Pandas dataframe remove last "\" from Parent and Child columns

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I have a pandas data frame and am looking to remove everything before and the last \ so that all that is left is the executable. This is what I would like to achieve: C:\Windows\System32\services.exe to just services.exe

    Parent                              Child                           PID     PID System_Or_User
0   C:\Windows\System32\services.exe    C:\Windows\System32\svchost.exe 10396   752 System
1   C:\Windows\System32\services.exe    C:\Windows\System32\svchost.exe 11688   752 System
2   C:\Windows\System32\services.exe    C:\Windows\System32\svchost.exe 11624   752 System

I have tried a few things like this but can't seem to get it right maybe because of the \ used in windows and python not liking it:

PID['Parent'] = PID['Parent'].apply(lambda x: x[0].split('\ ')[-1])

PID['Parent'] = PID['Parent'].apply(lambda x: x[0].split(' \ ')[+1])

Use str.split by escape \ with indexing - select last value of lists:

PID['Parent'] = PID['Parent'].str.split('\\').str[-1]
PID['Child'] = PID['Child'].str.split('\\').str[-1]

Another similar idea - use str.rsplit with n=1 for split by last \ for better performance:

PID['Parent'] = PID['Parent'].str.rsplit('\\', n=1).str[-1]
PID['Child'] = PID['Child'].str.rsplit('\\', n=1).str[-1]

Detail:

print (PID['Parent'].str.rsplit('\\', n=1))
0    [C:\Windows\System32, services.exe]
1    [C:\Windows\System32, services.exe]
2    [C:\Windows\System32, services.exe]
Name: Parent, dtype: object

print (PID)
         Parent        Child    PID PID System_Or_User
0  services.exe  svchost.exe  10396         752 System
1  services.exe  svchost.exe  11688         752 System
2  services.exe  svchost.exe  11624         752 System

Pandas: Remove last n rows of a given DataFrame, Write a Pandas program to remove last n rows of a given DataFrame. Sample Solution : Python Code : import pandas as pd d = {'col1': [1, 2, 3, 4,  df = df.drop(labels='column_to_delete', axis=1) # axis 1 drops columns, 0 will drop rows that match index value in labels Note also you misunderstand what tail does, it returns the last n rows (default is 5) of a dataframe. Additional

Use str.split and str.get, with escaping the backslash by typing \\

df.Parent.str.split('\\').str.get(-1)

0    services.exe
1    services.exe
2    services.exe
Name: Parent, dtype: object

How to delete the last row of data of a pandas dataframe, dropping last n rows: df.drop(df.tail(n).index,inplace=True) # drop last n rows. Similarly, you can drop first n rows: df.drop(df.head(n).index  Last update on February 26 2020 08:09:31 (UTC/GMT +8 hours) Pandas: DataFrame Exercise-63 with Solution Write a Pandas program to remove last n rows of a given DataFrame.

You're dealing with paths. If you want a cross platform solution, I recommend leaving the splitting to os.path.

This should be as fast as (or faster than) the str. methods.

import os
df['Parent'] = [os.path.basename(v) for v in df['Parent']]
df['Child'] = [os.path.basename(v) for v in df['Child']]

Alternatively, you may use os.path.split.

df['Parent'] = [os.path.split(v)[-1] for v in df['Parent']]
df['Child'] = [os.path.split(v)[-1] for v in df['Child']]

pandas.DataFrame.drop, Use drop() to delete rows and columns from pandas.DataFrame.Before version 0.21.0, specify row / column with parameter labels and axis. Use drop() to delete rows and columns from pandas.DataFrame.Before version 0.21.0, specify row / column with parameter labels and axis. index or columns can be used from 0.21.0.pandas.DataFrame.drop — pandas 0.21.1 documentation Here, the following contents will be described.Delete rows from DataFr

Or maybe str.replace

df.Parent.str.replace(r"C:\\Windows\\System32\\","")
Out[25]: 
0    services.exe
1    services.exe
2    services.exe
Name: Parent, dtype: object

pandas: Delete rows, columns from DataFrame with drop(), Drop a row if it contains a certain value (in this case, “Tina”). Specifically: Create a new dataframe called df that includes all rows where the  pandas.DataFrame.last ¶ DataFrame.last(self: ~FrameOrSeries, offset) → ~FrameOrSeries [source] ¶ Method to subset final periods of time series data based on a date offset. offsetstr, DateOffset, dateutil.relativedelta. subsetsame type as caller. If the index is not a DatetimeIndex. Select initial periods of time series based on a date offset.

Dropping Rows And Columns In pandas Dataframe, Pandas provide data analysts a way to delete and filter data frame using .drop() method. Rows or columns can be removed using index label or column name  Extract first n characters from left of column in pandas python; Extract last n characters from right of the column in pandas python; Replace a substring of a column in pandas python; Regular expression Replace of substring of a column in pandas python; Repeat or replicate the rows of dataframe in pandas python (create duplicate rows)

Python, The Pandas DataFrame – loading, editing, and viewing data in Python what a DataFrame actually is, renaming and deleting data frame columns and rows, and where to go The opposite is DataFrame.tail(), which gives you the last 5 rows. Drop a row if it contains a certain value (in this case, “Tina”) Specifically: Create a new dataframe called df that includes all rows where the value of a cell in the name column does not equal “Tina” df[df.name != 'Tina'] Drop a row by row number (in this case, row 3) Note that Pandas uses zero based numbering, so 0 is the first row

Python Pandas DataFrame: load, edit, view data, Cleaning your Pandas Dataframes: dropping empty or problematic data. If you'​re looking to drop rows (or columns) containing empty data, you're in Unlike previous methods, the popular way of handling this is simply by  pandas.DataFrame.drop¶ DataFrame.drop (self, labels=None, axis=0, index=None, columns=None, level=None, inplace=False, errors='raise') [source] ¶ Drop specified labels from rows or columns. Remove rows or columns by specifying label names and corresponding axis, or by specifying directly index or column names.