DataFrame manipulation—renaming, rearranging, reversing, and slicing

After creating a DataFrame object, you can perform various operations on it. This recipe covers the following operations on DataFrame objects. Renaming a column, rearranging columns, reversing the DataFrame, and slicing the DataFrame to extract a row, column, and a subset of data.

Getting ready

Make sure the df object is available in your Python namespace. Refer to Creating a pandas.DataFrame object recipe of this chapter to set up this object.

How to do it…

Execute the following steps for this recipe:

1. Rename the date column to timestamp for df. Print it:

>>> df.rename(columns={'date':'timestamp'}, inplace=True)
>>> df

We get the following output:

            timestamp    open    high     low   close volume
0 2019-11-13 09:00:00 71.8075 71.8450 71.7775 71.7925 219512
1 2019-11-13 09:15:00 71.7925 71.8000 71.7800 71.7925  59252
2 2019-11-13 09:30:00 71.7925 71.8125 71...