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[Solved] Value: DataFrame index must be unique for orient=’columns’

Hello Guys, How are you all? Hope You all Are Fine. Today I get the following error Value: DataFrame index must be unique for orient=’columns’ in python. So Here I am Explain to you all the possible solutions here.

Without wasting your time, Let’s start This Article to Solve This Error.

How Value: DataFrame index must be unique for orient=’columns’ Error Occurs?

Today I get the following error Value: DataFrame index must be unique for orient=’columns’ in python.

How To Solve Value: DataFrame index must be unique for orient=’columns’ Error ?

  1. How To Solve Value: DataFrame index must be unique for orient='columns' Error ?

    To Solve Value: DataFrame index must be unique for orient='columns' Error In my case where I used SQL it's better to change the query to not return the duplicate column you are joining on.

  2. Value: DataFrame index must be unique for orient='columns'

    To Solve Value: DataFrame index must be unique for orient='columns' Error In my case where I used SQL it's better to change the query to not return the duplicate column you are joining on.

Solution 1

The error indicates that your dataframe index has non-unique (repeated) values. Since it appears you’re not using the index, you could create a new one with:

df.reset_index(inplace=True)

or

df.reset_index(drop=True, inplace=True)

if you want to remove the previous index.

Solution 2

In my case I had duplicate columns in my pandas DataFrame. I read from a SQL query that did a join on two columns, which is allowed but becomes problematic when you want to create a JSON. Drop the columns:

df = df.drop(columns="duplicate_column")

Or simply rename them

df.rename(index=str, columns={"duplicate_column": "duplicate_column_2"})

In my case where I used SQL it’s better to change the query to not return the duplicate column you are joining on.

Summery

It’s all About this issue. Hope all solution helped you a lot. Comment below Your thoughts and your queries. Also, Comment below which solution worked for you? Thank You.

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