Python pandas: determining which "group" has the most entries
To sort by name: df.fruit.value_counts().sort_index()
To sort by counts: df.fruit.value_counts().sort_values()
Let's say that I have pandas DataFrame with a column called "fruit" that represents what fruit my classroom of kindergartners had for a morning snack. I have 20 students in my class. Breakdown would be something like this.
Oranges = 7, Grapes = 3, Blackberries = 4, Bananas = 6
I used sort to group each of these fruit types, but it is grouping based on alphabetical order. I would like it to group based on the largest quantity of entries for that class of fruit. In this case, I would like Oranges to turn up  first so that I can easily see that Oranges is the most popular fruit.
I'm thinking that sort is not the best way to go about this. I checked out groupby but could not figure out how to use that appropriately either.
Thanks in advance.