inputting and aligning protein sequence - input

Question

I have a script for finding mutated positions in protein sequence.The following script will do this.
import pandas as pd #data analysis python module
data = 'MTAQDDSYSDGKGDYNTIYLGAVFQLN,MTAQDDSYSDGRGDYNTIYLGAVFQLN,MTSQEDSYSDGKGNYNTIMPGAVFQLN,MTAQDDSYSDGRGDYNTIMPGAVFQLN,MKAQDDSYSDGRGNYNTIYLGAVFQLQ,MKSQEDSYSDGRGDYNTIYLGAVFQLN,MTAQDDSYSDGRGDYNTIYPGAVFQLN,MTAQEDSYSDGRGEYNTIYLGAVFQLQ,MTAQDDSYSDGKGDYNTIMLGAVFQLN,MTAQDDSYSDGRGEYNTIYLGAVFQLN' #protein sequences
df = pd.DataFrame(map(list,data.split(',')))
I = df.columns[(df.ix[0] != df).any()]
J = [pd.get_dummies(df[i], prefix=df[i].name+1, prefix_sep='') for i in I]
print df[[]].join(J)
Here I gave the data(hard coded) ie, input protein sequences .Normally in an application user has to give the input sequences ie, I mean soft coding.
Also here alignment is not done.I read biopython tutorial and i got following script,but I don't know how to add these scripts to above one.
from Bio import AlignIO
alignment = AlignIO.read("c:\python27\proj\data1.fasta", "fasta")
print alignment
How can I do these
What I have tried :
>>> import sys
>>> import pandas as pd
>>> from Bio import AlignIO
>>> data=sys.stdin.read()
MTAQDDSYSDGKGDYNTIYLGAVFQLN
MTAQDDSYSDGRGDYNTIYLGAVFQLN
MTSQEDSYSDGKGNYNTIMPGAVFQLN
MTAQDDSYSDGRGDYNTIMPGAVFQLN
MKAQDDSYSDGRGNYNTIYLGAVFQLQ
MKSQEDSYSDGRGDYNTIYLGAVFQLN
MTAQDDSYSDGRGDYNTIYPGAVFQLN
MTAQEDSYSDGRGEYNTIYLGAVFQLQ
MTAQDDSYSDGKGDYNTIMLGAVFQLN
MTAQDDSYSDGRGEYNTIYLGAVFQLN
^Z
>>> df=pd.DataFrame(map(list,data.split(',')))
>>> I=df.columns[(df.ix[0]!=df).any()]
>>> J=[pd.get_dummies(df[i],prefix=df[i].name+1,prefix_sep='')for i in I]
>>> print df[[]].join(J)
But it is giving empty DataFrame as output.
I also tried following, but i don't know how to load these sequences into my script
while 1:
var=raw_input("Enter your sequence here:")
print "you entered ",var
Please help me.

Answer 1

When you read in data via:
sys.stdin.read()
Sequences are separating using '\n' rather than ',' (printing data would confirm whether this is the case, it may be system dependent), so you should split using this:
df = pd.DataFrame(map(list,data.split('\n')))
A good way to check this kind of thing is to go through it line by line, where you would see that df was a one row DataFrame (which then propagates to make I empty).
Aside: what a well written piece of code you are using! :)