In this section, we go deep into NumPy and cover how to index, slice, filter values, replace missing values in NumPy.
pandas generally performs better than numpy for 500K rows or more. for 50K to 500K rows, it is a toss up between pandas and numpy depending on the kind of operation. Pandas Series & DataFrame, are the de facto standard to work with tabular data in Python. You can create, manipulate and access the information you need from these data structures.
We will be rehearsing the following skills in this notebook:
- Python | Numpy | Pandas
After this lesson, you'll be able to
- Selection, Indexing and Filters
- Filters
- Introduction to Pandas - Pandas Series