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How to Rename Columns in a Pandas DataFrame [All Method]️

The step-by-step guide on this page will show you How to Rename Columns in a Pandas DataFrame. What should you do if you come across a code error! Let’s get started on fixing it.
Question: What is the best solution for this problem? Answer: This blog code can help you solve errors How to Rename Columns in a Pandas DataFrame. Question: “What should you do if you run into code errors?” Answer:”You can find a solution by following this blog.

Suppose we’re dealing with a DataFrame df with columns A, B, and C.

Rename specific columns

We can rename specific columns using rename(). Note that we can rename any number of columns.

In this example, we want to lowercase the first two columns.

df = df.rename(columns={'A':'a', 'B':'b'})
df = df.rename({'A':'a', 'B':'b'}, axis=1) # Same output

We can also rename in place if we don’t want to make a copy.

df.rename(columns={'A':'a', 'B':'b'}, inplace=True)

Errors with non-existent columns

We can specify an errors parameter if we want to raise errors when a column doesn’t exist.

df.rename(columns={'D':'d'}, errors='raise')

If raise, raise a KeyError when a dict-like mapper, index, or columns contains labels that are not present in the Index being transformed. If ignore, existing keys will be renamed and extra keys will be ignored.

Revise the code and make it more robust with proper test case and check an error there before implementing into a production environment.
If you need assistance at any stage, please feel free to contact me.

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