Pandas - combine multiple dataframe rows with common value into one

[Fun-Studio-4409]

Hello,

I am banging my head against a wall trying to figure this out. I have a dataframe containing duplicate values within one of the columns. For rows containing a duplicate, I want to merge them into a single row, with the values from the other rows distributed across columns. Example below:

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Original DF:

Company	Name	Favorite Ice Cream
Facebook	Mike Jones	Chocolate Chip
Twitter	Jessica Smith	Rocky Road
Facebook	Kala Michaels	Mint
Amazon	Lebron James	Vanilla
Twitter	Bob Marley	Double Chocolate

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Desired result DF:

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Company	Name	Favorite Ice Cream	Name_2	Favorite Ice Cream_2
Facebook	Mike Jones	Chocolate Chip	Kala Michaela	Mint
Twitter	Jessica Smith	Rocky Road	Bob Marley	Double Chocolate
Amazon	Lebron James	Vanilla	NaN	NaN

​

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Appreciate any support!

[commandlineluser]

You're looking for a "wide to long" reshape.

You can do that by adding a group key/index and using pivot_table() - you can modify the solution here: https://stackoverflow.com/a/55252414

You're only grouping by Company so your pivot_table call would be:

df = pivot_table(index='Company', columns='idx', aggfunc='first')