The background:
Table$Gene=Gene1
time n.risk n.event survival std.err lower 95% CI upper 95% CI
0 2872 208 0.928 0.00484 0.918 0.937
1 2664 304 0.822 0.00714 0.808 0.836
2 2360 104 0.786 0.00766 0.771 0.801
3 2256 48 0.769 0.00787 0.754 0.784
4 2208 40 0.755 0.00803 0.739 0.771
5 2256 48 0.769 0.00787 0.754 0.784
6 2208 40 0.755 0.00803 0.739 0.771
Table$Gene=Gene2
time n.risk n.event survival std.err lower 95% CI upper 95% CI
0 2872 208 0.938 0.00484 0.918 0.937
1 2664 304 0.822 0.00714 0.808 0.836
2 2360 104 0.786 0.00766 0.771 0.801
3 2256 48 0.769 0.00787 0.754 0.784
4 1000 40 0.744 0.00803 0.739 0.774
#There is a new line ("\n") here too, it just doesn't come out in the code.
What I want seems simple. I want to turn the above file into an output that looks like this:
Gene1 0.755
Gene2 0.744
ie each gene, and the last number in the survival column from each section.
I have tried multiple ways, using regular expression, reading the file in as a list and saying ".next()". One example of code that I have tried:
fileopen = open(sys.argv[1]).readlines() # Read in the file as a list.
for index,line in enumerate(fileopen): # Enumerate items in list
if "Table" in line: # Find the items with "Table" (This will have my gene name)
line2 = line.split("=")[1] # Parse line to get my gene name
if "\n" in fileopen[index+1]: # This is the problem section.
print fileopen[index]
else:
fileopen[index+1]
So as you can see in the problem section, I was trying to say in this attempt:
if the next item in the list is a new line, print the item, else, the next line is the current line (and then I can split the line to pull out the particular number I want).
If anyone could correct the code so I can see what I did wrong I'd appreciate it.
Bit of overkill, but instead of manually writing parser for each data item use existing package like pandas to read in the csv file. Just need to write a bit of code to specify the relevant lines in the file. Un-optimized code (reading file twice):
import pandas as pd
def genetable(gene):
l = open('gene.txt').readlines()
l += "\n" # add newline to end of file in case last line is not newline
lines = len(l)
skiprows = -1
for (i, line) in enumerate(l):
if "Table$Gene=Gene"+str(gene) in line:
skiprows = i+1
if skiprows>=0 and line=="\n":
skipfooter = lines - i - 1
df = pd.read_csv('gene.txt', sep='\t', engine='python', skiprows=skiprows, skipfooter=skipfooter)
# assuming tab separated data given your inputs. change as needed
# assert df.columns.....
return df
return "Not Found"
this will read in a DataFrame with all the relevant data in that file
can then do:
genetable(2).survival # series with all survival rates
genetable(2).survival.iloc[-1] last item in survival
The advantages of this is that you have access to all the items, any mal-formatting of the file will probably be better picked up and prevent incorrect values from being used. If my own code i would add assertions on column names before returning the pandas DataFrame. Want to pick up any errors in parsing early so that it does not propagate.
This worked when I tried it:
gene = 1
for i in range(len(filelines)):
if filelines[i].strip() == "":
print("Gene" + str(gene) + " " + filelines[i-1].split()[3])
gene += 1
You could try something like this (I copied your data into foo.dat
);
In [1]: with open('foo.dat') as input:
...: lines = input.readlines()
...:
Using with
makes sure the file is closed after reading.
In [3]: lines = [ln.strip() for ln in lines]
This gets rid of extra whitespace.
In [5]: startgenes = [n for n, ln in enumerate(lines) if ln.startswith("Table")]
In [6]: startgenes
Out[6]: [0, 10]
In [7]: emptylines = [n for n, ln in enumerate(lines) if len(ln) == 0]
In [8]: emptylines
Out[8]: [9, 17]
Using emptylines
relies on the fact that the records are separated by lines containing only whitespace.
In [9]: lastlines = [n-1 for n, ln in enumerate(lines) if len(ln) == 0]
In [10]: for first, last in zip(startgenes, lastlines):
....: gene = lines[first].split("=")[1]
....: num = lines[last].split()[-1]
....: print gene, num
....:
Gene1 0.771
Gene2 0.774
here is my solution:
>>> with open('t.txt','r') as f:
... for l in f:
... if "Table" in l:
... gene = l.split("=")[1][:-1]
... elif l not in ['\n', '\r\n']:
... surv = l.split()[3]
... else:
... print gene, surv
...
Gene1 0.755
Gene2 0.744
Instead of checking for new line, simply print when you are done reading the file
lines = open("testgenes.txt").readlines()
table = ""
finalsurvival = 0.0
for line in lines:
if "Table" in line:
if table != "": # print previous survival
print table, finalsurvival
table = line.strip().split('=')[1]
else:
try:
finalsurvival = line.split('\t')[4]
except IndexError:
continue
print table, finalsurvival
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