Descriptive Statistics in Python
Descriptive Statistics in Python
How to Calculate Expected Value in Python (With Examples)
A probability distribution tells us the probability that a random variable takes on certain values.
For example, the following probability distribution tells us the probability...
Descriptive Statistics in Python
How to Perform Data Binning in Python (With Examples)
You can use the following basic syntax to perform data binning on a pandas DataFrame:
import pandas as pd
#perform binning with 3 bins
df = pd.qcut(df,...
Descriptive Statistics in Python
How to Center Data in Python (With Examples)
To center a dataset means to subtract the mean value from each individual observation in the dataset.
Once you’ve centered a dataset, the mean value...
Descriptive Statistics in Python
How to Normalize a NumPy Matrix (With Examples)
To normalize a matrix means to scale the values such that that the range of the row or column values is between 0 and...
Descriptive Statistics in Python
How to Calculate KL Divergence in Python (Including Example)
In statistics, the Kullback–Leibler (KL) divergence is a distance metric that quantifies the difference between two probability distributions.
If we have two probability distributions, P...
Descriptive Statistics in Python
How to Perform Bivariate Analysis in Python (With Examples)
The term bivariate analysis refers to the analysis of two variables. You can remember this because the prefix “bi” means “two.”
The purpose of bivariate analysis is...
Descriptive Statistics in Python
How to Perform Univariate Analysis in Python (With Examples)
The term univariate analysis refers to the analysis of one variable. You can remember this because the prefix “uni” means “one.”
There are three common ways...
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