Data visualization is a crucial aspect of data analysis, allowing us to gain insights and make informed decisions. MongoDB, a popular NoSQL database, offers flexibility in storing and retrieving data, making it a preferred choice for many applications. In this tutorial, we will explore how to visualize data retrieved from a MongoDB collection using Python. You can visit the detailed tutorial on MongoDB and Data Science here.

Code Overview

Below is the Python code to connect to a MongoDB Atlas cluster, retrieve data from a specified collection, and visualize it using matplotlib;

# Import Required Libraries
import pymongo
import matplotlib.pyplot as plt

# Connect to MongoDB Atlas
client = pymongo.MongoClient("mongodb+srv://user:password@cluster0.ergtejf.mongodb.net/?retryWrites=true&w=majority&appName=Cluster0")

# Select the Database and Collection
db = client.database
collection = db.collection

# Define a Function to Plot Data
def plot_data():
    try:
        # Retrieve data from MongoDB Atlas
        cursor = collection.find()

        # Initialize lists to store ids
        ages = []

        # Extract ids from documents
        for document in cursor:
            ages.append(document['age'])

        # Plotting
        plt.figure(figsize=(10, 6))
        plt.plot(ages)
        plt.title('ID Data from MongoDB Collection')
        plt.xlabel('Index')
        plt.ylabel('ID')
        plt.grid(True)
        plt.show()

    except Exception as e:
        print("An error occurred:", e)

# Call the Function to Plot Data
plot_data()

Explanation of Code

Import Required Libraries

# Import Required Libraries
import pymongo  # Importing pymongo library for MongoDB interaction
import matplotlib.pyplot as plt  # Importing matplotlib.pyplot for plotting

This line imports necessary libraries for our program, including pymongo for MongoDB interaction and matplotlib.pyplot for plotting.

Connect to MongoDB Atlas

# Connect to MongoDB Atlas
client = pymongo.MongoClient("mongodb+srv://user:password@cluster0.ergtejf.mongodb.net/?retryWrites=true&w=majority&appName=Cluster0")  # Establishing connection to MongoDB Atlas

This section establishes a connection to MongoDB Atlas by providing the connection string generated from the MongoDB dashboard. Use your database connection string with correct username and password.

Select the Database and Collection

# Select the Database and Collection
db = client.database# Selecting the "afzal" database
collection = db.collection  # Selecting the "afzal" collection within the database

Here, we specify the database and collection within MongoDB that we want to retrieve data from. In this case, it’s the “database” database and “collection” collection.

Define a Function to Plot Data

# Define a Function to Plot Data
def plot_data():
    try:
        # Retrieve data from MongoDB Atlas
        cursor = collection.find()  # Retrieving data from the specified collection

        # Initialize lists to store ids
        ages = []  # Initializing an empty list to store ids from documents

        # Extract ids from documents
        for document in cursor:
            ages.append(document['age'])  # Appending each 'id' to the ids list

        # Plotting
        plt.figure(figsize=(10, 6))  # Setting figure size
        plt.plot(ages)  # Plotting the ids data
        plt.title('ID Data from MongoDB Collection')  # Setting title for the plot
        plt.xlabel('Index')  # Setting label for x-axis
        plt.ylabel('ID')  # Setting label for y-axis
        plt.grid(True)  # Enabling grid lines
        plt.show()  # Displaying the plot

    except Exception as e:
        print("An error occurred:", e)  # Handling exceptions if any error occurs during the process

This section defines a function named plot_data() to encapsulate the process of retrieving data from MongoDB and plotting it.

Retrieve Data from MongoDB Atlas:

# Retrieve Data from MongoDB Atlas
cursor = collection.find()  # Retrieving data from the specified collection

We use the find() method to retrieve data from the specified MongoDB collection. The results are stored in a cursor.

Initialize Lists and Extract IDs:

# Initialize Lists and Extract IDs
ids = []  # Initializing an empty list to store ids from documents
for document in cursor:
    ids.append(document['id'])  # Appending each 'id' to the ids list

We initialize an empty list named ids to store the ‘id’ field from each document retrieved from MongoDB. Then, we iterate through the cursor and append each ‘id’ to the ids list.

Plotting:

# Plotting
plt.figure(figsize=(10, 6))  # Setting figure size
plt.plot(ids)  # Plotting the ids data
plt.title('ID Data from MongoDB Collection')  # Setting title for the plot
plt.xlabel('Index')  # Setting label for x-axis
plt.ylabel('ID')  # Setting label for y-axis
plt.grid(True)  # Enabling grid lines
plt.show()  # Displaying the plot

Using matplotlib, we plot the data stored in the ids list. We set labels for the axes, title for the plot, and enable grid lines for better visualization.

Exception Handling:

except Exception as e:
    print("An error occurred:", e)  # Handling exceptions if any error occurs during the process

We include exception handling to catch any errors that might occur during the process of data retrieval or plotting.

Call the Function to Plot Data:

# Call the Function to Plot Data
plot_data()  # Calling the function to execute the code and visualize the data

Finally, we call the plot_data() function to execute the code and visualize the data from the MongoDB collection.