The AttributeError: Series object has no attribute reshape occurs when you try to apply the reshape() method on the series data type. There can be also other reasons for getting this error as well. In this short article, we will discuss the reasons for getting AttributeError: Series object has no attribute reshape error and we will go through various possible solutions to solve the problem.

## AttributeError: Series object has no attribute reshape – Possible Solutions

The error is caused by the function reshape() when applied directly to the series object. Let us first take an example and see where and why we are facing this issue. Mostly, we use data frames in machine learning and data science. This error is common when you try to convert your output or input values into a 2D array for the training of the model but face AttributeError: Series object has no attribute reshape error.

Let us assume that we want to import the dataset and then apply the reshape() method on the series object.

```
# importing pandas
import pandas as pd
# importing dataset
data =pd.read_csv("Dushanbe_house.csv")
# output
output = data['price']
# type
print(type(output))
```

Output:

`<class 'pandas.core.series.Series'>`

As you can see the type is the Pandas series. Now, if we apply the reshape method directly on the series object we will get the error as shown below:

```
# applying the reshape method
output.reshape(-1, 1)
```

Output:

```
---------------------------------------------------------------------------
AttributeError Traceback (most recent call last)
Cell In[9], line 2
1 # applying the reshape method
----> 2 output.reshape(-1, 1)
File ~/.local/lib/python3.10/site-packages/pandas/core/generic.py:5902, in NDFrame.__getattr__(self, name)
5895 if (
5896 name not in self._internal_names_set
5897 and name not in self._metadata
5898 and name not in self._accessors
5899 and self._info_axis._can_hold_identifiers_and_holds_name(name)
5900 ):
5901 return self[name]
-> 5902 return object.__getattribute__(self, name)
AttributeError: 'Series' object has no attribute 'reshape'
```

As you can see, we got an error. The error occurs because there is no function as reshape for the Pandas series object. Now, let us go through various steps in order to see how we can solve this issue.

### Solution-1: Using Values class

If you want to apply the reshape() method on the series object, then first you need to use the values method in order to get access to the values inside your series object. For example, see the following code:

```
# applying the reshape method
output.values.reshape(-1, 1)
```

Output:

```
array([[ 330000],
[ 340000],
[ 700000],
...,
[ 361220],
[1500000],
[ 304650]])
```

Notice that we were able to apply the reshape method on a series object by accessing the values.

### Solution-2: Converting Series to np.array

Another method to apply the reshape method is to convert the series object into a NumPy array. We can use np.array() method to convert the series into a NumPy array and then apply the reshape() method.

```
# importing the numpy array
import numpy as np
# applying the reshape method
np.array(output).reshape(-1, 1)
```

Output:

```
array([[ 330000],
[ 340000],
[ 700000],
...,
[ 361220],
[1500000],
[ 304650]])
```

Notice that we first converted the series object into a NumPy array and then applied the reshape method.

### Solution-3: Using pd.DataFrame method

If you are facing the** ValueError: Expected 2D array, got 1D array instead **error because of the training process of the model and want to convert your array into 2D, then instead of converting the data using reshape() method, you can use the StandardScaler() method and apply the fit function then.

See the example below:

```
# importing the modules
from sklearn.preprocessing import StandardScaler
# initializng standardscaler
scaler = StandardScaler()
# scaling
scaler.fit_transform(output)
```

Output:

```
ValueError: Expected 2D array, got 1D array instead:
array=[ 330000. 340000. 700000. ... 361220. 1500000. 304650.].
Reshape your data either using array.reshape(-1, 1) if your data has a single feature or array.reshape(1, -1) if it contains a single sample.
```

If this is the reason you want to apply the reshape() method, then instead of using the reshape method, you can directly convert your Series object into a Pandas data frame which will be 2D in nature.

```
# importing the modules
from sklearn.preprocessing import StandardScaler
# initializng standardscaler
scaler = StandardScaler()
# scaling with data frame
scaler.fit_transform(pd.DataFrame(output))
```

Now, you will be able to use the fit function in order to train the model as our data is now in 2D.

## Understanding the AttributeError: Series object has no attribute reshape error

The error has two main parts which help us to figure out the possible solutions to the issue. The first part of the error shows the category of the error which in this case is the AttributeError. The AttributeError occurs when we use a function on an object that does not support it.

The second part of the error gives more specific detail about the error which in this case says that the series object has no attribute reshape which means we are trying to use the reshape method on a series object which does not support it.

## Summary

In this short article, we discussed the reasons for getting AttributeError: Series object has no attribute reshape error. We went through various possible solutions in order to solve the problem. We learned that the series objects do not have any attribute named reshape and we discussed how to reshape a series object without getting any error.

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