df.drop if it exists

Question

Below is a function that takes a file and drops column names 'row_num", 'start_date', 'end_date.'

The problem is not every file has each of these column names, so the function returns an error.

My goal is to alter code so that it removes these columns if it exists but does not return an error if the column does not exist.

def read_df(file):     df = pd.read_csv(file, na_values=['', ' '])     # Drop useless junk and fill empty values with zero      df = df.drop(['row_num','start_date','end_date','symbol'], axis=1).fillna(0)     df=df[df!=0][:-1].dropna().append(df.iloc[-1])     return df 

Answer 1

Add parameter errors to DataFrame.drop:

errors : {'ignore', 'raise'}, default 'raise'

If 'ignore', suppress error and only existing labels are dropped.

df = df.drop(['row_num','start_date','end_date','symbol'], axis=1, errors='ignore') 

Sample:

df = pd.DataFrame({'row_num':[1,2], 'w':[3,4]}) df = df.drop(['row_num','start_date','end_date','symbol'], axis=1, errors='ignore') print (df)    w 0  3 1  4