What are the main steps in exploratory data analysis?

Exploratory data analysis (EDA) involves examining and visualizing the data to gain insights, identify patterns, and understand the characteristics of the dataset. The main steps in EDA generally include data collection and cleaning, summarizing the data using descriptive statistics, visualizing the data through graphs and plots, identifying relationships and correlations between variables, and finally, drawing preliminary conclusions and formulating hypotheses for further analysis. Throughout the EDA process, it is important to check for outliers, missing values, and inconsistencies in the data, as well as to explore the distributions, central tendencies, and variability of the variables. EDA serves as a crucial initial step before diving into more complex statistical modeling and inference.

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