Monday, August 24, 2020

Python — Filtering data with Pandas Dataframe

If you are working as Python developer where you have to accomplished a lot of data cleansing stuffs. One of the data cleansing stuff is to remove unwanted data from your dataframe. Pandas is one of the most important packages that makes importing and analyzing data much easier with the help of its strong library.

For analyzing data, a programmer requires a lot of filtering operations. Pandas provide many methods to filter a Data frame and Dataframe.query() is one of them.

To understand filtering feature of Pandas, we are creating some sample data by using list feature of Python.

In this example, dataframe has been filtered on multiple conditions.

# Import pandas library

import pandas as pd


# intialise data of lists.

data = {'Name':['Ryan Arjun', 'Kimmy Wang', 'Rose Gray', 'Will Smith'],

        'Age':[20, 21, 19, 18],




# Create DataFrame

df = pd.DataFrame(data)


#show data in the dataframe



   Age |   Country |       Name   |  Sex


0   20 |     India | Ryan Arjun   |  Male

1   21 |    Taiwan | Kimmy Wang   |Female

2   19 |    Canada |  Rose Gray   |Female

3   18 | Greenland | Will Smith   | Male



# filtering with query method

# Where sex must be male

# and Country must be India

# and age must be greater than 15

df.query('Sex =="Male" and Country =="India" and Age>15', inplace = True)


#show data in the dataframe




Age | Country   |     Name  | Sex


20  |India      |Ryan Arjun | Male


By using query feature of pandas in Python can save a lot of data processing time because we can use multiple filters conditions in a single go.

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