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In this part, we will explore more about pandas library and its uses in data science.

I will continue from where I left. If you haven’t seen part 2. Please visit https://medium.com/analytics-vidhya/getting-started-with-data-science-with-python-part-2-e3cc3411ac70. Because it will help you to understand.

Let’s go.

- Open jupytier notebook.
- Import pandas
- Load the CSV dataset into dataframes.

Now we will mainly focus on commands.

**df.describe(): This commads tells us some important stuff about integer columns. Lets do it and see.**

- count: It gives us the total number of not null values in the column.
- mean: It gives us the mean of column.
- std: A quantity expressing by how much the members of a group differ from the mean value for the group.
- min: The minimum value in the column.
- max: The max value in the column.

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