compare previous and present hash key values from a Pandas dataFrame

Question

I would like to compare the a previous and present dictionary keys values from a pandas DataFrame. I have something like this:

MyFrame= pd.DataFrame({"A":[6,4,7,10], "B":[8,10,90,100]})

for k,v in MyFrame.iteritems():

  for k1,v1 in MyFrame[k].iteritems():
        if MyFrame[k1+1]-MyFrame[k1]> 5: print("The threshold has been exceeded")

I would like to compare 4 with 6, 7 with 4 and so one from the column "A". Same with column "B". Any help will be appreciated

Answer 1

It's unclear what you're attempting but you can compare the entire Series or df by calling shift:

In [169]:
MyFrame['A'].shift()

Out[169]:
0   NaN
1     6
2     4
3     7
Name: A, dtype: float64

In [168]:
MyFrame.shift()

Out[168]:
    A   B
0 NaN NaN
1   6   8
2   4  10
3   7  90