Value error array with 0 features in linear regression scikit

Question

My input and output data are written in an 6xn row-column excel file,thatI read them using pandas

using this code :

from sklearn import linear_model
import os
import pandas as pd
import numpy as np
import openpyxl as pyx
import numpy as np
import matplotlib.pyplot as plt

path = r"E:\"
os.chdir( path )

data1 = pd.read_excel("input.xlsx", header=None,index=False)
data2 = pd.read_excel("target.xlsx", header=None,index=False)

# print df.head()

le= 20;lg=len(data1)
x_train=[];x_t=[];y_train=[];y_t=[];x_test=[];x_ts=[];y_test=[];y_ts=[];
for i in range(le):    
    x_t = data1.iloc[i,:]
    x_train.append(x_t)
    y_t = data2.iloc[i,:]
    y_train.append(y_t)
    if i > le :
        x_ts = data1.iloc[lg-i,:]
        x_test.append(x_ts)
        y_ts = data2.iloc[lg-i,:]
        y_test.append(y_ts)



ols = linear_model.LinearRegression()
model = ols.fit(x_train, y_train)

print (model.predict(x_test)[0:5]) 

I get this error :

File "C:\ProgramData\Anaconda3\lib\site-packages\spyder\utils\site\sitecustomize.py", line 880, in runfile execfile(filename, namespace)

File "C:\ProgramData\Anaconda3\lib\site-packages\spyder\utils\site\sitecustomize.py", line 102, in execfile exec(compile(f.read(), filename, 'exec'), namespace)

File "E:/Scikit-Learn.py", line 46, in print (model.predict(x_test)[0:5])

File "C:\ProgramData\Anaconda3\lib\site-packages\sklearn\linear_model\base.py", line 268, in predict return self._decision_function(X)

File "C:\ProgramData\Anaconda3\lib\site-packages\sklearn\linear_model\base.py", line 251, in _decision_function X = check_array(X, accept_sparse=['csr', 'csc', 'coo'])

File "C:\ProgramData\Anaconda3\lib\site-packages\sklearn\utils\validation.py", line 424, in check_array context))

ValueError: Found array with 0 feature(s) (shape=(1, 0)) while a minimum of 1 is required.

Answer 1

The error says that the array you feed into predict has shape=(1,0) meaning that it must be an empty iterable.

And by looking at your code, it's easy to see why. x_test starts of as empty, and in your code, the only way to add things to it is if i > le. But since your loop is defined as for i in range(le), by definition i will never be greater than le since the last value of range is le-1