Exercise

# 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?

Instructions

**50 XP**

##### Possible Answers

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