Jupyter notebooks from my YouTube videos

Do you enjoy my YouTube channel (https://YouTube.com/reuvenlerner)? If so, then you've probably noticed I use Jupyter a lot. This repo contains the notebooks from some of my videos. As I do more videos, I'll add more notebooks here.

If you have comments about my videos, or suggestions for topics I can/should address in the future, please let me know at @reuvenmlerner on Twitter or via e-mail at reuven@lerner.co.il.

Name		Name	Last commit message	Last commit date
Latest commit History 74 Commits
subdir		subdir
args and *kwargs.ipynb		args and *kwargs.ipynb
.gitignore		.gitignore
Advanced unpacking in Python loops.ipynb		Advanced unpacking in Python loops.ipynb
All about identifiers.ipynb		All about identifiers.ipynb
Assignment expression (aka "the walrus").ipynb		Assignment expression (aka "the walrus").ipynb
Averages in pandas.ipynb		Averages in pandas.ipynb
BW 106 — using Pandas to check flu infections.ipynb		BW 106 — using Pandas to check flu infections.ipynb
BW 107 — Consumer confidence.ipynb		BW 107 — Consumer confidence.ipynb
BW 108 — Measles.ipynb		BW 108 — Measles.ipynb
BW 109 - cocoa prices.ipynb		BW 109 - cocoa prices.ipynb
BW 110 -- credit access .ipynb		BW 110 -- credit access .ipynb
BW 111 -- state taxes.ipynb		BW 111 -- state taxes.ipynb
BW 112 -- number of programmers.ipynb		BW 112 -- number of programmers.ipynb
BW 113 -- US airports.ipynb		BW 113 -- US airports.ipynb
BW 115 -- Sahm rule.ipynb		BW 115 -- Sahm rule.ipynb
BW 116 -- Philadelphia Fed survey.ipynb		BW 116 -- Philadelphia Fed survey.ipynb
BW 117 - Electricity.ipynb		BW 117 - Electricity.ipynb
Better inputs with Rich.ipynb		Better inputs with Rich.ipynb
Boolean indexes.ipynb		Boolean indexes.ipynb
By value or by reference?.ipynb		By value or by reference?.ipynb
Comparing different types.ipynb		Comparing different types.ipynb
Comparing groupby and pivot tables.ipynb		Comparing groupby and pivot tables.ipynb
Constant vs. immutable.ipynb		Constant vs. immutable.ipynb
Context managers in Python.ipynb		Context managers in Python.ipynb
Data selection with filter.ipynb		Data selection with filter.ipynb
Dispatch tables.ipynb		Dispatch tables.ipynb
Don't use dict.keys to search in a dict.ipynb		Don't use dict.keys to search in a dict.ipynb
Don't use dot notation in Pandas!.ipynb		Don't use dot notation in Pandas!.ipynb
Dummies in Pandas.ipynb		Dummies in Pandas.ipynb
Exceptions.ipynb		Exceptions.ipynb
Extension DTypes.ipynb		Extension DTypes.ipynb
Filenames and paths.ipynb		Filenames and paths.ipynb
For loops vs. comprehensions.ipynb		For loops vs. comprehensions.ipynb
Fun with dtype_backend.ipynb		Fun with dtype_backend.ipynb
Function return values.py		Function return values.py
Grouping on dates.ipynb		Grouping on dates.ipynb
Grouping.ipynb		Grouping.ipynb
Immutable vs. hashable.ipynb		Immutable vs. hashable.ipynb
Intro to pivot tables in Pandas.ipynb		Intro to pivot tables in Pandas.ipynb
Jupyter keyboard hints video.ipynb		Jupyter keyboard hints video.ipynb
JupyterLite.ipynb		JupyterLite.ipynb
List comprehensions in Python.ipynb		List comprehensions in Python.ipynb
List sizes.ipynb		List sizes.ipynb
Lists in Python functions.ipynb		Lists in Python functions.ipynb
Lists vs. tuples.ipynb		Lists vs. tuples.ipynb
Loops and loop variables.ipynb		Loops and loop variables.ipynb
Magic commands.ipynb		Magic commands.ipynb
Method chaining in Pandas.ipynb		Method chaining in Pandas.ipynb
