Python Dataframe Result Based On Values Of 2 Different Columns

Say I have the following dataframe. import pandas as pd df = pd.DataFrame() df['close'] = (7980,7996,8855,8363,8283,8303,8266,8582,8586,8179,8206,7854,8145,8152,8240,8373,8319,829

Solution 1:

you can use np.select after changing the '-' in outcome1 with the following available value by replace the - by nan and bfill.

s = df['outcome1'].replace('-', np.nan).bfill().astype(float)

conds = [df['A'].eq('TDOWN')&df['close'].gt(s),
         df['A'].eq('BUP')&df['close'].lt(s)]
choices = ['SELL','BUY']
df['B'] = np.select(conds, choices, '-')

print (df.head(20))
    close       A outcome1     B
0    7980   TDOWN        -     -
1    7996   TDOWN        -     -
2    8855   TDOWN        -  SELL
3    8363     TOP        -     -
4    8283     TOP        -     -
5    8303     TOP        -     -
6    8266     TOP        -     -
7    8582     TOP     8582     -
8    8586     BUP        -     -
9    8179     BUP        -     -
10   8206     BUP        -     -
11   7854     BUP        -   BUY
12   8145     BUP        -   BUY
13   8152  BOTTOM     8152     -
14   8240  BOTTOM        -     -
15   8373  BOTTOM        -     -
16   8319     BUP        -     -
17   8298     BUP        -     -
18   8048     BUP        -   BUY
19   8218     BUP        -     -