Importance of Variance in Machine Learning Selecting a column from a Dataframe, plotting its Histogram using matplotlib and then finding the variance is the steps that I have to take for this part of a project. 

The final goal of the project is detecting anomalies in data. 

I understand the part of plotting the data in form of a graph to understand it better.
On the other hand I’m not sure why finding the variance of this column is so important.

Would really appreciate if I get any information regarding this. 

I know the definition of variance but just can’t seem to understand the usage and importance of it in this project.
Variance in a feature (defined as the average of the squared differences from the mean) is important in machine learning because variance impacts the capacity of the model to use that feature.

For example, if a feature has no variance (e.g., is not a random variable), the feature has no ability to contribute to task performance. A zero variance feature will be constant for different levels of the target.

Additionally, some machine learning models make strong assumptions about the distribution of features. Variance is one way to check for distributional assumptions.