Storing a dictionary within a pandas dataframe cell-CodePudding

I am trying to record changes I make to a dataframe and I am looking for the best way to add a dictionary to a cell for later use:

Example code:

trade_information = {'Jim' : ['1','2'], 'Matt' : ['3','4']}
current_time = datetime.datetime.now(pytz.timezone('Australia/Sydney')) 
transaction_details =  pd.DataFrame({'Transaction_Number': 1 , 'Transaction_DateTime': current_time, 'Transaction_Type': 'Trade', 'Transaction_Details': trade_information }) 

transaction_details

gives me:

But my desired result id:

    Transaction_Number   Transaction_DateTime       Transaction_Type    Transaction_Details
           1    2022-01-18 23:06:41.335809 11:00    Trade               {Jim:[1, 2], Matt: [3,4]}

I'm not sure if this is possible or not. The use case is that i need this information to restore transactions on the original dataframe (by accessing the dictionary within Transaction_Details).

Any help would be much appreciated! Thanks!

CodePudding user response：

Use one elemenet list for store dict:

trade_information = {'Jim' : ['1','2'], 'Matt' : ['3','4']}
current_time = datetime.datetime.now(pytz.timezone('Australia/Sydney')) 
transaction_details =  pd.DataFrame({'Transaction_Number': 1 ,
                                     'Transaction_DateTime': current_time, 
                                     'Transaction_Type': 'Trade', 
                                     'Transaction_Details': [trade_information] }) 
print (transaction_details)
   Transaction_Number             Transaction_DateTime Transaction_Type  \
0                   1 2022-01-18 23:15:20.970362 11:00            Trade   

                       Transaction_Details  
0  {'Jim': ['1', '2'], 'Matt': ['3', '4']}

For unpack is possible use Series.str.get:

print (transaction_details['Transaction_Details'].str.get('Jim'))
0    [1, 2]
Name: Transaction_Details, dtype: object