I have a pandas dataframe like below
import pandas as pd
data = [[5, 10], [4, 20], [15, 30], [20, 15], [12, 14], [5, 5]]
df = pd.DataFrame(data, columns=['x', 'y'])
I am trying to attain the value of this expression.
I havnt got an idea how to mutiply first value in a column with 2nd value in another column like in the expression.
Try pd.DataFrame.shift() but I think you need to enter -1 into shift judging by the summation notation you posted. i + 1 implies using the next x or y, so shift needs to use a negative integer to shift 1 number ahead. Positive integers in shift go backwards.
Can you confirm 320 is the right answer?
0.5 * ((df.x * df.y.shift(-1)) - (df.x.shift(-1) + df.y)).sum()
>>>320
I think the below code has the correct value in expresion_end
import pandas as pd
data = [[5, 10], [4, 20], [15, 30], [20, 15], [12, 14], [5, 5]]
df = pd.DataFrame(data, columns=['x', 'y'])
df["x+1"]=df["x"].shift(periods=-1)
df["y+1"]=df["y"].shift(periods=-1)
df["exp"]=df["x"]*df["y+1"]-df["x+1"]*df["y"]
expresion_end=0.5*df["exp"].sum()
You can use pandas.DataFrame.shift(). You can one times compute shift(-1) and use it for 'x' and 'y'.
>>> df_tmp = df.shift(-1)
>>> (df['x']*df_tmp['y'] - df_tmp['x']*df['y']).sum() * 0.5
-202.5
# Explanation
>>> df[['x+1', 'y+1']] = df.shift(-1)
>>> df
x y x+1 y+1
0 5 10 4.0 20.0 # x*(y+1) - y*(x+1) = 5*20 - 10*4
1 4 20 15.0 30.0
2 15 30 20.0 15.0
3 20 15 12.0 14.0
4 12 14 5.0 5.0
5 5 5 NaN NaN
320. you can check @Atanas Atanasov's answer too.