Paula  Hall

Paula Hall

1623389988

4 Pandas GroupBy Tricks You Should Know

Use Pandas GroupBy more flexibly and creatively

As one of the most popular libraries in Python, Pandas has been utilised very commonly especially in data EDA (Exploratory Data Analysis) jobs. Very typically, it can be used for filtering and transforming dataset just like what we usually do using SQL queries. They share a lot of similar concepts such as joining tables. However, some features from them have the same names but different concepts. “Group By” is one of them.

In this article, I’ll introduce some tricks for the Pandas group by function, which could improve our productivity in EDA jobs. Hopefully at least one is something you never familiar with so that it could help you.

I’m sure that you know how to import Pandas in Python, but still, let me put it here. All the rest of the code in this article assume Pandas has been imported as follows.

import pandas as pd

#python #technology #data-science #programming #4 pandas groupby tricks you should know #pandas groupby tricks

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4 Pandas GroupBy Tricks You Should Know
Paula  Hall

Paula Hall

1623389988

4 Pandas GroupBy Tricks You Should Know

Use Pandas GroupBy more flexibly and creatively

As one of the most popular libraries in Python, Pandas has been utilised very commonly especially in data EDA (Exploratory Data Analysis) jobs. Very typically, it can be used for filtering and transforming dataset just like what we usually do using SQL queries. They share a lot of similar concepts such as joining tables. However, some features from them have the same names but different concepts. “Group By” is one of them.

In this article, I’ll introduce some tricks for the Pandas group by function, which could improve our productivity in EDA jobs. Hopefully at least one is something you never familiar with so that it could help you.

I’m sure that you know how to import Pandas in Python, but still, let me put it here. All the rest of the code in this article assume Pandas has been imported as follows.

import pandas as pd

#python #technology #data-science #programming #4 pandas groupby tricks you should know #pandas groupby tricks

Ray  Patel

Ray Patel

1619518440

top 30 Python Tips and Tricks for Beginners

Welcome to my Blog , In this article, you are going to learn the top 10 python tips and tricks.

1) swap two numbers.

2) Reversing a string in Python.

3) Create a single string from all the elements in list.

4) Chaining Of Comparison Operators.

5) Print The File Path Of Imported Modules.

6) Return Multiple Values From Functions.

7) Find The Most Frequent Value In A List.

8) Check The Memory Usage Of An Object.

#python #python hacks tricks #python learning tips #python programming tricks #python tips #python tips and tricks #python tips and tricks advanced #python tips and tricks for beginners #python tips tricks and techniques #python tutorial #tips and tricks in python #tips to learn python #top 30 python tips and tricks for beginners

WORKING WITH GROUPBY IN PANDAS

In my last post, I mentioned the groupby technique  in Pandas library. After creating a groupby object, it is limited to make calculations on grouped data using groupby’s own functions. For example, in the last lesson, we were able to use a few functions such as mean or sum on the object we created with groupby. But with the aggregate () method, we can use both the functions we have written and the methods used with groupby. I will show how to work with groupby in this post.

#pandas-groupby #python-pandas #pandas #data-preprocessing #pandas-tutorial

Practice Problems: How To Use Pandas DataFrames' GroupBy Method

It’s now time for some practice problems! See below for details on how to proceed.

Course Repository & Practice Problems

All of the code for this course’s practice problems can be found in this GitHub repository.

There are two options that you can use to complete the practice problems:

  • Open them in your browser with a platform called Binder using this link (recommended)
  • Download the repository to your local computer and open them in a Jupyter Notebook using Anaconda (a bit more tedious)

Note that binder can take up to a minute to load the repository, so please be patient.

Within that repository, there is a folder called starter-files and a folder called finished-files. You should open the appropriate practice problems within the starter-files folder and only consult the corresponding file in the finished-files folder if you get stuck.

The repository is public, which means that you can suggest changes using a pull request later in this course if you’d like.

#pandas #groupby methods #pandas dataframe #example #practice problems: how to use pandas dataframes' groupby method #practice problems

4 Tricks for Making Python Pandas More Efficient

Making the most out of Pandas

Pandas is arguably the most popular data analysis and manipulation library in the data science ecosystem. The user-friendly and intuitive Python syntax is a significant factor in the popularity of Pandas. However, it is not the only reason why Pandas is adapted by a vast majority of data scientists.

Pandas provides numerous functions and methods that expedite the data analysis and manipulation operations. In this article, we will go over 4 tricks for using these functions even more efficiently.

Let’s start with creating a data frame. We will use the Melbourne housing dataset available on Kaggle.

#programming #artificial-intelligence #python #data-science #4 tricks for making python pandas more efficient #tricks for making python pandas