![]() ![]() axis : The default values of axis is ‘index’ i.e., 0. Only change is that the column names can be modified using there index value instead of name of the column. index : It acts just like columns parameter. So it can either function or dict like object. columns : It’s specifies the column names that is to be modified and also it can accept a function which is applied to each column in the dataframe. This mapper can be target to axis parameter. Parameters: mapper : It can be dictionary type or a function that is used to map the specified column names with existing ones. rename(mapper=None , columns=None, index=None , axis=None , copy=True, errors=’ignore’, level=None, inplace=False ) The syntax and each of the parameters is explained below. The column parameter in the rename() method also accepts a function or a dict type to modify the column names. Rename() method in pandas data frame is used to modify the name of single or multiple columns in a dataframe. Let’s look at them in detail in the below approaches. There are several methods to rename the columns in pandas. In such cases, renaming is a better choice to access the data easily and make the data frame more readable. Sometimes the data frame or the dataset that is loaded may not contain the names of the columns. Rename column in the panda’s data frame is used to change or modify the column names in the specified data frame. Columns parameter in rename() with function.Renaming All Columns Using list assignment. ![]()
0 Comments
Leave a Reply. |
AuthorWrite something about yourself. No need to be fancy, just an overview. ArchivesCategories |