In this tutorial, we'll learn Introduction to Pandas. Find out carefully. It will help your projects complete quickly.
Pandas is a widely-used Python library built on top of NumPy. Much of the rest of this course will be dedicated to learning about pandas and how it is used in the world of finance.
Pandas is a Python library created by Wes McKinney, who built pandas to help work with datasets in Python for his work in finance at his place of employment.
According to the library's website, pandas is "a fast, powerful, flexible and easy to use open source data analysis and manipulation tool, built on top of the [Python_](https://www.python.org/) programming language."_
Pandas stands for 'panel data'. Note that pandas is typically stylized as an all-lowercase word, although it is considered a best practice to capitalize its first letter at the beginning of sentences.
Pandas is an open source library, which means that anyone can view its source code and make suggestions using pull requests. If you are curious about this, visit the pandas source code repository on GitHub
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...
In the real world, datasets are dirty. This data must be processed before data analysis. Data preprocessing is one of the most important…
Data science is the process of deriving knowledge and insights from a huge and diverse set of data through organizing, processing and analysing the data. It involves many different disciplines like mathematical and statistical modelling, extracting data from it source and applying data visualization techniques.
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.
In my last post, I mentioned groupby technique in Pandas library. After creating a groupby object, it is limited to make calculations on…