Pandas is Python’s opensource library that allows to you to perform data visualization. Pandas library is built on top of Numpy, means Pandas needs Numpy to get operated. Pandas is an easy way for data creation and manipulation. It provides highly optimized performance with back-end source code is purely written in C or Python.
How to install Pandas?
To install any Data visualization tools, like Pandas in Python, go to your command line or terminal and type “pip install pandas” . In case if you have anaconda already installed in the system, type in “conda install pandas”. Post the successful installation, go to your IDE (Jupyter, PyCharm etc.) and you can simply import it as “import pandas as pd”
Operations using Pandas –
Using Python pandas – one of the most popular Data visualization techniques, we can perform a lot of operations with series, data frames, missing data, group by, etc. Some of the common operations for data visualization are listed below:
- Slicing the Data Frame
- Merging and Joining
- Concatenation of Data frames
- Changing the Index in Data frames
- Data Munging
Getting started with Pandas Data Visualization in Python
To know more about pandas, visit www.edugrad.com