When you have data with values over time, you’ll want to specify the time period (e.g. year) in the column labels. This will make data selection easier and enable you to make a time series chart with your data.
Formatting your data
The data upload system currently only recognizes dates between January 1, 1900 and January 1, 2100.
Put the time period at the beginning or end of a column label (i.e. ‘2010_population’ or ‘population_April_01_2020’)
Be consistent in how the time period is formatted. Changing between 'Jan 2010' and 'January 2010' will result in the system creating 2 different months.
Column labels for different time periods
Year: Use a 4-digit year
e.g. 2010, 2020, 2050, 1961
Month: Include month and year
Each of the following formats specify the month January 2019
January_2019 | 2019_January | January 2019 | Jan 2019 | 2019_01 | 01 2019
Day: Include the day, month, and year
Each of the following formats specify the day June 30, 2019
2019_06_30 | 2019_June_30 | 06_30_2019 | June 30 2019
Quarter: Include the year and quarter; abbreviate quarters as q1, q2, q3, or q4
Each of the following formats specify the second quarter of 2019
2019_q2 | 2019 q2 | 2019_Q2 | 2019 Q2
Labeling variables and time
‘Population’, ‘total 311 calls’, ‘people with health insurance’, and ‘people in poverty’ are all examples of variables. When your file contains one or more variables, the following are important for ensuring a successful upload.
Word use and spelling matters for the system to recognize the variable as the same thing (i.e. ‘2010_pop’ and ‘2020_population’ will be mapped as two different variables of 'pop' and 'population', respectively)
You can have multiple variables in the same layer (i.e. households, population, area, educational attainment, etc)
Example:
2010_population
2015_population
2020_population
people_in_poverty_2010
people_in_poverty_2015
people_in_poverty_2020
By repeating the name 'population' and 'people_in_poverty' with the three different years, the system will recognize two variables: 'population' and 'people_in_poverty' and pair each one with the three years: 2010, 2015, and 2020.
Why does this matter? When your data is formatted like this, in the selection experience, you will be given the option to choose between two variables 'population' or 'people_in_poverty' first, and then be able to choose the appropriate year. It also means you will be able to view each variable in a time series chart.
Step-by-step with example data
For more help, review this example upload of
Age-Adjusted Deaths 2004-2020 for Clay County, FL.