[FIXED] pandas concat dataframe by converting all columns to json

Issue

I have a pandas dataframe like this

import pandas as pd                                                                         
technologies = [                                                                            
            ("Spark", 22000,'30days',1000.0),                                               
            ("PySpark",25000,'50days',2300.0),                                              
            ("Hadoop",23000,'55days',1500.0)                                                
            ]                                                                               
df = pd.DataFrame(technologies,columns = ['Courses','Fee','Duration','Discount'])           
print(df) 

   Courses    Fee Duration  Discount
0    Spark  22000   30days    1000.0
1  PySpark  25000   50days    2300.0
2   Hadoop  23000   55days    1500.0

I want the output to be converted to the following.

Courses    Fee Duration  Discount       json
  Spark  22000   30days    1000.0       {"Courses":"Spark","Fee":22000,"Duration":"30days","Discount":1000.0}
PySpark  25000   50days    2300.0       {"Courses":"PySpark","Fee":25000,"Duration":"50days","Discount":2300.0}
 Hadoop  23000   55days    1500.0       {"Courses":"Hadoop","Fee":23000,"Duration":"55days","Discount":1500.0}
                                                                              

Solution

You can apply a lambda function to create the new json column

import json
import pandas as pd

df['json'] = df.apply(lambda row: json.dumps(dict(row)), axis=1)

Alternatively, if you want to get the entire DataFrame as a list of dicts you may use

df.to_dict(orient='records')

PS: wrap your lambda operation with json.dumps() as necessary (depending on if you want the output as dict or JSON)

Answered By - Sanidhya Singh