Import 2 columns from 8 .csv files into pandas df (side by side) and write a new csv
I have 8 .csv files with 16 columns and "n" rows with no Header. I want to parse each of these .csv and get column [0, 8] [#where column 0 is the value of x, y, z etc and column 8 is always the value of a#] and put the data into a new.csv. Once this is done, the new.csv should have 16 columns (2 from each input.csv) and "n" rows.
Now, I want to just take the average of Column[1,3,5,7,9,11,13,15] from new.csv and append it to another file or this file. Basically in the new csv, i want to have the average of colum[8] form the input files and each of the column[0] from the input files. So the final output expecting should have a shape of 9 columns and n rows.
sample input files:
Then I was to do the looping for all the 16 columns (taking the following sets as[n,n+8] where n=0 to 7.
Apologize for the lengthy description, but I can't seem to append the columns in python.
Thanks in advance.
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Here is a sample code I started with:
Hi everyone,
I need to merge two files side by side
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HOSTNAME
fishtornado-K52F 127.0.1.1
UPTIME
20:17:01 up 2:19, 3 users,
load average: 0.00, 0.04, 0.05
DISK USAGE
(Size/Used/Avail/Use%)
29G 6.5G 21G 25%
RUN QUEUE
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file6324
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