Seaborn, one of the data visualization libraries in Python has a new version, Seaborn version 0.11, with a lot of new updates. One of the biggest changes is that Seaborn now has a beautiful logo. Jokes apart, the new version has a lot of new things to make data visualization better. This is a quick […]
Pandas value_counts: How To Get Counts of Unique Variables in a Dataframe?
As part of exploring a new data, often you might want to count unique values of one or more columns in a dataframe. Pandas value_counts() can get counts of unique values of columns in a Pandas dataframe. Starting from Pandas version 1.1.0, we can use value_counts() on a Pandas Series and dataframe as well. In […]
SVD: One Matrix Decomposition to Rule Them All
One of the nice things about twitter, when you follow awesome people, is that you will come across tweets that will just blow your mind. Last week is just one such week with some fantastic and funniest tweetorials. One of the tweetorials was from Prof. Daniela Witten for @WomenInStat. And it starts like this and […]
Principal Component Analysis with Penguins Data in Python
Who does not love PCA with Penguins in Python. Sorry, could not resist saying this :). If you are tired of seeing Iris data for introducing all things Machine Learning, Data Science algorithms and Data Visualization examples, you are in for much needed treat in the form of Penguins. Thanks to Alison Horst, who has […]
PCA with tidymodels in R
tidymodels, is one of the new suite of packages for doing machine learning analysis in R with tidy principles from RStudio. Tidymodels, the metapackage, has a core set of packages for statistical/machine learning models like infer, parsnip, recipes, rsample, and dials in addition to the core tidyverse packages dplyr, ggplot2, purr, and broom. In addition […]