![]() ![]() DataFrame() Here we will create three columns with the names A, B, and C. We will create some dummy data to illustrate the various techniques. The first steps involve importing the pandas library and creating some dummy data that we can use to illustrate the process of column renaming. You can rename those columns with a dictionary where you can use. If you are interested in learning about other popular Python libraries then you may be interested in this article. If you want to change name of all columns of your dataframe. These tables (dataframes) can be manipulated, analyzed, and visualized using a variety of functions that are available within pandas. It allows data to be loaded in from a number file formats (CSV, XLS, XLSX, Pickle, etc.) and stored within table-like structures. According to Wikipedia, the name originates from the term “panel data”. The Pandas name itself stands for “Python Data Analysis Library”. Renaming Columns in Pandas We will accomplish two things: Show two ways to rename columns in pandas Show the most perfomant method. Here we have two examples of how to rename columns in a Pandas DataFrame. In this short article, we will cover a number of ways to rename columns in a pandas dataframe.īut first, what is Pandas? Pandas is a powerful, fast, and commonly used python library for carrying out data analytics. Renaming DataFrame Columns Using Dictionaries & Lists. ![]() set_axis() function and specify axis = 1 to rename columns, like below □ df.set_axis(, axis=1).A short guide on multiple options for renaming columns in a pandas dataframeĮnsuring that dataframe columns are appropriately named is essential to understanding what data is contained within, especially when we pass our data on to others. this method can be used to label columns as well as rows.Īll you need to do is simply pass the list of column names to the. To use this, we have to pass a key (the original name of. ![]() This method is originally used to set labels to DataFrame’s axis i.e. The Pandas have one in-built function called rename( ) which can change the column name instant. When all above points kept in mind, this is the best method to change all columns in one go. □ Note: The sequence of the column names list should be same in which you have columns in the DataFrame, otherwise the column names can be assigned incorrectly. So, I would suggest to use it only when you are 100% sure that you want to change the column names. The length of this names list must be exactly equal to the total number of columns in the DataFrame.Īnd without any other options like inplace, the column names are changed directly and permanently, this method is a bit risky take.⚠️ Extra labels listed don’t throw an error. Labels not contained in a dict / Series will be left as-is. Function / dict values must be unique (1-to-1). □ Note: You need to pass the names of all the columns. rename DataFrame.rename(mapperNone,, indexNone, columnsNone, axisNone, copyNone, inplaceFalse, levelNone, errors'ignore') source Alter axes labels. But instead of passing the old name - new name key-value pairs, we can also pass a function to columns parameter.įor example, converting all column names to upper case is quite simple using this trick, like below df.rename(columns= str.upper).head()Ĭhanging all column names at once using df.columns | Image by AuthorĪs you can see, I assigned list of new column names to df.columns and names of all columns are changed accordingly. Just like the first method above, we will still use the parameter columns in the. The next methods is a slight variation of. Renaming the columns through a list in pandas requires knowing the shape of the dataset you have. □ Note: Before making inplace = True in any function, it is always good idea to use. How to rename the columns in DataFrame using Pandas In line 1, we use the rename() function and pass in the old column name and the new column name. ![]() head() method to only see how it looks with changed column name. This method is quite useful when we need to rename some selected columns because we need to specify information only for the columns which are to be renamed. In order to retain the changes in the column names, you need to make inplace = True.Īs I did not wanted to retain the changed column names I used. One way of renaming the columns in a Pandas Dataframe is by using the rename () function. □ Note: df.rename() consists an inplace parameter which is False by default. 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. And values are Order_Status and Order_Quantity which are new column names. This method is a way to rename the required columns in Pandas. Rename pandas dataframe columns using df.rename() | Image by AuthorĪs you can see, I passed dictionary in the parameter columns in df.rename(), where keys are Status and Quantity which are old column names. ![]()
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