A free sample of the course An introduction to data analysis using Python, from Scratch

What you will learn

Perform exploratory data analysis using the pandas library in python

Write code in python that will assist them in analyzing data

Produce visually appealing graphs that summarise their findings

Understand the data analysis process, from reading the data set to formatting the data, leading to producing summary statistics


This course provides a free sample of the full course. You can enroll in this sample for free. If you like what you see, then you can enroll in the full course. This is done in order to help the students know exactly what the course is and the teaching style before having to pay any money.

The purpose of this course is to introduce non-technical students to data analysis using python. This course is for anyone who is interested in becoming a data analyst and has no experience at all with data analysis or with python. If you have no experience at all with python and with data analysis then this course is for you. At the start of the course the students will have no knowledge of data analysis or python. By the end of the course the student will be able to:

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  • Use the Pandas library to read, modify, and analyze data
  • Install packages in python
  • Produce visually appealing graphs that help you tell a story
  • Uncover relationships between different types of variables
  • Understand how a data analyst thinks
  • Have a basic but solid understanding of how python can be used to analyze data
  • Create interactive maps
  • Manipulate the data so that it is in a proper format

The course starts from the very basics and slowly introduces the student to the most important functions and commands used in data analysis. This is done without relying heavily on programming. This course will show how to analyze data without having to write long lines of code.




Downloading the necessary program
The Anaconda interface
Jupyter lab – navigating the user interface and executing code
Back to the Anaconda interface – viewing libraries

A First Look at the Pandas library

First look at the Pandas library
First look at the data
Adjusting the name of the data set

Looking More Closely at the Data

Using the info() function
Counting the null values
Zooming in to a specific row
Zooming into a specific column
Zooming in to a certain row and column
Removing rows and columns

Using Conditions to Perform Operations

One condition – part 1
One condition – part 2
Two conditions – the AND operator
Two conditions – the OR operator
Less than or equal to and greater than or equal to
Not equal to
The isin() method
The isna() method