pandas error on linux, but working on windows

So, i ran my "ml" model on my local windows machine, everything runs smooth, it just takes 48 hour to fully run every process, naturally i ask the company more procesing power to cut times, they give me a linux simulation server to run my models, but for some reason pandas is giving me the next error:

    Traceback (most recent call last):
  File "/ANACONDATA/Prediccion_de_Fallas/03_Modelos_y_Scripts/testv14.py", line 894, in <module>
    dlist[xx][namer2] = np.where((dlist[xx].too_soon == 0),dlist[xx][column].shift(24) , 0)
  File "/opt/anaconda3/lib/python3.9/site-packages/pandas/core/frame.py", line 3643, in __setitem__
    self._setitem_array(key, value)
  File "/opt/anaconda3/lib/python3.9/site-packages/pandas/core/frame.py", line 3702, in _setitem_array
    self._iset_not_inplace(key, value)
  File "/opt/anaconda3/lib/python3.9/site-packages/pandas/core/frame.py", line 3721, in _iset_not_inplace
    raise ValueError("Columns must be same length as key")

this is the code where i fails (runs ok on windows), tried using pandas 1.3.5, and 1.4.2 same result

features=['AN_Utility_Supply_Press','AN_LPC_ASV_Position',
'AN_Eng_Brg_3Y_Gap',... 200 something list of features]
    
    
dlist = {}
turbo= np.unique(dfx2['SAP'])
for xx in (turbo):
    dlist[xx]=dfx2.loc[(dfx2['SAP'] == xx)]
    
for column in dlist[xx][features]:

                    namer2=[column+'_'+'Lag']
   fails here------>dlist[xx][namer2] = np.where((dlist[xx].too_soon == 0),dlist[xx][column].shift(24) , 0)
            #        namer3=[column+'_'+'Lchg'+"24"]
            #        dlist[xx][namer3] = np.where((dlist[xx].too_soon == 0),(dlist[xx][column]-dlist[xx][column].shift(24)) , 0)
                    namer4=[column+'_'+'mean']
                    dlist[xx][namer4] = np.where((dlist[xx].too_soon == 0),(dlist[xx][column].rolling(min_periods=1, window=feature_window).mean()),  dlist[xx][column])        
                    namer5=[column+'_'+'max']
                    dlist[xx][namer5] = np.where((dlist[xx].too_soon == 0),(dlist[xx][column].rolling(min_periods=1, window=feature_window).max()),  dlist[xx][column])         
                    
               
dfx2 = pd.concat(dlist)
dfx2.reset_index(drop=True)
dfx2=dfx2.droplevel(level=0)

am i missing something?, why this happens?