I have created a pandas dataframe called df using this code: import numpy as np import pandas as pd The dataframe looks like this: The columns contain some special characters (/ and @) that I need to replace with a blank space. Now, I have a list of special characters: listOfSpecialChars = ‘¬`!”£$£#/,.+*><@|”‘ How can I replace any of the
Tag: special-characters
Python 2.7 convert special characters into utf-8 byes
I have strings that I need to replace into an URL for accessing different JSON files. My problem is that some strings have special characters and I need only these as UTF-8 bytes, so I can properly find the JSON tables. An example: I managed to get the spaces converted right using urllib.quote(), but it does not convert the special
pyspark – filter rows containing set of special characters
I have a data frame as follow:- Now I want to find the count of total special characters present in each column. So I have used str. contains function to find it, though it is running but it does not find the special characters. Answer You may want to use rlike instead of contains, which allows to search for regular