Trying to compare to values in a pandas dataframe for max value

I’ve got a pandas dataframe, and I’m trying to fill a new column in the dataframe, which takes the maximum value of two values situated in another column of the dataframe, iteratively. I’m trying to build a loop to do this, and save time with computation as I realise I could probably do it with more lines of code.

for x in ((jac_input.index)):
    jac_output['Max Load'][x] = jac_input[['load'][x],['load'][x+1]].max()

However, I keep getting this error during the comparison

IndexError: list index out of range

Any ideas as to where I’m going wrong here? Any help would be appreciated!

>Solution :

Many things are wrong with your current code.

When you do ['abc'][x], x can only take the value 0 and this will return 'abc' as you are slicing a list. Not at all what you expect it to do (I imagine, slicing the Series).

For your code to be valid, you should do something like:

jac_input = pd.DataFrame({'load': [1,0,3,2,5,4]})
for x in jac_input.index:
    print(jac_input['load'].loc[x:x+1].max())

output:

1
3
3
5
5
4

Also, when assigning, if you use jac_output['Max Load'][x] = ... you will likely encounter a SettingWithCopyWarning. You should rather use loc: jac_outputLoc[x, 'Max Load'] = .

But you do not need all that, use vectorial code instead!

You can perform rolling on the reversed dataframe:

jac_output['Max Load'] = jac_input['load'][::-1].rolling(2, min_periods=1).max()[::-1]

Or using concat:

jac_output['Max Load'] = pd.concat([jac_input['load'], jac_input['load'].shift(-1)], axis=1).max(1)

output (without assignment):

0    1.0
1    3.0
2    3.0
3    5.0
4    5.0
5    4.0
dtype: float64