Styjun

My dataframe looks like this:

 mid price dse_high_born
0 0.002039 False
1 0.002039 False
2 0.002039 False
3 0.002039 False
4 0.002039 False
5 0.002038 False
6 0.002039 True
7 0.002037 False
8 0.002037 False
9 0.002037 False
10 0.002036 False
11 0.002036 False
12 0.002038 False
13 0.002038 False
14 0.002038 False
15 0.002038 False
16 0.002039 False
17 0.002039 False
18 0.002040 False
19 0.002040 False
20 0.002040 False
21 0.002039 False
22 0.002039 False
23 0.002039 False
24 0.002040 True
25 0.002040 False
26 0.002041 False
27 0.002041 False
28 0.002041 False
29 0.002042 False
30 0.002044 False
31 0.002049 True
32 0.002049 False
33 0.002048 False

... ...

I tried to use a for loop to add a new column price based on a condition as followed:

for index, row in df.iterrows():
 if df['dse_high_born'] == True:
 df.at[index,'price'] = row['mid price']
 else:
 df.at[index,'price'] = 'nan'

I received the following error: The truth value of a Series is ambiguous. Use a.empty, a.bool(), a.item(), a.any() or a.all().

I tried every combination (with bool(), any(), item(), etc) but when I do the following request df[df['price'] != 'nan'] there is nothing in my dataframe with this condition, any idea why? thanks!

This can be done in a much more simple and efficient way using np.where:

import numpy as np
df['price'] = np.where(df.dse_high_born, df.mid_price, np.nan)

 mid_price dse_high_born price
0 0.002 False NaN
1 0.002 False NaN
2 0.002 False NaN
3 0.002 False NaN
4 0.002 False NaN
5 0.002 False NaN
6 0.002 True 0.002
7 0.002 False NaN
...

The problem with your code, is that in the if statement, when checking the condition df['dse_high_born'] == True:, you are not indexing on a particular row, but on the entire colum. You need to index both on row and column using .loc, df.loc[index,'dse_high_born']. So you want something like:

for index, row in df.iterrows():
 if df.loc[index,'dse_high_born'] == True:
 df.loc[index,'price'] = df.loc[index,'mid_price']
 else:
 df.loc[index,'price'] = np.nan

The error is refering to df['dse_high_born'] == True. I think it should be replaced by row like this?

for index, row in df.iterrows():
if row['dse_high_born'] == True:
 df.at[index,'price'] = row['mid price']
else:
 df.at[index,'price'] = 'nan'