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Learn Python: pandas for Data Analysis

Standard Course
£800 +VAT
per delegate
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Course duration: 2 Days

This course covers topics to enable you to build a base layer of knowledge to start programming with pandas. By attending this training, you will:

  • Learn how to connect to existing data files and read data into a pandas DataFrame
  • Gain a range of techniques to prepare and cleanse data
  • Discover how to aggregate and explore a DataFrame
  • Start to create programs in python to solve business problems using data.
An excellently structured, presented and delivered course
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Who is it for?

This course is designed for people with a basic understanding of the Python language, who wish to learn how to use python for data analysis in pandas. It will teach everything that someone needs to know to get started programming with the pandas library.

Prerequisites

Basic knowledge of Python, as covered by Learn Python: Introduction. Including: data types and structures (float, int, str bool, list, tuple, dict); conditional logic and control flow; how to use the Python standard library; basic understanding of NumPy. 

What you will learn

  • An intro to the pandas package
  • Introduction to pandasdata structures: Series and DataFrame
  • Utilising the documentation

  • Reading and writing data from csv files
  • Processing data from a SQL database

  • Exploring a DataFrame
  • Methods and attributes
  • Data Types
  • DataFrame indexes
  • Filtering rows and column from a data frame

  • Conditionally filtering a DataFrame
  • Create new columns
  • String manipulation
  • Categorical data
  • Working with:
  • Sorting data, Duplicate data, Missing data

  • Concatenating multiple DataFrames
  • Multiple techniques to join / merge DataFrames

  • Standalone aggregate methods
  • Agg() method
  • Grouping and summarising data
  • Plot basic bar chart usingplot() method

Working with dates in pandas:

  • Pandas Timestamp,Timedelta and DateOffset class
  • Converting strings into a datetime object
  • Plotting timeseries analysis
  • Working with Python’s Datetime module

  • Conditional processing with If-elif-else statements
  • Defensive programming
  • For and While loops
  • Break statement
  • User-defined functions

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