30. Using masks to filter data, and perform search and replace, in NumPy and Pandas

In both NumPy and Pandas we can create masks to filter data. Masks are ’Boolean’ arrays – that is arrays of true and false values and provide a powerful and flexible method to selecting data.

NumPy

creating a mask

Let’s begin by creating an array of 4 rows of 10 columns of uniform random number between 0 and 100. Continue reading “30. Using masks to filter data, and perform search and replace, in NumPy and Pandas”