Introduction to List Comprehensions¶
- Definition
- List comprehensions are a concise and efficient way to create lists in Python
- They provide a syntactically elegant method to perform operations and apply conditions to iterables, allowing the creation or transformation of lists in a single line of code
Why Do We Use List Comprehensions?:
- Conciseness: Reduces the amount of code needed compared to traditional loops, making the code cleaner and easier to read read more
Grouping, filtering with Pandas and plotly
Grouping¶
- Grouping is a way to break data into subsets for further analysis
- Why do we group data? grouping data -and making comparisons between groups- is usually the only way to identify interesting patterns and trends
- By grouping data you effectively create a 'new' grouped data structure
- You may recognize that by taking an input and making a new data structure from it, we keep the original data intact, aligning with functional programming concepts
- i.e., we always want to maintain the integrity of the original data and keep things clear and concise read more
Exploring Fire Incident Data
Exploring Fire incident Data¶
Introduction to Functional Programming
Functional programming¶
- a style of programming where your output is determined solely by your input
- The function does not change anything outside of it or depend on external data to produce the output
Why use Functional programming?:
- makes your code easier to understand, test, debug and build upon
- It's widely used in data analysis and other fields where computation is important read more
Introduction to Jupyter Notebooks and Pandas
Jupyter Notebooks¶
- This is a jupyter notebook file (file extension is .ipynb for python notebook versus .py for standard python scripts)
- It is a format used by many data scientists and researchers for analysis and visualization tasks