Introducing the project dataset

For the final chapter, you'll be looking at some of the Gapminder datasets combined into one tidy file called "gapminder_tidy.csv". This data set is available as a pandas DataFrame under the variable name data.

It is always a good idea to begin with some Exploratory Data Analysis. Pandas has a number of built-in methods that help with this. For example, data.head() displays the first five rows/entries of data, while data.tail() displays the last five rows/entries. data.shape gives you information about how many rows and columns there are in the data set. Another particularly useful method is data.info(), which provides a concise summary of data, including information about the number of entries, columns, data type of each column, and number of non-null entries in each column.

Use the IPython Shell and the pandas methods mentioned above to explore this data set. How many entries and columns does this data set have?

Possible Answers

7 entries, 10111 columns.
10111 entries, 7 columns.
9000 entries, 7 columns.

Exercise

Introducing the project dataset

Instructions

Possible Answers