如何在pandas的数据透视表中搜索数据？

Question

I created a pivot table from a dataframe using:

table = pd.pivot_table(df , index=['student','year','subject'] , values=['mark'])

and I got a table like this:

student       year        subject 

'Martin'      2014        Algebra      5
                          Chemistry    3.5 
                          Programming  8

'Sara'        2013        Algebra 2.2
 ....         ....        .....

How can I get Martin 2014 Algebra's mark?

I tried as a dataframe:

 t[t.student=='Martin'][t.year=2014][t.subject==Algebra]

but it doesn't works

Can somebody help me? Thank's!

Answer 1

You need to reset the index in order to use boolean indexing

t= table.reset_index()
t[(t.student=='Martin') & (t.year=2014) & (t.subject=='Algebra')]

Or you can use MultiIndex Selection

table.loc[('Martin', 2014, 'Algebra')]

Answer 2

您有一个多索引数据框，使用loc with tuple来访问该值：

table.loc[("'Martin'",2014,"Algebra")]

Answer 3

the resulting pivot table is just another dataframe. However, this dataframe has a multiindex. Multiindexes can be referenced with tuples of the levels. This is @psidom's and @TedPetrou's answers

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However, an alternative would be to use the xs cross section method

table.xs(('Martin', 2014, 'Algebra'))

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In this particular case, table is really a Series. You can use query on a dataframe. So we can make it a dataframe and then query

table.to_frame().query('student == "Martin" & year == 2014 & subject == "Algebra"')