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I have a pandas dataframe in the following format:
user percent
x 0.2
x 0.5
x 0.8
y 0.1
y 0.6
y 0.2
y 0.6
I am trying to multiply the percents in the rows for each user.
In the example, the result for x will be 0.2*0.5*0.8 = 0.08
The dataframe should therefore look like that:
user result
x 0.08
y 0.0072
How to get my expected output?
225
Use count() by Column Name Use pandas DataFrame. groupby() to group the rows by column and use count() method to get the count for each group by ignoring None and Nan values. It works with non-floating type data as well.
DataFrame. multiply() Method. This method is used to multiply two dataframe columns, we need to define the column which has to be multiplied inside square brackets with our dataframe like df[col], and then multiply() method will take another column with whom we want to multiply.
First of all, create a data frame with multiple rows and a data frame with single row. Then, use mapply function to multiply row values in the data frame having multiple rows with single row data frame.
groupby + prod.
df.groupby('user', as_index=False).prod()
user percent
0 x 0.0800
1 y 0.0072
Or, using apply + np.prod -
df.groupby('user', as_index=False).apply(np.prod)
user percent
0 x 0.0800
1 y 0.0072
cumprod + iloc[-1]
df.groupby('user').percent.apply(lambda x : x.cumprod().iloc[-1])
Out[532]:
user
x 0.0800
y 0.0072
Name: percent, dtype: float64
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