Python Pandas: Data Manipulation and Analysis

Python Pandas: Data Manipulation and Analysis

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Python Pandas: Data Manipulation and Analysis

Python Pandas: Data Manipulation and Analysis, Learn with real world examples of Python Pandas to analyse large data files. Create visual representations of your data.

Created by Tony Staunton

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What you'll learn

  • How-to install Python and Anaconda - the worlds largest Data Science platform.
  • How-to create a virtual environment using Conda.
  • How-to setup the Atom Text Editor.
  • How to clone a GitHub Repository in Atom Text Editor.
  • How-to create a new branch in Atom Text Editor.
  • Use Python Pandas to read in large data-sets such as stock price information, customer information, purchase information and more.
  • Use Pandas DataFrames to work with tabular data.
  • Inspect datasets to gain quick valuable insights.
  • Use conditional filtering to select relevant information from datasets.
  • Using NumPy and Pandas together.
  • Create Pandas DataFrames from scratch.
  • Create DataFrames from Python dictionaries.
  • Using Broadcasting with DataFrames.
  • Correctly labeling data and columns.
  • Data cleansing techniques.
  • Using Python Pandas to create graphical plots such as bar, line, area, scatter etc.
  • How-to analysis datasets using statistical methods such as min, mas, mean, std.
  • Create filters in your code to extract targeted data from large datasets.
  • How-to manage time data in Python with Pandas.
  • Correctly index time data and create DateTime indexes.
  • Partial String Indexing and slicing.
  • Resampling Pandas Time Data.
  • Method Chaining.
  • Separating and Resampling.

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