From the course: Deep Learning and Generative AI: Data Prep, Analysis, and Visualization with Python
Join today to access over 24,400 courses taught by industry experts.
Solution: Data preprocessing the telecom dataset
From the course: Deep Learning and Generative AI: Data Prep, Analysis, and Visualization with Python
Solution: Data preprocessing the telecom dataset
(upbeat music begins) - [Instructor] In this challenge lab, we pre-process the telecom data set. First, make sure your data set is loaded, then run all the cells in the load and explore the data section. To do that, if your notebook shows your load and explore section expanded, simply collapse it and run all the cells. The challenge lab begins in the data pre-processing section. So let's expand that. First, we want to handle missing values. So let's do a df.info method to remind ourselves what they are. We had 7,043 entries, but some features have less than that. Here's offer with 3,166 entries. Here's internet type with 5,517 entries. And you'll notice that some of the entries are numeric that are missing and some are object or strings. So it may be good to calculate the missing values for numeric and object columns. And that is what we do here. This section calculates the missing values for numeric and object columns, and this section displays the results. Let's handle the missing…
Download courses and learn on the go
Watch courses on your mobile device without an internet connection. Download courses using your iOS or Android LinkedIn Learning app.
