This repo contains material covered in 'Intro to Pandas' talk given as a part of Victoria Data Science Meetup. For more details about the Data Science community in Victoria, please visit the following link - Victoria Data Science Meetup

• Anaconda (Download Link: https://www.anaconda.com/download/)
• Windows/Mac/Linux machine
• Some convenient IDE: VSCode, PyCharm etc.

• Create Anaconda environment. Open your terminal and type the following commands.

$ conda create -n Intro2Pandas python=3.6
$ source activate Intro2Pandas
(Intro2Pandas) $ conda install pandas
(Intro2Pandas) $ conda install jupyter notebook

For this talk we will be using the Kaggle's Competition dataset - 'House Prices: Advanced Regression Techniques'. Kaggle is a great place to participate and learn Data Science related concepts and it has a rich community ranging from Beginners to Advanced. If you haven't created an account yet, please sign up, join the competition and download the data from the following link - https://www.kaggle.com/c/house-prices-advanced-regression-techniques

Once the environment is setup. You can run jupyter notebook and start following the Intro to Pandas.ipynb notebook. The objectives of the talk are as follows:

• Get familiarized with Kaggle
• Understand how to use Pandas library
• Cover foundations for data science.
• Submit final results to the Kaggle competition.

By the end of this talk, you will see yourself on the leaderboard of an ongoing data science competition on Kaggle :-)

Sri Raghu Malireddi / @r4ghu