{"id":2489,"date":"2026-08-10T08:56:49","date_gmt":"2026-08-10T08:56:49","guid":{"rendered":"https:\/\/nokobox.com\/index.php\/item\/udemy-500-exercises-to-master-python-pandas-2023-6\/"},"modified":"2026-08-10T08:56:49","modified_gmt":"2026-08-10T08:56:49","slug":"udemy-500-exercises-to-master-python-pandas-2023-6","status":"publish","type":"digital_item","link":"https:\/\/nokobox.com\/index.php\/item\/udemy-500-exercises-to-master-python-pandas-2023-6\/","title":{"rendered":"Udemy \u2013 500 Exercises to Master Python Pandas 2023-6"},"content":{"rendered":"
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Description<\/span><\/h2>\n

500 Exercises to Master Python Pandas course. Who is this course for? This course is for those who intend to take a step into the field of data science and beginner to intermediate data analysts, data scientists and data engineers. Most of the exercises are based on my experience working as a data scientist with real-life datasets, so you can benefit from this course even if you already use Pandas in your work. If you have never used Panda before or have little experience, you can learn a lot because the exercises are made simple and easy to understand. All you need is a basic level of Python knowledge.<\/span><\/p>\n

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What is required for this course? The lectures are structured as I explain exercises over Jupyter notebooks. Notebooks can be found in the description of each lecture. If you want to download and follow the notebooks, be sure to download the corresponding datasets in the data folder in the course repository. You also need to install Jupyter Notebook on your computer. You can also Google Colab, which allows to run Jupyter notebook in your browser for free.<\/span><\/p>\n

Course structure<\/span><\/p>\n

This course is divided into 6 chapters:<\/span><\/p>\n

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  1. Introduction<\/span><\/li>\n
  2. Data exploration and manipulation<\/span><\/li>\n
  3. Data filtering<\/span><\/li>\n
  4. Composition of DataFrames<\/span><\/li>\n
  5. More about \u201cme\u201d<\/span><\/li>\n
  6. Uses<\/span><\/li>\n
  7. More tutorials<\/span><\/li>\n<\/ol>\n

    Each chapter contains several lectures, each focusing on a specific task such as how to filter a DataFrame, how to create pipelines with multiple steps, and how to use Python dictionaries to extend the power of Pandas functions. By the time you finish this course, you will have solved at least 500 exercises and will be able to solve most tabular data problems.<\/span><\/p>\n<\/div>\n

    What you will learn in the 500 Exercises to Master Python Pandas course<\/span><\/h3>\n
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