I have a df like so:
import pandas a=[['1/2/2014', 'a', '6', 'z1'], ['1/2/2014', 'a', '3', 'z1'], ['1/3/2014', 'c', '1', 'x3'], ] df = pandas.DataFrame.from_records(a[1:],columns=a[0])
I want to flatten the df so it is one continuous list like so:
['1/2/2014', 'a', '6', 'z1', '1/2/2014', 'a', '3', 'z1','1/3/2014', 'c', '1', 'x3']
I can loop through the rows and extend
to a list, but is a much easier way to do it?
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Answer
You can use .flatten()
on the DataFrame converted to a NumPy array:
df.to_numpy().flatten()
and you can also add .tolist()
if you want the result to be a Python list
.
Edit
In previous versions of Pandas, the values
attributed was used instead of the .to_numpy()
method, as mentioned in the comments below.