R Leveraging jsonlite: A Step-by-Step Guide to Manipulating JSON Data in R with Practical Example

Here’s an example of how you can use the jsonlite library in R to parse the JSON data and then manipulate it as needed.

# Load necessary libraries
library(jsonlite)
library(dplyr)

# Parse the JSON data
data <- fromJSON('your_json_data')

# Convert the payload.hours column into a long format
long_df <- lapply(data$payload, function(x) {
  hours <- strsplit(x, "]")[[1]]
  names(hours) <- c("start", "end")
  
  # Extract times in proper order (some days have multiple operating hours)
  hours_long <- hours
  for (i in 1:nrow(hours_long)) {
    if (hours_long$start[i] > hours_long$end[i]) {
      temp <- hours_long[order(hours_long$start, hours_long$end), ]
      hours_long[start(i), ] <- temp[1]
      hours_long[end(i), ] <- temp[nrow(temp)]
    }
  }
  
  return(hours_long)
})

# Create a data frame from the long format
long_df <- lapply(long_df, function(x) {
  cbind(name = names(x)[1], 
        day = names(x)[2], 
        start = as.POSIXct(unlist(x[start]), zone = "local"),
        end = as.POSIXct(unlist(x[end]), zone = "local"))
})

# Filter the data for Sundays and hours before 12 pm
sunday_hours <- long_df %>%
  filter(day == "Sunday") %>%
  mutate(end = ifelse(end < "12:00 PM", "12:00 AM", end))

# Print the result
print(sunday_hours)

This code will first parse the JSON data and convert it into a long format, where each row represents a single hour. Then, it will filter out the rows where the start time is after 12 pm on Sundays.

Please replace 'your_json_data' with your actual JSON data.

Note that this assumes that the hours are always in the format y m d h:i PM, where h:i is the hour and minute. If the hours can be in a different format, you may need to adjust the code accordingly.

Last modified on 2024-09-23