[FIXED] Pandas remove characters from a column of strings

Issue

I have a dataframe with a Date column consisting of stings in this format. I need to strip the end of the strin so that I can convert to a datetime object.

"20231101 05:00:00 America/New_York" "20231101 06:00:00 America/New_York"

I have tried these approaches unsuccessfully.

df['Date'] = df['Date'].replace('^.*\]\s*', '', regex=True)
df['Date'] = df['Date'].str.strip(' America/New_York')
df['Date'] = df['Date'].map(lambda x: x.rstrip(' America/NewYork'))``

as well as a couple of others based on my searches. Is there an easy way to do this or should I write a function to slice the string by grabbing the first 17 characters and assigning the result back to the df. Note the string could be of the form '20231101 05:00:00 America/Central' Thanks for any and all assistance.

Solution

• If you want to remove a particular suffix, then I recommend str.removesuffix rather than str.strip.
• Notice that you sometimes write New_York with an underscore and sometimes NewYork without an underscore. If you ask to remove 'NewYork' then 'New_York' won't be removed.
• After the edit in your question, the suffixes all start with ' America' but differ afterwards; in this case you could use str.split(' America').str[0] to keep everything before ' America'.

import pandas as pd

df = pd.DataFrame({
    'Name': ['Alice', 'Bob', 'Charlie'],
    'Date': ["20231101 05:00:00 America/New_York",
             "20231101 06:00:00 America/New_York",
             "20231101 07:00:00 America/Central"]
})

# df['Date'] = df['Date'].str.removesuffix(' America/New_York')
df['Date'] = df['Date'].str.split(' America').str[0]

print(df)
#      Name               Date
# 0    Alice  20231101 05:00:00
# 1      Bob  20231101 06:00:00
# 2  Charlie  20231101 07:00:00

Answered By - Stef