To confirm the latter limit, let's print the last five rows of the dataset by using the tail() method: women_majors.tail()Īlmost every FTE graph is part of an article. As mentioned before, we have data from 1970 to 2011.

Thus, every row describes the percentage for various Bachelors conferred to women in a given year. Every datapoint in the Bachelor columns represents the percentage of Bachelor degrees conferred to women. Year column, every other column name indicates the subject of a Bachelor degree. Social Sciences and History 42 non-null float64 Public Administration 42 non-null float64 Print information about the dataset by using the info()Ĭommunications and Journalism 42 non-null float64.Read in the data by using read_csv(), and assign the content to women_majors.Assign the direct link toward the dataset as a string to a variable named direct_link.To save yourself some time, you can skip downloading the file, and just pass in the direct link to pandas' read_csv() function. If you want to follow along by writing code yourself, you can download the data from Randal's blog. Randal Olson, who collected the data from the National Center for Education Statistics. We'll use a dataset compiled by data scientist We'll work with data describing the percentages of Bachelors conferred to women in the US from 1970 to 2011. If you know what's the difference between methods and attributes, then you're good to go. We'll start here: And, at the end of the tutorial, arrive here: To follow along, you'll need at least some basic knowledge of Python. Using Python's matplotlib and pandas, we'll see that it's rather easy to replicate the core parts of any FiveThirtyEight (FTE) visualization. You still can't get the graphs done yourself. You received some answers, but they were rather vague. You wanted to make your own awesome visualizations and so asked Quora and Reddit how to do it. Naturally, you were impressed by their awesome visualizations. If you read data science articles, you may have already stumbled upon FiveThirtyEight's content.

Change colors seaborn scatter plot