Seaborn is a Python visualization library based on matplotlib. It provides a high-level interface for drawing attractive statistical graphics.
I prefer Seaborn due to its wonderful color schemes cough and close integration with pandas, but there are other Python visualization tools. You can see the comparison here.
Let's begin! I will be using a CSV I created for this tutorial:
import pandas as pd import seaborn as sns import matplotlib.pyplot as plt # Read the csv using pandas module budget = pd.read_csv("~/your_file.csv") # Sort by Number of Stays column DESC budget = budget.sort_values(by='Number of Stays', ascending=False) sns.set_style("darkgrid") # Create a bar graph bar_plot = sns.barplot(x=budget["Name"],y=budget["Number of Stays"], palette="deep") # Set title of the bar graph bar_plot.set_title("Arkham's Patients", size=30, color="r", alpha=0.5) # Set x-axis of the bar graph bar_plot.set_xlabel("Patients", size =16, color="r", alpha=0.5) # Set y-axis of the bar graph bar_plot.set_ylabel("# of Stays", size=16, color="r", alpha=0.5) # Saves the bar graph as png plt.savefig("output.png") # Show the bar graph plt.show()
Ta-da. You can see the result below.