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Exploratory Data Analysis (EDA) is a critical step in the data science process that involves analyzing and summarizing data in order to gain insights and understand its characteristics. Python provides several libraries for EDA, such as pandas, matplotlib, and seaborn , which make it easy to perform complex data manipulations and visualization tasks. Steps for EDA in Python: Import the data Clean the data Summarize the data Visualize the data Feature engineering Repeat the process Import data : To import data into Python using pandas, you can use the pd.read_csv() function. Here is an example of how to import a CSV file into a pandas DataFrame: python Copy code import pandas as pd # import the data df = pd.read_csv( 'data.csv' ) In this example, the data from the file "data.csv" is imported into a pandas DataFrame named df . The pd.read_csv() a function is a convenient way to read data from a CSV file, but pandas also provide other functions for importing data f...