A Practical Approach to Timeseries Forecasting Using Python - Shape and NULL Check

The video tutorial explains how to analyze a dataset by examining its columns, data types, shape, and null values. It demonstrates using commands like DF.columns, DF.shape, and DF.isnull().any() to gather insights. The tutorial also covers preparing the dataset for time series analysis by setting the date column as the index, ensuring no null values are present. The next steps involve converting the dataset into a time series format.

What are the names of the columns in the data set?

What is the data type of the columns in the data set?

What command would you use to check the shape of the data set?

How can you check for null values in the data set?

What is the significance of setting the date column as the index?