• Understand data visualization capabilities in python
• Introduction to Numpy
• Introduction to Pandas

poetry env use $(pyenv which python)

poetry add matplotlib seaborn

poetry run jupyter lab

• The basic statistical functions like mean, median, mode, sum, count are all types of "reduce" functions because they accept an iterable and return a single value in response
• Lambda functions in python are only expression lambda, unlike java it does not support statement lambda.
• map, filter, reduce - similar to how these concepts are used in Java, they return an iterator

• What is the difference between list comprehensions and generator expressions?
• How to perform case-insensitive compare in strings? (hint: str.casefold())
• Recollect how dictionary comprehension works? see - Dictionary comprehension
• How to represent an empty set, why we can't represent an empty set like {} similar to how we could represent an empty list using []
• Dictionary comprehensions
• Recollect Set mathematical operations (union, intersection, difference, symmetric difference), see Set Math

• What are the basic stat functions in python (mean, median, mode, sum, count, range) Stat functions
• How can you chart a barplot for a six-sided dice roll ? See - Static Visualizations

• seaborn
• matplotlib

• sum
• count
• range
• minimum
• maximum

• mean
• median
• mode : Most frequent occurrence

Dispersion - Defines spread of given numbers how closer or distant they are Standard deviation: sqrt of variance

• Numeric python - most two-dimensional array in python always use numpy
• Pandas library is based on numpy

Numpy has a high performance array called as ndarray that is 35% more performant than the list array data structure in python.

See numpy_ndarray

• How to find out the datatype of a numpy array?
• What are dimensions in ndarray?
• What are shape attribute in ndarray?
• What is the difference between size and itemsize in a ndarray?
• How to flatten a ndarray? What is the difference between flatten() and .flat attribute?
• Explain the arange function? How similar or different is it from range?
• How to generate floating point array ranges using numpy?
• What is the purpose of reshape in numpy?
• How does array broadcasting work in numpy?
• What is the use of linspace function in numpy?

• Does numpy have built-in values for stats? Numpy stats
• How to find average by row or column using numpy?
• What are universal functions in python, how to use them? Numpy universal functions

See - Numpy Array Operations

• How to choose to find specific rows in ndarray?
• How to find specific columns in ndarray?
• How to slice data from ndarray?
• How to transpose an ndarray?
• How does array horizontal stack and vertical stacking work?

See - Numpy References

• What is the difference between copy and view in numpy?
• How does deepcopy work?
• What is the difference between flatten and ravel?

• Created by Wes Mckinney
• pandas - panel datas, for data measurements derived over time
• 2 key data structures - Series and DataFrames
• Series is used for one-dimensional collections, Dataframes for two-dimensional data
• SQL style data manipulations

Pandas uses numpy under the hood hence good basics on numpy helps!

Later read Wes Mckinney's book - Data wrangling with numpy, pandas and ipython

See - Pandas Intro

• How to create a pandas Series with custom indices?
• Does pandas have inbuilt stats methods, how does it offer more convenience than using numpy?
• What happens when we add string functionality into Series, does it modify parent array?

• Enhanced two-dimensional array with support for missing data. This is a key benefit as numpy only handles homogeneous integer types.
• Additional operations and capabilities that are useful in datascience tasks.

Practice: Pandas Dataframes

• How is pandas Dataframe stats compare to numpy or pandas.Series stats?
• How to define precision for stats returned in pandas describe operation?
• How to assign custom index labels while creating a dataframe?
• What is the difference between loc and iloc attributes in dataframes?
• Explain how slicing by row and column works in pandas dataframes?
• How to select specific rows or columns ?
• How to select all rows while slicing data?
• How does boolean indexing work in dataframes? What value is replaced in columns that don't match given condition?
• Explain at and iat, when is this useful?
• What is the difference between using T vs transpose() methods for dataframes / numpy?
• How to sort dataframes?
• How does transpose work?