#### Overview of this book

The pandas library is massive, and it's common for frequent users to be unaware of many of its more impressive features. The official pandas documentation, while thorough, does not contain many useful examples of how to piece together multiple commands as one would do during an actual analysis. This book guides you, as if you were looking over the shoulder of an expert, through situations that you are highly likely to encounter. This new updated and revised edition provides you with unique, idiomatic, and fun recipes for both fundamental and advanced data manipulation tasks with pandas. Some recipes focus on achieving a deeper understanding of basic principles, or comparing and contrasting two similar operations. Other recipes will dive deep into a particular dataset, uncovering new and unexpected insights along the way. Many advanced recipes combine several different features across the pandas library to generate results.
Preface
Pandas Foundations
Free Chapter
Essential DataFrame Operations
Creating and Persisting DataFrames
Exploratory Data Analysis
Selecting Subsets of Data
Combining Pandas Objects
Visualization with Matplotlib, Pandas, and Seaborn
Debugging and Testing Pandas
Other Books You May Enjoy
Index

# Visualizing data with matplotlib

Matplotlib has a few dozen plotting methods that make nearly any kind of plot imaginable. Line, bar, histogram, scatter, box, violin, contour, pie, and many more plots are available as methods on the Axes object. It was only in version 1.5 (released in 2015) that matplotlib began accepting data from pandas DataFrames. Before this, data had to be passed to it from NumPy arrays or Python lists.

In this section, we will plot the annual snow levels for the Alta ski resort. The plots in this example were inspired by Trud Antzee (`@Antzee_`) who created similar plots of snow levels in Norway.

## How to do it…

1. Now that we know how to create axes and change their attributes, let's start visualizing data. We will read snowfall data from the Alta ski resort in Utah and visualize how much snow fell in each season:
``````>>> import pandas as pd
>>> import numpy as np