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Getting started with Matplotlib

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(keyboard clicks) Python never ceases to surprise. Python is every data scientist’s first choice for conducting analysis. The language is also a favourite in the data analytics space, for preparing data visualisations. Due to its easy to comprehend, and easy to debug features, this open source language comes with many benefits. One such benefit is Python’s libraries, which programmers and data scientists leverage for solving high level problems on a day-to-day basis. One of the many libraries in Python is Matplotlib. Matplotlib is a data visualisation library for plotting graphs. Matplotlib is built on NumPy arrays, the numerical mathematics extension. In this section of the course, you will be learning to write codes using Matplotlib in Python.
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You will learn writing codes to draw figures and axes, plot colours, markers, and different line styles. You will also learn how to add labels and tics for the axis of your graph. And finally, adding legends to your charts. Let’s get started.

Before we delve any deeper and get ready for an immersive experience of learning to build plots using Matplotlib, watch this video to:

  • understand what plotting time series data really is and why is it crucial in data visualisation

  • recognise the various aspects of the Matplotlib for plotting a time series data on a chart.

Download your Jupyter Notebook

Download your accompanying Jupyter Notebook containing explanations and codes in cells that you can run to receive outputs.

Download: Plotting Time Series Data using Matplotlib

The Notebook contains only the code snippets that you can run to get an immersive and interactive experience, as well as instant results of the codes alongside the explanations. Make best use of this opportunity to familiarise yourself with using the Notebook.

At the end of this week, you’ll find a set of interesting poll activities to check your knowledge.

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Data Visualisation with Python: Matplotlib and Visual Analysis

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