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Uploading Divvy datasets (csv files) here

Oct_2020_tripdata <- read_csv("Oct 2020.csv")
Nov_2020_tripdata <- read_csv("Nov 2020.csv")
Dec_2020_tripdata <- read_csv("Dec 2020.csv")
Jan_2021_tripdata <- read_csv("Jan 2021.csv")
Feb_2021_tripdata <- read_csv("Feb 2021.csv")
Mar_2021_tripdata <- read_csv("Mar 2021.csv")

Converting relevant columns to character so that they can stack correctly

Oct_2020_tripdata <-  mutate(Oct_2020_tripdata, start_station_id = as.character(start_station_id)
                             ,end_station_id = as.character(end_station_id))
Nov_2020_tripdata <-  mutate(Nov_2020_tripdata, start_station_id = as.character(start_station_id)
                             ,end_station_id = as.character(end_station_id))
Dec_2020_tripdata <-  mutate(Dec_2020_tripdata, start_station_id = as.character(start_station_id)
                             ,end_station_id = as.character(end_station_id))
Jan_2021_tripdata <-  mutate(Jan_2021_tripdata, start_station_id = as.character(start_station_id)
                             ,end_station_id = as.character(end_station_id))
Feb_2021_tripdata <-  mutate(Feb_2021_tripdata, start_station_id = as.character(start_station_id)
                             ,end_station_id = as.character(end_station_id))
Mar_2021_tripdata <-  mutate(Mar_2021_tripdata, start_station_id = as.character(start_station_id)
                             ,end_station_id = as.character(end_station_id))

Binding data frames

all_trips <- bind_rows(Oct_2020_tripdata, Nov_2020_tripdata, Dec_2020_tripdata, 
                       Jan_2021_tripdata, Feb_2021_tripdata, Mar_2021_tripdata)

Removing rows with missing values

colSums(is.na(all_trips))
all_trips_cleaned <- all_trips[complete.cases(all_trips), ]

Flitering started_at data that is greater than ended_at

all_trips_cleaned <- all_trips_cleaned %>% 
  filter(all_trips_cleaned$started_at < all_trips_cleaned$ended_at)

Creating new columns to list the date, month, day, and year of each ride

all_trips_cleaned$date <- as.Date(all_trips_cleaned$started_at, format= "%m/%d/%Y")
all_trips_cleaned$month <- format(as.Date(all_trips_cleaned$date), "%m")
all_trips_cleaned$day <- format(as.Date(all_trips_cleaned$date), "%d")
all_trips_cleaned$year <- format(as.Date(all_trips_cleaned$date), "%Y")
all_trips_cleaned$day_of_week <- format(as.Date(all_trips_cleaned$date), "%A")

Trying to add a new column to calculate each ride length in seconds as numeric using R

all_trips_cleaned$ride_length <- as.numeric(difftime(all_trips_cleaned$ended_at, all_trips_cleaned$started_at))

This is the error message I'm getting:

Error in as.POSIXlt.character(x, tz, ...) : 
  character string is not in a standard unambiguous format
Ugochukwu Orji
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    Hi. If you want some help, please consider the following guidelines. https://stackoverflow.com/help/minimal-reproducible-example In the current state, your question is impossible to answer, although the error message of course hints at the fact that your input variables aren't in a unambiguous date format. – deschen Nov 06 '21 at 23:04
  • Hi @deschen, thanks for the feedback. I've updated the flow of my code, hopefully, it makes sense now. I'm pretty new to R. – Ugochukwu Orji Nov 06 '21 at 23:23

0 Answers0