Creates a wide summary table showing prices by city/airport and date, with an average price column. When multiple flights exist for the same date, uses the minimum (cheapest) price. This is useful for visualizing price patterns across multiple dates and comparing different origin airports. Supports filtering by various criteria such as departure time, airlines, travel time, stops, and emissions.
Usage
fa_summarize_prices(
flight_results,
include_comment = TRUE,
currency_symbol = "$",
round_prices = TRUE,
time_min = NULL,
time_max = NULL,
airlines = NULL,
price_min = NULL,
price_max = NULL,
travel_time_max = NULL,
max_stops = NULL,
max_layover = NULL,
max_emissions = NULL,
excluded_airports = NULL
)Arguments
- flight_results
A flight_results object from [fa_fetch_flights()].
- include_comment
Logical. If TRUE and Comment column exists, includes it in the output. Default is TRUE.
- currency_symbol
Character. Currency symbol to use for formatting. Default is "$".
- round_prices
Logical. If TRUE, rounds prices to nearest integer. Default is TRUE.
- time_min
Character. Minimum departure time in "HH:MM" format (24-hour). Filters flights departing at or after this time. Default is NULL (no filter).
- time_max
Character. Maximum departure time in "HH:MM" format (24-hour). Filters flights departing at or before this time. Default is NULL (no filter).
- airlines
Character vector. Filter by specific airlines. Default is NULL (no filter).
- price_min
Numeric. Minimum price. Default is NULL (no filter).
- price_max
Numeric. Maximum price. Default is NULL (no filter).
- travel_time_max
Numeric or character. Maximum travel time. If numeric, interpreted as hours. If character, use format "XX hr XX min". Default is NULL (no filter).
- max_stops
Integer. Maximum number of stops. Default is NULL (no filter).
- max_layover
Character. Maximum layover time in format "XX hr XX min". Default is NULL (no filter).
- max_emissions
Numeric. Maximum CO2 emissions in kg. Default is NULL (no filter).
- excluded_airports
Character vector. Airport codes to exclude from results. Default is NULL (no additional filtering beyond global excluded_airports list).
Value
A wide data frame with columns: City, Origin, Comment (optional), one column per date with prices, and an Average_Price column.
Examples
# Create summary table
fa_summarize_prices(sample_flight_results)
#> City Origin 2025-12-18 2025-12-19 2025-12-20 2025-12-21 2025-12-22
#> 1 Mumbai BOM $624 $587 $658 $609 $625
#> 2 Delhi DEL $564 $591 $647 $671 $541
#> 3 Gaya GAY $716 $668 $816 $778 $704
#> 4 Patna PAT $679 $634 $697 $715 $697
#> 5 Varanasi VNS $635 $609 $679 $722 $653
#> 6 Best Day X
#> 2025-12-23 2025-12-24 2025-12-25 2025-12-26 2025-12-27 2025-12-28 2025-12-29
#> 1 $679 $778 $961 $1,031 $1,353 $1,539 $1,715
#> 2 $643 $853 $692 $ 955 $1,364 $1,464 $1,359
#> 3 $857 $926 $990 $1,218 $1,711 $1,751 $1,846
#> 4 $851 $900 $979 $1,114 $1,467 $1,641 $1,658
#> 5 $811 $901 $910 $ 939 $1,393 $1,880 $1,772
#> 6
#> 2025-12-30 2025-12-31 2026-01-01 2026-01-02 2026-01-03 2026-01-04 2026-01-05
#> 1 $1,872 $2,011 $1,846 $1,648 $1,640 $615 $618
#> 2 $1,878 $2,195 $1,672 $1,375 $1,606 $694 $567
#> 3 $2,127 $2,438 $2,083 $1,994 $2,098 $767 $674
#> 4 $2,178 $2,480 $2,210 $1,938 $1,983 $784 $668
#> 5 $1,979 $2,006 $2,079 $1,960 $1,947 $754 $664
#> 6
#> Average_Price
#> 1 $1,127
#> 2 $1,070
#> 3 $1,324
#> 4 $1,278
#> 5 $1,226
#> 6
# With filters
fa_summarize_prices(
sample_flight_results,
max_stops = 0
)
#> City Origin 2025-12-18 2025-12-19 2025-12-20 2025-12-21 2025-12-22
#> 1 Gaya GAY $716 $668 <NA> <NA> $704
#> 2 Patna PAT $679 $634 $697 $715 $697
#> 3 Mumbai BOM <NA> <NA> $658 <NA> <NA>
#> 4 Varanasi VNS <NA> <NA> $679 $722 $653
#> 5 Delhi DEL <NA> <NA> <NA> <NA> <NA>
#> 6 Best Day
#> 2025-12-23 2025-12-24 2025-12-25 2025-12-26 2025-12-27 2025-12-28 2025-12-29
#> 1 $857 $926 <NA> $1,218 $1,711 $1,751 $1,846
#> 2 <NA> $900 <NA> $1,114 $1,467 <NA> $1,658
#> 3 <NA> $778 $961 <NA> $1,353 <NA> <NA>
#> 4 <NA> <NA> <NA> <NA> $1,393 <NA> <NA>
#> 5 <NA> $853 $692 $ 955 <NA> <NA> <NA>
#> 6
#> 2025-12-30 2025-12-31 2026-01-01 2026-01-03 2026-01-04 2026-01-05
#> 1 $2,127 $2,438 <NA> $2,098 <NA> $674
#> 2 $2,178 $2,480 $2,210 $1,983 <NA> $668
#> 3 <NA> <NA> $1,846 <NA> $615 $618
#> 4 $1,979 <NA> <NA> $1,947 $754 <NA>
#> 5 $1,878 <NA> $1,672 <NA> $694 <NA>
#> 6 X
#> Average_Price
#> 1 $1,364
#> 2 $1,291
#> 3 $ 976
#> 4 $1,161
#> 5 $1,124
#> 6