[FIXED] convert diction with single values to dataframe

Issue

let us suppose we have following code :

import numpy as np
import pandas as pd
from sklearn.linear_model import LinearRegression,Ridge,Lasso,ElasticNet
from sklearn.neighbors import KNeighborsRegressor
from sklearn.tree import DecisionTreeRegressor
from sklearn.svm import SVR
from sklearn.datasets import make_regression
from sklearn.model_selection import train_test_split
X,y =make_regression(n_samples=2000,n_features=20,n_informative =7,noise=3.1,random_state=1)
X_train,X_test,y_train,y_test =train_test_split(X,y,test_size=0.3,random_state=1)
algo_list =[('linear_Regression',LinearRegression()),('Ridge',Ridge()),('Lasso',ElasticNet()),('KNN',KNeighborsRegressor()),('CART',DecisionTreeRegressor()),('SVR',SVR())]
algo_results ={}
for name,model in algo_list:
  model.fit(X_train,y_train)
  algo_results[name] =model.score(X_test,y_test)
print(algo_results)

result of this algorithm is :

{'linear_Regression': 0.999615308811996, 'Ridge': 0.9996150421204321, 'Lasso': 0.8758019197852375, 'KNN': 0.6274472685707742, 'CART': 0.46164502153497877, 'SVR': 0.17305435111869027}

i would like to convert this dictionary to dataframe, here is my code :

algo_dataframe =pd.DataFrame.from_dict(algo_results)
print(algo_dataframe.head())

but there is error :

ValueError: If using all scalar values, you must pass an index

maybe because it contains single values?how can i fix it?

Solution

algo_dataframe =pd.DataFrame(algo_results, index =[0])

Or put your dict in a list

algo_results =[{'linear_Regression': 0.999615308811996, 'Ridge': 0.9996150421204321, 'Lasso': 0.8758019197852375, 'KNN': 0.6274472685707742, 'CART': 0.46164502153497877, 'SVR': 0.17305435111869027}]
algo_dataframe =pd.DataFrame(algo_results)

Answered By - LazyClown