Pandas boolean DataFrame selection ambiguity

Question

EDIT: Fixed values in tables.

Let\'s say I have a pandas dataframe df:

>>>df
                  a         b         c
        0  0.016367  0.         


        

Answer 1

You need to use the bitwise or and put the conditions in parentheses:

df[(df > 0.5) | (df < 0)]

The reason is because it is ambiguous to compare arrays when maybe some of the values in the array satisfy the condition, that is why it becomes ambiguous.

If you called the attribute any then it would evaluate to True.

The parentheses is required due to operator precedence.

Example:

In [23]:

df = pd.DataFrame(randn(5,5))
df
Out[23]:
          0         1         2         3         4
0  0.320165  0.123677 -0.202609  1.225668  0.327576
1 -0.620356  0.126270  1.191855  0.903879  0.214802
2 -0.974635  1.712151  1.178358  0.224962 -0.921045
3 -1.337430 -1.225469  1.150564 -1.618739 -1.297221
4 -0.093164 -0.928846  1.035407  1.766096  1.456888
In [24]:

df[(df > 0.5) | (df < 0)]
Out[24]:
          0         1         2         3         4
0       NaN       NaN -0.202609  1.225668       NaN
1 -0.620356       NaN  1.191855  0.903879       NaN
2 -0.974635  1.712151  1.178358       NaN -0.921045
3 -1.337430 -1.225469  1.150564 -1.618739 -1.297221
4 -0.093164 -0.928846  1.035407  1.766096  1.456888