Mastering Python for Finance - Second Edition

Preparing the dataset of multiple assets as input variables

We will be reusing the pandas DataFrame variables, df_assets_1m and df_assets_3m, from the previous section containing the lagged 1-month and 3-month percentage returns of the four assets and combine them into a single variable, df_input, with the following code:

In [ ]:        df_input = df_assets_1m.join(df_assets_3m).dropna()

Use the info() command to view its properties:

In [ ]:    df_input.info()Out[ ]:    <class 'pandas.core.frame.DataFrame'>
    Index: 2971 entries, 2007-05-25 to 2019-03-14
    Data columns (total 8 columns):
    ...

The output is truncated, but you can see we have eight features as our independent variables spanning the years 2007 to 2019. With our input and target variables created, ...