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If I understand the problem correctly, you want to fill all missing values in the Fare column by the median value of the Fare column where Pclass=3. This can be achieved by putting the extra row filter test['Pclass']=3 on median of the fare column, see below. test['Fare'] = test['Fare'].fillna(test.loc[test['Pclass']=3,'Fare'].median())


You would expect that to be the case, however, by default seaborn.pointplot uses the average estimator to calculate the number for each hour. So the numbers you are seeing on the y-axis is the average number of bikes shared for each hour. Since the number of bikes shared is not equal for category workingday=0 and workingday=1 the two averages for those ...

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