Preparing and Cleaning Data FRED data in GAUSS

▤ Summary

In today’s blog, we look at how to save time and reduce errors using GAUSS’s new data management tools. Using the quarterly real GDP dataset from the FRED database we explore GAUSS’s new data management tools. The data preview window indicates that there are a number of issues to address in our raw dataset: • The variable names are not correct. To finish our real GDP FRED data cleaning example, lets filter the dataframe to include only observations that occur in 1970 and later. Today, we’ve examined how the interactive data management tools in GAUSS can make this process less painful and less tedious.

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