Manipulating data in DataFrames
Once we have data in a DataFrame, we often need to apply some simple transformations or filters to the data before we can perform any analysis. This could include, for example, filtering the rows that are missing data or applying a function to individual columns.
In this recipe, we will learn how to perform some basic manipulation of DataFrame objects to prepare the data for analysis.
Getting ready
For this recipe, we will need the pandas package imported under the pd alias, the NumPy package imported under the np alias, and a default random number generator object from NumPy to be created using the following commands:
from numpy.random import default_rng rng = default_rng(12345)
Let’s learn how to perform some simple manipulations on data in a DataFrame.
How to do it...
The following steps illustrate how to perform some basic filtering and manipulations on a pandas DataFrame:
- First, we will create a sample
DataFrame...
