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Calculate total sum of weights for a particular Date

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by vigneshchennai74 dot icon Updated: Feb 17, 2023

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Using Pandas, we can see calculating the Relationship Between Bookings and Weight in Data. The program will demonstrate the use of pandas, a powerful data analysis library in Python, for manipulating and analyzing data. The ability to work with large and complex datasets is becoming increasingly important in many fields, including business, finance, healthcare, social sciences, and many more. 


By allowing users to read, clean, and manipulate data easily, pandas can help in a wide range of applications, including: 

  • Exploratory data analysis: Before we can build models or make predictions with our data, we need to understand the data and identify patterns or relationships—Pandaprovidees tools for exploring and summarizing data, such as grouping, filtering, and aggregation. 
  • Statistical analysis: Pandas also provides tools for statistical analysis, such as hypothesis testing, correlation analysis, and regression analysis. 
  • Machine learning: Pandas is often used with machine learning libraries like scikit-learn to build predictive models. Pandas can preprocess data and prepare it for machine learning algorithms. 


The ability to efficiently manipulate and analyze data is becoming increasingly important in many industries and fields, and pandas are one of the key tools used to accomplish this. This program is just one instance of how pandas can quickly manipulate and analyze data in Python. 


Here is an example of how to calculate the total weight of a particular date: 

Preview of the output that you will get on running this code

Code

In this code we have used groupby Function .

Groupby with a condition on another column in pandas

PythondotLines of Code : 19dotLicense : Strong Copyleft (CC BY-SA 4.0)

Dependent Libraries : 
import pandas as pd
from io import StringIO
csv = StringIO('''Date_1    weight isBooked
        01/09/2019  181  1
        01/09/2019  189  1
        01/09/2019  174  1
        01/09/2019  267  1
        01/09/2019  308  1
        02/09/2019  79   0
        02/09/2019  179  1
        02/09/2019  435  1''')
df = pd.read_csv(csv, delim_whitespace=True)
df1 = df.loc[df.isBooked == 1 ].groupby('Date_1')['weight'].sum().reset_index(name='total_weight')
print(df1)

       Date_1  total_weight
0  01/09/2019          1119
1  02/09/2019           614
  1. Copy this code using "Copy" button above and paste it in your Python ide
  2. Import Pandas library of python.
  3. Run the code to get Output.


I hope you have found this useful. I have added the dependent library and version information in the following section.


I found this code snippet by searching "Groupby with a conditio on another column in pandas" in kandi. you can try any use case.

Environment Tested

In this solution we have used the following versions. Be mindful to change when working with other versions.


  1. This solution is created using Python version 3.7.15
  2. This solution is Tested using Pandas 1.5.2


Using this solution we can able to calculate the total weight of a particular date using Pandas library in python with simple Steps. This process also facilities an easy to use, hassle free method to create a hands-on working version of code which would help us aggregate the weight in Python.

Dependent Library

pandasby pandas-dev

Python doticonstar image 38689 doticonVersion:v2.0.2doticon
License: Permissive (BSD-3-Clause)

Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more

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            pandasby pandas-dev

            Python doticon star image 38689 doticonVersion:v2.0.2doticon License: Permissive (BSD-3-Clause)

            Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more
            Support
              Quality
                Security
                  License
                    Reuse

                      If you do not have Pandas that is required to run this code you can install it by clicking on th above link and copying the pip install command from the pandas page in Kandi. You can search for any dependent library in Kandi like Pandas.

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