aggregate statistics on each cell of grid and plot heatmap in R - r

Question

Below is the cycle hire data of london. Each point represent one cycle hire point.
I have created a grid using st_make_grid(). Now I wish to -
plot heatmap of number of cycle hire point in each cell of grid
plot heatmap of total nbikes in each cell of grid
(nbikes - The number of bikes currently parked)
library(spData)
library(sf)
# cycle hire data of london
# Each observaion represent a cycle hire point in London.
hire_sf <- spData::cycle_hire
head(hire_sf)
# create grid
grid_area <- st_make_grid(hire_sf)
# 1. plot heatmap of number of cycle hire point in each cell
# 2. plot heatmap of total nbikes in each cell
# (nbikes - The number of bikes currently parked)

Answer 1

This is indeed a duplicate; but we may as well offer a possible solution. So consider the following code:
It is built on sf::st_join() which spatially joins two sf objects (in this case grid and points) while preserving the data attributes.
Note that the join is by default left (in SQL speak) so all rows (grid cells) are maintained in the first object. There will NAs for cells with no hires, and duplicate rows for multiple points (so be sure to assign each cell a unique ID in advance, to make aggregation easier).
The type of the first object in join drives the resulting geometry type, so be sure to start with grid if you want to end up with polygon type result / starting with points you would get point result.
Once the points are assigned to grid cells it is an exercise in aggregation - I suggest via {dplyr} techniques, but base R would do as well.
For the final heatmap you will likely want ggplot for polished results, but base plot will do for a proof of concept.
library(spData)
library(sf)
library(dplyr)
# cycle hire data of london
# Each observaion represent a cycle hire point in London.
hire_sf <- spData::cycle_hire
head(hire_sf)
# create grid
grid_area <- st_make_grid(hire_sf) %>%
st_as_sf() %>%
mutate(grid_id = 1:n())
# join data to grid; make sure to join points to grid
# the first object drives the output geometry
result <- grid_area %>%
st_join(hire_sf) %>%
group_by(grid_id) %>%
summarise(point_count = n(),
total_bikes = sum(nbikes))
# draw heatmap
plot(result["point_count"])