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United Nations Voting Correlations4 months ago
Pairwise correlations | Visualizing clusters in a network
widyr: Widen, process, and re-tidy a dataset4 months ago
Towards a precise definition of "wide" data | Example: gapminder | Pairwise operations
Get started with pins4 months ago
Getting started | Reading and writing data | How and what to store as a pin | Metadata | Versioning | Reading and writing files | Caching
Version, share, and deploy a model with vetiver7 months ago
Create a vetiver_model() | Store and version your model | Deploy your model | Predict from your model endpoint
Getting started with bundle7 months ago
Saving things is hard | Native serialization, and where it falls short | Using bundle
Create consistent metadata for pins10 months ago
A function to store factors | A function to read factors | Examples of using consistent metadata
Managing custom formats10 months ago
Upload a single file | Function to manage uploading | Another example: upload a zipped directory archive as a pin
Posit Connect10 months ago
Sharing tidied data | Automating | Shiny apps
Upgrading to pins 1.0.010 months ago
Examples | Pinning files | Pinning a url | Implicit board | Equivalents | Board functions | Pin functions
Using web-hosted boards10 months ago
Publishing | Consuming | Publishing platforms | pkgdown | S3
Converting to and from Document-Term Matrix and Corpus objects11 months ago
Tidying document-term matrices | Casting tidy text data into a DocumentTermMatrix | Tidying corpus data
Introduction to tidytext11 months ago
The Life-Changing Magic of Tidying Text | A few first tidy text mining examples | Most common positive and negative words | Wordclouds | Looking at units beyond just words
Term Frequency and Inverse Document Frequency (tf-idf) Using Tidy Data Principles11 months ago
Tidy Log Odds4 years ago
A motivating example: what words are important to a text? | Jane Austen and bigrams | Counting things other than words