Data science Pandas CSV - csv

Question

I have a csv file with 1461 attributes. I want to load it into a pandas data frame. The problem is, many rows do not have values for trailing consecutive columns. So pandas gives parsing error due to irregular length. How to put missing values for the leading columns for once and load the csv file into the data frame?
Edit1
We can see that the data set csv file is as follows
a,b,c,d,e,f,g,h,i"""
1,2,4,5
1,0,9,8,7,6,5,4,7
1,3,5,6,7
6,7,8,8,9,4,5,3,5"""
I want a pandas data frame like below
"""a b c d e f g h i
1 2 4 5 ? ? ? ? ?
1 0 9 8 7 6 5 4 7
1 3 5 6 7 ? ? ? ?
6 7 8 8 9 4 5 3 5"""
NaN in place of ? can be ok
we don't have enough commas unequal length problem.

Answer 1

It seems you can use parameter names in read_csv for column names by range (if attributes are columns):
import pandas as pd
from pandas.compat import StringIO
temp=u"""
a,v
c,v,f,r
b,g
y"""
#after testing replace 'StringIO(temp)' to 'filename.csv'
#in real data change 4 to 1461
names = range(4)
df = pd.read_csv(StringIO(temp), names=names)
print (df)
0 1 2 3
0 a v NaN NaN
1 c v f r
2 b g NaN NaN
3 y NaN NaN NaN
EDIT:
temp=u"""a,b,c,d,e,f,g,h,i
1,2,4,5
1,0,9,8,7,6,5,4,7
1,3,5,6,7
6,7,8,8,9,4,5,3,5"""
#after testing replace 'StringIO(temp)' to 'filename.csv'
df = pd.read_csv(StringIO(temp))
print (df)
a b c d e f g h i
0 1 2 4 5 NaN NaN NaN NaN NaN
1 1 0 9 8 7.0 6.0 5.0 4.0 7.0
2 1 3 5 6 7.0 NaN NaN NaN NaN
3 6 7 8 8 9.0 4.0 5.0 3.0 5.0