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Pandas - Beyond the Basics training course

Become fluent and adopt best practices in the use of the pandas library for Python

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  • Free tasters
PUBLIC COURSES
  • £995.00+VAT
  • Next on 11 Oct

JBI training course London UK

– Efficient data modelling
– Deep-dive into pandas data types
– Choosing data types when loading the data
– Data type conversions
– Best practices to improve your memory usage
– Efficient data pipelines
– Understanding immutability
– Method chaining to improve readability
– Best practices data transformation and query pipelines
– Efficient slicing and dicing
– Complex aggregations (groupby) on multiple columns
– Mastering the hierarchical (multi-level) index
– Index stacking and unstacking
– Pivoting and reshaping
– Beyond pandas

A taster video for Python Remote Training

"The course was very comprehensive with clear examples and good exercises. It was a good to understand the capabilities and basics of python. The material is very clear. I like the fact that additional material has been shared for practice."

EW, Electronic Engineer, Python, January 2021


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The pandas beyond the basics syllabus is designed to help analysts, researchers, BI experts and developers becoming fluent in the use of the pandas library for Python, learning the more advanced features of pandas and adopting the best practices, in order to slice and dice complex data.


Using interactive examples and hands-on exercises, the course provides a full immersion in the advanced features of the pandas library. The course focuses on making your pandas code more efficient, so some very basic familiarity with pandas and its core concepts is assumed.


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JBI training course London UK
JBI training course London UK

Quants, Analysts, BI professionals, Data Scientists, Developers and Researchers who use the pandas library for data analysis, already grasp the basics of pandas and would like to take their knowledge to the next level.

This is a course best suited for “advanced beginners” or intermediate pandas users, who want to master the best practices.


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Related Courses

Efficient data modelling

– Deep-dive into pandas data types
– Choosing data types when loading the data
– Data type conversions
– Best practices to improve your memory usage when dealing with larger data sets

Efficient data pipelines

– Understanding immutability
– Method chaining to improve readability
– Best practices to develop and maintain complex data transformation and query pipelines

Efficient slicing and dicing

– Complex aggregations (groupby) on multiple columns
– Mastering the hierarchical (multi-level) index
– Index stacking and unstacking
– Pivoting and reshaping


Beyond pandas – Exploring the pandas ecosystem

– Overview and examples of usage of other libraries built on top of pandas to address
specific needs in data preparation, data analysis and data visualisation

 
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