<s>[INST] The total item count of the "NoSuchMethodError" I have collected is currently 513. The "itemcount" is my dataset for a range from 2001 to 2019. I would like to interpolate for missing values before putting in my forecast model. 

Here is my DataFrame:

```
import pandas as pd
import numpy as np


itemcount = pd.DataFrame({
    'Year': [2001, 2002, 2003, 2004, 2005, 2006, 2007, 2009, 2011, 2013, 2015, 2017, 2019],
    'NoSuchMethodError': [428, 433, 436, 443, 449, 457, 464, 475, 482, 492, 502, 509, 513]
})
```

I would like to interpolate using linear interpolation. I can't seem to find the right way to do this:

```
from sklearn.impute import SimpleImputer
from sklearn.preprocessing import Imputer
from sklearn.linear_model import LinearRegression


# I don't want to impute for column 'Year'. I only want to impute missing values for 'NoSuchMethodError'.
# itemcount['NoSuchMethodError'] = itemcount['NoSuchMethodError'].interpolate()

# I tried using the following imputer but it does not work because it is not interpolating 
# but rather replacing the values by a constant number
itemcount.impute('NoSuchMethodError', strategy='linear')
#itemcount.impute('NoSuchMethodError', strategy='mean')


# I also tried:
itemcount = SimpleImputer(strategy='linear')
# itemcount.fit_transform(itemcount)


# I have also tried using an imputer from sklearn.preprocessing but it seems to have been 
# deprecated and does not work with the new version of sklearn
#itemcount = Imputer(strategy='linear')
#itemcount.fit_transform(itemcount)


# Because the above is not working I would like to try using linear regression
itemcount = LinearRegression()
# but I don't know how to proceed
```

I can see that my data is not properly formatted for a linear regression model but I am unsure how to proceed. 

I would like to know 1) how to format my data for a linear regression model. 2) use linear regression for interpolation (is it even the best option for this task?[/INST]