CODEWITHSUNDEEP
pythonpandasdataframemultiple-columnsrename
Philippe
Philippe

Reputation: 857

Rename a column based on the content of it

I saw some similar questions but not quite the one I was looking for.

I have a excel sheet that is delivered to me:

This is how to replicate:

data = [['name','name','number'], ['Nick','Brussels', 15], ['Tom','Paris', 14]]
df = pd.DataFrame(data)

I make my first row the column headers like this:

df=df.rename(columns=df.iloc[0]).drop(df.index[0])

What I know for sure is that the value 'Brussels' is always in the dataset, so my question is : can I change the name of the column based on a value in that column.

so in pseudo code this would be :

if the column contains the word 'Brussels' rename the column to 'city'

All my attempts so far change both column names, because it returns 'name' as the index to change when I select the column containing Brussels. I would like to have the iloc, returned...

My goal is to have this:

   name      city number
1  Nick  Brussels     15
2   Tom     Paris     14

Upvotes: 0

Views: 385

Answers (2)

fsimonjetz
fsimonjetz

Reputation: 5802

This is similar to Corralien's answer in using a boolean mask, but instead of a list comprehension, it modifies the source row first and then assigns it as columns like you did.

df.iloc[0][df.eq('Brussels').any()] = 'city'
df = df.rename(columns=df.iloc[0]).drop(df.index[0])

Upvotes: 0

Corralien
Corralien

Reputation: 120391

You can use a boolean mask to find the right column:

df.columns = [c if not m else 'city'
                  for c, m in zip(df.columns, df.eq('Brussels').any())]
print(df)

# Output
   name      city number
1  Nick  Brussels     15
2   Tom     Paris     14

Upvotes: 2

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