If you want to convert a CSV file into Pandas, you can use
The function takes several options. One of them is
sep (default value is
You can use a regular expression to customize the delimiter.
Let’s say your data looks like this:
vhigh,high,2,2,more,small med,vhigh,3,more,big ...
You want to load that data into a Pandas DataFrame. You can split each line on the comma, but you want to ignore the comma inside floating point numbers like
pd.read_csv("../path/to/file.csv", sep="(?<=\D)\,|\,(?=\D)", engine="python");
That’s quite a complicated regular expression which uses group constructs.
But Pandas is able to handle it. Use
engine="python" for the parser engine.
The default parser uses C. It’s faster, but not as feature-complete.
You’ll get a result similar to this: