Python Tutorial: Using the Census API

Want to learn more? Take the full course at https://learn.datacamp.com/courses/analyzing-us-census-data-in-python at your own pace. More than a video, you'll learn hands-on coding & quickly apply skills to your daily work. --- The data frame used in the first lesson was downloaded from the Census API server. Now we'll learn how to construct an API request and load the response into a pandas data frame. This is a basic Census API request. The part up to the question mark is referred to as the "base URL", and specifies, the host, year, and dataset. The part after the question mark is referred to as the query string. This is where we specify parameters such as the variables being requested, and the desired geography. Although the URL can be constructed using simple string manipulation... ...we will use the requests library, imported here, to construct the URL. We define variables for the HOST, year, and dataset, then build the base URL by joining these variables with a slash. dataset = "dec/sf1" stands for "Summary File 1", and refers to the full count data from the decennial census. The requests.get method accepts query parameters as a dictionary. The Census API documentation refers to these parameters as "predicates", so we name the dictionary "predicates". The variables to request are assigned to a list, get_vars. These include the name of the geographic unit, the land area in square meters, and the full population count. Don't worry about the obscure name "P001001". We'll learn where to find these variable names later. A dictionary key "get" is created by joining the variable names into a comma-separated string. Set the "for" key to the geographic level. We use "state", followed by the asterisk wild card, to request all states. Finally, execute the request and store the return value in the response object "r". Now inspect the text attribute of the response object. This is a string with the form of a list of lists. Each sublist is a "row" of da