I want to create a column of (downstream value*1 + middlestream value*2 + upstream value*3)/ 3 from this data
The error unsupported operation type(s) for /: 'list' and 'int' continues to appear
//result1 = ta1_sample["downstream"*1 + "middlestream"*2 + "upstream"*3]/3]
Isn't this how you make the code? In the first file, the type is object, so I changed all of those numerical values to int32. But I don't know why I keep getting errors.
And I thought I should calculate it with a column value, so I calculated it after changing the matrix using transpose() from the existing data.
Can we still create columns or rows calculated as above?
pandas dataframe
You have to do it like the bottom.
>> df = pd.dataFrame(np.random.randint(100, 1000, size=(5,3)), columns=["downstream", "upstream", "upstream", index=[f"{year}"2006, 2006+year"inward]
>>> df
downstream and upstream
2006 819 530735
2007 712 319820
2008 932 892 630
In 2009, 53711939
2010 913 400 218
>>> result = (df["downstream"]*1 + df["middlestream"]*2 + df["downstream"]*3)/3
>>> result
2006 1361.333333
2007 1270.000000
In 2008, 1535.33333
2009: 1592.000000
2010 789.000000
dtype: float64
It seems more cumbersome to calculate with a transparent data frame. Calculate it in its original form, and transform it when necessary.
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