Normalize the values of nested dictionary into [0,1]

Input dictionary

d = {'PQR':{"LMN":1.345,'PST':1.278,'BQR':2.345,'RMT':9.867},

Is there any way to normalize the nested dictionary values in the range [0,1] using this formula

(value - min(x))/(max(x)- min(x))

However, for normalization, min and max values should find in every inner dictionary. Expected Output

output = {'PQR':{"LMN":0.0078006752823378675,'PST':0.0,'BQR':0.12422866457096288,'RMT':1.0},

1 answer

  • answered 2022-05-04 11:07 Kris

    You can loop the inner dicts and mutate them accordingly. An example approach below:

    d = {'PQR': {"LMN": 1.345, 'PST': 1.278, 'BQR': 2.345, 'LMN': 9.867},
         'HGE': {'VRM': 1.765, 'TRM': 1.567, 'FRM': 1.456, 'DRM': 1.678}}
    # Find the normalized value
    fn = lambda value, x_max, x_min: (value - x_min) / (x_max - x_min)
    # In each inner dict
    for _d in d.values():
        # find min and max values
        max_x = max(_d.values())
        min_x = min(_d.values())
        # normalize each value in the dict
        for k, v in _d.items():
            _d[k] = fn(v, max_x, min_x)

    Gives you an output like below:

    {'PQR': {'LMN': 1.0, 'PST': 0.0, 'BQR': 0.12422866457096288}, 'HGE': {'VRM': 1.0, 'TRM': 0.3592233009708738, 'FRM': 0.0, 'DRM': 0.7184466019417476}}

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