missing (%)13.6%
Memory size308.0 B

Unnamed: 11
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3
Missing (%)13.6%
Memory size308.0 B

Unnamed: 12
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3
Missing (%)13.6%
Memory size308.0 B

Unnamed: 13
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing2
Missing (%)9.1%
Memory size308.0 B

Unnamed: 14
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3
Missing (%)13.6%
Memory size308.0 B

Unnamed: 15
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3
Missing (%)13.6%
Memory size308.0 B

Unnamed: 16
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing3
Missing (%)13.6%
Memory size308.0 B

Missing values

2024-03-13T22:18:52.116212image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-13T22:18:52.320852image/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.
2024-03-13T22:18:52.812694image/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

1. 생활폐기물 관리 구역 현황Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7Unnamed: 8Unnamed: 9Unnamed: 10Unnamed: 11Unnamed: 12Unnamed: 13Unnamed: 14Unnamed: 15Unnamed: 16
0가. 시·도 생활폐기물 관리구역 현황NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
1<NA>NaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaNNaN
2시도전체행정구역NaNNaNNaN생활폐기물 관리구역NaNNaNNaN생활폐기물 관리제외지역NaNNaNNaN관리제외지역 비율(%)NaNNaNNaN
3<NA>면적(㎢)인구(명)동(읍·면)수(개소)세대수(가구)면적(㎢)인구(명)동(읍·면)수(개소)세대수(가구)면적(㎢)인구(명)동(읍·면)수(개소)세대수(가구)면적비인구비동수비세대수비
4전국100491.1952628623352423705814100085.4152614663351823697131405.7813960686830.400.20
5서울605.2496676694264446296605.249667669426444629600000000
6부산771.2633606752051555867771.263360675205155586700000000
7대구885.2223932591421070873885.222393259142107087300000000
8인천1067.04303916315513226321060.05303877815513223856.9938502470.7000
9광주501.12145401797652355501.1214540179765235500000000
1. 생활폐기물 관리 구역 현황Unnamed: 1Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7Unnamed: 8Unnamed: 9Unnamed: 10Unnamed: 11Unnamed: 12Unnamed: 13Unnamed: 14Unnamed: 15Unnamed: 16
12세종464.9138892722159386464.913889272215938600000000
13경기10198.3313972297567591369410198.3313972297567591369400000000
14강원16875.1155697019375548116716.171556521191755197158.9344922840.9010
15충북7406.7116363281537718487390.91163631115377183515.8170130.2000
16충남8247.21219419620810190938228.952192231208101801118.261965010820.20.100.1
17전북8078.2518045482438558498068.251802954243854762101594010870.10.100.1
18전남12360.34185668529790771012221.931849892293903448138.416793442621.10.41.30.5
19경북19036.072657547330128687319033.77265736633012867722.318101010000
20경남10541.533350883305151693010486.443348307305151532355.092576016070.50.100.1
21제주1850.21699751433113551850.216997514331135500000000

Duplicate rows

Most frequently occurring

1. 생활폐기물 관리 구역 현황# duplicates
0<NA>2