Overview

Dataset statistics

Number of variables9
Number of observations48
Missing cells123
Missing cells (%)28.5%
Duplicate rows1
Duplicate rows (%)2.1%
Total size in memory3.6 KiB
Average record size in memory75.8 B

Variable types

Unsupported8
Text1

Dataset

Description대기오염측정망운영결과202011
Author전라북도
URLhttps://www.bigdatahub.go.kr/opendata/dataSet/detail.nm?contentId=37&rlik=49451aebf056b486&serviceId=204366

Alerts

Dataset has 1 (2.1%) duplicate rowsDuplicates
Unnamed: 0 has 48 (100.0%) missing valuesMissing
2020년 도시 대기측정망(11월) has 27 (56.2%) missing valuesMissing
Unnamed: 2 has 10 (20.8%) missing valuesMissing
Unnamed: 3 has 6 (12.5%) missing valuesMissing
Unnamed: 4 has 6 (12.5%) missing valuesMissing
Unnamed: 5 has 6 (12.5%) missing valuesMissing
Unnamed: 6 has 7 (14.6%) missing valuesMissing
Unnamed: 7 has 7 (14.6%) missing valuesMissing
Unnamed: 8 has 6 (12.5%) missing valuesMissing
Unnamed: 0 is an unsupported type, check if it needs cleaning or further analysisUnsupported
2020년 도시 대기측정망(11월) 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

Reproduction

Analysis started2024-03-14 02:25:38.948430
Analysis finished2024-03-14 02:25:39.360549
Duration0.41 seconds
Software versionydata-profiling vv4.5.1
Download configurationconfig.json

Variables

Unnamed: 0
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing48
Missing (%)100.0%
Memory size564.0 B

2020년 도시 대기측정망(11월)
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing27
Missing (%)56.2%
Memory size516.0 B

Unnamed: 2
Text

MISSING 

Distinct38
Distinct (%)100.0%
Missing10
Missing (%)20.8%
Memory size516.0 B
2024-03-14T11:25:39.468607image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Length

Max length6
Median length3
Mean length3.4736842
Min length2

Characters and Unicode

Total characters132
Distinct characters60
Distinct categories2 ?
Distinct scripts2 ?
Distinct blocks2 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique38 ?
Unique (%)100.0%

Sample

1st row노송동
2nd row삼천동
3rd row송천동
4th row팔복동
5th row혁신동
ValueCountFrequency (%)
평균 6
 
13.3%
신풍동 1
 
2.2%
정읍시 1
 
2.2%
요촌동 1
 
2.2%
고산면 1
 
2.2%
봉동읍 1
 
2.2%
완주군 1
 
2.2%
진안읍 1
 
2.2%
무주읍 1
 
2.2%
연지동 1
 
2.2%
Other values (30) 30
66.7%
2024-03-14T11:25:39.845435image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/

