Dataframe How To Update A Column Based Many Str Values

I am creating a small financial management program which imports my transactions from CSV into Python. I want to assign values to a new column 'category' based on strings found in

Solution 1:

If you have one value, we can use str.extract:

df['category'] = df['details'].str.extract(f'({str_xfer})')

   amount          details  category
0-68.23  PAYPAL TRANSFER  TRANSFER
1-12.46     RALPHS #0079       NaN2-8.51   SAVE AS YOU GO       NaN325.34    VENMO CASHOUT       NaN4-2.23  PAYPAL TRANSFER  TRANSFER
5-64.29  PAYPAL TRANSFER  TRANSFER

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If you have multiple strings to match, we have to delimit your strings first by |, which is the or operator in regular expressions.

str_xfer = ['TRANSFER', 'RALPHS', 'CASHOUT']
str_xfer = '|'.join(str_xfer)

df['category'] = df['details'].str.extract(f'({str_xfer})')

amountdetailscategory0-68.23PAYPALTRANSFERTRANSFER1-12.46RALPHS#0079RALPHS2-8.51SAVEASYOUGONaN325.34VENMOCASHOUTCASHOUT4-2.23PAYPALTRANSFERTRANSFER5-64.29PAYPALTRANSFERTRANSFER

Solution 2:

I think you need str.findall

df['category']=df.details.str.findall('TRANSFER').str[0].fillna(0)
df
   amount          details  category
0  -68.23  PAYPAL TRANSFER  TRANSFER
1  -12.46     RALPHS #0079         0
2   -8.51   SAVE AS YOU GO         0
3   25.34    VENMO CASHOUT         0
4   -2.23  PAYPAL TRANSFER  TRANSFER
5  -64.29  PAYPAL TRANSFER  TRANSFER

If you have more than one string in str_xfer adding '|'

df.details.str.findall('TRANSFER|VENMO').str[0]0TRANSFER1NaN2NaN3VENMO4TRANSFER5TRANSFERName: details, dtype: object