Replace values based on months in a dataframe with values in another column in r, using apply functions

I am working with a time series of precipitation data and attempting to use the median imputation method to replace all 0 value data points with the median of all data points for the corresponding month that that 0 value was recorded.

I have two data frames, one with the original precipitation data:

 > head(df.m)
       prcp       date
1 121.00485 1975-01-31
2 122.41667 1975-02-28
3  82.74026 1975-03-31
4 104.63514 1975-04-30
5  57.46667 1975-05-31
6  38.97297 1975-06-30

And one with the median monthly values:

> medians
   Group.1         x
1       01 135.90680
2       02 123.52613
3       03 113.09841
4       04  98.10044
5       05  75.21976
6       06  57.47287
7       07  54.16667
8       08  45.57653
9       09  77.87740
10      10 103.25179
11      11 124.36795
12      12 131.30695

Below is the current solution that I have come up with utilizing the 1st answer here:

df.m[,"prcp"] <- sapply(df.m[,"prcp"], function(y) ifelse(y==0, medians$x,y))

This has not worked as it only applies the first value of the df medians$Group.1, which is the month of January (01). How can I get the values so that correct median will be applied from the corresponding month?

Another way I have attempted a solution is via the below:

df.m[,"prcp"] <- sapply(medians$Group.1, function(y)
                 ifelse(df.m[format.Date(df.m$date, "%m") == y & 
                 df.m$prcp == 0, "prcp"], medians[medians$Group.1 == y,"x"], 
                 df.m[,"prcp"]))   

Description of the above function - this function tests and returns the amount of zeros for every month that there is a zero value in df.m[,"prcp"] Same issue here as the 1st solution, but it does return all of the 0 values by month (if just executing the sapply() portion).

How can I replace all 0 in df.m$prcp with their corresponding medians from the medians df based on the month of the data?

Apologies if this is a basic question, I'm somewhat of a newbie here. Any and all help would be greatly appreciated.