Reuven M. Lerner
@lernerpython.com
Helping you become more confident with Python and Pandas since 1995.
• Courses: LernerPython.com
• Newsletters: BetterDevelopersWeekly.com • BambooWeekly.com
• Books: PythonWorkout.com • PandasWorkout.com
• Videos: YouTube.com/reuvenlerner
• Courses: LernerPython.com
• Newsletters: BetterDevelopersWeekly.com • BambooWeekly.com
• Books: PythonWorkout.com • PandasWorkout.com
• Videos: YouTube.com/reuvenlerner
Pinned
Reuven M. Lerner
@lernerpython.com
· Nov 12
Hi there! 👋 I'm Reuven, and I've been teaching #Python and Pandas around the world since 1995.
Just about every day, my students ask great questions. I love sharing those questions (and my answers), along with other resources to help you improve your Python/Pandas fluency.
Just about every day, my students ask great questions. I love sharing those questions (and my answers), along with other resources to help you improve your Python/Pandas fluency.
Instead of choosing which #Python function to run with if/elif/else, use a dispatch table — a dict with functions as values:
from operator import add, sub, mul
ops = {'+':add, '-':sub, '*':mul}
s = input('Enter +, -, or * : ')
r = ops[s](10, 20)
print(f'10 {s} 20 = {r}')
from operator import add, sub, mul
ops = {'+':add, '-':sub, '*':mul}
s = input('Enter +, -, or * : ')
r = ops[s](10, 20)
print(f'10 {s} 20 = {r}')
February 12, 2026 at 4:30 PM
Instead of choosing which #Python function to run with if/elif/else, use a dispatch table — a dict with functions as values:
from operator import add, sub, mul
ops = {'+':add, '-':sub, '*':mul}
s = input('Enter +, -, or * : ')
r = ops[s](10, 20)
print(f'10 {s} 20 = {r}')
from operator import add, sub, mul
ops = {'+':add, '-':sub, '*':mul}
s = input('Enter +, -, or * : ')
r = ops[s](10, 20)
print(f'10 {s} 20 = {r}')
Woo hoo! 🎉
My book, #Python Workout (2nd edition), is now the #20 best-selling book in programming languages at Amazon.
Thanks so much to everyone who has bought it, and also to everyone leaving such kind reviews.
My book, #Python Workout (2nd edition), is now the #20 best-selling book in programming languages at Amazon.
Thanks so much to everyone who has bought it, and also to everyone leaving such kind reviews.
February 11, 2026 at 7:05 PM
Woo hoo! 🎉
My book, #Python Workout (2nd edition), is now the #20 best-selling book in programming languages at Amazon.
Thanks so much to everyone who has bought it, and also to everyone leaving such kind reviews.
My book, #Python Workout (2nd edition), is now the #20 best-selling book in programming languages at Amazon.
Thanks so much to everyone who has bought it, and also to everyone leaving such kind reviews.
Modern #Python dicts remember insertion order:
d = {'a':10, 'b':20, 'c':30}
list(d) # ['a', 'b', 'c']
d.pop('b') # remove 'b'
d['b'] = 99 # re-add 'b'
list(d) # ['a', 'c', 'b']
This applies in for loops, too!
d = {'a':10, 'b':20, 'c':30}
list(d) # ['a', 'b', 'c']
d.pop('b') # remove 'b'
d['b'] = 99 # re-add 'b'
list(d) # ['a', 'c', 'b']
This applies in for loops, too!
February 11, 2026 at 4:30 PM
Modern #Python dicts remember insertion order:
d = {'a':10, 'b':20, 'c':30}
list(d) # ['a', 'b', 'c']
d.pop('b') # remove 'b'
d['b'] = 99 # re-add 'b'
list(d) # ['a', 'c', 'b']
This applies in for loops, too!
d = {'a':10, 'b':20, 'c':30}
list(d) # ['a', 'b', 'c']
d.pop('b') # remove 'b'
d['b'] = 99 # re-add 'b'
list(d) # ['a', 'c', 'b']
This applies in for loops, too!
