I would like to vectorize this piece of python code with for loop conditioned on current state for speed and efficiency.
values for df_B are computed based on current-state (state
) AND corresponding df_A value.
Any ideas would be appreciated.
import pandas as pd df_A = pd.DataFrame({'a': [0, 1, -1, -1, 1, -1, 0, 0] ,}) df_B = pd.DataFrame( data=0, index=df_A.index, columns=['b']) print(df_A) state = 0 for index, iter in df_A.iterrows(): if df_A.loc[index ,'a'] == -1: df_B.loc[index ,'b'] = -10 -state elif df_A.loc[index, 'a'] == 1: df_B.loc[index, 'b'] = 10 - state elif df_A.loc[index, 'a'] == 0: df_B.loc[index, 'b'] = 0 - state temp_state = state state += df_B.loc[index, 'b'] print(df_B)
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Answer
This seems overkill. Your state
variable basically is the previous value in df_A['a']*10
. So we can just use shift
:
s = df_A['a'].mul(10) df_B['b'] = s - s.shift(fill_value=0)