Formatting

A big part of making our visualizations presentable is choosing the right plot type and having them well labeled so they are easy to interpret. By carefully tuning the final appearance of our visualizations, we make them easier to read and understand. Note that everything in this section needs to be called before running plt.show() or within the same Jupyter Notebook cell if using the %matplotlib inline magic command.

Let's now move to the 2-formatting_plots.ipynb notebook, run the setup code to import the packages we need, and read in the Facebook stock data:

>>> %matplotlib inline
>>> import matplotlib.pyplot as plt
>>> import numpy as np
>>> import pandas as pd
>>> import seaborn as sns

>>> fb = pd.read_csv(
...    'data/fb_stock_prices_2018.csv', 
...     index_col='date', 
...     parse_dates...