Dimension Reduction techniques are one of the most useful methods in unsupervised learning of high dimensional datasets. In this post, we will learn how to use Python to perform 7 most commonly used dimensionality reduction techniques by example, PCA: Principal Component Analysis SVD: Singular Value Decomposition ICA: Independent Component Analysis NMF: Non-negative Matrix Factorization FA: […]
Python
2 Ways to Randomly Sample Rows from a large CSV file
In this post, we will be learning how to randomly sample/select rows from a large CSV file that is either taking too long to load as a Pandas dataframe or can’t load at all. The key idea is to not to load the whole file as a Pandas dataframe. Instead, we use skiprows argument in […]
Pandas Cumulative Sum by Group
In this tutorial as part of our Pandas 101 series, we will learn how to compute cumulative sum of a column based on values from a grouping column in Pandas dataframe. Pandas cumsum() function can compute cumulative sum over a DataFrame, In this example we are interested getting cumulative sum of just one column by […]
Pandas pipe function in Pandas: performing PCA
Pandas pipe function can help us chain together functions that takes either dataframe or series as input. In this introductory tutorial, we will learn how to use Pandas pipe method to simplify code for data analysis. We start with a dataframe as input and do a series of analysis such that that each step takes […]
How to Change Matplotlib Plot’s Style
In this post we will learn how to find all available style options for matplotlib plot themes and learn to set a style for matplotlib plot. To illustrate the styling options available in Matplotlib, we will use histogram made from beta distributions. To get started, let us load the modules needed. We can use style […]