Conditional values for column in pandas

Question

i'm trying to do something like this:

d={'Month':['January','February','March','April'], 'Saves':[2000, 2100, 1900, 1500]}
saves=pd.DataFrame(data=d)

and turns like this:

    Month       Saves
0   January     2000
1   February    2100
2   March       1900
3   April       1500

What i would like is to create a new column 'Spent' with the logic: if the value of the last month is more ->"Yes", else -> 'No', like:

    Month       Saves    Spent
0   January     2000       -
1   February    2100      No
2   March       1900      Yes
3   April       1500      Yes

I have no idea how to do it, tried iterating in many ways, but it didn't work.

Thanks!

Answer 1

You can use shift to access the next column

saves['Spent'] = np.where(saves['Saves'] < saves['Saves'].shift(), 'Yes', 'No')


    Month       Saves   Spent
0   January     2000    No
1   February    2100    No
2   March       1900    Yes
3   April       1500    Yes

Answer 2

Notice , here the first row need to be treated differently

saves.at[1:,'Spent']=saves.Saves.diff().gt(0).map({True:'No',False:'Yes'}).iloc[1:]
saves
Out[190]: 
      Month  Saves Spent
0   January   2000   NaN
1  February   2100    No
2     March   1900   Yes
3     April   1500   Yes
saves.fillna('')
Out[191]: 
      Month  Saves Spent
0   January   2000      
1  February   2100    No
2     March   1900   Yes
3     April   1500   Yes