This page provides an overview of data science fundamentals, highlighting its multidisciplinary nature and lifecycle, which involves data acquisition, exploration, analysis, and reporting. It introduc...This page provides an overview of data science fundamentals, highlighting its multidisciplinary nature and lifecycle, which involves data acquisition, exploration, analysis, and reporting. It introduces key Python libraries, including NumPy for numerical tasks and Pandas for data management. The importance of Exploratory Data Analysis (EDA) and data visualization techniques is emphasized, along with functions for data structure manipulation in Python.
This page covers the process of loading and analyzing data in Python using Jupyter Notebook and Google Colaboratory. It focuses on essential libraries like Pandas for data manipulation, including hand...This page covers the process of loading and analyzing data in Python using Jupyter Notebook and Google Colaboratory. It focuses on essential libraries like Pandas for data manipulation, including handling CSV files and using DataFrames and Series. The text explains filtering data and visualizing it with Matplotlib, providing examples with the Iris dataset and movie profits.
