import pandas as pd a = [[1,2],[3,4]] df = pd.DataFrame(a) df-> 0 1 0 1 2 1 3 4 df.values -> array([[1, 2], [3, 4]]) df.ix[1].values -> array([3, 4]) a = [[1,None],[3,4]] df = pd.DataFrame(a) df-> 0 1 0 1 NaN 1 3 4 df.values -> array([[ 1., nan], [ 3., 4.]]) df[0].values -> array([1, 3]) df[1].values -> array([ nan, 4.]) df.ix[1].values -> array([ 3., 4.]) df[0][1] -> 3 df[1][1] -> 4.0This threw me because I have a data structure that is all ints, but I have a few Nones on one column and that column was suddenly returned as floats.
As you can see it's just the relevant column that is forced to float.
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