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Data Wrangling Python Workshop: Visualization and List

Data Wrangling Python Workshop: Visualization and List

Data Wrangling Python Workshop: Data Visualization and List EDA, cleaning, graphical analysis, wrangling, visualization, list, tuples, arrays

What you'll learn

  • Data Wrangling: How to upload, manage , and clean/prepare datasets and quickly get an overview of the data that you will be working with
  • Data Visualization: How to make graphs, charts, and other data visualization to understand the data and target key variables for analyses
  • List and Tuple: How to use this data format for creating and accessing data. To understand the difference and when to employ Lists or Tuples
  • Data Wrangling: How to upload and manage datasets and clean the datasets
  • Advanced Data Visualization: How to use Matplotlib and Seaborn to make nice Data visualizations. How to make more advanced visualizations and interpret them
  • How to use Jupyter Notebooks to enter the code that will enable uploading and visualizing data, seeing the results of the data through visualization, etc.
  • Arrays: How to create Arrays to hold data, and access and manipulate data in the Arrays


  • be able to install Python and Jupyter notebooks


In this course, you will learn how to properly upload and wrangle datasets, and how to clean datasets in order to produce downstream data visualization based on the correlation of 2 or 3 variables where graphs such as scatterplots, and histograms, and other data visualizations can be employed to understand the data and the relationship between parameters in a dataset. You will also learn how to employ List and Tuples, and how to access data in List and Tuples, and also how to create Arrays, and manipulate, access, and use the power of Arrays in analyzing numerical data. This course is designed for someone who is just beginning to learn Python, either as a supplement to their highschool or college class, as someone who just wants to pick up Python for other reasons (i.e. Career advancement or Adult learning), or anyone that would like to learn Python a little bit at a time. This series is deigned to be watched in less than 35-40 minutes, and the student should be able to download Python 3.7 and Jupyter notebooks so that after the course the can study the material. Python is a very versatile and useful language and it is actually also, a very straightforward language that if learned properly, can be applied to a myriad of ways to earn money, analyze data, be creative with code, and to use as a stepping stone to learn other languages. I hope that you will enjoy this series, and join me subsequent courses. John

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