I have the following ddataframe:
Company Name Time Expectation
0 Asta Funding Inc. (ASFI) 9:35 AM ET -
1 BlackBerry (BBRY) 7:00 AM ET ($0.03)
2 Carnival Corp. (CCL) 9:15 AM ET $0.09
3 Carnival PLC (CUK) 0:00 AM ET -
I would like to have the company symbols in their own seperate column instead of inside the Company Name column. Right now I just have it iterate over the company names, and a RE pulls the symbols, puts it into a list, and then I apply it to the new column, but I'm wondering if there is a cleaner/easier way.
I'm new to the whole map reduce lambda stuff.
for company in df['Company Name']:
ticker = re.search("\(.*\)",company).group(0)
ticker = ticker[1:len(ticker)-1]
tickers.append(ticker)
Regex search is built into the Series class in pandas. You can find the documentation here. In your case, you could use
df['ticker'] = df['Company Name'].str.extract("\((.*)\)")
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