Data Wrangling with Python

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About the Course

Our Data Wrangling with Python course is your gateway to mastering data manipulation in the data science industry. Learn to work with essential libraries like Pandas and NumPy, manipulate DataFrames, and use powerful built-in functions to analyze and transform data. By the end of the course, you’ll be equipped to handle diverse file types, solve business problems through data analysis, and present your findings using Pandas.

Curriculum

  • Module 1: Data Wrangling Fast-Track

    Overview:

    This module will demonstrate the overview of data wrangling with Python and how to apply it

    Topics to Cover:

    • Pandas library
    • Working with DataFrames
    • Manipulate data

  • Module 2: Introduction to Pandas Data Structures

    Overview:

    This modules focuses on the foundational data structures in Pandas, including Series and DataFrames, and understand how they can be utilized for efficient data analysis.

    Topics to Cover:

    • Dive into Pandas Series
    • Create and work with Pandas DataFrame
    • Understand Pandas Index

  • Module 3: Essential Functionalities

    Overview:

    This module explores the core functionalities of Pandas, including indexing, selecting, and filtering data to streamline data manipulation tasks.

    Topics to Cover:

    • Learn to reindex and drop data
    • Select and filter data by conditions
    • Apply functions and mapping
    • Sort and rank data

  • Module 4: Reading and Writing Data

    Overview:

    This module explores techniques for importing and exporting data from various file formats, including CSV, Excel, and SQL databases, ensuring seamless data integration.

    Topics to Cover:

    • Read and write data
    • Deal with common types of data files
    • Learn relevant modules

  • Module 5: Reshaping and Pivoting Data

    Overview:

    This module teaches participants to reshape and pivot data for better analysis, utilizing methods like pivot_table to reorganize your datasets.

    Topics to Cover:

    • Reshape using hierarchical indexing
    • Change long format to wide format

  • Module 6: Data Transformation

    Overview:

    This module allows participants to gain proficiency in manipulating strings within datasets, applying string functions to clean and format textual data efficiently.

    Topics to Cover:

    • Remove duplicate values
    • Transform data using functions and mapping
    • Replace values and categorize data
    • Dealing with outliers
    • Random sampling and compute dummy variables

  • Module 7: String Manipulation

    Overview:

    This module teaches participants to work with string objects effectively

    Topics to Cover:

    • What are string object methods?
    • Understand the basics of regular expression
    • Working with Vectorized string functions

  • Module 8: Combining and Merging Data Sets

    Overview:

    This module focuses on how to combine multiple datasets through merging, concatenating, and joining operations, facilitating comprehensive data analysis.

    Topics to Cover:

    • Merging DataFrames
    • Combing using index
    • Concatenation along an axis

  • Module 9: Groupby Mechanics

    Overview:

    This module centers around aggregation techniques to summarize data effectively, allowing for quick insights and reporting.

    Topics to Cover:

    • What is GroupBy?
    • Working through the different groupby objects
    • Grouping DataFrame through different methods

  • Module 10: Groupby Operations

    Overview:

    This module focuses on detailed analysis through aggregation methods

    Topics to Cover:

    • What is Data Aggregation?
    • Examine column-wise function applications
    • Creating a new dataframe with aggregated results

  • Module 11: Group-wise Operations and Transformations

    Overview:

    This module delves into group-wise operations and transformations, applying functions to groups of data for tailored analysis results.

    Topics to Cover:

    • Split-Apply-Combine
    • Binning into quartiles and bucket analysis
    • Application of group-wise operations

Learning Outcomes

By the end of this course, participants will be able to:

  • Develop proficiency in data cleaning and preparation techniques to ensure data quality and integrity.
  • Employ various data transformation methods to convert raw data into usable formats.
  • Apply filtering, aggregation, and merging techniques to effectively manipulate datasets.
  • Utilize data visualization tools to uncover trends and insights within datasets.
  • Leverage programming languages like Python or R for efficient data wrangling and analysis.
  • Automate data wrangling tasks to enhance workflow efficiency.
  • Prepare data for analysis and reporting in diverse contexts, such as business intelligence and research.

Tools

Python
Jupyter
Data Wrangling with Python
$99.00
what you will get
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FAQ

Frequently asked questions about the bootcamp

The course is structured into weekly modules, each containing video lectures, reading materials, assignments, and quizzes. You can complete the modules at your own pace, but we recommend following the weekly schedule to stay on track.

You can get support in multiple ways:

  • TA Support on Slack: Our teaching assistants are available on Slack to answer your questions and provide guidance.
  • Peer Community on Discord: Join our Discord community to discuss course topics, share ideas, and collaborate with fellow students.

TAs are available on Slack from 9 AM to 6 PM (ET) Monday to Friday. Outside these hours, you can still post your questions, and TAs will respond as soon as they are back online.

After enrolling in the course, you will receive an invitation link to join the Discord community. Follow the link to create an account or log in to your existing account.

The Discord community offers peer-to-peer support, where you can discuss course topics, share resources, collaborate on projects, and network with fellow learners

The optional mentoring service includes one-on-one sessions with an experienced mentor who can provide personalized guidance, feedback on your progress, and help you set and achieve your learning goals.

Please talk to our Program Advisors to sign up for Mentorship services for an additional cost

Yes, you will have lifetime access to the course materials, including any updates made to the content in the future.

We accept all major credit cards, PayPal, and bank transfers. You can choose your preferred payment method at checkout

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