How to pass the value of previous row to the dataframe apply function?-CodePudding

I have the following pandas dataframe and would like to build a new column 'c' which is the summation of column 'b' value and column 'a' previous values. With shifting column 'a' it is possible to do so. However, I would like to know how I can pass the previous values of column 'a' in the apply() function.

l1 = [1,2,3,4,5]
l2 = [3,2,5,4,6]
df = pd.DataFrame(data=l1, columns=['a'])
df['b'] = l2
df['shifted'] = df['a'].shift(1)
df['c'] = df.apply(lambda row: row['shifted']  row['b'], axis=1)
print(df)

   a  b  shifted     c
0  1  3      NaN   NaN
1  2  2      1.0   3.0
2  3  5      2.0   7.0
3  4  4      3.0   7.0
4  5  6      4.0  10.0

I appreciate your help.

Edit: this is a dummy example. I need to use the apply function because I'm passing another function to it which uses previous rows of some columns and checks some condition.

CodePudding user response：

First let's make it clear that you do not need apply for this simple operation, so I'll consider it as a dummy example of a complex function.

Assuming non-duplicate indices, you can generate a shifted Series and reference it in apply using the name attribute:

s = df['a'].shift(1)

df['c'] =df.apply(lambda row: row['b'] s[row.name], axis=1)

output:

   a  b  shifted     c
0  1  3      NaN   NaN
1  2  2      1.0   3.0
2  3  5      2.0   7.0
3  4  4      3.0   7.0
4  5  6      4.0  10.0