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Merge signed ordered

welcome back in this last chapter we will start discussing marriage order this method can merge time series and other ordered data the merge ordered method will allow us to merge the left and right tables shown here we can see the output of the merge when we merge on a c column the results are similar to the standard merge method with an outer join but here the results are sorted the sorted results make this a useful method for ordered or time series data so let's give context to this method it has many of the same arguments we have already covered with the merge method they both contain arguments to allow us to merge two tables on different columns both methods support different types of joins although the default for the merge method is enter it is outer for the merge order method also both methods support suffixes for overlapping column names however how you call each of the methods is different earlier in the course we call the merged method by first listing a table and calling the method afterward for merge ordered you need to first call pandas then merge order let's look at an example in this chapter we will be working with financial macroeconomics and stock market data in this example we have a table of the stock prices of the apple corporation from february to june 2007. we also have a table of the stock price for mcdonald's corporation from january to may 2007 and we want to merge them the first two arguments are the left and right tables we set the on argument equal to date finally we set the suffixes argument to determine which table the data originated this results in a table sorted by date there isn't a value for apple in january or a value for mcdonald's for june since values for these time periods are not available in the two original tables we can fill in this missing data using a technique called forward filling it will interpolate missing data by filling the missing values with the previous value in the table shown here the second and fourth rows of column b are filled with the values of b in the rows preceding them going back to our stock example from before we now set the fill method argument to f fill for forward fill in the result notice that the missing value from mcdonald's in the last row is now filled in with the row before it the table from before is shown on the right for easier comparison notice the missing value for apple in the first row is still missing since there isn't a row before the first row to copy into the missing value for apple you might think about using the merge order method instead of the regular merge method when you are working with ordered or time series data like in our example additionally the feel forward feature is useful...