Ignore character while importing with pandas
csv, pandas, python
Solution
Expanding on Peruz's answer:-
For your case, using regex
`df = pd.read_csv(filename, sep="(?<!<>)\s+", engine='python') `
This should read in the columns properly, except that the first column would be named `<> A`
To change this, simply alter the first column name
`df.columns = pd.Series(df.columns.str.replace("<>\s", ""))`
In the regex expression, `\s+` matches any number of space characters except when preceded by whatever is mentioned in the negative lookaround denoted by `(?<!charceters_to_ignore)`
Problem
I could not find such an option in the documentation. A measuring device spits out everything in Excel: ``` <> A B C 1 2 3 ``` When I delete the "<>" characters manually everything works fine. Is there a way to circumvent that (without conversion to csv)? I do: ``` import pandas as pd df = pd.read_excel(filename,sheetname,skiprows=0,header=0,index_col=0) ``` `skiprow = 1` does not do the trick since pandas uses the first row as names. If I supply `names = list(range(1, 4))` the first data row is lost.