wbucklerbillboard/independant-coursework-moocs-

These files were the result of "Building Big Data Pipelines with R & Sparklyr & PowerBI". The product is EarthquakeVis.

Independant-Coursework-MOOCs-

These files were the result of "Building Big Data Pipelines with R & Sparklyr & PowerBI". The product is EarthquakeVis.

Originally, processing occurred through the R library, Sparklyr. The library was buttressed by the particular installation sequence of Java, & Apache Spark.
I learned a great deal on how differing versions of such installations can interfere with software functioning. Rather than interpret the course as broken, working with differing software installation versions was a value-added moment. These version conflicts prevented me from performing the final crucial step, the loading step in ETL (https://stackoverflow.com/questions/67775916/spark-write-csv-doesnt-work-anymore-with-sparklyr)

As an alternative, I used Pandas as a work around. I referred to Lesson 6 in Geo-Python 2021. After succeeding through Pandas, I loaded the two .csv files into Power BI. The final third .csv file, predicted results, was produced in a separate MOOC (SpaDataVisML_Quakes). The predicted results file was also loaded into Power BI.