masterpython4ds/assignment-1-Munga-Em

assignment-1-Munga-Em created by GitHub Classroom # Master Python for DataScience The master python for data science is an initiative of the Nairobi Women in Machine Learning and Data Science community. This initiative sorts to empower community members by improving their skill sets and by so doing enabling the members to be ready to take up the various opportunities in the industry. The course is virtual and completely self paced with a slack community to help you collaborate with others who are interested in the course as well. ### At the end of this assignment you will be required to upload a notebook with the data challenge (as per below) before you proceed to the next assignment. --- ## Chapter 1 - 3 For this lesson we will move through chapter one to three of the Python for data science handbook by Jake VanderPlas (link below) and learn: ### Chapter 1 : IPython: Beyond Normal Python - IPython: Beyond Normal Python - Help and Documentation in IPython - Keyboard Shortcuts in the IPython Shell - IPython Magic Commands - Input and Output History - IPython and Shell Commands - Errors and Debugging - Profiling and Timing Code - More IPython Resources ### Chapter 2 : Introduction to NumPy - Introduction to NumPy - Understanding Data Types in Python - The Basics of NumPy Arrays - Computation on NumPy Arrays: Universal Functions - Aggregations: Min, Max, and Everything In Between - Computation on Arrays: Broadcasting - Comparisons, Masks, and Boolean Logic - Fancy Indexing - Sorting Arrays - Structured Data: NumPy's Structured Arrays ### Chapter 3 : Data Manipulation with Pandas - Introducing Pandas Objects - Data Indexing and Selection - Operating on Data in Pandas - Handling Missing Data - Hierarchical Indexing - Combining Datasets: Concat and Append - Combining Datasets: Merge and Join - Aggregation and Grouping - Pivot Tables - Vectorized String Operations - Working with Time Series - High-Performance Pandas: eval() and query() - Further Resources ## Course challenge : Data Manipulation with Pyth …