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So let's go ahead and read the contents of this file with Pandas.

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A very powerful data analysis library.

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We are going to dive deep into Pandas later on,
we have a section dedicated to Pandas.

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And we have applications where we are going to use Pandas a lot.

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But for now let me just give you a quick demo

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how Pandas works.

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Make sure you import it. I have imported it in here.

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And then while true let's keep this conditional to check if the file is there.

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In this case that would be temps_today.csv.

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And then if the file exists we want to load the data
in this data variable, the way we do that is by

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using the read_csv method of Pandas.

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And there goes you guessed it for the path of the file

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like that.

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So if the file exists reads the data, and then print out 

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data.mean.

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So this object has a mean method.

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Let me show you later

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what's this object is.

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But for now let's go ahead and execute this script,
so we are getting the mean of each of the columns.

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That is a mean for a station one.

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And that is a mean for station two.

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So it's working.

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Now if you wanted the mean of only the st1 column,
you just do that.

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So that will give you the mean of the st1 of the station one column,

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and so on.

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So the idea here is that

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import Pandas and when you execute this

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what's happening there is that an object called a data frame is being created.

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You can see that you have a structured view of these data.

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So this is a specific object type just like we have integers and we have floats.

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We also have these other types that's you can find in libraries, in these third party libraries.

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So everyone can create their own types.

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And this is about libraries.

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So built in libraries, standard libraries written in Python, and third party libraries which are almost always

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written in Python.

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That's about libraries.