Python sum() error for converting SQL query to Pandas-CodePudding

I am trying to convert a SQL query to equivalent python pandas. My data for SQL is

x=(2.2,2.2,2.2,2.2,2.2)
y=(3.3,3.3,3.3,3.3,3.3)
z=(4.4,4.4,4.4,4.4,4.4)
r=(5.5,5.5,5.5,5.5,5.5)
t=(6.6,6.6,6.6,6.6,6.6)

and the SQL query is:

select sum(sum(x),sum(y),sum(z),
            sum(r),sum(t)) into :m
        from _fx_ght;

I have created Python code to convert the SQL query into pandas:

 x=(2.2,2.2,2.2,2.2,2.2)
    y=(3.3,3.3,3.3,3.3,3.3)
    z=(4.4,4.4,4.4,4.4,4.4)
    r=(5.5,5.5,5.5,5.5,5.5)
    t=(6.6,6.6,6.6,6.6,6.6)

m=sum(sum(x),sum(y),sum(z),sum(r),sum(t))

print(m)

While executing the code I am getting an error which shows:

Traceback (most recent call last):
  File "./prog.py", line 9, in <module>
TypeError: sum() takes at most 2 arguments (5 given)

How can I covert this to the equivalent pandas?

CodePudding user response：

if i understand your question you want to get total sum of each sum x,y,z,r,t?
if yes then

m=sum((sum(x),sum(y),sum(z),sum(r),sum(t)))

CodePudding user response：

Try:

m=sum([sum(x),sum(y),sum(z),sum(r),sum(t)])

sum() iterates all elements in list and sum.

CodePudding user response：

hmm sum does not work like that you have to put the individual sums into another array so for example try:

sum_tot = None
sum_arr_list = [x,y,z,r,t]

def sum_arr(array):
  return sum(array)
for item in sum_arr_list:
  sum_tot  = sum_arr(item)
m = sum_tot

There are better ways to do this Or Like below put it in a tuple within sum

m = sum((sum(x), ..))

CodePudding user response：

Here is the equvalent pandas

import pandas as pd

df=pd.DataFrame({"x":[2.2,2.2,2.2,2.2,2.2],
                    "y":[3.3,3.3,3.3,3.3,3.3],
                    "z":[4.4,4.4,4.4,4.4,4.4],
                    "r":[5.5,5.5,5.5,5.5,5.5],
                    "t":[6.6,6.6,6.6,6.6,6.6]})


m=df.sum().sum()