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data-wrangling

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wetneb
wetneb commented Feb 18, 2022

Sometimes the cell UI gets URL boundaries wrong.

To Reproduce

Create a project and put the following string in a cell:

{{Information
|Description    = {{en|1=<br>
:'''Species''' {{Species-inline|vernacular=Wood Duck|binominal=Aix sponsa}}
:'''Recordist''' Jonathon Jongsma
:'''Remarks''' Bird seen. Several widely-spaced and rather strange hoarse 'screams' from a female wood duck s
davis68
davis68 commented Sep 17, 2020
  • I felt like nunique was arbitrarily (re)introduced when it was necessary. It wouldn't be top-of-mind for students solving problems.
  • The lesson answers need to be adjacent to the exercises.
  • I like the pre-introduction of masks and then circling back around to explain them.
  • I feel like Part 4 needs to be broken up and integrated across other lessons: it felt thin on its own.
  • Horizo
umnik20
umnik20 commented May 4, 2020

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

jdinklo
jdinklo commented Feb 24, 2022

https://swcarpentry.github.io/python-novice-gapminder/01-run-quit/index.html
Update in wording

I would like to suggest improvement to the below opening paragraph, found at https://swcarpentry.github.io/python-novice-gapminder/01-run-quit/index.html

"Many software developers will often use an integrated development environment (IDE) or a text editor to create and edit their Python programs

lachlandeer
lachlandeer commented Jul 30, 2018

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

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