从字符串的开头删除提供的字母列表

Question

I have a dataframe-df with column "Names" as below :

Names
AL GHAITHA & AL MOOSA
AL ASEEL ELECTRONICS T
SUNRISE SUPERMARKET-QU
EMARAT-AL SAFIYAH(6735
LULU CENTRE LLC EFT TE
THE MAX

Code :

remove_letters = ['AL ', 'THE ']

# my function below :

def remove_start_words(df, col, letters):
    for l in letters:
        for i in df.index:
            x = df.at[i, col]
            if x.startswith(l):
                df.at[i, col] = x[len(l):]
            else:
                df.at[i, col] = x

def remove_strings(self, df, col):
    for i in df.index:
        x = df.at[i, col]
        x = x.split(' ')
        if len(x) > 1:
            if len(x[1]) > 2:
                x[1] = ''.join(e for e in x[1] if e.isalnum())
                x = ' '.join(x[0:2])
                df.at[i, col] = x
            else:
                df.at[i, col] = x[0]
        else:
            df.at[i, col] = df.at[i, col]


def remove_end_digits(self, df, col):
    for i in df.index:
        x = df.at[i, col]
        df.at[i, col] = x.rstrip(string.digits)

# calling my function
remove_start_words(df=df, col='Names',
                          letters=remove_letters)

remove_strings(df=df, col='Names')
remove_end_digits(df=df, col='Names')

Now the problem is i have a dataframe of more than 1 million column values. My code is not well optimized ? How to get a optimized solution ?

Issue 1 : I can understand i have used 2 loops ( 1 for remove_letters and other for all the column values) that is causing slowness.

Is there a better way ? where i can check if the column values start with the letters mentioned in remove_letters list and strip them at one shot ?

Issue 2 & 3 : What is objective of the function - "remove_strings" : Get only the 2 strings from the column names. For eg : ASEEL ELECTRONICS T output will be : ASEEL ELECTRONICS

Is there a faster way for the functions : remove_strings,remove_end_digits

Main issue : Can all this 3 functions can be done at one shot all together ?

Expected dataframe:

Names
GHAITHA
ASEEL ELECTRONICS
SUNRISE SUPERMARKET
EMARAT-AL SAFIYAH
LULU CENTRE
MAX

NOTE : The function "remove_start_words" should check if any of the mentioned letters are starting in the "Names" if so, remove them. For eg : "AL THEMAX" should be "THEMAX" not as "MAX" (removing both AL and THE)

Thanks in advance.

Answer 1

You can use the replace method like this:

import pandas as pd

file_path = 'file3.xlsx'

df = pd.read_excel(file_path)

words_to_remove = ["THE", "AL"]

for word in words_to_remove:
    df.Names = df.Names.str.replace(word, "")

print(df)

Answer 2

Since you said you only wanted the words removed from the beginning of the sentence, you could use regular expression :

import pandas as pd

file_path = 'file3.xlsx'

df = pd.read_excel(file_path)

words_to_remove = ["THE", "AL"]
regular_expression = '^' + '|'.join(words_to_remove)

df.Names = df.Names.apply(lambda x : re.sub(regular_expression, "", x))

the regular_expression expression variable would contain ^THE|AL in this case meaning THE or AL at the beginning of the string.

Answer 3

A couple minutes of searching on Google tells me that

def stripper(delete_list):
    def delete(item):
        nonlocal delete_list
        for rm in delete_list:
            item = item.lstrip(rm)
        return item
    return delete

df['Names'] = df['Names'].apply(stripper(['AL', 'THE'])

should do the trick.