Create a cool matlabplot of the sample movies data in Atlas using Seaborn!

Installing Seaborn Open up the terminal

Install Seaborn by running the following command:

pip3 install seaborn

Configuring access to MongoDB Atlas Movies collection Sign in to your MongoDB Atlas account at https://www.mongodb.com/cloud/atlas (or create an account if you don't have one).

Open your terminal or Jupyter Notebook.

Install the PyMongo library if you haven't already by running the following command:

pip3 install pymongo

Import the necessary libraries in your Python script:

from pymongo import MongoClient
import seaborn as sns
import matplotlib.pyplot as plt

Set up a connection to your MongoDB Atlas cluster using the connection string you copied earlier:

Replace the connection string with your MongoDB Atlas connection string

connection_string = "mongodb+srv://<username>:<password>@<cluster-address>/test?retryWrites=true&w=majority"
client = MongoClient(connection_string)

Access the "movies" collection in the "sample_mflix" database:

Replace the database and collection names as needed

db = client['sample_mflix']
collection = db['movies']

Query the data from the collection:

# Retrieve the data from MongoDB
documents = collection.find({})

Convert the MongoDB documents to a pandas DataFrame:

import pandas as pd

Convert MongoDB documents to a pandas DataFrame

df = pd.DataFrame(list(documents))

Perform any necessary data cleaning and transformation on the DataFrame.

Use Seaborn to create visualizations based on the data in the DataFrame. For example, you can create a scatter plot as follows:

sns.scatterplot(data=df, x='year', y='imdb.rating')

Show the plot

plt.show()

Run your Python script or execute the code in your Jupyter Notebook to visualize the data from the MongoDB Atlas Movies collection using Seaborn.

Seaborn Documentation