Rcode for latinamerica map code#

Practice version control, discussed further below, which includes archiving previous versions.You may want to rerun a specific analysis or output for a specific table, and having to run everything together is time-consuming.

Rcode for latinamerica map code#

It should be possible to run the master do-file, cleaning code, analysis code, and code that produces figures separately. Keep a master do-file, which is a single do-file that calls all relevant do-files (see more below).For example, keep a separate do-file for data cleaning code (which produces a cleaned dataset from the raw data), a do-file for exploratory analysis code (which is used for trial and error, to play around with data, run regressions, produce summary statistics, and a do-file for final analysis code (which produces estimation results reported into LaTeX tables, properly formatted and annotated graphs, etc.). It is also useful to keep the steps in data manipulation or analysis separate.Examples of data manipulation include dropping, adding, or editing data. Keep data, coding files, and results separate, and include sufficient documentation to make the order and degree of data manipulation clear.See J-PAL's data de-identificationВ resource to learn more. Preserve original, de-identified data.In planning file structure, you should at a minimum do the following:

Files are commonly organized by type: do-files, raw data, cleaned data, and survey instruments. Researchers typically will negotiate a data flow with study partners-and in tandem can begin creating a plan for storing and managing data and other files. Setting up a clear folder structure early on in a study will enable consistent management of data, documents, and other files.