class: center, middle, inverse, title-slide # Your Turn ## I am my own experiment. I am my own work of R. ### Otho Mantegazza<br>2019-11-20 --- class: blueblue, middle .big[Pick your dataset and go...] --- class: blueblue, middle .verybig[Structured] --- class: middle # 1 - Nobel Prizes https://github.com/rfordatascience/tidytuesday/tree/master/data/2019/2019-05-14 -- # 2 - US Births https://github.com/rfordatascience/tidytuesday/tree/master/data/2018/2018-10-02 -- # 3 - Ecological Footprint https://www.kaggle.com/footprintnetwork/ecological-footprint --- class: blueblue, middle .verybig[Challenging] --- class: middle # 4 - Forest Fires in Brazil https://www.kaggle.com/gustavomodelli/forest-fires-in-brazil -- # 5 - Genetic Variations https://www.kaggle.com/kevinarvai/clinvar-conflicting --- class: blueblue, middle .verybig[When you approach new Data...] --- ## Get Familiar with the Topic Gather some background. Know at least just a bit of what the dataset is about. What is the issues that this dataset can solve? -- ## Do you have a data dictionary? Which **variable are stored in the columns** and how? - If you don't have this information, can you gather it? - Do those description match what you observe in R? If not, what does not match? - Did you get warnings when you loaded the data in R? Can you fix them? --- # Are the data Tidy? Or can you make them so? - Are there missing values? How are they encoded? How are they distributed in the dataset? - Do the column have a practical names, do they need renaming? - Do the data are structured according to the tidy principles, do they need spreadong/gathering? Remember: - Each variable must have its own column. - Each observation must have its own row. - Each value must have its own cell. --- # Can you find any pattern in your data? Show it with a viz!