I have 30 items in each group.
To find mean of entire items, I use this code.
y = df[["Value", "Date"]].groupby("Date").mean()
That returns a value like this.
Date Value
2020-01-01 00:30:00 7172.36
2020-01-01 01:00:00 7171.55
2020-01-01 01:30:00 7205.90
2020-01-01 02:00:00 7210.24
2020-01-01 02:30:00 7221.50
However, I would like to find the mean of the first 10 items in the group instead of the entire items.
y1 = df[["Value", "Date"]].groupby("Date").head(10).mean()
That code return only a single Value instead of a pandas series.
So I’m getting errors like this.
AttributeError: 'numpy.float64' object has no attribute 'shift'
What is the proper way to get the pandas series instead of a single value?
>Solution :
You can try
y1 = df[["Value", "Date"]].groupby("Date").apply(lambda g: g['Value'].head(10).mean())
print(y1)
Date
2020-01-01 00:30:00 7172.36
2020-01-01 01:00:00 7171.55
2020-01-01 01:30:00 7205.90
2020-01-01 02:00:00 7210.24
2020-01-01 02:30:00 7221.50
dtype: float64
In .groupby("Date").head(10).mean(), groupby.head() returns the DataFrame, .mean() is operated on the whole DataFrame rather than the group.