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Investigate-a-Dataset-Gapminder-Health

Udacity Data Analytics Nanodegree Project 1 - Exploring Gapminder Datasets using Python and Jupyter Notebook

Project Overview

In this project, I will analyze a dataset and then communicate my findings about it. I will use the Python libraries NumPy, pandas, and Matplotlib to make my analysis easier.

What do I need to install?

I will need an installation of Python, plus the following libraries:

  • pandas
  • NumPy
  • Matplotlib
  • csv

What will I learn?

After completing the project, I will:

  • Know all the steps involved in a typical data analysis process
  • Be comfortable posing questions that can be answered with a given dataset and then answering those questions
  • Know how to investigate problems in a dataset and wrangle the data into a format you can use
  • Have practice communicating the results of your analysis
  • Be able to use vectorized operations in NumPy and pandas to speed up your data analysis code
  • Be familiar with pandas' Series and DataFrame objects, which let you access your data more conveniently
  • Know how to use Matplotlib to produce plots showing your findings

Project details

Step One - Choose the data

I chose four datasets from Gapminder.

  • Female salaried employee
  • Female literacy rate
  • Gdp per capita
  • Life expectancy at birth

Step two - Get Organized

Create a single folder (repositories) that contains:

  • The report communicating your findings
  • Any Python code you wrote as part of your analysis
  • The data set you used

Step three - Analyse the data

Make questions that promote looking at relationships between multiple variables. I aimed to analyze at least one dependent variable and three independent variables in my investigation. Make sure I use NumPy and pandas where they are appropriate!

Step four - Share your findings

Create a report that shares the findings I found most interesting.

Reference

https://www.gapminder.org/data/