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.