R-Ladies Freiburg: Tidy Tuesdays Online 21.07.2020

# R-Ladies Freiburg: Tidy Tuesdays Online 21.07.2020 This is an online space for members and guests of R-Ladies Freiburg to exchange Tidy Tuesday ideas and results during our online meetups. ## What is Tidy Tuesday? TidyTuesday is an iniative from the [R for Data Science](https://r4ds.had.co.nz) community and focuses on data wrangling and plotting, but can also be used to practice modeling and just about anything else. Many participants choose to share their resulting graphs on [Twitter](https://twitter.com/hashtag/tidytuesday?lang=en) and/or their code in a [Github repository](https://github.com/kyla-mcconnell/tidy-tuesday). ## Data Source: https://github.com/rfordatascience/tidytuesday Select the week you want to work with, and copy and paste the readr command, which will load the dataset directly from a Github link (no downloads required) ## Where do I start? - Read the ReadMe file of the dataset you're interested in using -- this often links to relevant articles! - Narrow it down! Select only 2 or 3 columns of a dataset and start there. - Think about data types (i.e. how can I plot a continuous variable like speed against a categorical data like car model?) - Do you expect a certain variable to be related with another? - Can you imagine a certain visualization given the variables? - Start by exploring -- make several quick and dirty graphs (if your ggplot skills allow for this!) and decide which is the most interesting, then try to refine that one! - Check out past Twitter entries on [this Shiny server](https://nsgrantham.shinyapps.io/tidytuesdayrocks/?_ga=2.50665705.195055622.1591790935-834839152.1591790935) to see what others have done (past datasets only) - Watch live coding on Youtube from one of the previous datasets, i.e. machine learning with tidymodels with Julia Silge of RStudio - Start with a topic you want to learn (i.e. sentiment analysis of text, interactive maps) and look for a dataset that could be used for that ## Ideas - [Week 23: African American History](https://github.com/rfordatascience/tidytuesday/blob/master/data/2020/2020-06-16/readme.md) - Ages, genders and countries of freed slaves - Map data of ship routes - [Week 22: African American Achievements](https://github.com/rfordatascience/tidytuesday/blob/master/data/2020/2020-06-09/readme.md) - Timeline of (highlighted) achievements by Black women - [Week 22: Marble Races](https://github.com/rfordatascience/tidytuesday/blob/master/data/2020/2020-06-02/readme.md) - ? - [Week 22: Cocktails](https://github.com/rfordatascience/tidytuesday/blob/master/data/2020/2020-05-26/readme.md) - Shiny dashboard where you enter which alcohol types you have at home and are suggested a random cocktail to make - [Week 21: Beach Volleyball](https://github.com/rfordatascience/tidytuesday/blob/master/data/2020/2020-05-19/readme.md) - Bar chart of number of wins by country - [Week 20: Volcanic Erruptions](https://github.com/rfordatascience/tidytuesday/blob/master/data/2020/2020-05-12/readme.md) - Map marked for location of erruptions in the past 50 years - [Week 19: Animal Crossing](https://github.com/rfordatascience/tidytuesday/blob/master/data/2020/2020-05-05/readme.md) - Bar chart of # of characters by species, colored by character gender - Sentiment analysis of game reviews by rating ## Status & Results: 21.07.2020 ### NAME - TEMPLATE Status: - [x] Thinking of idea - [x] Wrangling data into appropriate format - [ ] Working on basic code for the graph - [ ] Refining graph with colors / extras Goal/Idea: Results (or in-process code): ```{r} test <- 3 test ``` ![](link to final image, i.e. from imgur) [Full code on Github](github link if you have one) ### Alena Status: - Wrangling data into appropriate format (animal_outcomes) Goal/Idea: The data are inthe wide format, so I'll first convert it to the narrow format Results (or in-process code): ```{r} animal_outcomes <- read_csv('https://raw.githubusercontent.com/rfordatascience/tidytuesday/master/data/2020/2020-07-21/animal_outcomes.csv') ``` converting to long ```{r} animal_outcomes %>% gather(state, animals, ACT:WA) -> animal_long ``` cats_dogs %>% ggplot(aes(x= year, y = animals, fill = outcome)) + geom_bar(stat="identity") + facet_grid(.~ animal_type) + theme_minimal() ![](link to final image, i.e. from imgur) [Full code on Github](github link if you have one) ### Julia Status: - [x] Thinking of idea - [X] Wrangling data into appropriate format - [X] Working on basic code for the graph - [ ] Refining graph with colors / extras Goal/Idea: Use the coffee data from a few weeks ago to learn how to make ridgeline plots with ggridges Results (or in-process code): ```{r} test <- 3 test ``` ### Kyla Status: - [x] Thinking of idea - [x] Wrangling data into appropriate format - [ ] Working on basic code for the graph - [ ] Refining graph with colors / extras Goal/Idea: Simple bar chart with animal data (not much time today!) ~~Neural net predicting rating giving other stats: aroma, uniformity, etc. (Probably will run out of time...)~~ Results (or in-process code): ```{r} test <- 3 test ``` ### Kaustav Status: - [x] Thinking of idea - [ ] Wrangling data into appropriate format - [ ] Working on basic code for the graph - [ ] Refining graph with colors / extras Goal/Idea: Prepare a alluvial plot using the Animal Shelter data An alluvial diagram (still work in progress) ![](https://raw.githubusercontent.com/kaustavSen/tidytuesday/master/2020/plots/week_30.png) Results (or in-process code): ```{r} test <- 3 test ``` ### Manasi Status: - [x] Thinking of idea - [x] Wrangling data into appropriate format - [X] Working on basic code for the graph - [ ] Refining graph with colors / extras Goal/Idea: Prepare a alluvial plot using the Animal Shelter data Results (or in-process code): ```{r} test <- 3 test ``` Quick check on the data (missing values, totals etc.) ```{r} tuesdata <- tidytuesdayR::tt_load(2020, week = 30) tuesdata animal_outcomes <- tuesdata$animal_outcomes animal_outcomes_test <- animal_outcomes %>% rowwise() %>% mutate(total_calc = sum(across(.cols = ACT:WA), na.rm = TRUE), check = Total - total_calc) animal_outcomes_test %>% anti_join(temp) ``` ![](link to final image, i.e. from imgur) [Full code on Github](github link if you have one) ### Divya Status: - [x] Thinking of idea - [x] Wrangling data into appropriate format - [x] Working on basic code for the graph - [ ] Refining graph with colors / extras Goal/Idea: Make a gif across years, for animal complaints ![](link to final image, i.e. from imgur) [Full code on Github](github link if you have one)

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