How to plot a dictionary that I want to sort by values?

Question

I have the following dictionary, model_dict:

zip_iterator = zip(classifier_names, model_scores) 
model_dict = dict(zip_iterator)

model_dict

{'AdaBoostClassifier()': 0.8101063257934118,
 'DecisionTreeClassifier()': 0.7317264413290904,
 'GradientBoostingClassifier()': 0.8080247842665061,
 'KNeighborsClassifier()': 0.7572879934634902,
 'RandomForestClassifier()': 0.7962904231530059,
 'SVC()': 0.8025361228175797}

How can I plot this dictionary showing the algorithm on the x-axis and the score on the y-axis going from lowest to highest according to the score and having x-ticks as the corresponding algorithm?

The outlook should look something like this, but having the algorithms sorted from lowest to highest:

I use the following very simple code to create the plot:

plt.plot(classifier_names, model_scores)
plt.xlabel('Classifier Algorithms')
plt.xticks(classifier_names, rotation=45) 
plt.ylabel('Cross-Validated Accuracy')

Answer 1

To sort in descending order (largest first):

sorted_dict_descending = dict(sorted(model_dict.items(),key=lambda x:x[1], reverse=True))

To sort in ascending order (smallest first):

sorted_dict_ascending = dict(sorted(model_dict.items(),key=lambda x:x[1]))

I seem to be unable to mark as a duplicate, but another answer can be found here. With the one-liner comprehension for descending order (largest first):

sorted_dict = {k: v for k, v in sorted(model_dict.items(), key=lambda item: item[1], reverse=True)}

and with the one-liner comprehension for ascending order (smallest first):

sorted_dict = {k: v for k, v in sorted(model_dict.items(), key=lambda item: item[1])}