Get your data ready for Vesta.

Every dataset needs a geographic identifier that links your values to spatial boundaries. This is what lets Vesta merge your data with boundaries and draw it on a map.

• —State or county FIPS codes Standard digit codes from the US Census Bureau. Keep them as text so leading zeros survive.
• —ZIP codes Common in health and consumer data.
• —Census tract IDs For neighborhood-level demographic work.
• —Latitude / longitude For point data, in WGS 1984.

Time is optional. Without a time variable, choose "Always valid" during import. With one, Vesta can animate and analyze change over time.

• —Single year YYYY, e.g. 2015
• —Full date MMDDYYYY or MM/DD/YYYY
• —Time interval Two columns: start and end

Work on a copy of the raw file in R, Python, SPSS, SAS or Excel. Leave missing values blank, or use a placeholder such as -99 and list it as a missing value code on the import Variables step (see Missing data in the docs). Keep only the variables and records your question needs; smaller files are easier to check and merge.

Vesta works at the geographic-unit level, so each area needs one record. Point data (latitude/longitude) can skip this step.

• —Proportion (%) For categorical responses, e.g. share of youth reporting depression symptoms.
• —Mean or median For continuous measures, e.g. average income or BMI by county.

One row per area and period, an identifier column, a time column and numeric values.

FIPS,County,Year,Deaths,Population
39001,Adams,2014,6,27907
39001,Adams,2015,9,27850
39003,Allen,2014,21,105040
39003,Allen,2015,,104425