Track
Importing & Cleaning Data in Python
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PythonImporting & Cleaning Data13 hours19,994
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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 trackCourse
Learn to import data into Python from various sources, such as Excel, SQL, SAS and right from the web.
Course
Improve your Python data importing skills and learn to work with web and API data.
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
Apply your data importing, cleaning and manipulation skills to explore New York City Airbnb data.
Skill Assessment
Importing & Cleaning Data in Python
4 Courses
Track Complete
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