Today was a pretty packed lesson where we introduced a lot of new concepts. In this lesson we looked at how to:

• Use nested loops to remove unwanted characters from multiple columns

• Filter Pandas DataFrames based on multiple conditions using both .loc[] and .query()

• Create bubble charts using the Seaborn Library

• Style Seaborn charts using the pre-built styles and by modifying Matplotlib parameters

• Use floor division (i.e., integer division) to convert years to decades

• Use Seaborn to superimpose a linear regressions over our data

• Make a judgement if our regression is good or bad based on how well the model fits our data and the r-squared metric

• Run regressions with scikit-learn and calculate the coefficients.

You can download the completed code for today in this lesson.

Well done on completing the next step in your data science journey 👏👏👏 Upwards and onwards!