Python : Replace two for loops with the fastest way to sum the elements-CodePudding

I have list of 5 elements which could be 50000, now I want to sum all the combinations from the same list and create a dataframe from the results, so I am writing following code,

x =list(range(1,5))
t=[]
for i in x:
    for j in x:
        t.append((i,j,i j))


df=pd.Dataframe(t)

The above code is generating the correct results but taking so long to execute when I have more elements in the list. Looking for the fastest way to do the same thing

CodePudding user response：

Combinations can be obtained through the pandas.merge() method without using explicit loops

x = np.arange(1, 5 1)
df = pd.DataFrame(x, columns=['x']).merge(pd.Series(x, name='y'), how='cross')
df['sum'] = df.x.add(df.y)
print(df)

    x  y  sum
0   1  1    2
1   1  2    3
2   1  3    4
3   1  4    5
4   1  5    6
5   2  1    3
6   2  2    4
...

CodePudding user response：

List Comprehension can make it faster. So, you can use t=[(i,j,i j) for i in x for j in x] instead of for loop, as the traditional for loop is slower than list comprehensions, and nested loop is even slower. Here's the updated code in replacement of nested loops.

x =list(range(1,5))
t=[(i,j,i j) for i in x for j in x]

df=pd.Dataframe(t)