Pandas rename column with list. Often you may want to merge two pandas DataFrames on multiple columns. This method is a way to rename the required columns in Pandas. You just need to separate the renaming of each column using a comma: df = df.rename(columns = {'Colors':'Shapes','Shapes':'Colors'}) So this is the full Python code to rename the columns: Fortunately this is easy to do using the pandas rename() function, which uses the following syntax:. The syntax to replace single column within the same file would be: pandas.DataFrame.rename(columns = {'':''}, inplace = True/False) In this example we will rename Column name "Company" with "Brand" Pandas is one of those packages and makes importing and analyzing data much easier.. Pandas rename() method is used to rename any index, column or row. In this section, we are going to rename grouped columns in Pandas dataframe. Watch out though – Pandas does not know which columns you’re trying to rename. We will re-order the column by moving column z to second and y to third and swap p and q. Let’s see how we can do this by simply assigning the new values in a list to df.columns Often you may want to rename one or more columns in a pandas DataFrame. Renaming of column can also be done by dataframe.columns = [#list].But in the above case, there isn’t … The concept to rename multiple columns in pandas DataFrame is similar to that under example one. pandas.DataFrame.join¶ DataFrame.join (other, on = None, how = 'left', lsuffix = '', rsuffix = '', sort = False) [source] ¶ Join columns of another DataFrame. Renaming Grouped Columns in Pandas Dataframe. Join columns with other DataFrame either on index or on a key column. df.columns = ['x','y','z','p','q'] df Re-Order Columns. The rename method outlined below is more versatile and works for renaming all columns or just specific ones. rename (columns={'old_col':'new_col', 'old_col2':'new_col2'}, inplace= True) This tutorial shows several examples of how to use this function in practice on the following pandas DataFrame: You can just replace the existing column values with the new column in the list. Method 1: Using Dataframe.rename(). $\begingroup$ The whole point is renaming columns with the same name, so this doesn't really help... $\endgroup$ – Danny David Leybzon May 29 '20 at 15:43 $\begingroup$ df.columns[1] will give a column name, and then it replaces all the columns with that name as "new_col_name" which defeats the whole purpose of this question. Fortunately this is easy to do using the pandas merge() function, which uses the following syntax: pd. pd.merge(df1, df2, left_on='UserName', right_on='UserID', keep_column='left') df. Only the ways I can think of are either re-naming the columns to be the same before merge, or droping one of them after merge. The other technique for renaming columns is to call the rename method on the DataFrame object, than pass our list of labelled values to the columns parameter: df.rename(columns={0 : 'Title_1', 1 : 'Title2'}, inplace=True) The second way to rename your columns is by setting DataFrame.columns to the list of your new column names. Efficiently join multiple DataFrame objects by index at once by passing a list. This will completely overwrite your original columns with your new list. merge (df1, df2, left_on=['col1','col2'], right_on = ['col1','col2']) This tutorial explains how to use this function in practice. Python is a great language for doing data analysis, primarily because of the fantastic ecosystem of data-centric python packages. 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