special-characters

来源： https://stackoverflow.com/questions/64238735/to-prevent-entering-special-characters-on-textbox-already-have-thousand-of-tex

来源： https://stackoverflow.com/questions/47301795/removing-special-characters-from-a-list-of-items-in-python

来源： https://stackoverflow.com/questions/47301795/removing-special-characters-from-a-list-of-items-in-python

来源： https://stackoverflow.com/questions/33695132/importing-data-with-special-characters-in-r

来源： https://stackoverflow.com/questions/42948228/removing-null-characters-from-big-files-in-windows

来源： https://stackoverflow.com/questions/42948228/removing-null-characters-from-big-files-in-windows

来源： https://stackoverflow.com/questions/42948228/removing-null-characters-from-big-files-in-windows

问题 Sorry if the title is confusing but I have literally researched this for two hours and have no idea how I am supposed to ask this question so anyone feel free to edit this post. I have this string variable that I created using web scraping and it uses special characters and looks something like "\ud83d\ude00\u0107\u00e7 \n hello" without the quotations when I print it. The issue is that I want it to print the actual special characters but I am not sure what encoding method I should use. If I

问题 I have a dataframe in pyspark which has 15 columns. The column name are id , name , emp.dno , emp.sal , state , emp.city , zip ..... Now I want to replace the column names which have '.' in them to '_' Like 'emp.dno' to 'emp_dno' I would like to do it dynamically How can I achieve that in pyspark? 回答1: You can use something similar to this great solution from @zero323: df.toDF(*(c.replace('.', '_') for c in df.columns)) alternatively: from pyspark.sql.functions import col replacements = {c:c

问题 I have a dataframe in pyspark which has 15 columns. The column name are id , name , emp.dno , emp.sal , state , emp.city , zip ..... Now I want to replace the column names which have '.' in them to '_' Like 'emp.dno' to 'emp_dno' I would like to do it dynamically How can I achieve that in pyspark? 回答1: You can use something similar to this great solution from @zero323: df.toDF(*(c.replace('.', '_') for c in df.columns)) alternatively: from pyspark.sql.functions import col replacements = {c:c