How corrupt is your country? The latest index from Transparency International was just released — and in the latest Bamboo Weekly, I pose 6 #Python #Pandas challenges for you to solve with that data.
New questions every Wednesday: bambooweekly.com
New questions every Wednesday: bambooweekly.com
February 11, 2026 at 4:20 PM
How corrupt is your country? The latest index from Transparency International was just released — and in the latest Bamboo Weekly, I pose 6 #Python #Pandas challenges for you to solve with that data.
New questions every Wednesday: bambooweekly.com
New questions every Wednesday: bambooweekly.com
Using #Python defaultdict? Don't pass a value:
d = defaultdict(0) # ❌ Error!
Pass a function that returns the default:
d = defaultdict(int) # int() returns 0
d = defaultdict(list) # list() returns []
d = defaultdict(dict) # dict() returns {}
d = defaultdict(0) # ❌ Error!
Pass a function that returns the default:
d = defaultdict(int) # int() returns 0
d = defaultdict(list) # list() returns []
d = defaultdict(dict) # dict() returns {}
February 10, 2026 at 4:30 PM
Using #Python defaultdict? Don't pass a value:
d = defaultdict(0) # ❌ Error!
Pass a function that returns the default:
d = defaultdict(int) # int() returns 0
d = defaultdict(list) # list() returns []
d = defaultdict(dict) # dict() returns {}
d = defaultdict(0) # ❌ Error!
Pass a function that returns the default:
d = defaultdict(int) # int() returns 0
d = defaultdict(list) # list() returns []
d = defaultdict(dict) # dict() returns {}
Your #Python function takes a filename and **kwargs. But this raises an error, since "filename" is passed twice:
myfunc('outfile.txt', filename='abcd', x=100)
Solution: Set filename to be positional only:
def myfunc(filename, /, **kwargs):
Now *any* keyword argument works!
myfunc('outfile.txt', filename='abcd', x=100)
Solution: Set filename to be positional only:
def myfunc(filename, /, **kwargs):
Now *any* keyword argument works!
February 9, 2026 at 4:30 PM
Your #Python function takes a filename and **kwargs. But this raises an error, since "filename" is passed twice:
myfunc('outfile.txt', filename='abcd', x=100)
Solution: Set filename to be positional only:
def myfunc(filename, /, **kwargs):
Now *any* keyword argument works!
myfunc('outfile.txt', filename='abcd', x=100)
Solution: Set filename to be positional only:
def myfunc(filename, /, **kwargs):
Now *any* keyword argument works!
Break a #Python string into a list of strings with str.split:
s = 'ab cd ef'
s.split() # ['ab', 'cd', 'ef']
Limit splits with maxsplit:
s.split(maxsplit=1) # ['ab', 'cd ef']
Or split from the right, with a limit:
s.rsplit(maxsplit=1) # ['ab cd', 'ef']
s = 'ab cd ef'
s.split() # ['ab', 'cd', 'ef']
Limit splits with maxsplit:
s.split(maxsplit=1) # ['ab', 'cd ef']
Or split from the right, with a limit:
s.rsplit(maxsplit=1) # ['ab cd', 'ef']
February 8, 2026 at 4:30 PM
Break a #Python string into a list of strings with str.split:
s = 'ab cd ef'
s.split() # ['ab', 'cd', 'ef']
Limit splits with maxsplit:
s.split(maxsplit=1) # ['ab', 'cd ef']
Or split from the right, with a limit:
s.rsplit(maxsplit=1) # ['ab cd', 'ef']
s = 'ab cd ef'
s.split() # ['ab', 'cd', 'ef']
Limit splits with maxsplit:
s.split(maxsplit=1) # ['ab', 'cd ef']
Or split from the right, with a limit:
s.rsplit(maxsplit=1) # ['ab cd', 'ef']
Reposted by Reuven M. Lerner
fun fact (or opinion...?) friday: @lernerpython.com's python workout, second edition can help fight AI brain rot.
