ozone | Pure-rust key/value store based on BoltDB | Key Value Database library

I just had to re-install Ableton 11 and all plugins after a computer crash (reset Windows). I opened my last project in Ableton and three tracks cut out randomly for about 1-2 seconds before coming back (all are audio tracks with vocals, lots of filters (stock, Ozone, etc)). It only happens to these three tracks with the vocals, the other 10+ tracks are running fine (audio and MIDI). Weirdly, these random drop outs also happen at the exported WAV/MP3 files.

I tried all things I found on Google:

Update and reinstall Ableton (11.0.5 now) Freeze the audio tracks Turn off all plugins/filters on the affected tracks. Edit buffer size (tried 256, 512, 2014, 2096 and maximum buffer size) I have an i7 processor, 8GB ram, 512GB SSD hard drive (it worked perfectly before so it can't be the hardware).

Any ideas why this is happening?

Cheers

My Goal: use pyelftool to retrieve variables absolute placement and functions absolute address from an elf file to automatize breakpoint placement for whitebox testing.

my code:

In R, I am trying to generate a column of normally distributed random values based on columns existing in the dataframe. As there are NAs in the columns I am using, NAs are returned in the new column. Is there a way I can ignore these NAs?

I've used the built-in "airquality" data set as a dummy example to illustrate my problem as it includes NAs.

Example Code:

I have 2 dataframes which i need to make into one. The first is 'GDP' and the second is 'Death_rates'. I want to combine the data from both matching up to the country and year columns. Assume i need to use rbind but not sure on how to match up the data from the 2nd dataset with the first.

GDP has colnames of 'Country' 'Year' 'GDP' Death_rates has colnames of 'Country' 'Year' 'Total deaths' 'Indoor deaths' 'Particlate matter' 'Ozone'

Intending to get one dataframe with 'Country' 'Year' 'Total deaths' 'Indoor deaths' 'Particlate matter' 'Ozone' 'GDP'

I have a list with approximately 50 (slots) - dataframes. Each and every element of this list (dataframe) has 10 columns, 3 of which correspond to "year", "month" and "day". How can I cbind those three columns into one (by creating new column), in every dataframe of this list, and convert them at the same time to as.Date format without using the dplyr package .

I'm sending a reproducible example:

I want to apply broom::tidy() to models nested in a fixest_multi object and extract the names of each list level as data frame columns. Here's an example of what I mean.

Here is small portion of my data in dictionary format.

I have hourly data for each day of the year for 11 years. I want to find the maximum ozone value each day (I have 6 ozone columns), but I want to keep the entire row of data for the hour mark that the maximum value occurred, incluiding the date. I have a lot of meteorological parameters stored in this dataframe (like temperature, wind speed, etc) and don't want the code to drop any of the other columns. I want the code to show me every detail of the line, including the datetime column, that the maximum ozone value occurs. The important component of this code is that I need the maximum ozone value for any given day, while preserving all other rows of data, including the datetime column, meaning I want to see the year-month-day-hour that the maximum ozone value occurred.

Here's the link to my csv file: https://drive.google.com/file/d/1iyrvbD9gPHoTmwhSxo8aPfgfAIbpOBK6/view?usp=sharing

Here's the code I have tried thus far:

I have an app that I'd like to be able to have the title change once there is more than 1 input selected in a selectizeInput. I know this is a simple thing but I can't seem to figure it out!

Sample of data: