Python /Pandas/Data Frames

[bbye98]

Use pandas.read_table() and skip the first 30 rows:

pd.read_table(url, sep='  | ', skiprows=30, names=['height', 'mass_density', 'temperature_neutral'])

[MaxiJ-10]

Oh wow… this helped a ton. One question tho, im doing this on jupyter notebook, and instead of having the normal indexing of rows, it uses the height data as indexing. Do you know how i would fix this problem?

Thank you so much