Matplotlib Tutorial 9 - converting data from the internet

TL;DR

In this tutorial, you will learn how to convert date data using a decoding function and plot price data using Matplotlib in Python.

Transcript

what is going on everybody Welcome to the ninth data visualization with python and matap plot lib tutorial video where we left off we were basically pulling data from the internet we were we got the data we've separated it and we can even unpack it into these variables here but the problem is the date stamp here is a little problematic for us becau... Read More

Key Insights

• 🧑‍🤝‍🧑 Matplotlib has its own system for converting date stamps, which is different from Unix time.
• 💁 Python 3 requires a custom decoding function to convert byte strings to readable date formats.
• ⌛ The plot_date() function in Matplotlib is used to plot time-series data.
• 🧑‍🤝‍🧑 The appearance of the plot can be enhanced by rotating the dates and making other adjustments.
• 🧑‍🤝‍🧑 Date stamp conversion is essential for accurate visualization of time-series data.
• 💁 Matplotlib provides flexibility in zooming and displaying different levels of date information.
• 🏛️ The decoding process is necessary only for Python 3, as Python 2 had the function built-in.

Questions & Answers

Q: Why is date stamp conversion necessary in Python, especially with Matplotlib?

Date stamp conversion is necessary because Matplotlib uses its own conversion system for dates. By converting the date stamp to a readable format, we can effectively plot time-series data.

Q: What is the purpose of the custom decoding function?

The custom decoding function converts byte strings to a string format using UTF-8 encoding. It ensures that the date stamp data can be properly used for plotting.

Q: How can we plot price data using Matplotlib?

To plot price data, we need to use the plot_date() function in Matplotlib. We pass the converted dates as the x-axis values and the corresponding price values as the y-axis values.

Q: How can we improve the appearance of the plot?

To improve the appearance of the plot, we can rotate the dates and make other adjustments, which will be covered in the next tutorial. For now, the price line can be plotted successfully.

Summary & Key Takeaways

• The tutorial begins with a discussion on the challenges of date stamp conversion in Python, particularly with Matplotlib, which uses its own conversion system.

• The tutorial introduces a custom decoding function to convert byte strings to a readable date format.

• The tutorial then demonstrates how to plot price data, using the converted dates and price values.