Pandas set column names

Pandas The rename function can be used for renaming the columns. We use cookies to provide a more personalized and relevant experience for you, and web analytics for us.

For more information, see the following article:. The sample code in this article uses pandas version 2. The following DataFrame is used as an example. The columns argument is used for changing column names, and the index argument is used for changing index names. If you want to change either, you should specify only one of columns or index.

Pandas set column names

When data is imported into Pandas DataFrame, it sometimes contains incorrect or messy column names, requiring you to go through the tedious process of renaming all or some of them. Replacing messy column names with meaningful ones is an essential step in data cleaning. It makes the entire code more readable and saves a lot of time during the next steps of data processing. It is a simple x 12 data set, which I created. Here, the word — axis — refers to both rows and columns depending on which value we set for the parameter axis in this function. So, the important parameter for us in. To replace some or all of the column names, all you need to do is pass a dictionary where keys will be old column names and values will be the new column names as mentioned below. As you can see, I passed dictionary in the parameter columns in df. The next method is a slight variation of. Just like the first method above, we will still use the parameter columns in the. But instead of passing the old name-new name key-value pairs, we can also pass a function to the columns parameter. For example, converting all column names to upper case is quite simple using this trick below. I simply used a string function str. In this way, all the column names will be altered in one go. However, this can be made flexible through user defined functions.

His vision is to build an AI product using a graph neural network for students struggling with mental illness. Advertisement Advertisement. By default, the original DataFrame is not changed, and a new DataFrame is returned.

Here, we will discuss 5 different ways to rename column names in pandas DataFrame. One way of renaming the columns in a Pandas Dataframe is by using the rename function. 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. Example 1: Rename a single column. Example 2: Rename multiple columns. The columns can also be renamed by directly assigning a list containing the new names to the columns attribute of the Dataframe object for which we want to rename the columns. The disadvantage of this method is that we need to provide new names for all the columns even if want to rename only some of the columns.

Flexiple helps you build your dream team of developers and designers. Last updated on 26 Feb When working with Pandas DataFrames, there comes a time when you need to remove certain columns to streamline your analysis or to prepare data for further processing. In such cases, understanding how to drop columns efficiently becomes essential. Pandas, a powerful data manipulation library in Python, offers a straightforward method to drop columns from DataFrames using the drop function. This function allows you to specify the columns you want to remove, providing flexibility and ease in data manipulation tasks.

Pandas set column names

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For example, we have created a new dataframe using a dictionary and renamed the columns by providing a list of strings to column attributes. Here is how it works. Last Updated : 04 Dec, The following DataFrame is used as an example. Everyone is using it for data analytics, machine learning, data engineering, and even software development. Work Experiences. For this to work, you need to pass the names of all the columns. The changed column names can be noticed in the above output. This is how you can change the column names for all or some of the columns. Engineering Exam Experiences. As we can see, the columns A and B have been renamed to X and Y , respectively. Rename Duplicated Columns after Join in Pyspark dataframe. Pandas provides a simple and powerful way to rename columns and indexes with the rename method.

In Python, the pandas library provides a powerful and flexible tool for working with tabular data through its DataFrame class. In this article, we will see how we can create a Pandas DataFrame from a dictionary as keys as column names.

One also has to consider all of the points that I mentioned in the previous method. Necessary Necessary. Working with Missing Data in Pandas. Enhance the article with your expertise. You can suggest the changes for now and it will be under the article's discussion tab. It provides powerful tools for data manipulation and analysis. You can pass any user defined function to the parameter columns to change the column names based on a function. How to rename columns in Pandas DataFrame. As you can see, I assigned a list of new column names to df. Additional Information. If omitted, the index is updated by default. However, in the reverse way, we can also pass the list of new column names to df. We can rename one or more columns and indexes by passing a dictionary as an argument, where the keys are the old names, and the values are the new names. Suggest changes. Get paid for your published articles and stand a chance to win tablet, smartwatch and exclusive GfG goodies!