I’m doing a full merge of 3 data sets
I have 3 data sets to merge, I’ve done a full merge as I want them all to combine with each other rather than bind rows which just stacks them.

str(country)
data.frame':    228 obs. of  4 variables:
 $ location     : Factor w/ 135 levels "Afghanistan",..: 1 2 3 4 5 6 7 8 9 10 ...
 $ lockdown_date: Date, format: "2020-03-24" "2020-03-08" "2020-03-24" "2020-03-16" ...
 $ Type         : chr  "Full" "Full" "Full" "Full" ...
 $ Reference    : chr  "https://www.thestatesman.com/world/afghan-govt-imposes-lockdown-coronavirus-cases-increase-15-1502870945.html" "https://en.wikipedia.org/wiki/2020_coronavirus_pandemic_in_Albania" "https://www.garda.com/crisis24/news-alerts/325896/algeria-government-implements-lockdown-and-curfew-in-blida-an"| __truncated__ "https://en.wikipedia.org/wiki/2020_coronavirus_pandemic_in_Andorra" 

Str(covid)
 data.frame':   1575 obs. of  8 variables:
 $ location      : chr  "Australia" "Australia" "Australia" "Australia" ...
 $ date          : chr  "2019-12-31" "2020-01-01" "2020-01-02" "2020-01-03" ...
 $ total_cases   : int  0 0 0 0 0 0 0 0 0 0 ...
 $ new_cases     : int  0 0 0 0 0 0 0 0 0 0 ...
 $ total_deaths  : num  0 0 0 0 0 0 0 0 0 0 ...
 $ new_deaths    : num  0 0 0 0 0 0 0 0 0 0 ...
 $ gdp_per_capita: num  44649 44649 44649 44649 44649 ...
 $ population    : int  25499881 25499881 25499881 25499881 25499881 25499881 2                  38                  33

 str(vaccination)
  data.frame':  187 obs. of  5 variables:
 $ location                         : Factor w/ 187 levels "Afghanistan",..: 1 2 3 4 5 6 7 8 9 10 ...
 $ Doses.administered.per.100.people: int  17 102 35 64 237 73 162 229 207 137 ...
 $ total_doses_administered         : num  6.45e+06 2.91e+06 1.52e+07 2.04e+07 1.06e+08 ...
 $ X..of.population.vaccinated      : num  15 46 19 41 92 38 84 88 77 53 ...
 $ perc_pop_vaccinated              : num  13 44 16 22 84 33 78 86 75 48 ...

 str(df) Merged dataframe after using distinct
'data.frame':   5811 obs. of  11 variables:
 $ location                : Factor w/ 202 levels "Afghanistan",..: 1 2 3 4 5 6 7 8 8 8 ...
 $ date                    : chr  NA NA NA NA ...
 $ total_cases             : int  NA NA NA NA NA NA NA 4 4 0 ...
 $ new_cases               : int  NA NA NA NA NA NA NA 0 0 0 ...
 $ total_deaths            : num  NA NA NA NA NA NA NA 0 0 0 ...
 $ new_deaths              : num  NA NA NA NA NA NA NA 0 0 0 ...
 $ gdp_per_capita          : num  NA NA NA NA NA ...
 $ population              : int  NA NA NA NA NA NA NA 25499881 25499881 25499881 ...
 $ lockdown_date           : Date, format: "2020-03-24" "2020-03-08" "2020-03-24" "2020-03-16" ...
 $ total_doses_administered: num  6445359 2906126 15205854 NA 20397115 ...
 $ perc_pop_vaccinated     : num  13 44 16 NA 22 84 33 86 86 86 ...

Some dates in the date column are being repeated due to the lockdown_date column having multiple lockdown dates per country. For example china 31/12/19 is repeated 3 times in the df dataframe, whereas in the covid data frame it only appears once. How do i merge these dataframes better?

this is my merge

df <- merge(country, covid, by = "location", all = TRUE)

df <- merge(df, vaccination, by = "location", all = TRUE)

there should be a total of 1990 rows, but once merged it creates 5811 even after using distinct