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I want to explain my question with an example. I have a dataset which includes avocado average prices and many features about these prices(I guess avocado prices dataset is very popular, idk). And there is a feature called "region" that shows where avocadoes grew. I wrote this line of code to get to avocados feature which grews on "west". my data's name is data btw

west = data[data['region'] =='West']

And i thinked that what if i wanted to get the avocadoes which grew in 2016 and also grew on West. How can i get these data at the same time ?

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    Can you add few rows of your dataframe Commented May 2, 2021 at 20:32

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I think the pandas DataFrame filter with boolean conditions can solve your question.

Suppose your column name for avocado growing year is grew_in. Then try this:

west_2016 = data[(data['region'] =='West') & (data['grew_in'] == 2016)]
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You can try query interfrace of pandas.

In particular, if your "grew in" data is present in year column, you could do something like,

data.query('region == "West" and year == 2016')

References:

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I've learned a new thing thanks to you sir.
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west = data[(data['region']=='west')&(data['year']==2016)]
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Thank you for your answer sir. You solved my problem.

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