Deleting rows based on multiple conditions Python Pandas

Question

I want to delete rows when a few conditions are met:

For instance, a random DataFrame is generated:

import pandas as pd import numpy as np df = pd.DataFrame(np.random.randn(10, 4), columns=['one', 'two', 'three', 'four']) print df 

one instance of table is shown as below:

        one       two     three      four 0 -0.225730 -1.376075  0.187749  0.763307 1  0.031392  0.752496 -1.504769 -1.247581 2 -0.442992 -0.323782 -0.710859 -0.502574 3 -0.948055 -0.224910 -1.337001  3.328741 4  1.879985 -0.968238  1.229118 -1.044477 5  0.440025 -0.809856 -0.336522  0.787792 6  1.499040  0.195022  0.387194  0.952725 7 -0.923592 -1.394025 -0.623201 -0.738013 8 -1.775043 -1.279997  0.194206 -1.176260 9 -0.602815  1.183396 -2.712422 -0.377118 

I want to delete rows based on the conditions that:

Row with value of col 'one', 'two', or 'three' greater than 0; and value of col 'four' less than 0 should be deleted.

Then I tried to implement as follows:

df = df[df.one > 0 or df.two > 0 or df.three > 0 and df.four < 1] 

However, resulting in a error message as follow:

ValueError: The truth value of an array with more than one element is ambiguous. Use a.any() or a.all() 

Could someone help me on how to delete based on multiple conditions?

Answer 1

For reasons that aren't 100% clear to me, pandas plays nice with the bitwise logical operators | and &, but not the boolean ones or and and.

Try this instead:

df = df[(df.one > 0) | (df.two > 0) | (df.three > 0) & (df.four < 1)]