Part 2: Data Analysis with powerful Python

Analyzing and visualizing data from a SQLite database in Python can be a powerful way to gain insights and present your findings. In this blog, I will walk you through the steps to retrieve data from a SQLite database file named gold.db and display it in the form of a chart using Python. We'll use some essential tools and libraries for this task.

Tools you will need !

Before we start, make sure you have the following tools and libraries installed:

1. Python: Python is the core programming language for this task. You can download it from python.org.

2. SQLite Database Browser: You can use a tool like DB Browser for SQLite to explore the database and its structure. This is optional but can be helpful for understanding the database schema.

3. Jupyter Notebook (optional): Jupyter Notebook is an interactive environment that makes data analysis and visualization easier. You can install it using pip: pip install jupyter.

4. Python Libraries:

   • sqlite3: This is a built-in library for Python that allows you to work with SQLite databases.

   • pandas: A popular data manipulation library for Python.

   • matplotlib: A widely used library for creating charts and visualizations.

You can install the required libraries using pip:

Steps to analyze and visualize data from SQLite database

Now, let's dive into the steps to analyze and display data from the gold.db database:

Step 1: Connect to the database

First, you need to connect to the SQLite database using the sqlite3 library. Here's how you can do it:

Step 2: Query the database to retrieve the required data

Execute the query and fetch the data into a Pandas dataframe:

Step 3: Pivot the data for plotting

Step 4: Create a chart

Now, it's time to create a chart using the matplotlib library. Let's say you want to create a line chart to visualize the type product prices over time:

Step 5: Save or display the chart

You can choose to save the chart to a file using plt.savefig("gold_prices_chart.png") or display it within a Jupyter Notebook if you're using one.

That's it! You have successfully analyzed data from the SQLite database and displayed it as a chart in Python. You can adapt these steps to your specific data and charting requirements. Remember to close the database connection when you're done:

In this blog post, we've covered the essential steps and tools to analyze and visualize data from a SQLite database in Python. Data analysis and visualization are crucial skills for various fields, and Python makes it accessible and powerful for these tasks.