This really adds to the flexibility and power that rename() function offers. If you wish to change rename columns of pandas dataframe programmatically it can be done by rename() by using lambda function. In : df.rename(columns= str.upper, inplace = True)Įxample 7 – Rename Pandas Column Names with Lambda Function Just like the above example, we can also change column names to upper cases with rename() function as shown below. In : df.rename(columns= str.lower, inplace = True)Įxample 6 – Change Column Names to Upper Case in Pandas It is quite easy to rename all columns of pandas dataframe to lower case with rename() function as shown in the below example. In : df.rename(, inplace = True)Įxample 5 – Rename Column Names to Lower Case in Pandas Also, the axis =1 tells Pandas that this rename is for columns and inplace=True allows the change to persist in place in the dataframe. It should be noted that here only those columns are passed that are to be renamed. In this example, we are passing the mapping of existing and new column names in the dictionary data structure to rename() function. Let us understand this with various examples. And it also supports the use of the lambda function to let you modify the columns programmatically. This is where rename() comes in very handy as it lets you work with only the column that needs to be renamed in pandas. It is okay when the total number of columns is less but when there are hundreds of columns then it is not practical to pass all column names just to change a couple of them. In the earlier examples with column and set_axis attributes, we had to pass the entire list of columns even though we had a requirement to change an only couple of them. Rename Column Names in Pandas with rename() In : df.set_axis(, axis=1, inplace = True) The axis = 1 tells pandas that the changes are to be applied on the columns and also inplace = True is used so that changes are persisted in the current dataframe df. Just like the previous approach, here also we have to pass the entire list of columns even though we want to change just the first two columns. In this example, we shall use set_axis attribute of Pandas to modify the column name. In : df.columns = Ĭhange Column Names in Pandas with set_axis() Example 2 But still, we passed the Department column even though it was unchanged. In the below example we wanted to rename Employee_Id to Emp_Id and Emloyee_Name to Emp_Name. It should be noted here that even though we don’t want to change the names of all columns, it is mandatory to pass all names of columns. As shown in the below example, we have assigned the list of columns with modified names to df.column attribute. The first way to change the column name in pandas is to use the column attribute of the datframe. Change Column Names in Pandas with Column Attribute Example 1
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