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Importing & Cleaning Data in Python

Updated 03/2026
Gain the real-world data prepping skills you need to reveal the insights that matter! Discover how to import, clean, and work with APIs and web data.
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PythonImporting & Cleaning Data13 hr24,540

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Track Description

Importing & Cleaning Data in Python

Master Data Importing and Cleaning in Python

Unlock the power of your data by learning how to efficiently import and clean it using Python. In this Track, you'll gain the essential skills needed to prepare your data for accurate and meaningful analysis. Discover how to handle various file formats, work with APIs, and tackle real-world data quality issues.

Learn to Import Data from Multiple Sources

Expand your data importing toolkit as you learn to:
  • Read data from .csv, .xls, and text files
  • Connect to databases and import data using SQL queries
  • Scrape data from the web and access APIs
  • Handle different file encodings and delimiters
  • Combine data from multiple sources into a single dataset

Develop Robust Data Cleaning Techniques

Ensure the accuracy and reliability of your analysis by mastering essential data cleaning techniques. Through hands-on exercises, you'll learn how to diagnose and treat missing, duplicate, and inconsistent data, convert data types, and handle improper formatting. You'll also perform data validation, address outliers, and apply advanced string manipulation for standardizing data. In addition, you'll implement record linkage methods to merge datasets effectively, preparing your data for accurate and meaningful analysis.

Gain Practical Skills with Real-World Datasets

Throughout the Track, you'll work with diverse, real-world datasets such as restaurant reviews, housing prices, and social media data. By applying your skills to realistic scenarios, you'll develop the confidence to tackle data cleaning challenges in your own projects and professional work.

Leverage the Power of Python's Data Ecosystem

Utilize Python's rich data science libraries and tools, including:
  • pandas for data manipulation and cleaning
  • NumPy for numerical computing
  • Regular expressions for advanced string processing
  • Tweepy for accessing Twitter's API
  • Beautiful Soup for web scraping

Prepare for a Data-Driven Career

Whether you're an aspiring data scientist, analyst, or business professional, the ability to import and clean data is essential in today’s data-driven world. By completing this Track, you'll be well-equipped to efficiently prepare data for analysis and machine learning, ensure the quality and integrity of your datasets, and combine data from various sources for comprehensive insights. You’ll also be prepared to collaborate effectively with data teams and stakeholders, and tackle data-related challenges across a wide range of industries.

Prerequisites

There are no prerequisites for this track
  • Course

    1

    Introduction to Importing Data in Python

    Learn to import data into Python from various sources, such as Excel, SQL, SAS and right from the web.

  • Course

    Learn to diagnose and treat dirty data and develop the skills needed to transform your raw data into accurate insights!

  • Course

    Reshape DataFrames from a wide to long format, stack and unstack rows and columns, and wrangle multi-index DataFrames.

  • Project

    bonus

    Exploring Airbnb Market Trends

    Apply your data importing, cleaning and manipulation skills to explore New York City Airbnb data.

Importing & Cleaning Data in Python
4 Courses
Track
Complete

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FAQs

Is this Track suitable for beginners?

Yes, this track is suitable for beginner data science learners. It is designed to cover the fundamentals of importing and cleaning data and the tracks and courses are self-paced, so can suited to various different abilities.

What is the programming language of this Track?

This track uses Python as the programming language to work with datasets and data cleansing.

Which jobs will benefit from this Track?

This track can benefit data science professionals, data analysts, data engineers or anyone working with data and wanting to upskill their knowledge in data importing and cleaning.

How will this Track prepare me for my career?

This track will equip you with the right skills in importing and cleaning data which is a fundamental aspect of data science. It will provide you with the tools, resources and techniques to work towards mastering data science tasks.

How long does it take to complete this Track?

The track comprises of four courses and requires approximately 13 hours to complete.

What's the difference between a skill track and a career track?

A skill track focuses on developing a specific skill, such as importing and cleaning data, which complements your career path. It focuses on building your skillset so you can become an expert in this field. A career track focuses on a more holistic approach such as Data Science which may contain several skill tracks integrated together.

Are the datasets provided for the exercises?

Yes, the datasets that will be used throughout the various courses in this track are provided.

Is there any guidance on which tasks are more suitable for my level?

Yes, all the courses in the track are self-paced, so you can work through them at your own pace and ability. The courses also contain multiple exercises which are designed to challenge and grow your knowledge.

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