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Exercise

Missing data

In this exercise, let's examine missing values. When working with data, you will inevitably come across missing values. These can occur for a number of reasons - they could be intentionally missing, or they could have been left out accidentally. Either way, identifying missing values is critical to understand before making any changes or drawing any insight from your data.

In this example you will first show the missing values in each column of the data, and you will then drop missing values from a column. Sample data has been loaded for you into the DataFrame sales_df.

Instructions 1/2

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  • Describe the DataFrame to find columns with missing values.
  • Count the number of rows in the DataFrame.