In this article, we'll help you understand about vectorize your code to manipulate data 1000 times faster
Just days in to hands-on learning data manipulation with Pandas, my instructor paused to make a point. “Do yourself a favor,” he said to the class, with more intention than ever before, “before going too much further in learning Pandas, watch this talk on vectorization.” The value of vectorization seemed apparent, both from our instructor’s affect when he was directing us to the clip, and from the claim that the presenter in the clip was suggesting—vectorize your code to manipulate data 1000 times faster. The video breaks down several examples of using a variety of manipulation operations—Python for-loops, NumPy array vectorization, and a variety of Pandas methods—and compares the speed that outputs are returned for such methods. The results are clear: using techniques that take advantage of vectorization in Pandas would result in, just as the video’s click-attracting headline suggests, staggeringly faster data manipulation.
In this post, we will learn about pandas’ data structures/objects. Pandas provide two type of data structures:- ### Pandas Series Pandas Series is a one dimensional indexed data, which can hold datatypes like integer, string, boolean, float...
Pandas is a fast, powerful, flexible and easy to use open source data analysis and manipulation tool, built on top of the Python programming language.
We will be working with pandas and NumPy libraries. These libraries are essential for performing exploratory data analysis. We will see how can we create different arrays and manipulate them. With pandas, we will work with both Series and data frames.
Welcome to Part 2 of Become a Data Scientist! Today we go over the Python programming language, along with its central data science libraries: Pandas, NumPy, and Matplotlib. We describe Pandas Dataframes, NumPy n-dimensional arrays, and show off how to perform graphing both in Pandas and Matplotlib. We use Google Colab Notebooks, an interactive environment for writing Python code where we don't have to worry about any system dependencies!
This free 12-hour Python Data Science course will take you from knowing nothing about Python to being able to analyze data. You'll learn basic Python, along with powerful tools like Pandas, NumPy, and Matplotlib. This is a hands-on course and you will practice everything you learn step-by-step. This course includes a full codebase for your reference [https://github.com/datapublishings/Course-python-data-science]. It kicks off with a one-hour introduction to basic programming concepts, proble