ValueError: at least one array or dtype is required

Question

My code:

import numpy as np
from pandas import read_csv
from matplotlib import pyplot as plt
from sklearn.neural_network import MLPClassifier
from sklearn.model_selection import train_test_split

data = read_csv('data.csv', usecols=['col_1'])

df_x = data.iloc[:, 1:]
df_y = data.iloc[:, 0]

x_train, x_test, y_train, y_test = train_test_split(df_x, df_y, test_size=0.9, random_state=4)

nn = MLPClassifier(activation='logistic', solver='sgd', hidden_layer_sizes=(2,), random_state=1)
#nn.fit(x_train[x], y_train[x])

print(nn)

nn.fit(x_train, y_test)

pred = nn.predict(x_test)

I am getting the error as shown in the title from .fit() method, and didn't understand much from the documentation as I am new to ML.

Full error:

File "C:/NNC/Main.py", line 14, in <module>
    data.target.array([])
  File "C:\NNC\venv\lib\site-packages\pandas\core\generic.py", line 5179, in __getattr__
    return object.__getattribute__(self, name)
AttributeError: 'DataFrame' object has no attribute 'target'

Update -:
I'v since removed and updated this as this was to test a solution found in the documentation. I have updated the error

File "C:\Users\PycharmProjects\NNC\venv\lib\site-packages\sklearn\neural_network\_multilayer_perceptron.py", line 325, in _fit
    X, y = self._validate_input(X, y, incremental)
  File "C:\Users\PycharmProjects\NNC\venv\lib\site-packages\sklearn\neural_network\_multilayer_perceptron.py", line 932, in _validate_input
    multi_output=True)
  File "C:\Users\PycharmProjects\NNC\venv\lib\site-packages\sklearn\utils\validation.py", line 739, in check_X_y
    estimator=estimator)
  File "C:\Users\PycharmProjects\NNC\venv\lib\site-packages\sklearn\utils\validation.py", line 459, in check_array
    dtype_orig = np.result_type(*array.dtypes)
  File "<__array_function__ internals>", line 6, in result_type
ValueError: at least one array or dtype is required

Process finished with exit code 1

Solution

This error will occur cause of these reasons:

1. You don't have target column in your csv. There for check twice your csv.
2. If you have target column, there are white space or spaces in your targer column. It may be exist like these

< target>
<target >
< target >
<target   >...etc.

There for copy that column name with that white spaces. After that run this code

data = read_csv('data.csv', usecols=['col_1'])
data.columns = data.columns.str.strip()

Updated:

If your data frame look like this

       a         b
0      1         2
1      1         2
2      1         2
3      1         2
4      1         2

When you use iloc

df_y = data.iloc[:, 0]

output -:
       a         
0      1         
1      1         
2      1         
3      1         
4      1     

df_y = data.iloc[:, 1]   

output -:
       b
0      2
1      2
2      2
3      2
4      2

In your case you have used df_x = data.iloc[:, 1:]. Correct it as df_x = data.iloc[:, 1]. Understand how iloc works