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2. Calculate weighted average using a pandas/dataframe

   stackoverflow.com/questions/26205922

   First to calculate the "weighted average": In [11]: g = df.groupby('Date') In [12]: df.value / g.value.transform("sum") * df.wt Out[12]: 0 0.125000 1 0.250000 2 0.416667 3 0.277778 4 0.444444 dtype: float64 If you set this as a column, you can groupby over it: In [13]: df['wa'] = df.value / g.value.transform("sum") * df.wt

3. Weighted average in T-SQL (like Excel's SUMPRODUCT)

   stackoverflow.com/questions/1698408

   Calculate Weighted Average in SQL Server. 13. SQL Server: weighted average + GROUP BY. 3. TSQL Weighted ...

4. python - Weighted averaging a list - Stack Overflow

   stackoverflow.com/questions/29330792

   As a documented and tested function: def weighted_average(values, weights=None): """ Returns the weighted average of `values` with weights `weights` Returns the simple aritmhmetic average if `weights` is None.

5. groupby weighted average and sum in pandas dataframe

   stackoverflow.com/questions/31521027

   I need a sum of adjusted_lots , price which is weighted average , of price and adjusted_lots , grouped by all the other columns , ie. grouped by (contract, month , year and buys) Similar solution on R was achieved by following code, using dplyr, however unable to do the same in pandas.

6. sql - Calculate weighted average in single query - Stack Overflow

   stackoverflow.com/questions/26234311

   I'm trying to get the average rating for the above data. What it needs to be is the sum of rating * numReviews for each line divided by the total numReviews This is what I'm trying but it's giving incorrect result (49.07, should be 98.15):

7. how do I compute a weighted moving average using pandas

   stackoverflow.com/questions/9621362

   compute only the last exponential weighted moving average pandas 0 Custom function Weighted Moving Average using Pandas.DataFrame, for some reason the value drops to 0.0 after 26 iterations

8. Calculate weighted average with pandas dataframe

   stackoverflow.com/questions/33657809

   I have te following pandas dataframe: data_df = pd.DataFrame({'ind':['la','p','la','la','p','g','g','la'], 'dist':[10.,5.,7.,8.,7.,2.,5.,3.], 'diff'...

9. SQL Server: weighted average + GROUP BY - Stack Overflow

   stackoverflow.com/questions/42586178

   I am trying to calculate a weighted average in SQL Server. I'm aware that there are tons of questions out there addressing the problem, but I have the additional problem that I query a lot of other columns with a GROUP BY and aggregate functions like sum() and avg().

10. Calculating weighted average using grouped .agg in pandas

    stackoverflow.com/questions/61827881

    One solution has been posted here (pandas and groupby: how to calculate weighted averages within an agg, but it still doesn't seem very flexible because the weights column is hard coded in the lambda function definition. I'm looking to create a syntax closer to this:

11. Calculate Weighted Average in SQL Server - Stack Overflow

    stackoverflow.com/questions/41580172

    I am trying to calculate a weighted average based on the following calculations. I have a dataset that looks something like this: item | Date Sent | Date Received 1 | 2 Feb 10am | 3 Feb 10am 1 | 6 Feb 11am | 6 Feb 12pm 2 | 2 Feb 10am | 3 Feb 10am 2 | 6 Feb 11am | 6 Feb 12pm