• Optional: More Python…

• I found an excellent set of slides: (Kane, 2019).
• Rather than reinvent this excellent wheel, I suggest you work through the following:
  • Background & Basics
  • Digging Deeper into Python Programming Constructs

This talk was produced on 2020-04-14 in RStudio using R Markdown. The code and materials used to generate the slides may be found at https://github.com/psu-psychology/psy-525-reproducible-research-2020. Information about the R Session that produced the code is as follows:

## R version 3.6.2 (2019-12-12)
## Platform: x86_64-apple-darwin15.6.0 (64-bit)
## Running under: macOS Mojave 10.14.6
## 
## Matrix products: default
## BLAS:   /System/Library/Frameworks/Accelerate.framework/Versions/A/Frameworks/vecLib.framework/Versions/A/libBLAS.dylib
## LAPACK: /Library/Frameworks/R.framework/Versions/3.6/Resources/lib/libRlapack.dylib
## 
## locale:
## [1] en_US.UTF-8/en_US.UTF-8/en_US.UTF-8/C/en_US.UTF-8/en_US.UTF-8
## 
## attached base packages:
## [1] stats     graphics  grDevices utils     datasets  methods  
## [7] base     
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## other attached packages:
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## [4] purrr_0.3.3     readr_1.3.1     tidyr_1.0.2    
## [7] tibble_3.0.0    ggplot2_3.3.0   tidyverse_1.3.0
## 
## loaded via a namespace (and not attached):
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##  [4] lattice_0.20-40  colorspace_1.4-1 vctrs_0.2.4     
##  [7] generics_0.0.2   htmltools_0.4.0  yaml_2.2.1      
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