How to split a single column data by a specific expression?

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Pandas and Python Gurus,**

I have a single column data, with several information (changing all the time) and I'll love to separate by areas of expression, example:

Currently using the pandas.read_cvs to pull data into DF.

# Add the dependencies.
import pandas as pd
import os

# Files to load
Raw_Data_load = os.path.join("Resources", "Raw_Data.csv")

# Read the raw data file and store it in a Pandas DataFrame.
raw_data_df = pd.read_csv(Raw_Data_load)
raw_data_df
Raw Data
Sun Jan 11 07:46:33 -0600 [LKSDFLKLKJF-56: bacml: warn:error]: Address failed 7a-123478563412. Reason: Failed to access remote.
Mon Feb 21 13:31:45 -0400 [LHHKJLKJD-01: repi_exemptXY: create.done:info]: params: {'1', 'app'}:
Thu May 15 12:33:06 -0500 [DRHHFJJHS-08: UDPAgentRead: SessionFailed:debug]: Session Manager (999) failed

And I'll like the data separate like the below:

Data Time AZ Error Action
Sun Jan 11 07:46:33 -0600 [LKSDFLKLKJF-56: bacml: warn:error]: Address failed 7a-123478563412. Reason: Failed to access remote.
Mon Feb 21 13:31:45 -0400 [LHHKJLKJD-01: repi_exemptXY: create.done:info]: params: {'1', 'app'}:
Thu May 15 12:33:06 -0500 [DRHHFJJHS-08: UDPAgentRead: SessionFailed:debug]: Session Manager (999) failed

Please Note: Raw data is different, changes date, time, AZ, Error and Action.

Big question here using Pandas:

How can I tell my script to separate from Raw Data to Clean Data as per example above?

0 Answers
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