I have a fairly large dataset in the form of a dataframe and I was wondering how I would be able to split the dataframe into two random samples (80% and 20%) for training and testing.
Thanks!
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Answer
I would just use numpy’s randn
:
In [11]: df = pd.DataFrame(np.random.randn(100, 2)) In [12]: msk = np.random.rand(len(df)) < 0.8 In [13]: train = df[msk] In [14]: test = df[~msk]
And just to see this has worked:
In [15]: len(test) Out[15]: 21 In [16]: len(train) Out[16]: 79