Exercise

Using pandas to import flat files as DataFrames (2)

In the last exercise, you were able to import flat files into a pandas DataFrame. As a bonus, it is then straightforward to retrieve the corresponding numpy array using the attribute values. You'll now have a chance to do this using the MNIST dataset, which is available as digits.csv.

Instructions

100 XP

Import the first 5 rows of the file into a DataFrame using the function pd.read_csv() and assign the result to data. You'll need to use the arguments nrows and header (there is no header in this file).
Build a numpy array from the resulting DataFrame in data and assign to data_array.
Execute print(type(data_array)) to print the datatype of data_array.