Before we start: This Python tutorial is a part of our series of Python Package tutorials. You can find other Numpy related topics too!
Pandas and numpy work very well together. It is quite easy to transform a pandas dataframe into a numpy array. Simply using the to_numpy() function provided by Pandas will do the trick.
If we wanted to turn an entire dataframe into a numpy array, we can simply use the following line of code:
df.to_numpy()
This will return us a numpy 2D array of the same size as our dataframe (df), but with the column names discarded.
If we wanted to convert just the first two columns in a dataframe into a numpy array, we can use to_numpy() as follows:
df[["column1","column2"]].to_numpy()
If we wanted to convert just a few cells of data in a dataframe into a numpy array, we can simply slice the dataframe and convert the output using to_numpy():
df.iloc[[0,1,2],[0,1,2]].to_numpy()
The above code converts the first three columns and first three rows to a numpy array.
The following tutorials will provide you with step-by-step instructions on how to work with Numpy, including:
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