Eliminate rows with condition in pandas DataFrame in Python

This tutorial will teach us how to eliminate rows with conditions in Pandas DataFrame in Python.

So to delete/eliminate rows with conditions we first need to define a table with some data and for that, we need to import pandas.

import pandas as pd

Now that we have pandas imported, We are ready to define a table and use it.

We will define the table using DataFrame in pandas:

table = pd.DataFrame(
    {
        'name' : ['Maxx', 'May', 'Ron', 'Eliza'],
        'Age' : [25,27,22,31],
        'Department' : ['sales', 'marketing', 'marketing', 'sales'],
        'gender' : ['female', 'female', 'male', 'female']
    }
)

print(table)

In dataframe, when a table is defined it looks like a dictionary with key-value pairs, When we print the table it looks something like this:

Output:

  name  Age Department gender
0 Maxx  25  sales      female
1 May   27  marketing  female
2 Ron   22  marketing  male
3 Eliza 31  sales      female

Eliminate row with condition

Now that we have a table, We see how to delete a row with some particular condition.

• If we want to delete rows with an age greater than 25, we can do that by:

table.drop(table[(table['Age'] > 25)].index , inplace=True)

print(table)

Output:

  name Age Department gender
0 Maxx 25  sales      female
2 Ron  22  marketing  male

Eliminate rows with multiple conditions

This will help us eliminate rows with the specified conditions:

table.drop(table[ (table['Department'] == 'sales') | (table['Age'] > 25) ].index , inplace=True)

print(table)

Output:

  name Age Department gender
2 Ron  22  marketing  male