熊猫read_csv忽略每个值前面的列索引

Question

Is there a way to read a file like this in and skip the column index (1-5) like this example? I'm using read_csv.

24.0 1:0.00632 2:18.00 3:2.310 4:0 5:0.5380 
21.6 1:0.02731 2:0.00 3:7.070 4:0 5:0.4690 

Expected table read:

24.0 0.00632 18.00 2.310 0 0.5380 

Answer 1

read_csv won't handle this the way you want because it's not a CSV.

You can do eg

pd.DataFrame([[chunk.split(':')[-1] for chunk in line.split()] for line in f])

Answer 2

Your data is oddly structured. Given the colon index separator, you can read the file mostly as text via the usual read_csv . Then, loop through each column in the dataframe (except for the first one), split the string on ':', take the second element which represents your desired value, and convert that value to a float (all done via a list comprehension).

df = pd.read_csv('data.txt', sep=' ', header=None)

>>> df
      0          1        2        3    4         5
0  24.0  1:0.00632  2:18.00  3:2.310  4:0  5:0.5380
1  21.6  1:0.02731   2:0.00  3:7.070  4:0  5:0.4690

df.iloc[:, 1:] = df.iloc[:, 1:].applymap(lambda s: float(s.split(':')[1]))

>>> df
      0        1   2     3  4      5
0  24.0  0.00632  18  2.31  0  0.538
1  21.6  0.02731   0  7.07  0  0.469