Free Python Pandas Courses

Pandas is the data analysis tool licensed by BSD. It is an open-source Python library that provides high-performance and easy-to-use data structures. Python Pandas is widely used among fields like commercial domains, academics, economics, finance, analytics, statistics, etc. 

Python Pandas is considered one of the high-performance Python libraries that is a powerful data manipulation and analysis tool through its promising data structures. Pandas’ name is inspired by Panel Data (an Econometrics from Multidimensional data).

Earlier, Python was used mainly for data preparation and munging, resulting in minor data analysis contributions. Python Pandas came into the picture and has now grown as a powerful tool for data analysis. Python Pandas is used to accomplish five typical steps of data analysis and processing. Data is processed and analyzed regardless of its origin. Python Pandas helps you load, prepare, manipulate, model, and analyze.

Features of Python Pandas include:

• Data can be loaded using its tools to the data objects of in-memory from files of different formats
• Efficient and fast DataFrame object supporting customized and default indexing
• Allows data alignment and missing data is handled through the integrated methods
• Allows pivoting and reshaping of the data sets
• Large data sets can be label-based sliced, indexed, and subsetted
• Insertion and deletion of the columns from the data structure
• Allows aggregation and transformation of the Grouped data
• Shows high performance in merging and joining the data
• Supports time-series functionality

There are multiple Python Pandas environment setups. Python Pandas is not included in the standard Python package. To install Python Pandas, you can make use of a lightweight Python package called NumPy. Use the pip install pandas command to install Python Pandas on your machine.

The easiest way is to install a Python package called Anaconda that comes with Pandas. To use Python Pandas on your Windows system, you can install Anaconda, Canopy, or Python.

Linux machines can install Python packages with Python Pandas using the sudo apt-get install python-numpy python-scipy python-matplotlib ipython ipython-notebook python-pandas python-sympy python-nose command.

Python Pandas supports three data structures called Series, DataFrame, and Panel. These data structures are fast and are built on top of the NumPy array. These data structures can be visualized in a manner where data structures of higher dimensions are the container of the lower dimensional data structures. For example, Panel is the container for DataFrame and DataFrame is the container for Series.

Series is the data structure of dimension 1D described as the homogeneous array of 1D and is site immutable. DataFrame is a 2D dimension size mutable tabular form consisting of heterogeneously typed columns. The Panel is a 3D dimension data structure that is a mutable size array.

Handling various two or more dimensioned data structures is a hectic job, and all the burden is put on the user. The work is done with ease by utilizing Python Pandas data structures, reducing the user’s stress. 

All the data structures of Python Pandas except Series are size mutable, whereas Series is size immutable. Among all the three data structures of Python Pandas, DataFrame is highly utilized and is one of the critical data structures. The Panel is used less compared to DataFrame and is hard to showcase in a graphical representation. But it still can be illustrated as the DataFrame container.

There are many more interesting concepts to learn in Python Pandas. If you are looking forward to working with the Python Panda tool, it is better to understand it thoroughly. Great Learning is offering Python Pandas Free Courses. Enroll in the Python Pandas courses and achieve the course completion Certificate for Free that strengthens your resume to grab better job opportunities.