I have not found a way to group_by() a column and have a struct field for the new column.Here is a snippet of the dataframe:

Census_Tract             GEOID_Census    table_B24012   value
    str                      str        str           f64
"Census Tract 9…    "04001942600"   "B24012_001E"   32179.0
"Census Tract 9…    "04001942700"   "B24012_001E"   33483.0
"Census Tract 9…    "04001944000"   "B24012_001E"   33114.0
"Census Tract 9…    "04001944100"   "B24012_001E"   26993.0
"Census Tract 9…    "04001944201"   "B24012_001E"   33798.0
…   …   …   …
"Census Tract 2…    "56043000200"   "B24012_073E"   -6.6667e8
"Census Tract 3…    "56043000301"   "B24012_073E"   -6.6667e8
"Census Tract 3…    "56043000302"   "B24012_073E"   -6.6667e8
"Census Tract 9…    "56045951100"   "B24012_073E"   41042.0
"Census Tract 9…    "56045951300"   "B24012_073E"   -6.6667e8

Essentially what I am trying to do is to group by Census_Tract and GEOID_Census. The columns table_B24012 and value should be combined into one column.

In other words I would like the data to be a struct object such that for each GEOID_Census I have one row value with potential a dictionary structure built into the new column. It would look something like this

Census_Tract             GEOID_Census    table_B24012   
    str                      str        str    
"Census Tract 9…    "04001942600"   {"B24012_001E": 32179.0, "B24012_002E":..., ...}
"Census Tract 9…    "04001942700"   {"B24012_001E"  33483.0, "B24012_002E":..., ...}
"Census Tract 9…    "04001944000"   {"B24012_001E"  33114.0, "B24012_002E":..., ...}
"Census Tract 9…    "04001944100"   {"B24012_001E"  26993.0, "B24012_002E":..., ...}
"Census Tract 9…    "04001944201"   {"B24012_001E"  33798.0, "B24012_002E":..., ...}

If there is a more efficient way to store it in the column, I am open to other ways. I am just trying to condense the information.

I have tried casting the two columns to a list and then struct, as well as just to a dictionary. Nothing has helped. Any ideas? Thanks in advance!