openair | Tools for air quality data analysis | Data Visualization library

I have a time Series DataFrame:

[https://www.dropbox.com/s/elaxfuvqyip1eq8/SampleDF.csv?dl=0][1]

My intention is to divide this DataFrame into different seasons according to:

1. winter: Dec Jan Feb
2. Pre-monsoon: Mar Apr May Jun15 (i.e. till 15th of June)
3. Monsoon: 15Jun Jul Aug Sep (i.e. from 15th of June)
4. Post-monsoon: Oct Nov.

I tried using openair package function

selectByDate()

But no luck yet. Being novice in R. Any help would be highly appreciated.

Thanks!

I have two plots i.e. Taylor diagram and ggplot. I would like to plot them in a single plot (side-by-side). I tried "library(patchwork)", but unfortunately it doesn't work.

I'm working with a large dataset of different variables collected during the dives of elephant seals. I would like to analyze my data on a fine-scale (20 second intervals). I want to bin my data into 20 second intervals, basically I just want to get the mean for every 20 seconds, so I can run more analysis on these intervals of data. However, I need to group my data by dive # so that I'm not binning information from separate dives.

There are three methods I've tried so far:

• period.apply() but I cannot group with this function.
• split() to subset my data by dive #, but can't seem to find a way to then calculate the mean of different columns over 20 second intervals within these subsets.
• openair package, using timeaverage() but continue to get an error (see code below).

Below is what the data looks like, and the code I've tried. I would like the means of Depth, MSA, rate_s, and HR for each 20 second window - grouped by diveNum and ~ideally~ also D_phase.

I need to read OpenAir files in Python.

According to the following vector driver description, GDAL has built-in OpenAir functionality: https://gdal.org/drivers/vector/openair.html

However there is no example code for reading such OpenAir files. So far I have tried to read a sample file using the following lines:

I made a plot for season (summer, spring, autumn and winter) using pollutionRose from the openair package. Here is the code:

I have second-by-second data for channels A, B, and C as shown below (this just shows the first 6 rows):

I am new to utilizing R and have a question regarding subsetting data in a large dataset into months. I am attempting to subset the data into different months starting with data from January. The package that I have loaded is openair.

I load the following file into regarding COVID data and have named it COVIDcases:

COVIDcases <- read.csv("https://query.data.world/s/lysuc3ab7q3zubthc6paesbrsff3oo", header=TRUE, stringsAsFactors=FALSE);

After loading the dataset I convert the date column to date instead of character

COVIDcases$Date <- as.Date(paste(COVIDcases$Date), "%m/%d/%y")

I then do a selectByDate statement to try and only analyze the January data.

JanuaryCasesdata <-selectByDate(COVIDcases$Date, start = "2020-01-01", end = "2020-01-31")

This is where I encounter a problem and keep getting the error:

"Error in `[.default`(mydata, , Names) : incorrect number of dimensions"

Is there anything in particular that I am doing wrong such as taking the wrong steps to subset the data?

I have already converted my data to an xts object and this error persists. I think it is related to my date format but, I have used the function as.Date to make sure my date format is right. Here is my code so far:

I have 15-min observations of air temperature Temp data that I would like to derive a daily mean for. I have been trying to use the openair package with the timeAverage function to get to this answer because it allows the user to set a minimum threshold for the amount of missing data that is allowed before it will derive a daily mean. However I keep getting the same error message associated with not being able to find the variable date.

Here is an example of my dataframe