CODEWITHSUNDEEP
pythonpython-3.xpandas
Cameron McMains
Cameron McMains

Reputation: 59

How do I use the Pandas .loc() function when converting a column to DateTime?

I'm working on a small project to parse and create graphs based on DNC Primary data. It's all functional so far but I'm working on getting rid of the following SettingWithCopyWarning:

SettingWithCopyWarning: 
A value is trying to be set on a copy of a slice from a DataFrame.
Try using .loc[row_indexer,col_indexer] = value instead

See the caveats in the documentation: http://pandas.pydata.org/pandas-docs/stable/user_guide/indexing.html#returning-a-view-versus-a-copy
  candidate['end_date'] = pd.to_datetime(candidate_state['end_date'])

I've tried changing the referenced line to:

candidate.loc['end_date'] = pd.to_datetime(candidate_state['end_date'])

But that throws another error about some kind of comparison.

Upvotes: 0

Views: 1311

Answers (1)

Brett Romero
Brett Romero

Reputation: 353

It is hard to confirm without seeing the full code, but this warning is usually a result of the dataframe you are working on (candidate in this case) being a "copy" of a filtered selection of a larger dataframe. In other words, when you created candidate you did something like:

candidate = df_larger_dataset[df_larger_dataset['some_column'] == 'some_value']

The reason you get the warning is because when you do this, you don't actually create a new object, just a reference, which means when you start making changes to candidate, you are also modifying df_larger_dataset. This may or may not matter in your context, but to avoid the warning, when you create 'candidate' make it an explicit copy of df_larger_dataset:

candidate = df_larger_dataset[df_larger_dataset['some_column'] == some_value].copy()

Upvotes: 2

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