From the course: Deep Learning and Generative AI: Data Prep, Analysis, and Visualization with Python
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Solution: Perform exploratory data analysis
From the course: Deep Learning and Generative AI: Data Prep, Analysis, and Visualization with Python
Solution: Perform exploratory data analysis
(retro uptempo music) - [Instructor] So far, we have done an initial exploration of our telecom dataset. We have also pre-processed our telecom dataset and saved the pre-processed dataset into a new file called cleaned_telecom.csv. In this challenge, we will seek to gain insight into the data using visuals such as bar charts, heat maps, histograms, scatter plots, and more. Once we complete our exploratory data analysis section, it is then time to build and train our machine learning model. First load in both the telecom data set and the cleaned data set. And to do that, we're going to go to Files and grab both of our data sets and open. And so this exercise is under the exploratory data analysis section where you're going to count how contracts are distributed. You're going to create a bar chart for that. You're going to create a pie chart to graph contract type by distribution. You're going to create a scatter chart to graph tenure in months versus total revenue. You'll do a heat map…
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