06 01 Introduction to Seaborn - HannaAA17/Data-Scientist-With-Python-datacamp GitHub Wiki

What is Seaborn?

• Python data visualization library.
• Is useful for explore data and communicate results.
• Work well with pandas data structures and is built on top of matplotlib.
• sns.scatterplot(x= ,y= ),sns.countplot(x=, y=) can work with lists.

Using pandas with Seaborn

• Seaborn only works with tidy pandas dataframe

Making a count plot with a DataFrame

# Import Matplotlib, Pandas, and Seaborn
import pandas as pd
import matplotlib.pyplot as plt
import seaborn as sns

# Create a DataFrame from csv file
df = pd.read_csv(csv_filepath)

# Create a count plot with "Spiders" on the x-axis
sns.countplot(x='Spiders',data=df)

# Display the plot
plt.show()

Adding a third variable with hue

• hue allows us to easily make subgroups within Seaborn plots
• A scatter plot with hue
  sns.scatterplot(x='total_bill', y='tip', data=tips, hue='smoker')
• setting hue order
  sns.scatterplot(x='total_bill', y='tip', data=tips, hue='smoker', hue_order=['yes','No'])
• specifying hue colors

hue_colors = {"Yes": "black", "No": "red"}
sns.scatterplot(x='total_bill',
                y='tip', 
                data=tips, 
                hue='smoker', 
                palatte=hue_colors)