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Creating a Pandas dataframe column based on a given condition in Python
Pandas creates data frames to process the data in a python program. In this article we will see how we can add a new column to an existing dataframe based on certain conditions.
The Given Data Frame
Below is the given pandas DataFrame to which we will add the additional columns. It describes the Days and Subjects of an examination.
Example
import pandas as pd
# Lists for Exam subjects and Days
Days = ['Mon', 'Tue', 'Wed','Thu', 'Fri']
Sub = ['Chemisry','Physics','Maths','English','Biology']
# Dictionary for Exam Schedule
Exam_Subjects = {'Exam Day': Days,
'Exam Subject': Sub}
# Dictionary to DataFrame
Exam_Subjects_df = pd.DataFrame(Exam_Subjects)
print(Exam_Subjects_df)Output
Running the above code gives us the following result −
Exam Day Exam Subject 0 Mon Chemisry 1 Tue Physics 2 Wed Maths 3 Thu English 4 Fri Biology
Adding a New Column
Next we decide to add another column specifying the time of the exam. Here we add the condition using if statement and name the additional column as Time.
Example
import pandas as pd
# Lists for Exam subjects
Days = ['Mon', 'Tue', 'Wed','Thu', 'Fri']
Sub = ['Chemisry','Physics','Maths','English','Biology']
# Dictionary for Exam Schedule
Exam_Subjects = {'Exam Day': Days,
'Exam Subject': Sub}
# Dictionary to DataFrame
Exam_Subjects_df = pd.DataFrame(Exam_Subjects)
Exam_Subjects_df['Time'] = ['2 PM' if x in('Mon','Thu') else '10 AM' for x in Exam_Subjects_df['Exam Day']]
print(Exam_Subjects_df)Output
Running the above code gives us the following result −
Exam Day Exam Subject Time 0 Mon Chemisry 2 PM 1 Tue Physics 10 AM 2 Wed Maths 10 AM 3 Thu English 2 PM 4 Fri Biology 10 AM
Updated on: 26-Aug-2020
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