{
    1.3: {1: 10, 2: 1, 3: None, 4: 10},
    5.0: {1: None, 2: None, 3: None, 4: None},
    7.0: {1: 10, 2: 1, 3: None, 4: 10},
    7.1: {1: 100, 2: 10, 3: None, 4: 20},
    10.3: {1: 100, 2: 10, 3: None, 4: 20},
    10.4: {1: 103, 2: 20, 3: None, 4: 30},
    5000: {1: 5.0, 2: 7.8, 3: 10.4, 4: 7.5}
}

#Create a list of final prices
outcome = []
for prices, hours in df.items():
    if prices == 5000:
        for i in hours:
            outcome.append(df.get(hours[i]))
print("outcome:", outcome)
Out: outcome: [5.0, 7.8, 10.4, 10.4, 10.4, 10.4, 10.4, 7.5]

#Remove the nested Dict where key = 5000
def removekey(d, key):
    r = dict(d)
    del r[key]
    return r
d1 = removekey(d, 5000)

#Loop through the list With price outcomes, and find out where this coincides with a bid step by sorting the keys
for price in range(len(outcome)):
    for key in sorted(d1.keys()):
        if outcome[price] == key:
            print(key)
Out:
5.0
10.4