Data Analysis using Pandas & Python Practice Exam
Data Analysis using Pandas & Python Practice Exam
About the Data Analysis using Pandas & Python Exam
Data Analysis using Pandas & Python is a skillset primarily focused on data manipulation, cleaning, and analysis using the Pandas library in Python. It is one of the most widely used approaches for working with data in a structured format.
Skills Required to learn
To learn Data Analysis using Pandas & Python, the following skills are essential:
- Basic Python Knowledge
- Understanding of NumPy
- Basic Statistics
- Mathematical Background
- Familiarity with Data Formats
Knowledge Gained
The knowledge gained from a Data Analysis using Pandas & Python course includes:
- Introduction to data analysis with Python, focusing on the Pandas library
- Working with Pandas, iPython, and Jupyter Notebook
- Exploring key commands and functionalities in Pandas
- Handling data from various file types: CSV, Excel, TXT, JSON, and API responses
- Performing DataFrame operations: indexing, slicing, and modifications
- Gaining a strong foundation in Pandas
- Preparing for advanced data analysis techniques
Who should take the Exam?
- Individuals interested in pursuing a career in data analysis or data science
- Beginners who want to learn data analysis using Python and the Pandas library
- Python developers who want to expand their skills to include data manipulation and analysis
- Analysts looking to enhance their data handling and processing skills with Pandas
- Professionals seeking to validate their expertise in using Python for data analysis tasks
- Students or learners aiming for certification in data analysis or data science-related fields
Course Outline
- Introduction to the Course
- What is Pandas?
- Jupyter Notebooks
- Working on Data
- Conclusion
