Reputation: 109
I am trying to read some df with few columns and few rows where in some rows data are missing. For example df looks like this, also elements of the df are separated sometimes with uneven number of spaces:
0.5 0.03
0.1 0.2 0.3 2
0.2 0.1 0.1 0.3
0.5 0.03
0.1 0.2 0.3 2
Is there any way to extract this:
0.1 0.2 0.3 2
0.2 0.1 0.1 0.3
0.1 0.2 0.3 2
Any suggestions.
Thanks.
Upvotes: 0
Views: 46
Reputation: 1063
You can try this:
import pandas as pd
import numpy as np
df = {
'col1': [0.5, 0.1, 0.2, 0.5, 0.1],
'col2': [0.03, 0.2, 0.1, 0.03, 0.2],
'col3': [np.nan, 0.3, 0.1, np.nan, 0.3],
'col4': [np.nan, 2, 0.3, np.nan, 2]
}
data = pd.DataFrame(df)
print(data.dropna(axis=0))
Output:
col1 col2 col3 col4
0.1 0.2 0.3 2.0
0.2 0.1 0.1 0.3
0.1 0.2 0.3 2.0
Upvotes: 0
Reputation: 120409
You can parse manually your file:
import re
with open('data.txt') as fp:
df = pd.DataFrame([re.split(r'\s+', l.strip()) for l in fp]).dropna(axis=0)
Output:
>>> df
0 1 2 3
1 0.1 0.2 0.3 2
2 0.2 0.1 0.1 0.3
4 0.1 0.2 0.3 2
Upvotes: 1