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.

1. Open jupytier notebook.
2. Import pandas
3. 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.

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

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