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Data Manipulation with Pandas

The course on Data Manipulation with Pandas aims to provide learners with the necessary skills to efficiently manage and transform data utilizing the Pandas library in Python.

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Certificate :

After Completion

Start Date :

10-Jan-2025

Duration :

30 Days

Course fee :

$150

COURSE DESCRIPTION:

  1. The course on Data Manipulation with Pandas aims to provide learners with the necessary skills to efficiently manage and transform data utilizing the Pandas library in Python.

  2. As a robust tool for data analysis, Pandas allows users to easily clean, preprocess, reshape, and analyze extensive datasets.

  3. Key topics include DataFrames, Series, indexing, filtering, and more complex operations like grouping, pivoting, and merging datasets.

  4. Participants will engage in practical projects and real-world scenarios, building their confidence in data management and preparation for analysis and modeling.

CERTIFICATION:

  1. Participants who finish the course will be awarded a Certificate of Completion, confirming their skills in utilizing Pandas for data manipulation and preprocessing.

  2. This certification underscores their capability to handle intricate datasets and execute vital data preparation activities, positioning them effectively for roles such as data analyst, data scientist, or business intelligence professional.

LEARNING OUTCOMES:

By the conclusion of the course, participants will possess the skills to:

  1. Core Concepts
    Grasp the fundamental principles of the Pandas library and its significance in data manipulation.
    Utilize Pandas objects such as Series and DataFrames for data representation and manipulation.

  2. Data Handling
    Import and export data across various formats, including CSV, Excel, JSON, and databases.
    Effectively manage missing and duplicate data using Pandas tools.

  3. Data Exploration and Transformation
    Investigate datasets through indexing, slicing, and filtering methods.
    Implement transformations such as sorting, renaming, and reshaping data structures.
    Conduct arithmetic operations and apply functions to datasets.

  4. Advanced Data Operations
    Employ groupby functions for aggregation and summarization tasks.
    Efficiently merge, join, and concatenate datasets.
    Manipulate data through pivoting and unpivoting techniques for advanced reshaping.

  5. Practical Applications
    Clean, preprocess, and ready data for machine learning workflows.
    Address real-world data manipulation challenges utilizing Pandas.

  6. Ideal For:
    Individuals new to data science or data analysis.
    Professionals aiming to improve their data handling and preparation capabilities.
    Students gearing up for advanced courses in data analysis and machine learning.

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Course Curriculum

Introduction to Pandas
  1. Overview of Pandas and its importance in data analysis
  2. Installing Pandas and setting up the environment
  3. Introduction to Pandas Series and DataFrame.
Loading and Exploring Data
  1. Reading data from various sources: CSV, Excel, JSON, and databases
  2. Inspecting data: head(), tail(), info(), and describe()
  3. Identifying and handling missing values
Data Selection and Indexing
  1. Selecting rows and columns with loc[] and iloc[]
  2. Filtering data based on conditions
  3. Indexing and setting a custom index
Data Cleaning and Transformation
  1. Renaming columns and reordering rows
  2. Handling duplicate values
  3. Applying transformations: apply(), map(), and lambda functions
Aggregation and Grouping
  1. Using groupby() for grouping data
  2. Applying aggregate functions: mean(), sum(), count(), etc.
  3. Working with multi-level indexing
Merging, Joining, and Concatenating
  1. Combining datasets with merge(), concat(), and join()
  2. Understanding the types of joins: inner, outer, left, and right
  3. Appending and reshaping data
Advanced Data Manipulation
  1. Pivot tables and reshaping with pivot() and melt()
  2. Time-series data manipulation
  3. Working with categorical data

Training Features

Hands-On Practice

Interactive coding exercises with diverse datasets to master Pandas functions and methods.

Step-by-Step Tutorials

Guided lessons covering essential and advanced Pandas techniques with real-world examples.

Access to Preloaded Datasets

Ready-to-use datasets for immediate practice, covering industries like e-commerce, healthcare, and finance.

Real-World Projects

Comprehensive projects focusing on data cleaning, analysis, and transformation to build a strong portfolio.

Expert-Led Guidance

Mentorship from data analysts and data scientists to provide feedback and answer queries.

Certification

A certificate upon completion showcasing expertise in data manipulation with Pandas.

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