Analyzing Data Using Python: Filtering Data in Pandas

Not all data is useful. Luckily there are some powerful filtering operations available in pandas. The course begins with a detailed look at how loc and iloc can be used to access specific data from a DataFrame. Youll move on to filter data using the classic pandas lookup syntax and the pandas filter and query methods. Youll illustrate how the filter function accepts wildcards as well as regular expressions and use various methods such as the .isin method to filter data. Furthermore youll filter data using either two pairs of square brackets – in which case the resulting subset is itself a DataFrame – or a single pair of square brackets in which case the returned data takes the form of a Series. Youll drop rows and columns from a pandas DataFrame and see how rows can be filtered out of a DataFrame. Lastly youll identify a possible gotcha that arises when you drop rows in-place but neglect to reset the index labels in your object.