CODEWITHSUNDEEP
pythonpython-3.x
Gomelsar BARO
Gomelsar BARO

Reputation: 180

From Python dataframe to nested dictionary

I want to use an api and would need to put my dataframe in a dictionary format first. The dataframe df that looks like this:

    OrigC  OrigZ  OrigN Weigh  DestC   DestZ    DestN
0      PL     97    TP    59     DE      63       SN

Exepected output of the first row:

{"section":[
    {"location":
        {
        "zipCode":
            {"OrigC": "PL",
            "OrigZ":"97"},
        "location": {"id": "1"},
        "OrigN": "TP"
            },
    "carriageParameter":
        {"road":
            {"truckLoad": "Auto"}
        },
    "load":
        {"Weigh": "59",
        "unit": "ton",
        "showEmissionsAtResponse": "true"
        }
    },
    {"location":
        {
        "zipCode":
            {"DestC": "DE",
            "DestZ":"63"},
        "location": {"id": "2"},
        "DestN": "SN"
            },
    "carriageParameter":
        {"road":
            {"truckLoad":"Auto"}
        },
    "unload":
        {"WEIGHTTONS":"59",
        "unit": "ton",
        "showEmissionsAtResponse": "true"
        }
    }]}

Note that there is static information in the dictionary that doesn't require any change.

How can this be done in Python?

Upvotes: 1

Views: 47

Answers (1)

warped
warped

Reputation: 9481

You can use iterrows.

dic = {}
dic['section'] = []
for ix, row in df.iterrows():
    
    in_dict = {
        'location': {
            'zip_code': {
                'OrigC': row['OrigC'],
                'OrigZ': row['OrigZ'],
                },
            'location': {'id': ix+1}, # I am guessing here.
            'OrigN': 'TP',  
        },
        'CarriageParameter': {
            'road': {
                'truckLoad': 'Auto'}
            },
        'load': {
            'Weigh': str(row['Weigh']),
        } 
        }
    
    
    dic['section'].append(in_dict)

Note that this is not the entire entry, but I think it is clear enough to illustrate the idea.

Upvotes: 3

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