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I'm writing a script to reduce a large .xlsx file with headers into a csv, and then write a new csv file with only the required columns based on header name.
import pandas import csv df = pandas.read_csv('C:\\Python27\\Work\\spoofing.csv') time = df["InviteTime (Oracle)"] orignum = df["Orig Number"] origip = df["Orig IP Address"] destnum = df["Dest Number"] df.to_csv('output.csv', header=[time,orignum,origip,destnum]) The error I'm getting is with that last bit of code, and it says
ValueError: Writing 102 cols but got 4 aliases I'm sure i'm overlooking something stupid, but I've read over the to_csv documentation on the pandas website and I'm still at a loss. I know I'm using the to_csv parameters incorrectly but I can't seem to get my head around the documentation I guess.
Any help is appreciated, thanks!
932
By using pandas. DataFrame. to_csv() method you can write/save/export a pandas DataFrame to CSV File. By default to_csv() method export DataFrame to a CSV file with comma delimiter and row index as the first column.
Pandas is a very powerful and popular framework for data analysis and manipulation. One of the most striking features of Pandas is its ability to read and write various types of files including CSV and Excel.
to_csv() function write the given series object to a comma-separated values (csv) file/format. Parameter : path_or_buf : File path or object, if None is provided the result is returned as a string.
The way to select specific columns is this -
header = ["InviteTime (Oracle)", "Orig Number", "Orig IP Address", "Dest Number"] df.to_csv('output.csv', columns = header) If you love us? You can donate to us via Paypal or buy me a coffee so we can maintain and grow! Thank you!
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