Understanding Variant Sequences Over Time: A Step-by-Step R Example

Here’s the complete and corrected code:

# Convert month_year column to Date class
India_variant_df$date <- as.Date(paste0("01-", India_variant_df$month_year), format = "%d-%b-%Y")

# Group by date, variant, and sum num_seqs_of_variant
library(dplyr)
grouped_df <- group_by(India_variant_df, date, variant) %>%
  summarise(num_seqs_of_variant = sum(num_seqs_of_variant))

# Plot the data
ggplot(data = grouped_df, aes(x = date, y = num_seqs_of_variant, color = variant)) +
  geom_point(stat = "identity") +
  geom_line() +
  scale_x_date(
    date_breaks = "1 month",
    labels = function(z) ifelse(seq_along(z) == 2L | format(z, format="%m") == "01",
                                format(z, format = "%b\n%Y"),
                                format(z, "%b"))
  )

This code first converts the month_year column to a Date class using as.Date(). It then groups the data by date, variant, and sums up the num_seqs_of_variant for each group. Finally, it plots the grouped data with lines for each variant.

Note that I added the necessary library(dplyr) call to load the dplyr package, which provides the group_by() function used in the code.

Last modified on 2025-03-21