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[Solved] Python: ‘ValueError: can only convert an array of size 1 to a Python scalar’ when looping over rows in pd.DataFrame

Hello Guys, How are you all? Hope You all Are Fine. Today I get the following error Python: ‘ValueError: can only convert an array of size 1 to a Python scalar’ when looping over rows in pd.DataFrame 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 Python: ‘ValueError: can only convert an array of size 1 to a Python scalar’ when looping over rows in pd.DataFrame Error Occurs?

Today I get the following error Python: ‘ValueError: can only convert an array of size 1 to a Python scalar’ when looping over rows in pd.DataFrame in python.

How To Solve Python: ‘ValueError: can only convert an array of size 1 to a Python scalar’ when looping over rows in pd.DataFrame Error ?

  1. How To Solve Python: 'ValueError: can only convert an array of size 1 to a Python scalar' when looping over rows in pd.DataFrame Error ?

    To Solve Python: 'ValueError: can only convert an array of size 1 to a Python scalar' when looping over rows in pd.DataFrame Error pd.Series.item requires at least one item in the Series to return a scalar. If:

  2. Python: 'ValueError: can only convert an array of size 1 to a Python scalar' when looping over rows in pd.DataFrame

    To Solve Python: 'ValueError: can only convert an array of size 1 to a Python scalar' when looping over rows in pd.DataFrame Error pd.Series.item requires at least one item in the Series to return a scalar. If:

Solution 1

pd.Series.item requires at least one item in the Series to return a scalar. If:

df[(df['date_rank'] == next_home_fixture) & (df['localteam_id'] == df.at[index,'localteam_id'])]

is a Series with length 0, then the .index.item() will throw a ValueError.

Solution 2

FYI,

You will get similar error if you are applying .item to a numpy array.

You can solve it with .tolist() in that case.

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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