pandas.errors.InvalidIndexError: (slice(None, None, None), None)-CodePudding

this is my model for LinearRegression of salary pridict for pratcit but gating a error pl.plot(x_train, model.predict(x_train))

import pandas as pd
from sklearn.linear_model import LinearRegression
from sklearn.model_selection import train_test_split

df = pd.read_csv('Salary_Data.csv')
x = df[['YearsExperience']]
y = df['Salary']

x_train, x_test, y_train, y_test = train_test_split(x, y, test_size=.2, random_state=0)

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

import matplotlib.pyplot as plt
pl = plt
pl.scatter(x_train, y_train)
pl.plot(x_train, model.predict(x_train))
pl.show()

this is data iam using

YearsExperience,Salary
1.1,39343.00
1.3,46205.00
1.5,37731.00
2.0,43525.00
2.2,39891.00
2.9,56642.00
3.0,60150.00
3.2,54445.00
3.2,64445.00
3.7,57189.00
3.9,63218.00
4.0,55794.00
4.0,56957.00
4.1,57081.00
4.5,61111.00
4.9,67938.00
5.1,66029.00
5.3,83088.00
5.9,81363.00
6.0,93940.00
6.8,91738.00
7.1,98273.00
7.9,101302.00
8.2,113812.00
8.7,109431.00
9.0,105582.00
9.5,116969.00
9.6,112635.00
10.3,122391.00
10.5,121872.00

this is error iam fasing

Traceback (most recent call last):
  File "D:\Softwers\Python_3.9\lib\site-packages\pandas\core\indexes\base.py", line 3621, in get_loc
    return self._engine.get_loc(casted_key)
  File "pandas\_libs\index.pyx", line 136, in pandas._libs.index.IndexEngine.get_loc      
  File "pandas\_libs\index.pyx", line 142, in pandas._libs.index.IndexEngine.get_loc      
TypeError: '(slice(None, None, None), None)' is an invalid key

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
  File "d:\Project\data scince\main.py", line 16, in <module>
    pl.plot(x_train, model.predict(x_train))
  File "D:\Softwers\Python_3.9\lib\site-packages\matplotlib\pyplot.py", line 2757, in plot
    return gca().plot(
  File "D:\Softwers\Python_3.9\lib\site-packages\matplotlib\axes\_axes.py", line 1632, in plot
    lines = [*self._get_lines(*args, data=data, **kwargs)]
  File "D:\Softwers\Python_3.9\lib\site-packages\matplotlib\axes\_base.py", line 312, in __call__
    yield from self._plot_args(this, kwargs)
  File "D:\Softwers\Python_3.9\lib\site-packages\matplotlib\axes\_base.py", line 487, in _plot_args
    x = _check_1d(xy[0])
  File "D:\Softwers\Python_3.9\lib\site-packages\matplotlib\cbook\__init__.py", line 1327, in _check_1d
    ndim = x[:, None].ndim
  File "D:\Softwers\Python_3.9\lib\site-packages\pandas\core\frame.py", line 3505, in __getitem__
    indexer = self.columns.get_loc(key)
  File "D:\Softwers\Python_3.9\lib\site-packages\pandas\core\indexes\base.py", line 3628, in get_loc
    self._check_indexing_error(key)
  File "D:\Softwers\Python_3.9\lib\site-packages\pandas\core\indexes\base.py", line 5637, in _check_indexing_error
    raise InvalidIndexError(key)
pandas.errors.InvalidIndexError: (slice(None, None, None), None)

CodePudding user response：

this is solving my problem dont known why?

x = df.iloc[:, :-1].values
y = df.iloc[:, 1].values

thas full code

import pandas as pd
from sklearn.linear_model import LinearRegression
from sklearn.model_selection import train_test_split

df = pd.read_csv('Salary_Data.csv')
x = df.iloc[:, :-1].values
y = df.iloc[:, 1].values

x_train, x_test, y_train, y_test = train_test_split(x, y, test_size=.2, random_state=0)

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

import matplotlib.pyplot as plt
pl = plt
pl.scatter(x_train, y_train)
pl.plot(x_train, model.predict(x_train))
pl.show()

CodePudding user response：

You have to use a Series as x-axis not a DataFrame:

pl.plot(x_train['YearsExperience'], model.predict(x_train))

# OR

pl.plot(x_train.squeeze(), model.predict(x_train))