Mistakes learning Python.ipynb		Mistakes learning Python.ipynb
Modified variables.ipynb		Modified variables.ipynb
Most useful read_csv options.ipynb		Most useful read_csv options.ipynb
Multiple CSV to data frame.ipynb		Multiple CSV to data frame.ipynb
NumPy 2.0 and Pandas.ipynb		NumPy 2.0 and Pandas.ipynb
One function, Python three different errors.ipynb		One function, Python three different errors.ipynb
Optimizing your Pandas method chains.ipynb		Optimizing your Pandas method chains.ipynb
Pandas and slices.ipynb		Pandas and slices.ipynb
Pandas performance and Python built-in functions.ipynb		Pandas performance and Python built-in functions.ipynb
Parsing files with walruses, etc..ipynb		Parsing files with walruses, etc..ipynb
Passing keyword arguments as ** vs. a dict.ipynb		Passing keyword arguments as ** vs. a dict.ipynb
Peeking at Python bytecodes.ipynb		Peeking at Python bytecodes.ipynb
Pending input error in Jupyter.ipynb		Pending input error in Jupyter.ipynb
Python Pandas series vs. data frame.ipynb		Python Pandas series vs. data frame.ipynb
Python identifiers.ipynb		Python identifiers.ipynb
Python's "range" builtin.ipynb		Python's "range" builtin.ipynb
Python's ternary operator.ipynb		Python's ternary operator.ipynb
README.md		README.md
Randomly sampling your data frame.ipynb		Randomly sampling your data frame.ipynb
Regular expressions in Pandas.ipynb		Regular expressions in Pandas.ipynb
Removing dict pairs with a particular value.ipynb		Removing dict pairs with a particular value.ipynb
Replacing values in Pandas.ipynb		Replacing values in Pandas.ipynb
Retrieving from a multi-index with .loc and .xs.ipynb		Retrieving from a multi-index with .loc and .xs.ipynb
Searching in dicts and dict views.ipynb		Searching in dicts and dict views.ipynb
Shallow vs. deep copies.ipynb		Shallow vs. deep copies.ipynb
Simple interpolation.ipynb		Simple interpolation.ipynb
Sorting in Pandas.ipynb		Sorting in Pandas.ipynb
Sorting letter-number combinations.ipynb		Sorting letter-number combinations.ipynb
Sorting lists of strings vs. lists of ints.ipynb		Sorting lists of strings vs. lists of ints.ipynb
Stack and unstack.ipynb		Stack and unstack.ipynb
Stop using inplace=True!.ipynb		Stop using inplace=True!.ipynb
Strings, immutability, and +=.ipynb		Strings, immutability, and +=.ipynb
The "glob" module.ipynb		The "glob" module.ipynb
The "replace" method in Pandas.ipynb		The "replace" method in Pandas.ipynb
The columns keyword argument.ipynb		The columns keyword argument.ipynb
Underscores in numbers.ipynb		Underscores in numbers.ipynb
Understanding mask indexes.ipynb		Understanding mask indexes.ipynb
Understanding the SettingWithCopyWarning in Pandas.ipynb		Understanding the SettingWithCopyWarning in Pandas.ipynb
Unicode characters and Python.ipynb		Unicode characters and Python.ipynb
Untitled.ipynb		Untitled.ipynb
Untitled1.ipynb		Untitled1.ipynb
Untitled2.ipynb		Untitled2.ipynb
Untitled3.ipynb		Untitled3.ipynb
Untitled4.ipynb		Untitled4.ipynb
Untitled5.ipynb		Untitled5.ipynb
Untitled6.ipynb		Untitled6.ipynb
Use less memory in your Pandas data frames.ipynb		Use less memory in your Pandas data frames.ipynb
Uses for "vars".ipynb		Uses for "vars".ipynb
Using "cut" in Pandas.ipynb		Using "cut" in Pandas.ipynb
Using Jupyter as a Unix shell.ipynb		Using Jupyter as a Unix shell.ipynb
Using melt in Pandas.ipynb		Using melt in Pandas.ipynb

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