Objective
You will learn how to:
- Use Pandas to load data from databases, the web, and HDF5
- Merge datasets flexibly
- Create multi-level aggregations
- Resample time series data
... using real-world examples
Description
Pandas is a Python package providing fast, flexible, and expressive data structures designed to make working with “relational” or “labeled” data both easy and intuitive. It aims to be the fundamental high-level building block for doing practical, real world data analysis in Python. Additionally, it has the broader goal of becoming the most powerful and flexible open source data analysis / manipulation tool available in any language. It is already well on its way toward this goal.
Requirements
A working knowledge of Pandas.
You'll also need Pandas and iPython installed on your system
Speaker bio
Anand is the Chief Data Scientist at Gramener, a data analytics and visualisation company. He blogs at s-anand.net
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The code used at the talk is spread across these notebooks: