Examples of how to filter dataframe rows using multiple conditions with OR in pandas:

### Create a dataframe with pandas

Let's first create a dataframe with pandas using a dictionary:

`import pandas as pd`

`import numpy as np`

`data= {'A':[-1,-2,3,4,5],`

`'B':[6,-7,8,9,-10],`

`'C':[11,12,13,14,15],}`

`df = pd.DataFrame(data)`

returns here

`A B C`

`0 -1 6 11`

`1 -2 -7 12`

`2 3 8 13`

`3 4 9 14`

`4 5 -10 15`

### Filter using one column

To filter a dataframe with a OR statement, a solution is to use the logical operator |

`df[ (df['A'] < 0) | (df['A'] > 4) ]`

returns here

`A B C`

`0 -1 6 11`

`1 -2 -7 12`

`4 5 -10 15`

### Filter using two different columns

Another example using two different columns

`df[ (df['A'] < 0) | (df['B'] < 0) ]`

returns

`A B C`

`0 -1 6 11`

`1 -2 -7 12`

`4 5 -10 15`

### More than two columns

Another example using more than two different columns

`df[ (df['A'] < 0) | (df['B'] < 0) | (df['C'] >= 14) ]`

returns

`A B C`

`0 -1 6 11`

`1 -2 -7 12`

`3 4 9 14`

`4 5 -10 15`

### Multiple conditions witn OR and AND

`df[ (df['A'] < 0) | (df['B'] < 0) & (df['C'] == 11) ]`

returns

`A B C`

`0 -1 6 11`

`1 -2 -7 12`

Same as

`df[ (df['A'] < 0) | ( (df['B'] < 0) & (df['C'] == 11) ) ]`

returns

`A B C`

`0 -1 6 11`

`1 -2 -7 12`

or

`cond1 = (df['A'] < 0)`

`cond2 = (df['B'] < 0) & (df['C'] == 11)`

`df[ cond1 | cond2 ]`

returns

`A B C`

`0 -1 6 11`

`1 -2 -7 12`