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Alexander Hendorf - Introduction to Data-Analysis with Pandas

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Published on Jul 26, 2017

Description
Pandas is the Swiss-Multipurpose Knife for Data Analysis in Python. With Pandas dealing with data-analysis is easy and simple but there are some things you need to get your head around first as Data-Frames and Data-Series. The tutorial provides a compact introduction to Pandas for beginners for I/O, data visualisation, statistical data analysis and aggregation within Jupiter notebooks.

Abstract
Pandas is the Swiss-Multipurpose Knife for Data Analysis in Python. With Pandas dealing with data-analysis is easy and simple but there are some things you need to get your head around first as Data-Frames and Data-Series.

The tutorial provides a compact introduction to Pandas for beginners:

-reading and writing data across multiple formats (CSV, Excel, JSON, SQL, HTML,…)
-data visualisation
-statistical data analysis and aggregation.
-work with built-in data visualisation
-inner-mechanics of Pandas: Data-Frames, Data-Series & Numpy.
-working and making the most of indexes.
-how to mangle, reshape and pivot

The tutorial will be provided as Jupiter notebooks.

www.pydata.org

PyData is an educational program of NumFOCUS, a 501(c)3 non-profit organization in the United States. PyData provides a forum for the international community of users and developers of data analysis tools to share ideas and learn from each other. The global PyData network promotes discussion of best practices, new approaches, and emerging technologies for data management, processing, analytics, and visualization. PyData communities approach data science using many languages, including (but not limited to) Python, Julia, and R.

PyData conferences aim to be accessible and community-driven, with novice to advanced level presentations. PyData tutorials and talks bring attendees the latest project features along with cutting-edge use cases.

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