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Merge countersign fact

hey everyone my name is braden in this video we're going to go over how to combine panda's data frames there are four ways we can accomplish this depending on our needs if we want to combine data frames by placing them side by side we can use either merge or join if we want to combine data frames by stacking them on top of one another we can use concat or append when it comes to combining data frames merge and concat are kind of the all-stars or superheroes they do all the heavy lifting and what i mean by that is merge can do everything and more than join and can cat can do everything and more than append so i will go over each of these methods however the focus will be on merge and concat so here we see i've already imported pandas as pd and i've created two data frames a couple things to note is that both data frames have an id column and a column four these have the same column names i do have a second column four down here that is commented out which i'll use as an example later on so first let's start with pd.merge so here i'm going to create a new data frame called inner and that's because by default merge does an inner join if that doesn't make sense to you don't worry we're going to cover that in just a moment so what i say is pd.merge df1 comma df2 those are the two data frames we want to merge on or combine side by side so let's look at that so here we see that a data frame was created that contains only rows that were shared by both data frames in the id and column four columns what merge is doing is it goes through the columns of both data frames and it's looking for any columns that have the same name in our example both data frames have id and call4 merge then looks for rows that have the same value between the two data frames in the matching columns looking at our example again we can see that row 0 has the same value in the id column in both data frames we then need to check if the values in row 0 column 4 match and we see that they do because the row values in the columns id and call 4 both matched in each data frame merge then takes these two rows and stitches them together and adds it to the new merged data frame this new merge data frame i'm going to call the returned data frame because it's what is being returned if we move down to the next row in data frame 2 we see that the id columns match with a value of 1 but the values in call 4 apple and orange do not match this means the criteria is not met and...