Thinking in Pandas How to Use the Python Data Analysis Library the Right Way by Hannah Stepanek 2020.pdf
What You Will Learn 📌 Understand the underlying data structure of pandas and why it performs the way it does under certain circumstances 📌 Discover how to use pandas to extract, transform, and load data correctly with an emphasis on performance 📌 Choose the right DataFrame so that the data analysis is simple and efficient. 📌 Improve performance of pandas operations with other Python libraries
Thinking in Pandas How to Use the Python Data Analysis Library the Right Way by Hannah Stepanek 2020.pdf
What You Will Learn 📌 Understand the underlying data structure of pandas and why it performs the way it does under certain circumstances 📌 Discover how to use pandas to extract, transform, and load data correctly with an emphasis on performance 📌 Choose the right DataFrame so that the data analysis is simple and efficient. 📌 Improve performance of pandas operations with other Python libraries
BY Python 🐍 Work With Data
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To pay the bills, Mr. Durov is issuing investors $1 billion to $1.5 billion of company debt, with the promise of discounted equity if the company eventually goes public, the people briefed on the plans said. He has also announced plans to start selling ads in public Telegram channels as soon as later this year, as well as offering other premium services for businesses and users.
Why Telegram?
Telegram has no known backdoors and, even though it is come in for criticism for using proprietary encryption methods instead of open-source ones, those have yet to be compromised. While no messaging app can guarantee a 100% impermeable defense against determined attackers, Telegram is vulnerabilities are few and either theoretical or based on spoof files fooling users into actively enabling an attack.
