["python","list","numpy","pandas","dataframe"]
python pandas flatten a dataframe to a list

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?
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.