How Pandas Profiling Can Speed up your Exploratory Data Analysis (EDA) in Machine Learning
Pandas Profiling Data analysis is a process of inspecting, cleansing, transforming and modeling data with the goal of discovering useful information, informing conclusion and supporting decision-making. According to Wikipedia, Exploratory Data Analysis is defined as follows In statistics, exploratory data analysis (EDA) is an approach to analyzing data sets to summarize their main characteristics, often with visual methods. A statistical model can be used or not, but primarily EDA is for seeing what the data can tell us beyond the formal modeling or hypothesis testing task. EDA is very important in understanding large datasets while building machine learning models.Generally speaking, EDA is a collection of various findings like Data Quality, Data Spread and Variable Relationships. Data Quality refers to information that define the quality of data and makes sure if is an information is actually necessary for decision making and also helps us determine the overlea
