SimpleImputer
We figured out the identification of missing values. Time now to find out what to do with them and how.
SimpleImputer
- it is a class from the scikit-learn library, and which is used to work with the missing values.
SimpleImputer()
. This method replaces the missing values with more logical values. It has such main arguments, let's look at them.
- missing_values - a way to represent missing values, by default is NaN, but as we have already said, it can be for example 0.
- strategy - here we indicate which values we will replace with. It can be
mean
(default),median
,most_frequent
andconstant
. - fill_value - a constant value, with which we will replace the missing values, if we chose
strategy = constant
.
We learn
fit()
andtransform()
functions a little more later.
Swipe to start coding
Let's try to fill the empty space in your small dataset.To use SimpleImputer you have to implement the next steps:
- Import the class.
- Create an instance of the class (imputer object).
- Specify the parameters you need, especially: we see that here the missing values are represented by NaN, so replace them with the constant value 15.
- Fit the imputer on your data using
fit()
function - Impute all missing values in you data using
transform()
function.
Lösung
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SimpleImputer
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We figured out the identification of missing values. Time now to find out what to do with them and how.
SimpleImputer
- it is a class from the scikit-learn library, and which is used to work with the missing values.
SimpleImputer()
. This method replaces the missing values with more logical values. It has such main arguments, let's look at them.
- missing_values - a way to represent missing values, by default is NaN, but as we have already said, it can be for example 0.
- strategy - here we indicate which values we will replace with. It can be
mean
(default),median
,most_frequent
andconstant
. - fill_value - a constant value, with which we will replace the missing values, if we chose
strategy = constant
.
We learn
fit()
andtransform()
functions a little more later.
Swipe to start coding
Let's try to fill the empty space in your small dataset.To use SimpleImputer you have to implement the next steps:
- Import the class.
- Create an instance of the class (imputer object).
- Specify the parameters you need, especially: we see that here the missing values are represented by NaN, so replace them with the constant value 15.
- Fit the imputer on your data using
fit()
function - Impute all missing values in you data using
transform()
function.
Lösung
Danke für Ihr Feedback!
Awesome!
Completion rate improved to 12.5single