I want to convert a table, represented as a list of lists, into a
Pandas DataFrame. As an extremely simplified example:
a = [['a', '1.2', '4.2'], ['b', '70', '0.03'], ['x', '5', '0']] df = pd.DataFrame(a)
What is the best way to convert the columns to the appropriate types, in this case columns 2 and 3 into floats? Is there a way to specify the types while converting to DataFrame? Or is it better to create the DataFrame first and then loop through the columns to change the type for each column? Ideally I would like to do this in a dynamic way because there can be hundreds of columns and I don't want to specify exactly which columns are of which type. All I can guarantee is that each columns contains values of the same type.