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By use + operator simply you can combine/merge two or multiple text/string columns in pandas DataFrame. Note that when you apply + operator on numeric columns it actually does addition instead of concatenation.

In pandas you can add/append a new column to the existing DataFrame using DataFrame. insert() method, this method updates the existing DataFrame with a new column. DataFrame. assign() is also used to insert a new column however, this method returns a new Dataframe after adding a new column.

You can add/append a new column to the DataFrame based on the values of another column using df. assign() , df. apply() , and, np. where() functions and return a new Dataframe after adding a new column.

Add a prefix to all columns using add_prefix() The add_prefix() function is actually somewhat limited and takes a single argument containing a string that is to be appended to the beginning of each column name. It returns the original dataframe with the column names prefixed with the provided value.

To add a string after each column label of DataFrame in Pandas, call add_suffix() method on this DataFrame, and pass the suffix string as argument to add_suffix() method.

Select a cell in the column you want to sort. On the Data tab, in the Sort & Filter group, click Sort. In the Sort dialog box, under Column, in the Sort by or Then by box, select the column that you want to sort by a custom list.

To append dataframes with different column names, we need to rename the columns of the second dataframe to match the column names of the first dataframe. We can use the rename() function in Pandas to rename the columns. Now, df2 has the same column names as df1 , and we can append df2 to df1 without any NaN values.