Rename the specific column in python: Below code will rename the specific column. Pandas rename column with list. Rename single column. This method is a way to rename the required columns in Pandas. Fortunately this is easy to do using the pandas rename() function, which uses the following syntax:. Join columns with other DataFrame either on index or on a key column. Renaming of column can also be done by dataframe.columns = [#list].But in the above case, there isn’t … 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. 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. merge (df1, df2, left_on=['col1','col2'], right_on = ['col1','col2']) This tutorial explains how to use this function in practice. The concept to rename multiple columns in pandas DataFrame is similar to that under example one. First, we are going to use Pandas groupby method (if needed, check the post about Pandas groupby method for more information). In this section, we are going to rename grouped columns in Pandas dataframe. You can just replace the existing column values with the new column in the list. Method 2 – Pandas .columns attribute. 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: Often you may want to rename one or more columns in a pandas DataFrame. $\begingroup$ 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. The second way to rename your columns is by setting DataFrame.columns to the list of your new column names. I would be nice if pandas automatically drops one of them or I could do something like. 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) It allows us to specify the columns’ names to be changed in the form of a dictionary with the keys and values as the current and new names of the respective columns. # rename province to state df1.rename(columns={'Province': 'State'}, inplace=True) the column named Province is renamed to State with the help of rename() Function so the resultant dataframe will be pandas.DataFrame.join¶ DataFrame.join (other, on = None, how = 'left', lsuffix = '', rsuffix = '', sort = False) [source] ¶ Join columns of another DataFrame. 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" 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. Fortunately this is easy to do using the pandas merge() function, which uses the following syntax: pd. This will completely overwrite your original columns with your new list. Efficiently join multiple DataFrame objects by index at once by passing a list. Often you may want to merge two pandas DataFrames on multiple columns. df. Renaming Grouped Columns in Pandas Dataframe. Watch out though – Pandas does not know which columns you’re trying to rename. Python is a great language for doing data analysis, primarily because of the fantastic ecosystem of data-centric python packages. 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