Pandas Groupby / List to Multiple Rows

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IIUC, I think you can do it like this:

dfg = df.groupby(['AccountID', 'Last Name', df.groupby(['AccountID', 'Last Name']).cumcount() + 1]).first().unstack()
dfg.columns = [f'{i}{j}' for i, j in dfg.columns]
df_out = dfg.sort_index(axis=1, key=lambda x: x.str[-1])
df_out.reset_index()

Output:

   AccountID Last Name  Contract1 First Name1                Address1       City1 State1  Contract2 First Name2            Address2         City2 State2  Contract3 First Name3            Address3            City3 State3
0       1234      Pitt      622.0        Brad             466 7th Ave  Park Slope     NY    28974.0        Brad    1901 Vine Street  Philadelphia     PA        NaN         NaN                 NaN              NaN    NaN
1       2345    Rhodes      622.0       Dusty  1 Public Library Plaze    Stamford     CT    28974.0       Dusty  1001 Kings Highway   Cherry Hill     NJ    54122.0       Dusty  444 Amsterdamn Ave  Upper West Side     NY
2       4321      Ford    54122.0       Henry             93 Booth Dr      Nutley     NJ        NaN         NaN                 NaN           NaN    NaN        NaN         NaN                 NaN              NaN    NaN

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