Tag: python

Not all ñ’s are equal!
It’s a good idea to normalize #unicode input. Use unicodedata.normalize().#python pic.twitter.com/44XUeHSXzR

— Daily Python Tip (@python_tip) October 5, 2018

[FREE 2600-page book] #Pandas — #Python Data Analysis Toolkit for #DataScience https://t.co/RxbQXXR3iv #abdsc #BigData #Analytics #AI #MachineLearning #Coding #DataScientists pic.twitter.com/TLem7ukrZ8

— Kirk Borne (@KirkDBorne) October 1, 2018

One of my favorite things in Python. Testing if a string A contains a substring B is just "B in A", for example,

>>> x = 'hello'
>>> y = 'll'
>>> y in x
True#pythontip

— Daily Python Tip (@python_tip) September 24, 2018

Use "\N" escape sequence to print #unicode symbols by name.

>>> print('\N{smiling face with sunglasses}’)
😎#python

— Daily Python Tip (@python_tip) September 19, 2018

Finally the asyncio docs are not an embarrassment to us all. Thanks @1st1, @WillingCarol, @elprans and @andrew_svetlov! https://t.co/5QDid8fo1m

— Guido van Rossum (@gvanrossum) September 18, 2018

New mypy release: https://t.co/PolzR6FUKg -- Callable protocols and more fixes to overload.

— Guido van Rossum (@gvanrossum) September 17, 2018

When using expand=True in pandas.Series.str.split(), the elements will expand out into separate columns. #python #pandas #python pic.twitter.com/jJVLH2kX4P

— Daily Python Tip (@python_tip) September 17, 2018

Task Queues: A Celery Story by Tom Mandersonhttps://pyvideo.org/pycon-au-2018/task-queues-a-celery-story.html. In this talk, you'll learn about why you might want a task queue (and when you definitely don't), when Celery is appropriate, and what you can do when it's not.

— Python Software (@ThePSF) September 15, 2018

dict(zip(list1, list2)) creates a dictionary from two lists.

Example:
>>> keys = ['red', 'green', 'blue']
>>> values = ['#FF0000','#008000', '#0000FF']
>>> color_dictionary = dict(zip(keys, values)) pic.twitter.com/rYjtdkGvaz

— Daily Python Tip (@python_tip) September 13, 2018

#pythontip from @singhjayp:

zip stops without warning when one of the iterables is
exhausted; consider using https://t.co/yR33kQMdOF_longest to avoid that problem

Example: pic.twitter.com/CEvjrZgXP0

— Daily Python Tip (@python_tip) September 11, 2018

Data Anonymization by Bartlomiej Uscilowski - https://t.co/xgsiQriM0Q. This talk discusses two modules: faker and mimesis, for anonymizing customer data.

— Python Software (@ThePSF) September 9, 2018

enumerate() takes a second parameter to change the starting count:

>>> names = ["Alice", "Bob", "Charlie"]
>>> list(enumerate(names, start=101))
[(101, 'Alice'), (102, 'Bob'), (103, 'Charlie')]https://t.co/SECAO6sci5#python

— Daily Python Tip (@python_tip) September 3, 2018