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Data Wrangling With Python
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Gain insights into data wrangling using Python. Learn about cleaning, transforming, and organizing data with libraries like NumPy, pandas, and scikit-learn for data science and machine learning projects.

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Data wrangling is cleaning, transforming, and organizing data for further analysis. In this course, you will learn how to use Python to effectively wrangle and prepare data for use in data science and machine learning projects. Throughout the course, you will learn about the common challenges that arise when working with data and how to overcome them. You will use Python and several libraries commonly used in data wrangling, including NumPy and pandas. Then, you will learn how to use pandas to clean, transform, and aggregate data. Moreover, you will also use scikit-learn, a library for machine learning, to identify outliers in our data. By the end of the course, you will be able to use Python to effectively wrangle and prepare data for use in data science and machine learning projects. With these tools at your disposal, you can efficiently apply machine learning models and get realistic predictions after applying various wrangling techniques to the dataset.

Data wrangling is cleaning, transforming, and organizing data for further analysis. In this course, you will learn how to use Py...Show More

WHAT YOU'LL LEARN

Understanding of data wrangling and its application in developing data solutions

A working knowledge of common data wrangling challenges and their solutions

Hands-on experience applying data wrangling techniques using Python to prepare data for further analysis

Familiarity with the core components of data wrangling and the ability to differentiate between data wrangling techniques to understand their suitability

Hands-on experience with datasets to practice the data wrangling techniques in a mini project at the end of the course

Understanding of data wrangling and its application in developing data solutions

Content

47 Lessons1 Project9 Quizzes29 Challenges

About This Course

1 Lessons

Get familiar with data wrangling, essential techniques, and Python libraries NumPy and pandas.

Course Introduction

Introduction to Data Wrangling

4 Lessons

Look at transforming raw data into usable formats, improving quality, and applying core techniques.

Data Wrangling

Applications of Data Wrangling

How to Apply Data Wrangling

Quiz Yourself: Introduction to Data Wrangling

Reading Data

5 Lessons

Delve into reading and manipulating CSV, Excel, and local datasets using pandas.

Loading a CSV Dataset From a URL

Loading an Excel Dataset into a DataFrame

Loading a Dataset Locally

Coding Challenges on Reading Data

Quiz Yourself: Reading Data

Standardization

5 Lessons

Grasp the fundamentals of column fixing, data type conversion, string conversion, and coding challenges in standardization.

Fixing the Columns

Data Type Conversion

String Conversion

Coding Challenges on Standardization

Quiz Yourself: Standardization

Syntax Errors and Irrelevant Data

5 Lessons

Take a closer look at cleaning data by correcting typos, removing spaces, handling irrelevant data, and coding challenges.

Spelling Mistakes and Typos

Leading and Trailing Spaces

Handling Irrelevant Data

Coding Challenges on Syntax Errors and Irrelevant Data

Quiz Yourself: Syntax Errors and Irrelevant Data

Duplicate and Missing Data

6 Lessons

See how it works to manage and resolve duplicate and missing data issues with Python.

Duplicate Data

Handling Duplicate Data

Missing Data

Handling Missing Data

Coding Challenges on Duplicate and Missing Data

Quiz Yourself: Duplicate and Missing Data

Filtering and Sorting

6 Lessons

Master data filtering and sorting techniques in Python using pandas through practical examples.

Coding Challenges on Filtering and Sorting

Quiz Yourself: Filtering and Sorting

Splitting, Combining, and Merging

5 Lessons

Step through splitting, joining, and merging DataFrames with hands-on coding challenges.

Splitting a Column

Joining Columns

Merging DataFrames

Coding Challenges on Splitting, Combining, and Merging

Quiz Yourself: Splitting, Combining, and Merging

Handling Outliers

5 Lessons

Walk through outlier identification, advanced detection methods, and practical handling strategies in Python.

Outliers

Advanced Outlier Detection Methods

Handling Outliers

Coding Challenge on Handling Outliers

Quiz Yourself: Handling Outliers

10.

Exporting Data

4 Lessons

Go hands-on with exporting DataFrames to CSV and Excel, and tackle coding challenges.

Exporting to a CSV File

Exporting to an Excel File

Coding Challenge on Exporting Data

Quiz Yourself: Exporting Data

Humanitarian Aid Project

Project

11.

Conclusion

1 Lessons

Grasp the fundamentals of data wrangling using pandas and NumPy for effective data manipulation.

Course Summary

Certificate of Completion

Showcase your accomplishment by sharing your certificate of completion.

Course Author:

Valentine Mwangi

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Data Wrangling With Python Save

Data Wrangling With Python
Save