Most occurring characters

ValueCountFrequency (%)
동 16
 
12.1%
읍 10
 
7.6%
8
 
6.1%
평 7
 
5.3%
균 7
 
5.3%
면 5
 
3.8%
신 4
 
3.0%
시 4
 
3.0%
산 4
 
3.0%
창 3
 
2.3%
Other values (50) 64
48.5%

Most occurring categories

ValueCountFrequency (%)
Other Letter 124
93.9%
Space Separator 8
 
6.1%

Most frequent character per category

Other Letter
ValueCountFrequency (%)
동 16
 
12.9%
읍 10
 
8.1%
평 7
 
5.6%
균 7
 
5.6%
면 5
 
4.0%
신 4
 
3.2%
시 4
 
3.2%
산 4
 
3.2%
창 3
 
2.4%
고 3
 
2.4%
Other values (49) 61
49.2%
Space Separator
ValueCountFrequency (%)
8
100.0%

Most occurring scripts

ValueCountFrequency (%)
Hangul 124
93.9%
Common 8
 
6.1%

Most frequent character per script

Hangul
ValueCountFrequency (%)
동 16
 
12.9%
읍 10
 
8.1%
평 7
 
5.6%
균 7
 
5.6%
면 5
 
4.0%
신 4
 
3.2%
시 4
 
3.2%
산 4
 
3.2%
창 3
 
2.4%
고 3
 
2.4%
Other values (49) 61
49.2%
Common
ValueCountFrequency (%)
8
100.0%

Most occurring blocks

ValueCountFrequency (%)
Hangul 124
93.9%
ASCII 8
 
6.1%

Most frequent character per block

Hangul
ValueCountFrequency (%)
동 16
 
12.9%
읍 10
 
8.1%
평 7
 
5.6%
균 7
 
5.6%
면 5
 
4.0%
신 4
 
3.2%
시 4
 
3.2%
산 4
 
3.2%
창 3
 
2.4%
고 3
 
2.4%
Other values (49) 61
49.2%
ASCII
ValueCountFrequency (%)
8
100.0%

Unnamed: 3
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing6
Missing (%)12.5%
Memory size516.0 B

Unnamed: 4
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing6
Missing (%)12.5%
Memory size516.0 B

Unnamed: 5
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing6
Missing (%)12.5%
Memory size516.0 B

Unnamed: 6
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing7
Missing (%)14.6%
Memory size516.0 B

Unnamed: 7
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing7
Missing (%)14.6%
Memory size516.0 B

Unnamed: 8
Unsupported

MISSING  REJECTED  UNSUPPORTED 

Missing6
Missing (%)12.5%
Memory size516.0 B

Missing values

2024-03-14T11:25:39.030045image/svg+xmlMatplotlib v3.7.2, https://matplotlib.org/
A simple visualization of nullity by column.
2024-03-14T11:25:39.146871image/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.
2024-03-14T11:25:39.282799image/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

Unnamed: 02020년 도시 대기측정망(11월)Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7Unnamed: 8
0<NA>NaN<NA>NaNNaNNaNNaNNaNNaN
1<NA>측정지역<NA>측 정 항 목NaNNaNNaNNaNNaN
2<NA>환경기준\n \n 지 점<NA>O3NO2SO2COPM10PM2.5
3<NA>NaN<NA>8시간평균 0.06ppm이하연간 평균0.03ppm 이하연간평균0.02ppm이하8시간평균 9ppm이하연간평균 50㎍/㎥이하연간평균 15㎍/㎥이하
4<NA>NaN<NA>1시간평균 0.10ppm이하24시간평균0.06ppm 이하24시간 평균0.05ppm이하1시간평균 25ppm이하24시간평균100㎍/㎥이하24시간평균35㎍/㎥이하
5<NA>NaN<NA>NaN1시간평균 0.10ppm 이하1시간평균0.15ppm이하NaNNaNNaN
6<NA>전주노송동0.0220.0180.0030.63417
7<NA>NaN삼천동0.0230.020.0030.43720
8<NA>NaN송천동0.0180.0180.0030.43620
9<NA>NaN팔복동0.0220.0250.0020.33127
Unnamed: 02020년 도시 대기측정망(11월)Unnamed: 2Unnamed: 3Unnamed: 4Unnamed: 5Unnamed: 6Unnamed: 7Unnamed: 8
38<NA>NaN심원면0.0330.0070.0030.32819
39<NA>NaN고창군 평균0.0320.0080.0030.32819
40<NA>부안부안읍0.0270.0190.0020.54123
41<NA>NaN평 균0.0240.0140.0030.43622
42<NA>2020년 도로변 대기측정망(11월)<NA>NaNNaNNaNNaNNaNNaN
43<NA>NaN<NA>NaNNaNNaNNaNNaNNaN
44<NA>3지점O3NO2SO2COPM10PM2.5
45<NA>전주서신동-0.020.0030.53819
46<NA>1. 일(월,년)평균 = 해당지역의 전측정소 시간 측정치의 누적값÷해당지역의 모든측정소 시간측정치수<NA>NaNNaNNaNNaNNaN.
47<NA>2. 위 자료는 보건환경연구원 1차 확정 자료로, 환경부 자료와 상이할 수 있음<NA>NaNNaNNaNNaNNaNNaN

Duplicate rows

Most frequently occurring

Unnamed: 2# duplicates
0<NA>10