For example, if creating the dataframe required querying a snowflake database. I have often seen people fall into this case if creating the dataframe is an expensive task. Rename Columns in Pandas DataFrame Rename column names using rename() method in Dataframe dataframe.rename(columns,inplaceTrue) Rename Column Names with a.
dataframe.rename(mapper, index, columns, axis, copy, inplace, level. Not all the columns have to be renamed: df = df.rename(columns=, inplace=True)Īlternatively, there are cases where you want to preserve the original dataframe. The rename() method allows you to change the row indexes, and the columns labels. What is the key performance bottleneck? It’s doing an inplace replacement on a copy of the dataframe.Use the df.rename() function and refer the columns to be renamed. Technically it’s an Axis object, with column names as an attribute, but that’s more complicated than we need to be. df df.rename(columnsstr.lower) df. Alternatively, you can use inplaceTrue and skip the df bit at the beginning. To do this we reassign df.rename (columnsstr.lower) back to df. We can do that by simply specify inplaceTrue option as. The cleanest way to rename column names is to combine the rename () function with str.lower (). Renaming the columns through a list in pandas requires knowing the shape of the dataset you have. The parameter new_index is roughly the values of the new column names. Use either mapper and axis to specify the axis to target with mapper, or index and columns. As we see above, we selected only column Age of President to rename. Meaning that the variable result is just a copy of the dataframe.
Rename a column in pandas how to#
I need to break this call down a little bit. How to rename a column in pandas Use the Pandas dataframe rename () function to modify specific column names. Specifically, there is this line in the rename method: result._set_axis_nocheck(new_index, axis=axis_no, inplace=True)
To use this, we have to pass a key (the original name of. While there is a lot of control-flow logic (if/else statements), there’s also some hidden copying going on. The Pandas have one in-built function called rename( ) which can change the column name instant.
Rename a column in pandas code#
We dig a bit into the source code of the rename method to hypothesize. when we set copy=False using the rename method? It is obvious that copying the data frame will slow down performance, so it makes sense why copy=True is slow, but why is turning off copying still slow, i.e. What is clear is that in Method 2 changing the attribute directly is the fastest, whereas using the rename method with non-in place copying is the slowest. The following code shows how to rename specific columns in a pandas DataFrame: Notice that the ‘team’ and ‘points’ columns were renamed while all other column names remained the same.
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