From the course: Python Data Analysis
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Overview: Exploring data - Python Tutorial
From the course: Python Data Analysis
Overview: Exploring data
- [Instructor] Once we have imported our dataset and we are satisfied that it is clean and refactored, it's time to start exploring it, summarizing it, and visualizing it. We'll be trying to understand the typical values and the range of variation of our variables, and to identify which variables are correlated. In this chapter, we will again work with datasets from the Gapminder project. Let's have a look at the dataset. For all the countries in the world and for years starting in 1900, the dataset encodes a few basic trends: the approximate population, the expected lifetime, the percentage of children surviving to age five, the average number of babies per woman, and the gross national product divided by population. The unit is 2017 equivalent dollars. We also look at the second dataset that describes the distribution of incomes in China and in the USA in 1965 and 2015. The Gapminder website includes a number of beautiful and powerful visualizations. We will use Python to reproduce…
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