There are still many examples and areas of the docs that use the original plot_width and plot_height properties. We should update all of these to use width and height instead.

cc @tcmetzger

Hi,

Firstly, thank you for your work on Chart-Fx.

We are currently building an application using the library to display multiple huge datasets.
The library works well for 5 to 10 million points, however our clients would like to display even larger datas, going up to 50 to 100 million points. While it is possible to display such datasets, navigating them become difficult as the application

I suggest either adding a short code piece to use the rename() function to change the column "genus" to "genera" (thus alerting the learners to their relationship here, while adding a new function) or changing the column name in the original dataset. Otherwise, I've found that using the correct plural for genus confuses learners who are not biologists. Although it's the R ecology lesson and one

Hello, I would like to know if there is already any method developed to match the flight_ids obtained from So6 to ADS-B files. I’m trying to use the assign_id method for both files but it seems to be assigned differnent new flight-ids for SO6 and ADS-B same flights.

Thank you.

Good afternoon! In line 36 of the 14-tidyr.Rmd, it says

write.csv(gap_wide_betterID,"data/gapminder_wide.csv",row.names = FALSE)

but considering lines 28 to 33, it should be simply

write.csv(gap_wide, "data/gapminder_wide.csv", row.names = FALSE)

I think it would benefit from applying the styler package to the gap_wide code in general, as it seems inconsistent in spacin

Dear Community,

There is a typo in the section titled "The StringsAsFactors argument" after the second block of code that demonstrates the use of the str() function. Right after the code boxes is written "We can see that the $Color and $State columns are factors and $Speed is a numeric column", but the box shows that the $Color column is a vector of strings.

Regards,

Rodolfo

In episode 3 (https://datacarpentry.org/python-ecology-lesson/03-index-slice-subset/index.html, actually listed as 4. in https://datacarpentry.org/python-ecology-lesson/ ), the distinction between .iloc method for accessing entries by position and .loc to access them by identifier is made, but a third possibility is shown with surveys_df[0:3], which accesses the indices by position.

That

We did the first half of this lesson as an online workshop today. The thing that caused the most problems was to start Jupyter Lab in the terminal / command prompt, and to access the files.

We had added a section on downloading and unzipping the dataset to the installation instructions on the course website (https://uio-carpentry.github.io/2021-03-02-uio-python-online/). I tried to instruct peo

Currently all of the metrics computed are independent of a target variable or column, but if lens.summarise took the name of a column as the target variable, the output of some metrics could be more interpretable even if the target variable is not used in any kind of predictive modelling.

A good example of this could be PCA (see #14), which could plot the different categories of the target va

In episode _episodes_rmd/12-time-series-raster.Rmd

There is a big chunk of code that can probably be made to look nicer via dplyr:

# Plot RGB data for Julian day 133
 RGB_133 <- stack("data/NEON-DS-Landsat-NDVI/HARV/2011/RGB/133_HARV_landRGB.tif")
 RGB_133_df <- raster::as.data.frame(RGB_133, xy = TRUE)
 quantiles = c(0.02, 0.98)
 r <- quantile(RGB_133_df$X133_HARV_landRGB.1, q