Closed
Description
related to #3588
This test
def test_pivot_index_with_nan(self):
# GH 3588
nan = np.nan
df = DataFrame({"a":['R1', 'R2', nan, 'R4'], 'b':["C1", "C2", "C3" , "C4"], "c":[10, 15, nan , 20]})
result = df.pivot('a','b','c')
expected = DataFrame([[nan,nan,nan,nan],[nan,10,nan,nan],
[nan,nan,nan,nan],[nan,nan,15,20]],
index = Index(['R1','R2',nan,'R4'],name='a'),
columns = Index(['C1','C2','C3','C4'],name='b'))
tm.assert_frame_equal(result, expected)seems very odd to me, even though the expected result is constructed by hand.
Here's df and result:
In [2]: df
Out[2]:
a b c
0 R1 C1 10
1 R2 C2 15
2 NaN C3 NaN
3 R4 C4 20
In [3]: result
Out[3]:
b C1 C2 C3 C4
a
R1 NaN NaN NaN NaN
R2 NaN 10 NaN NaN
NaN NaN NaN NaN NaN
R4 NaN NaN 15 20
The way I understand pivot here is that it makes a DataFrame with a as the index, b as the columns and then uses the third argument, in this case c as values, where a and b form a kind of coordinate system for c. Thus, instead of the current output, I would expect the result to be
In [14]: e
Out[14]:
b C1 C2 C3 C4
a
R1 10 NaN NaN NaN
R2 NaN 15 NaN NaN
NaN NaN NaN NaN NaN
R4 NaN NaN NaN 20
If, on the other hand, you don't have any nans in your frame, the result is what I would expect:
In [16]: df.loc[2, 'a'] = 'R3'
In [17]: df.loc[2, 'c'] = 17
In [18]: df
Out[18]:
a b c
0 R1 C1 10
1 R2 C2 15
2 R3 C3 17
3 R4 C4 20
In [19]: df.pivot('a','b','c')
Out[19]:
b C1 C2 C3 C4
a
R1 10 NaN NaN NaN
R2 NaN 15 NaN NaN
R3 NaN NaN 17 NaN
R4 NaN NaN NaN 20
I'll have a look at #3588 to see if this is a regression, or if I'm just misunderstanding how this is supposed to work.
I have a suspicion that this is related to #7403