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On Sun, 18 Nov 2018 at 18:18, Martin Sch??n <martin.schoon at gmail.com> wrote: > > I am in this project where I try to get an overview of a bunch of > computer generated (finite element program) data. I have it stored in a > number of csv files. > > Reading the data into spreadsheet programs works fine but is very labour > intensive so I am working with Pandas in Jupyter notebooks which I find > much more efficient. > > Now I hit a bump in the road when some of the data is not in plain > decimal notation (xxx,xx) but in 'scientific' (xx,xxxe-xx) notation. > Martin, I believe this should be done by pandas itself while reading the csv file, I took an example in scientific notation and checked this out, my sample.csv file is, col1,col2 1.1,0 10.24e-05,1 9.492e-10,2 and then I execute, In [29]: a= pd.read_csv('sample.csv') In [30]: a.values Out [30]: array([[1.100e+00, 0.000e+00], [1.024e-04, 1.000e+00], [9.492e-10, 2.000e+00]]) In [31]: a.values[1][0] Out[31]: 0.0001024 As you can see, pandas has converted scientific notation to float, even the data type of these values is numpy.float64 What best I can guess is a problem with your pandas version, there were some updates with the 0.17.x coming in, maybe give a shot upgrading your pandas with, pip install --upgrade pandas or in case you?re using anaconda then, conda update pandas > [snipped for brevity] > /Martin > -- > https://mail.python.org/mailman/listinfo/python-list -- Shakti.

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