Create a json file based on data of the two given column in a csv which needs to be mapped together in python [closed]

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Column_A	Column_B
Ram	Menu
Ram	Radha
Shyam	Rishi
Rishi	Ram
Rishi	Ram
Menu	Ram

SO i have a csv like this now what i have to i get a json which looks like this. Keys: these are the unique value of each of the entires in the csv columns except the columns headers. pairs: just like it suggests if Ram pairs with menu and Ram also pairs with Radha them "Ram" : ["Meenu","Radha"]

{
    "keys": {
        "Ram" :1,
        "Shyam" :2,
        "Rishi": 3,
        "Menu": 4,
        "Radha": 5,
        "Shyam": 6
        },
    "pairs": {
        "1" : [4,5],
        "2" : [3],
        "3" : [1],
        "4" : [1],
        "5" : []
        }
}

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I agree with some of the comments that the question could have been framed a little more clearly, but I think I may have been able to interpret what you were looking for based on your input and output.

See if this does what you are looking for.

import pandas as pd
import json

df = pd.DataFrame([
    {"Column_A":"Ram", "Column_B":"Menu"},
    {"Column_A":"Ram", "Column_B":"Radha"},
    {"Column_A":"Shyam", "Column_B":"Rishi"},
    {"Column_A":"Rishi", "Column_B":"Ram"},
    {"Column_A":"Rishi", "Column_B":"Ram"},
    {"Column_A":"Menu", "Column_B":"Ram"},
])

a = pd.concat([df["Column_A"], df["Column_B"]]).unique()
keys = {v:i+1 for (i,v) in enumerate(a)}
pairs = df.replace(keys).groupby("Column_A").apply(lambda df: [int(v) for v in list(set(df["Column_B"].values))]).to_dict()

result = {
    "keys":keys,
    "pairs":pairs
}

print(json.dumps(result))

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Output:

{"keys": {"Ram": 1, "Shyam": 2, "Rishi": 3, "Menu": 4, "Radha": 5}, "pairs": {"1": [4, 5], "2": [3], "3": [1], "4": [1]}}

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If, as in the comments, you are looking to create your DataFrame from a string variable, you can include something like this:

from os import StringIO
pd.read_csv(StringIO("A,B,C\n1,2,3\n4,5,6"))