How to read data from a text file in Python?

Question

I have obtained a dataset in text format and want to perform analysis on that using Python. The data looks like this:

1 1 -0.0007 -0.0004 100.0 518.67 641.82 1589.70 1400.60 14.62 21.61 554.36 2388.06 9046.19 1.30 47.47 521.66 2388.02 8138.62 8.4195 0.03 392 2388 100.00 39.06 23.4190  
1 2 0.0019 -0.0003 100.0 518.67 642.15 1591.82 1403.14 14.62 21.61 553.75 2388.04 9044.07 1.30 47.49 522.28 2388.07 8131.49 8.4318 0.03 392

I want to read this data like a csv file in Python with proper column names(I will define that). Any ideas on how to do that would be appreciated.

Answer 1

You could try to read the file line by line, then split each line by spaces and have each element in the split list be associated to a certain column name.

You can use something like that to start:

with open('filename') as f:
    lines = f.readlines()

for line in lines:
    l = line.split(" ");
    for el in l:
        #do stuff

Answer 2

Read and use split(' ') to split it into columns. Maybe assign it to a dataframe for easier access.

file1 = open("myfile.txt","r+") 
print ("Output of Read function is")
lines = file1.readlines() 
print("Col1  Col2  ....")
for line in lines:
  temp = line.split(' ')
  print(temp[0],temp[1])

Answer 3

尝试 read_csv from pandas ( documentation ) 并用空格定义分隔符，如下所示：

data = pandas.read_csv(delimiter: ' ')

Answer 4

Suppose the text file is temp.txt and the separator between your columns is space, you can then use read_csv function to read such file:

import pandas as pd
names = ['col1', 'col2', 'col3'] # define your column names here, the lentgh of the list should match the actual number of columns you load into the dataframe
df = pd.read_csv('temp.txt', delimiter=' ', header=None, names=names)  # use header=None to indicate that your file has no header