Issue
I have a csv file with 6901 rows x 42 column. 39 columns of this file is a matrix of data that I would like to do some analysis on. I do not know how to extract this data from pandas as a matrix which does not need index and treat it as a numerical matrix.
df1=pd.read_csv(fileName, sep='\\t',lineterminator='\\r', engine='python', header='infer')
df1.info()
< bound method DataFrame.info of Protein.IDs ... Ratio.H.L.33
0 A0A024QZP7;P06493;P06493-2;E5RIU6;A0A087WZZ9 ... 47.88100
1 A0A024QZX5;A0A087X1N8;P35237 ... 0.13615
2 A0A024R0T9;K7ER74;P02655;Q6P163;V9GYJ8 ... NaN
3 A0A024R4E5;Q00341;Q00341-2;H0Y394;H7C0A4;C9J5E... ... 5.97650
4 A0A087WZA9;A0A024R4K9;A0A087X266;Q9BXJ8-2;Q9BXJ8 ... NaN
... ... ...
6896 V9GYT7 ... NaN
6897 V9GZ54 ... NaN
6898 X5CMH5;A0A140T9S0;A0A0G2JLV0;A0A087WYD6;E7ENX8... ... NaN
6899 X6RAL5;H7BZW6;U3KPY7 ... NaN
6900 X6RJP6 ... NaN
[6901 rows x 42 columns] >
Then I would like to put the column 4 to 42 as a normal matrix for computation. Does anyone knows how to do it?
Solution
pandas provides you with everything you need. :) You dont need to convert it to a numpy array. This way you will keep a couple of handy methods from pandas DataFrames :)
You have a .csv file which means "comma seperated values" - that has historical reason but nowdays the values are seperated by different signs or in panda-terms by different seperators, short sep. For example commas, semi-colons, tabs.
Your data shows a seperation by semi-colons, so you should use sep=';' in your pd.read_csv command.
You want to ignore the first 3 columns as i understood. So you just set the pd.read_csv
variable usecols
(=use columns)
usecols=range(4,43)
usecols expects you to tell him exactly the columns you wanna use. You can just give him a range from 4 to 43 or you can pass a list
a=[4,5,6,7,....,42]
which is obviously only handy if you want to define specific columns. The python-function range does this messy job for you.
So your command should look like this:
df1=pd.read_csv(fileName, sep=';',lineterminator='\\r', engine='python', header='infer',usecols=range(4,43))
Best regards
Answered By - Jakob Answer Checked By - Clifford M. (PHPFixing Volunteer)
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