I have these columns in my dataframe:
I need to find average of all the [Count] values where Day is 1
or 2
and so on.
I've tried that by using key dictionary:
col_dict = dict(zip(df6.Day, df6.Count))
k=2 # Enter Day
#print(k)
for keys in col_dict.keys():
if keys == k:
for i in col_dict:
a=col_dict[keys] where col_dict==k
But I think this code is not correct.
Pandas has purpose-built methods for grouping and aggregating data. Here you can use groupby
+ mean
:
res = df6.groupby('Day')['Count'].mean()
There is no need for dictionary conversion or explicit iteration when vectorised operations are available. If you need a dictionary result, you can convert in a separate step:
res_dict = res.to_dict()
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