Nonprofits typically operate on fiscal years that don’t align with the calendar year. fundr provides comprehensive tools for working with fiscal years, partial dates (common with birth dates), and other date utilities.
Fiscal Year Functions
Most educational institutions and many nonprofits use a July 1 - June 30 fiscal year. fundr defaults to this convention.
Basic Fiscal Year Conversion
# Key dates around fiscal year boundary
dates <- as.Date(c("2024-06-30", "2024-07-01", "2025-01-15", "2025-06-30"))
# Get the fiscal year number
fy_year(dates)
#> [1] 2024 2025 2025 2025
# Get a formatted label
fy_label(dates)
#> [1] "FY24" "FY25" "FY25" "FY25"
# Get the fiscal quarter
fy_quarter(dates)
#> [1] 4 1 3 4Note that June 30, 2024 is in FY24, while July 1, 2024 starts FY25.
Customizing the Fiscal Year Start
If your organization uses a different fiscal year, specify the starting month:
Setting a Global Default
Use fundr_setup() to set your organization’s fiscal year
start globally:
# Set fiscal year to start in October
fundr_setup(fy_start_month = 10)
# Now all fiscal year functions use October
fy_year(as.Date("2024-10-15")) # Returns 2025Fiscal Year Labels
fy_label() provides human-readable fiscal year
labels:
Fiscal Quarters
fy_quarter() returns the fiscal quarter (1-4):
# Sample dates throughout fiscal year 2025
dates <- as.Date(c(
"2024-07-15", # Q1
"2024-10-15", # Q2
"2025-01-15", # Q3
"2025-04-15" # Q4
))
fy_quarter(dates)
#> [1] 1 2 3 4Partial Dates
Birth dates in fundraising databases often have incomplete information - sometimes only the year, or year and month. fundr handles these gracefully.
Parsing Partial Dates
# Various date formats from the portfolio
dob_samples <- c(
"03/15/1985", # Full date
"March 1985", # Month and year
"1985", # Year only
"1985-03-15", # ISO format
"03-15-85" # Two-digit year
)
parse_partial_date(dob_samples)
#> [1] NA "1985-03-01" "1985-01-01" "1985-03-15" NADate Precision
Determine what level of precision each date has:
dob_samples <- c("03/15/1985", "March 1985", "1985", NA)
date_precision(dob_samples)
#> [1] <NA> year-month year <NA>
#> Levels: year year-month fullCalculating Age with Partial Dates
calc_age_partial() calculates age from potentially
incomplete dates:
dob_samples <- c("03/15/1985", "March 1985", "1985")
calc_age_partial(dob_samples)
#> [1] NA 41 40For year-only dates, the function assumes mid-year (July 1) for the calculation.
Working with Portfolio DOBs
The portfolio dataset includes dates in various formats:
# Sample DOBs from the portfolio
sample_dobs <- fundr_portfolio$dob[!is.na(fundr_portfolio$dob)][1:10]
sample_dobs
#> [1] "1950" "1979" "12-09-1966" "February 1962"
#> [5] "01/12/65" "04/10/73" "May 19, 1948" "1972"
#> [9] "06/25/1941" "04-20-1972"
# Parse them
parsed <- parse_partial_date(sample_dobs)
parsed
#> [1] "1950-01-01" "1979-01-01" NA "1962-02-01" NA
#> [6] NA NA "1972-01-01" NA NA
# Check precision
date_precision(sample_dobs)
#> [1] year year full year-month <NA> <NA>
#> [7] <NA> year <NA> <NA>
#> Levels: year year-month fullDate Utilities
fundr includes several helpful date utility functions.
Time Intervals
Calculate time between dates:
start <- as.Date("2020-01-15")
end <- as.Date("2024-06-30")
date_interval(start, end, unit = "years")
#> [1] 4.5
date_interval(start, end, unit = "months")
#> [1] 53.5
date_interval(start, end, unit = "days")
#> [1] 1628Years Since
Calculate years since a date (useful for giving recency):
last_gift_dates <- as.Date(c("2024-01-15", "2022-06-30", "2018-03-01"))
years_since(last_gift_dates)
#> [1] 2.2 3.7 8.0Recency Bucketing
Categorize dates by how recent they are:
dates <- as.Date(c("2025-12-01", "2024-06-15", "2022-01-01", "2018-06-30"))
bucket_recency(dates)
#> [1] Last year 2-4 years ago 2-4 years ago 5+ years ago
#> 5 Levels: This year < Last year < 2-4 years ago < ... < 5+ years agoFinding Weekdays
Useful for scheduling and reporting:
date <- as.Date("2025-02-28")
# What day is this?
weekday_name(date)
#> [1] "Friday"
# Find next Monday
next_weekday("Monday", as_of = date)
#> [1] "2025-03-03"
# Find last Friday
last_weekday("Friday", as_of = date)
#> [1] "2025-02-28"Practical Examples
Fiscal Year Giving Summary
# Add fiscal year to giving data
portfolio_fy <- fundr_portfolio
portfolio_fy$last_gift_fy <- fy_year(portfolio_fy$last_gift_date)
# Count donors by fiscal year
table(portfolio_fy$last_gift_fy, useNA = "ifany")
#>
#> 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006
#> 4 7 18 25 25 41 36 35 50 53 56 51 76 68 88 76
#> 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022
#> 77 91 106 109 125 110 118 134 122 137 137 147 165 159 153 177
#> 2023 2024 2025 2026 <NA>
#> 170 180 184 3691 2999Age Distribution
# Calculate ages from DOBs
ages <- calc_age_partial(fundr_portfolio$dob)
# Summary statistics
summary(ages)
#> Min. 1st Qu. Median Mean 3rd Qu. Max. NA's
#> 21.0 44.0 54.0 54.1 64.0 95.0 6413Donor Recency Analysis
# Categorize donors by recency
recency <- bucket_recency(fundr_portfolio$last_gift_date)
table(recency, useNA = "ifany")
#> recency
#> This year Last year 2-4 years ago 5-6 years ago 5+ years ago
#> 3587 196 543 0 2675
#> <NA>
#> 2999Summary
| Function | Purpose |
|---|---|
fy_year() |
Convert date to fiscal year number |
fy_label() |
Convert date to fiscal year label (e.g., “FY25”) |
fy_quarter() |
Get fiscal quarter (1-4) |
parse_partial_date() |
Parse dates with varying precision |
date_precision() |
Determine date precision level |
calc_age_partial() |
Calculate age from partial dates |
date_interval() |
Calculate time between dates |
years_since() |
Years elapsed since a date |
bucket_recency() |
Categorize by recency |
is_within() |
Check if within time range |
last_weekday() |
Find previous occurrence of weekday |
next_weekday() |
Find next occurrence of weekday |
weekday_name() |
Get day of week name |