Calculating the total daily amount of confirmed cases of Coronavirus
So it seams like you have a Pandas dataframe you are working with.
At the moment it looks like this section of code does the following

worldCases = []                   

for i in range(0,len(dd)):               #iterate through all dates
    count = 0                            #setup a counter
    for j in range(0,len(dd)):           #iterate through all dates
        if dd[j]==dd[i]:                 
            count+=dc[i]                 #add one to counter if inner date == outer date
    worldCases.append(count)             #track number of times a unique date occurs


You are effectively binning your data, getting a count of the number of times each unique date occurs. Pandas offers you more efficient and convenient tools for doing this. Specifically look into the groupby method. 

A much faster way to get the same output for worldCases would be to do the following:

# group the daily cases data by the date and then compute 
# the sum of cases within each date group

dc = 'Daily confirmed cases (cases)'
worldCases = cases.loc[:, dc].groupby(cases['Date']).sum()


Also, if you find yourself writing lots of loops like the above, you may want to check out the user guide for "group by" operations in the pandas documentation. It is a very powerful way of handling situations like this, and more, but can take a bit of getting used to. It can feel like a whole different way of thinking about your data.