02: Data Manipulation, Analysis and Visualization

• Introduction to Data Analysis
• Setting Up Jupyter Notebook and Pandas
• Data Manipulation with Pandas
  • Introduction to Pandas
  • Basics statistics in data analysis (descriptive statistics, shape of distribution, inferential statistics)
  • Pandas Series
  • Pandas DataFrame
  • Reading and writing data with Pandas
  • Accessing and selecting data
  • Data manipulation (filtering, sorting, grouping)
  • Data Cleaning
  • Merge, Join and Concatenating
• Numerical computations with NumPy
  • NumPy array operations (slicing, indexing)
  • NumPy array manipulation
  • Working with random numbers in NumPy
  • Analyzing sales data with NumPy
• Data visualization Basics
  • Line plot, Scatter plot, and Bar plot
  • Histogram, Box plot, and Violin plot
• Assignment 1 : Analyzing E-commerce Orders using Pandas
• Assignment 2 : Exploratory Data Analysis (EDA) using Pandas, NumPy, and Matplotlib