How to create a Lower and Upper bound column for Pandas Dataframe-CodePudding

enter code hereCurrently the pandas dataframe in one column is set up as

Allocation
8100 
8195
8195
8815

Trying to create a lower and upper bound column where it looks like down below. There is thousands of rows for this and I am not sure how to create this at scale using pandas.

Lower Bound   Upper Bound
8100                8195
8195                8815

CodePudding user response：

This should work if you need to alternate rows between upper and lower bound.

(df.set_index(list(divmod(np.arange(df.shape[0]),2)))
.squeeze()
.unstack()
.rename({0:'Lower Bound',1:'Upper Bound'},axis=1))

Output:

   Lower Bound  Upper Bound
0         8100         8195
1         8195         8815

CodePudding user response：

It's not very clear, but it looks like you want your data structured like so:

out = pd.DataFrame(df.to_numpy().reshape(2, len(df)//2), columns=['Lower_Bound', 'Upper_Bound'])

Output:

   Lower_Bound  Upper_Bound
0         8100         8195
1         8195         8815