Time Series Visualization Techniques Using Matplotlib and Plotly in Python
Learn how to visualize time series data using Python. This lesson covers the basics of time-based data, setting up your environment, and using popular libraries like Matplotlib and Plotly for creating clear and interactive charts. You will practice loading real datasets, handling date formats, and making line and bar plots to explore trends and patterns.
By the end of this video, you will know how to customize visualizations, focus on specific time periods, calculate averages, and save your charts for future use. You will also get a mini project to compare seasonality across years and tips for troubleshooting common plotting issues. Perfect for anyone looking to improve their data analysis skills with Python.
00:00 Introduction to time series visualization
00:18 What is a time series
00:56 Setting up the Python environment
01:29 Loading and inspecting data
01:57 Handling date formats
02:21 Plotting a basic time series chart
02:57 Choosing between Matplotlib and Plotly
03:19 Creating interactive plots with Plotly
03:48 Zooming into a single year
04:25 Dynamic year selection for plots
05:08 Handling missing years and errors
05:49 Customizing plot styles
06:24 Focusing on specific seasons
07:07 Calculating yearly averages and bar charts
07:45 Highlighting peak months with scatter plots
08:16 Saving charts as image files
08:55 Adding rolling averages for trends
09:38 Mini project: comparing seasonality across years
10:11 Interactive multi-year comparison with Plotly
11:11 Troubleshooting common plotting issues
11:45 Saving interactive Plotly charts
12:41 Recap and key takeaways
13:19 Challenge and next steps
#Python #DataVisualization #TimeSeries
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