Construct pandas DataFrame from list of tuples of (row,col,values)

Question

I have a list of tuples like

data = [
(\'r1\', \'c1\', avg11, stdev11),
(\'r1\', \'c2\', avg12, stdev12),
(\'r2\', \'c1\', avg21, stdev21),
(\'r2\', \'c2\',          


        

Answer 1

I submit that it is better to leave your data stacked as it is:

df = pandas.DataFrame(data, columns=['R_Number', 'C_Number', 'Avg', 'Std'])

# Possibly also this if these can always be the indexes:
# df = df.set_index(['R_Number', 'C_Number'])

Then it's a bit more intuitive to say

df.set_index(['R_Number', 'C_Number']).Avg.unstack(level=1)

This way it is implicit that you're seeking to reshape the averages, or the standard deviations. Whereas, just using pivot, it's purely based on column convention as to what semantic entity it is that you are reshaping.