A Practical Approach to Timeseries Forecasting Using Python - Data Pre-Processing

The video tutorial covers data preprocessing in Python, including data cleaning and visualization. It introduces advanced data processing techniques like RVT, feature engineering, and stationarity. The tutorial demonstrates using Matplotlib for plotting data features, creating subplots, and plotting graphs separately for better clarity. It concludes with a discussion on RVT and resampling for time series forecasting.

What is the significance of the DPI setting in matplotlib?

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What steps are involved in plotting the 'pollution_today' column?

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What is the preferred method of plotting mentioned in the text?

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What is RVT and how is it related to time series forecasting?

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