The exploratory data analysis is a very important step in a Data Science project. It helps us to visualize the data and identify any hidden trends that might not be visible with summary statistics alone. So, we can use matplotlib and seaborn libraries to create stunning visuals in Python. However, the pandas.plotting module of the […]
Create pair plots using scatter_matrix method in pandas Read More »
We know that EDA (Exploratory Data Analysis), is the process of organizing, plotting, and summarizing the data to find trends, patterns, and outliers using statistical and visual methods. Here, we have already discussed various methods of performing EDA with their pros and cons on an underlying dataset. ECDF plot is another visual method of performing
In this post, we are going to discuss the Relationship between Binomial and Poisson distributions. We know that Poisson distribution is a limit of Binomial distribution for a large n (number of trials) and small p (independent probability for each trial) values. A large number of trials n with very small probability p indicates a
Relationship between Binomial and Poisson distributions Read More »
In the previous post, “Tidy Data in Python – First Step in Data Science and Machine Learning”, we discussed the importance of the tidy data and its principles. In a Machine Learning project, once we have a tidy dataset in place, it is always recommended to perform EDA (Exploratory Data Analysis) on the underlying data
