marooned20 / udacity-analyze-dataset Goto Github PK

In the frame of this project, we will explore three datasets from Gapminder's treasure of data collection. The collection can be found HERE. It is a rich collection to play with. We will try to explore three datasets (indicators):

• Oil Consumption
• CO2 Emissions
• GDP

Python 3.6 (or higher)
matplotlib 2.1 (or higher)
numpy 1.10 (or higher)
pandas 0.20 (or higher)
cartopy 0.16.0

The structure of the project is as follows:

• Data Wrangling
• Data Cleaning
• Data Visualization
• Conclusions

We will explore the data and remove the inconsistencies such as missing data, variable data types etc.

Data will be cleaned in order to have smoothness across all the datasets.

We will use various plots to see how the different parameters correlate to one another. How the distribution of GDP, Oil Consumption and CO2 emissions look like among chosen set of countries. At the end we shall have an overview of all the indicators in an animation to get an idea on how the three evolved with time. The inspiration behind the animation was the TED Talk by Hans Rosling of Gapminder. And lastly, we will attempt to see the data on a Choropleth map!