Add values from pandas dataframe to a list

From your expected result I see that:

• The first bin contains elements in the range [0.4 - 0.8].
• The next bin starts from 3.0.

So you:

• Don't want one-side-open bins (the first bin is closed at both sides).
• Want neither "ëmpty bins" nor "adjacent ranges" (e.g. [0.4 - 0.8), then [0.8 - 1.2) and so on.

You want rather something like this:

• Set the üpper limit to the lowest element in the source list + 0.4.
• Put in the first "bin" elements <= limit (append this list to averages).
• Drop these elements from the list.
• Repeat the above procedure while the list is not empty.

I also assume that the result should be a plain Python list of lists.

To get this result, try the following code:

averages = []
src = df['GPA_year1'].sort_values()
while not src.empty:
    limit = src.min() + 0.4
    currBin = src[src <= limit]
    averages.append(currBin.to_list())
    src.drop(currBin.index, inplace=True)

This code should run quicker, beacause:

• Due to sort_values() there is no need for the inner loop.
• All values for the current bin are selected in a single instruction.
• Dropping of "used" values is performed also in a single instruction.

For GPA_year1 column from your DataFrame this code generates:

[[0.74], [1.95, 2.18, 2.34], [3.23, 3.23, 3.44, 3.49], [3.64, 3.78, 3.82]]

One more remark concerning your code:

averages = [[] for w in range(len(df['GPA_year1'])//4)]

looks strange. How do you know that the output list will contain just 4 lists? Accidentally this is the case for your sample data, but consider such case that:

• One part of values will be "very bad" (all around some lower limit).
• The second part of values will be "very good" (all around some upper limit).

Then the number of "bins" will be just 2 (not 4).

This is my way: assuming df is your Dataframe:

GPA_year1 = df['GPA_year1'].tolist()
GPA_year1 = [3.82, 3.64, 1.95, 3.44, 2.18, 3.49, 3.78, 3.23, 0.74, 3.23, 0.74, 3.23, 2.34]

Sort the list:

GPA_year1.sort()

initialize the averages list with the first element

averages = [[GPA_year1[0]]]

loop trough your list:

for x, y in zip(GPA_year1, GPA_year1[1:]):
    if y - x <= 0.4:
        averages[-1].append(y)
    else:
        averages.append([y]) #if not create a new sublist
print(averages)
# [[0.74, 0.74], [1.95, 2.18, 2.34], [3.23, 3.23, 3.23, 3.44, 3.49, 3.64, 3.78, 3.82]]