10000 customers were selected randomly from three countries – France, Germany, Spain. To tackle this alarming situation, the bank decided to collect data for the past 6 months. The bank has noticed an increase in the number of customers leaving the bank. In this blog, I am going to show you the process of EDA through analysis using python libraries like pandas, seaborn, Matplotlib.īank Customer Churn dataset is available hereīefore we proceed to the solution, we will understand the problem statement and its goal. The standard definition of EDA is – The process of visualizing and analyzing the data to extract insights and understand the dataset in a better way. EDA is a methodology where we visualize the data using different charts & graphs and they provide an affirmation to our hypothesis. Because your view will remain a conjecture unless it has a firm base. I have used the word ‘conjecture’ and not ‘fact’ intentionally. We often make assumptions about a business and figure out a few conjectures. In data analysis, there is a term – Exploratory data analysis (EDA). A similar industrial revolution is happening in the 21st century because of data and Data Analysis is a key aspect of this revolution. Yes, in the 19th century the industrial revolution happened because of oil.
Y ou’ve probably heard “Data is the new oil”. “Torture the data, and it will confess” - Ronald Coase
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