Question

i'm receiving an 'a' is not defined error. what is the command to define 'a'?

import numpy as np
import pandas as pd

df = pd.read_csv('https://raw.githubusercontent.com/uiuc-cse/data-fa14/gh-pages/data/iris.csv')
df.head()

from sklearn.preprocessing import StandardScaler

a_scaled=StandardScaler().fit_transform(a)
a_scaled[:5]

Answer 1

The Standard Scaler is one of the preprocessing methods present in the scikit learn library. Actually, the Standard Scaler is a data pre-processing method which transforms our data/dataframe in such a way that its distribution would be having a 0 mean and unit (1) standard deviation/variance i.e  μ = 0 and σ = 1. So basically, the standard scaler just normalizes the features (columns) present in our data/data frame one by one and hence gives us the scaled data then.

Now, the error you are receiving as 'a' is not defined because when you are using the code:

1. import numpy as np
2. import pandas as pd
3. df = pd.read_csv('https://raw.githubusercontent.com/uiuc-cse/data-fa14/gh-pages/data/iris.csv')
4. df.head()
5. from sklearn.preprocessing import StandardScaler
6. a_scaled=StandardScaler().fit_transform(a)
7. a_scaled[:5]

is because, you have not defined what variable/object 'a' actually is before using the 6th line of code that is:

a_scaled=StandardScaler().fit_transform(a)

Here, you must know that the in the StandardScalre().fit_transform() function, the input parameter should be a data/data frame. So you should type the following line of code in the 6th line:

a_scaled=StandardScaler().fit_transform(df)

because here, the input to the StandardScalre().fit_transform() function is now (df) which is actually a data frame/CSV file you just loaded through Pandas in line 3. After correcting your code, you will not get this error anymore.

But, in case you wish to use the same 6th line of code as:

a_scaled=StandardScaler().fit_transform(a)

then you must first define what 'a' is. before using this 6th line of code.

You can simply do this by adding the following assignment before line 6:

a = df.copy();

it will simply copy your data frame named 'df' into am another data frame/variable named 'a', and then you can continue using your 6th line of code as a_scaled=StandardScaler().fit_transform(a).

Now you might have understood that you first need to define any variable before using it in your code. Your error will be surely solved now!

Thanks!