source (via linkedin): hubs.la/Q042bvtT0
the book:
• on manning: hubs.la/Q042bwqc0
• on amazon: hubs.la/Q042bwGq0
source (via linkedin): hubs.la/Q042bvtT0
the book:
• on manning: hubs.la/Q042bwqc0
• on amazon: hubs.la/Q042bwGq0
February 6, 2026 at 10:36 PM
fun fact (or opinion...?) friday: @lernerpython.com's python workout, second edition can help fight AI brain rot.
source (via linkedin): hubs.la/Q042bvtT0
the book:
• on manning: hubs.la/Q042bwqc0
• on amazon: hubs.la/Q042bwGq0
source (via linkedin): hubs.la/Q042bvtT0
the book:
• on manning: hubs.la/Q042bwqc0
• on amazon: hubs.la/Q042bwGq0
Want to learn #Python, but new to coding?
Most books expect too much. But not my new "AI-Assisted Python for Nonprogrammers"!
It's meant for you. And uses AI to help you learn, *not* to write code for you.
Check it out, in early release: buff.ly/4BCUU49
Most books expect too much. But not my new "AI-Assisted Python for Nonprogrammers"!
It's meant for you. And uses AI to help you learn, *not* to write code for you.
Check it out, in early release: buff.ly/4BCUU49
February 6, 2026 at 2:00 PM
Want to learn #Python, but new to coding?
Most books expect too much. But not my new "AI-Assisted Python for Nonprogrammers"!
It's meant for you. And uses AI to help you learn, *not* to write code for you.
Check it out, in early release: buff.ly/4BCUU49
Most books expect too much. But not my new "AI-Assisted Python for Nonprogrammers"!
It's meant for you. And uses AI to help you learn, *not* to write code for you.
Check it out, in early release: buff.ly/4BCUU49
Think you can't modify a #Python list while iterating? You can append to it:
mylist = [10, 20, 30]
for i in mylist:
print(i)
if i < 100:
mylist.append(i ** 2)
This prints 10, 20, 30, 100, 400, and 900.
BUT don't insert or remove. That'll cause real trouble.
mylist = [10, 20, 30]
for i in mylist:
print(i)
if i < 100:
mylist.append(i ** 2)
This prints 10, 20, 30, 100, 400, and 900.
BUT don't insert or remove. That'll cause real trouble.
February 5, 2026 at 4:31 PM
Think you can't modify a #Python list while iterating? You can append to it:
mylist = [10, 20, 30]
for i in mylist:
print(i)
if i < 100:
mylist.append(i ** 2)
This prints 10, 20, 30, 100, 400, and 900.
BUT don't insert or remove. That'll cause real trouble.
mylist = [10, 20, 30]
for i in mylist:
print(i)
if i < 100:
mylist.append(i ** 2)
This prints 10, 20, 30, 100, 400, and 900.
BUT don't insert or remove. That'll cause real trouble.
Happy 3rd anniversary, Bamboo Weekly!
This is issue 156, marking 3 years of weekly Pandas challenges.
This week, we look at Winter Olympic data. Since they love snow so much, we'll use #Polars along with #Python #Pandas.
Check it out, at bambooweekly.com.
This is issue 156, marking 3 years of weekly Pandas challenges.
This week, we look at Winter Olympic data. Since they love snow so much, we'll use #Polars along with #Python #Pandas.
Check it out, at bambooweekly.com.
February 4, 2026 at 7:27 PM
Happy 3rd anniversary, Bamboo Weekly!
This is issue 156, marking 3 years of weekly Pandas challenges.
This week, we look at Winter Olympic data. Since they love snow so much, we'll use #Polars along with #Python #Pandas.
Check it out, at bambooweekly.com.
This is issue 156, marking 3 years of weekly Pandas challenges.
This week, we look at Winter Olympic data. Since they love snow so much, we'll use #Polars along with #Python #Pandas.
