Before we continue onto Dataframes, I want to clear up something from the Series exercise. Note the line (from pandas import Series, DataFrame)

Using that line, I can call upon Series or DataFrame directly in my code

In this example below, I did not directly import the methods Series and DataFrame, so I when I tried x = Series() I go an error.

I had to use the full method name of pd.Series() for this to work.

DataFrame

DataFrames provide another level of data management for Python. Those of you who come from a more data driven background with appreciate DataFrames.

Let’s start by creating dictionary.

Now, pass the dictionary to the method DataFrame()

Note, now you have a table looking structure with named columns

You can call up a list of indexes or columns using the methods below:

DataFrame.info() will return a summary of your DataFrame

Head and Tail

Create a new DataFrame from a dictionary

If you want just see a few of the first elements, you can use the head() method

The tail() method does the last few. You can even choose how many rows you want.

Describe

The describe() method gives you some quick statistics on any numeric column

Slice

You can slice a DataFrame just as you would a list

Choose What to Display

DataFrames allow you to filter what rows to display by value or column

There is a lot more you can do with Series and DataFrame in pandas, and we will be covering them in later lessons. For now though, I think you have a general idea.

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