To begin, we can deconstruct the URL into three aspects: the base URL, the date, and the file extension. Notably, the URL is straightforward in its structure and allows for a fairly simple approach in attempting to create this URL from scratch. The URL for the most recent file from the webpage for August 2017 has the following format: “ ” However, the differences in the time required to execute the code are generally minimal between the two languages. First, Using PythonĪ distinct advantage of using Python over R is being able to write fewer lines for the same results. We will specifically explore downloading historical hourly locational marginal pricing (LMP) data files from PJM, a regional transmission organization coordinating a wholesale electricity market across 13 Midwestern, Southeastern, and Northeastern states. This blog post outlines how to download multiple zipped csv files from a webpage using both R and Python.
Often times, these data files can be separated by a range of times, site locations, or even type of measurement, causing them to be cumbersome to download manually. Being able to automate data retrieval helps alleviate encountering irritating, repetitive tasks.
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