Check it out, at bambooweekly.com.
Think #Python functions can return multiple values? They actually return ONE value, a tuple:
def sum_and_mean(nums):
return sum(nums), sum(nums)/len(nums)
Unpack it into separate variables:
num_sum, num_mean = sum_and_mean([10, 20, 25])
def sum_and_mean(nums):
return sum(nums), sum(nums)/len(nums)
Unpack it into separate variables:
num_sum, num_mean = sum_and_mean([10, 20, 25])
February 4, 2026 at 4:30 PM
Think #Python functions can return multiple values? They actually return ONE value, a tuple:
def sum_and_mean(nums):
return sum(nums), sum(nums)/len(nums)
Unpack it into separate variables:
num_sum, num_mean = sum_and_mean([10, 20, 25])
def sum_and_mean(nums):
return sum(nums), sum(nums)/len(nums)
Unpack it into separate variables:
num_sum, num_mean = sum_and_mean([10, 20, 25])
Let users assign using [] in #Python, with custom logic with __setitem__:
class StringList:
def __init__(self, d):
self.d = d
def __setitem__(self, i, v):
self.d[i] = str(v)
sl = StringList(['2', '4', '6', '8'])
sl[2] = 99
sl.d
['2', '4', '99', '8']
class StringList:
def __init__(self, d):
self.d = d
def __setitem__(self, i, v):
self.d[i] = str(v)
sl = StringList(['2', '4', '6', '8'])
sl[2] = 99
sl.d
['2', '4', '99', '8']
February 3, 2026 at 4:30 PM
Let users assign using [] in #Python, with custom logic with __setitem__:
class StringList:
def __init__(self, d):
self.d = d
def __setitem__(self, i, v):
self.d[i] = str(v)
sl = StringList(['2', '4', '6', '8'])
sl[2] = 99
sl.d
['2', '4', '99', '8']
class StringList:
def __init__(self, d):
self.d = d
def __setitem__(self, i, v):
self.d[i] = str(v)
sl = StringList(['2', '4', '6', '8'])
sl[2] = 99
sl.d
['2', '4', '99', '8']
The __getitem__ method in #Python can do more than simple lookups:
class DoubleIndex:
def __getitem__(self, i):
return i * 2
d = DoubleIndex()
d[5] # returns 10
Use [] for custom logic — returning filenames, random numbers, or database records.
class DoubleIndex:
def __getitem__(self, i):
return i * 2
d = DoubleIndex()
d[5] # returns 10
Use [] for custom logic — returning filenames, random numbers, or database records.
February 2, 2026 at 4:31 PM
The __getitem__ method in #Python can do more than simple lookups:
class DoubleIndex:
def __getitem__(self, i):
return i * 2
d = DoubleIndex()
d[5] # returns 10
Use [] for custom logic — returning filenames, random numbers, or database records.
class DoubleIndex:
def __getitem__(self, i):
return i * 2
d = DoubleIndex()
d[5] # returns 10
Use [] for custom logic — returning filenames, random numbers, or database records.
Want your #Python object to support bracket notation []? Define __getitem__:
class MyList:
def __init__(self, items):
self.items = items
def __getitem__(self, i):
return self.items[i]
m = MyList([1,2,3])
m[0] # returns 1
class MyList:
def __init__(self, items):
self.items = items
def __getitem__(self, i):
return self.items[i]
m = MyList([1,2,3])
m[0] # returns 1
February 1, 2026 at 4:30 PM
Want your #Python object to support bracket notation []? Define __getitem__:
class MyList:
def __init__(self, items):
self.items = items
def __getitem__(self, i):
return self.items[i]
m = MyList([1,2,3])
m[0] # returns 1
class MyList:
def __init__(self, items):
self.items = items
def __getitem__(self, i):
return self.items[i]
m = MyList([1,2,3])
m[0] # returns 1
Gold prices have gone up recently — but by how much?
In the latest Bamboo Weekly, we use #Python and #Pandas to find out. Then we compare its price with silver, and with central banks' gold and dollar holdings.
