Python for Data Analysis – Data Wrangling with pandas, NumPy, and Jupyter, Third Edition by Wes McKinney
Open access online version: https://wesmckinney.com/book/
Data files and materials: https://github.com/wesm/pydata-book
Chapter 1
Essential libraries/tools:
- NumPy
- pandas
- matplotlib
- IPython
- Jupyter Notebook
- SciPy
- scikit-learn
- statsmodels
- Anaconda/Miniconda
? – object introspection
def add_numbers(a, b):
"""
Add two numbers together
Returns
-------
the_sum : type of arguments
"""
return a + b
add_numbers?
output:
Signature: add_numbers(a, b)
Docstring:
Add two numbers together
Returns
-------
the_sum : type of arguments
File: <path>
Type: function