Reading from a .txt file to a pandas dataframe
When opening very large files, first concern would be memory availability on your system to avoid swap on slower devices (i.e. disk). 

Pandas is shipped with built-in reader methods. For example the pandas.read_table method seems to be a good way to read (also in chunks) a tabular data file.

In the specific case: 

import pandas

df = pandas.read_table('./input/dists.txt', delim_whitespace=True, names=('A', 'B', 'C'))


will create a DataFrame objects with column named A made of data of type int64, B of int64 and C of float64.

You can by the way force the dtype giving the related dtype argument to read_table. For example forcing the second column to be float64.

import numpy as np
import pandas

df = pandas.read_table('./input/dists.txt', delim_whitespace=True, names=('A', 'B', 'C'),
                   dtype={'A': np.int64, 'B': np.float64, 'C': np.float64})