PYTHON

pandas pivot

>>> df = pd.DataFrame({'foo': ['one', 'one', 'one', 'two', 'two',
...                            'two'],
...                    'bar': ['A', 'B', 'C', 'A', 'B', 'C'],
...                    'baz': [1, 2, 3, 4, 5, 6],
...                    'zoo': ['x', 'y', 'z', 'q', 'w', 't']})
>>> df

>>df.pivot(index='foo', columns='bar', values=['baz', 'zoo'])
bar  A   B   C
foo
one  1   2   3
two  4   5   6

how to unpivot dataframe pandas

df_unpivoted = df.melt(id_vars=['car_model'], var_name='date', value_name='0-60mph_in_seconds')
df_unpivoted

Pandas pivot table

table = pd.pivot_table(df, values='D', index=['A', 'B'],
...                     columns=['C'], aggfunc=np.sum)
>>> table
C        large  small
A   B
bar one    4.0    5.0
    two    7.0    6.0
foo one    4.0    1.0
    two    NaN    6.0

Pandas pivot table

>>> emp.pivot_table(index='dept', columns='gender',                     values='salary', aggfunc='mean').round(-3)

pivot table pandas

# Simplest pivot table must have a dataframe
# and an index/list of index.
table = pd.pivot_table(df, index =['A', 'B'])
  
table

pandas pivot tables

>>> df = pd.DataFrame({'foo': ['one', 'one', 'one', 'two', 'two',
...                            'two'],
...                    'bar': ['A', 'B', 'C', 'A', 'B', 'C'],
...                    'baz': [1, 2, 3, 4, 5, 6],
...                    'zoo': ['x', 'y', 'z', 'q', 'w', 't']})
>>> df
    foo   bar  baz  zoo
0   one   A    1    x
1   one   B    2    y
2   one   C    3    z
3   two   A    4    q
4   two   B    5    w
5   two   C    6    t

>>> df.pivot(index='foo', columns='bar', values='baz')
bar  A   B   C
foo
one  1   2   3
two  4   5   6

pd df pivot

df.pivot(index='foo', columns='bar', values=['baz', 'zoo'])

df.pivot_table

df.pivot_table(values, index, aggfunc={'value_1': np.mean,'value_2': [min, max, np.mean]})

pd df pivot table

table = pd.pivot_table(df, values='D', index=['A', 'B'],
...                     columns=['C'], aggfunc=np.sum, fill_value=0)

pd df pivot table

table = pd.pivot_table(df, values='D', index=['A', 'B'],
...                     columns=['C'], aggfunc=np.sum)

pandas from pivot to dataframe

df = pivot_name.reset_index()

pivot table pandas

df.pivot_table(index = [df.iloc[:,meet_friends], df.iloc[:,friendsgiving]])

pivot table pandas

df.pivot_table(['int_age'],index = [df.iloc[:,meet_friends], df.iloc[:,friendsgiving]])

pd df pivot

df.pivot(index='foo', columns='bar', values='baz')

pd df pivot

df.pivot(index="lev1", columns=["lev2", "lev3"],values="values")