pandas pivot table

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showing results for - "pandas pivot table"
Pia
05 Oct 2016
1>>> table = pd.pivot_table(df, values=['D', 'E'], index=['A', 'C'],
2...                     aggfunc={'D': np.mean,
3...                              'E': [min, max, np.mean]})
4>>> table
5                D    E
6            mean  max      mean  min
7A   C
8bar large  5.500000  9.0  7.500000  6.0
9    small  5.500000  9.0  8.500000  8.0
10foo large  2.000000  5.0  4.500000  4.0
11    small  2.333333  6.0  4.333333  2.0
12
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Gabriele
24 Jan 2017
1>>> df = pd.DataFrame({'foo': ['one', 'one', 'one', 'two', 'two',
2...                            'two'],
3...                    'bar': ['A', 'B', 'C', 'A', 'B', 'C'],
4...                    'baz': [1, 2, 3, 4, 5, 6],
5...                    'zoo': ['x', 'y', 'z', 'q', 'w', 't']})
6>>> df
7
8>>df.pivot(index='foo', columns='bar', values=['baz', 'zoo'])
9bar  A   B   C
10foo
11one  1   2   3
12two  4   5   6
Fynn
01 Nov 2016
1>>> emp.pivot_table(index='dept', columns='gender',                     values='salary', aggfunc='mean').round(-3)
source
Emmy
01 Apr 2020
1# Tips is the Dataframe:
2# Suppose we want to compute a table of group means, we can
3# use the Pivot_Table Method:
4
5# The Pivot Table automatically computes the mean
6
7tips.pivot_table(index=['day', 'smoker'])
8
9# The index represents the column names that you want to form groups
Barron
10 Mar 2020
1df.pivot_table(['int_age'],index = [df.iloc[:,meet_friends], df.iloc[:,friendsgiving]])
Thiago
01 Feb 2017
1df.pivot_table(index = [df.iloc[:,meet_friends], df.iloc[:,friendsgiving]])
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