I have a .dat file, containing column data separated by indices, for example here i show just 2 indices: # t= 400000 1601 -0.207587E-02 0.454623E-03 0.193855E-02 0.996661E+00 1602 -0.202550E-02 0.447789E-03 0.191164E-02 0.996661E+00 1603 -0.197461E-02 0.440763E-03 0.188373E-02 0.996660E+00 1604 -0.192326E-02 0.433553E-03 0.185483E-02 0.996660E+00 1605 -0.187150E-02 0.426169E-03 0.182494E-02 0.996659E+00 # t= 410000 1601 -0.207587E-02 0.454623E-03 0.193855E-02 0.996661E+00 1602 -0.202550E-02 0.447789E-03 0.191164E-02 0.996661E+00 1603 -0.197461E-02 0.440763E-03 0.188373E-02 0.996660E+00 1604 -0.192326E-02 0.433553E-03 0.185483E-02 0.996660E+00 1605 -0.187150E-02 0.426169E-03 0.182494E-02 0.996659E+00 I would like to import them as panda dataframes and give names at each column. Also, I want to keep the index information (probably in a new column). I have tried the following but it does not work import pandas as pd from io import StringIO df = pd.read_csv(StringIO(filename), sep="\t", skiprows=1, usecols=[0,1,2,3,4], names=['position','ux', 'uy', 'uz', 'rho']) print(df) It has multiple entries. Each index "t" corresponds to different times of a simulation output. And at each time I have the 5 columns. I want to save the .dat file in the following dataframe form t pos ux uy uz rho 400000 1601 -0.207587E-02 0.454623E-03 0.193855E-02 0.996661E+00 400000 1602 -0.202550E-02 0.447789E-03 0.191164E-02 0.996661E+00 .... 410000 1603 -0.197461E-02 0.440763E-03 0.188373E-02 0.996660E+00 410000 1604 -0.192326E-02 0.433553E-03 0.185483E-02 0.996660E+00 410000 1605 -0.187150E-02 0.426169E-03 0.182494E-02 0.996659E+00 like merging everything together. Continue reading...
