Nick

Python programmer, interested & tweeting about data gathering / web scraping + machine learning 🤖 #100daysofcode

[Nick @_stayml]

#Python has many HIGHLY useful string methods enabling of all kinds of character transformations.

🎨 In this thread, I have illustrated the 5 I use almost daily.

(p.s. code included too!)

.lower() - exchanges capital letters for lower case letters, like this 👇

#100DaysOfCode

[Nick @_stayml]

@Ahmedha37175961 Hey, what's up with it?

[Nick @_stayml]

@thephntmzn Yep! I learned lots in only a few months. DM me if you ever want help or advice

[Nick @_stayml]

@oxylabs https://t.co/dZyxEPY9Kn can help 😉

[Thomas Jepsen @JepsenThomas]

🔥🔥🔥 Retweet & follow in the next 24 hours to get this case.

After that, it won't be available for new people.

If you retweeted the last one, you're good. It'll start being sent out tonight.

Anyone that retweets later than 24 hours from now won't get it ❗️❗️❗️

[Nick @_stayml]

@KarthikS2206 Seo

[ソフトアンテナ @softantenna]

https://t.co/xUKiHEsDFp - スクレイピングが捗る！ユーザーエージェント文字列の最新リスト
https://t.co/1gLZyFfhC2

[@kaklabs @kaklabs]

User Agents List - Latest User Agents https://t.co/vIPpzHLBhg

[Cyb3rm0nk @cyb3rm0nk_]

This is really handy
A self-updating list of the most current useragents across operating systems and browsers.
Perfect for web scrapers, researchers, and website administrators looking for reliable, up to date user agent strings.
https://t.co/MCiE7sn5el
#web #scrape #python

[Nick @_stayml]

@angsuman Thanks for sharing it!

[Angsuman Chakraborty ✪ @angsuman]

#fyi A self-updating list of the most current useragents https://t.co/cMSkfEFsoN

[Nick @_stayml]

@dimensionmedia Wow, thanks so much for sharing it! 🤩

[David Bisset @dimensionmedia]

For web developers mainly:

https://t.co/EWPXGPr5l4 is a self-updating list of the most current useragents across operating systems and browsers (via @_stayml)

[Nick @_stayml]

@elonmusk Still get tagged by randoms in nft stuff

[Nick @_stayml]

@heyBarsee pricing

[Nick @_stayml]

Day 51 🚀

Progressing with the nlp course.

Today’s topic was Named-entity recognition: The techniques of identifying and extracting key information (titles, names, places) from within unstructured text.

#100DaysOfCode

[Nick @_stayml]

Day 50 #100DaysOfCode

Deviated from my course a little bit, but stayed on the topic of words.

I explored the wordcloud module in Python

[Samuel Wong @samuel_wong_]

A Very Dangerous Data Science Article https://t.co/4Mt2EM84s4

[Nick @_stayml]

Day 49 #100DaysOfCode

Learned the basics of nlp stemming and lemmatization.

These are methods used to reduce words (and their variations) back to their root.

For example “reading”, “reads” –> “read”

[Nick @_stayml]

Day 48 🚀

I learned about the basics of 🪄tokenization in spacy #python including prefixes, suffixes, infixes, and exceptions.

#100DaysOfCode

[Nick @_stayml]

Day 47 #100DaysOfCode

Continued with the NLP course I’m taking.

Today’s lesson introduced me to the spacy nlp module in #python.