Get data analysis puzzles every Wednesday: bambooweekly.com
In the latest Bamboo Weekly, we use #Python and #Pandas to find out. Then we compare its price with silver, and with central banks' gold and dollar holdings.
Get data analysis puzzles every Wednesday: bambooweekly.com
January 29, 2026 at 6:59 PM
Gold prices have gone up recently — but by how much?
In the latest Bamboo Weekly, we use #Python and #Pandas to find out. Then we compare its price with silver, and with central banks' gold and dollar holdings.
Get data analysis puzzles every Wednesday: bambooweekly.com
In the latest Bamboo Weekly, we use #Python and #Pandas to find out. Then we compare its price with silver, and with central banks' gold and dollar holdings.
Get data analysis puzzles every Wednesday: bambooweekly.com
#Python gotcha: Forgetting () on method calls!
d = {'a':2, 'b':4}
list(d.items()) # ✅ calls method
list(d.items) # ❌ passes method object
Result:
Error: 'builtin_function_or_method' object is not iterable
Remember: () calls the method!
d = {'a':2, 'b':4}
list(d.items()) # ✅ calls method
list(d.items) # ❌ passes method object
Result:
Error: 'builtin_function_or_method' object is not iterable
Remember: () calls the method!
January 29, 2026 at 4:30 PM
#Python gotcha: Forgetting () on method calls!
d = {'a':2, 'b':4}
list(d.items()) # ✅ calls method
list(d.items) # ❌ passes method object
Result:
Error: 'builtin_function_or_method' object is not iterable
Remember: () calls the method!
d = {'a':2, 'b':4}
list(d.items()) # ✅ calls method
list(d.items) # ❌ passes method object
Result:
Error: 'builtin_function_or_method' object is not iterable
Remember: () calls the method!
Still writing #Python yourself? That's so 2025! Many developers now code via AI.
In my AI-Powered workshops, you'll solve problems using Claude Code. We'll discuss prompts, code output, and testing, and the implications.
Hear more at my free info session today (Thursday): buff.ly/Rs7J4Eh
In my AI-Powered workshops, you'll solve problems using Claude Code. We'll discuss prompts, code output, and testing, and the implications.
Hear more at my free info session today (Thursday): buff.ly/Rs7J4Eh
January 29, 2026 at 8:42 AM
Still writing #Python yourself? That's so 2025! Many developers now code via AI.
In my AI-Powered workshops, you'll solve problems using Claude Code. We'll discuss prompts, code output, and testing, and the implications.
Hear more at my free info session today (Thursday): buff.ly/Rs7J4Eh
In my AI-Powered workshops, you'll solve problems using Claude Code. We'll discuss prompts, code output, and testing, and the implications.
Hear more at my free info session today (Thursday): buff.ly/Rs7J4Eh
Gold! Its price is soaring. 📈
In Bamboo Weekly, we use #Python #Pandas to look at its price, compared with silver, and as a proportion of central bank holdings.
Improve your data-analysis skills every Wednesday, with challenges based on current events, using real-world data sets: buff.ly/kU1JxPZ
In Bamboo Weekly, we use #Python #Pandas to look at its price, compared with silver, and as a proportion of central bank holdings.
Improve your data-analysis skills every Wednesday, with challenges based on current events, using real-world data sets: buff.ly/kU1JxPZ
January 28, 2026 at 11:33 PM
Gold! Its price is soaring. 📈
In Bamboo Weekly, we use #Python #Pandas to look at its price, compared with silver, and as a proportion of central bank holdings.
Improve your data-analysis skills every Wednesday, with challenges based on current events, using real-world data sets: buff.ly/kU1JxPZ
In Bamboo Weekly, we use #Python #Pandas to look at its price, compared with silver, and as a proportion of central bank holdings.
Improve your data-analysis skills every Wednesday, with challenges based on current events, using real-world data sets: buff.ly/kU1JxPZ
