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- [Instructor] Info provides a summary of the data frame

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including the number of entries, the data type,

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and the number of non-null entries

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for each series in the data frame.

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This is important because often when working

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with a real data set, there will be missing data.

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You want a view of this to determine

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how you will handle this missing data.

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Let's head back to the Jupyter notebook.

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So I enter the name of the data frame.

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We can see that we do not have

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any missing data in this data set.

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There are 29,216 entries,

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and none of them are non-null.

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What is also useful about the info method

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is that it also gives you the data types

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for the different series of columns.

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This is useful when you have to do

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any comparisons or queries.

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So for example, if you are querying what is a string,

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then you will know that you have to use quotes,

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and if you are using a comparison for an integer

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or a float value, then you won't need to use those quotes.

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In the next video, we will learn how to use Pandas

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to do some basic data analysis.