Reputation: 123
I am trying to create a pivot table that has the indexes listed in each row. Currently, I have them only appearing in the first instance.
df = pd.DataFrame({"A": ["foo", "foo", "foo", "foo", "foo",
"bar", "bar", "bar", "bar"],
"B": ["one", "one", "one", "two", "two",
"one", "one", "two", "two"],
"C": ["small", "large", "large", "small",
"small", "large", "small", "small",
"large"],
"D": [1, 2, 2, 3, 3, 4, 5, 6, 7],
"E": [2, 4, 5, 5, 6, 6, 8, 9, 9]})
df
A B C D E
0 foo one small 1 2
1 foo one large 2 4
2 foo one large 2 5
3 foo two small 3 5
4 foo two small 3 6
5 bar one large 4 6
6 bar one small 5 8
7 bar two small 6 9
8 bar two large 7 9
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
I would like for foo
and bar
to appear in the 2nd and 4th lines respectively so that all rows have a values.
Upvotes: 0
Views: 100
Reputation: 75150
This is documented in docs
:
So you can do:
with pd.option_context('display.multi_sparse', False):
print(table)
C large small
A B
bar one 4.0 5.0
bar two 7.0 6.0
foo one 4.0 1.0
foo two NaN 6.0
Upvotes: 3
Reputation: 5122
This is a by-product of the display mechanism for MultiIndex
data.
Use table.reset_index()
to move the index back into columns, and you will see all the columns being displayed with all values.
Upvotes: 2