Trump may be best remembered for his use of Twitter as a bully pulpit to stoke controversy or browbeat opponents, but the noise his tweets generated often distracted from the big policy changes he made over his four-year term https://t.co/shNVNMoDfg
The Trump administration put China’s rise in the spotlight and helped forge a bipartisan and increasingly adversarial U.S. view of the world’s second-largest economy
The U.S. economy under Trump had two distinct phases: pre-and post-COVID-19.
Before the pandemic hit in March of 2020, unemployment had hit 50-year lows, wages were rising for lower-income jobs, and the gap between Black and white unemployment was narrowing
Things could have been better, but an 18-month tariff war with China, which cost U.S. companies billions.
Three Federal Reserve rate cuts in 2019 helped blunt the impact
About 21 million jobs disappeared immediately, and 9 million of those still haven’t come back
Trump routinely dismissed scientific consensus that industry was causing global warming and gutted federal science agencies including the Environmental Protection Agency and the Department of Interior, and interfered with their scientific advisory panels
Trump wasn’t happy when judges he appointed ruled against his efforts to overturn the 2020 presidential election results, but his reshaping of the judiciary in a conservative direction is still one of his biggest legacies
The court now has a rock-solid 6-3 conservative majority
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Here we go. Tag 4 des Impeachments. Trumps Verteidigung.
Es wird argumentiert, dass Trump nur habe sicherstellen wollen, dass die Wahl fair abgelaufen sei. Die Verteidigung zeigt Clips einzelner Demokraten, die der Zertifizierung von Trumps Stimmen 2016 widersprechen. (Dass es 2016 keinen von Obama gesandten Mob aufs Kapitol gab?Egal!)
Die intellektuelle Unehrlichkeit ist so unfassbar, ich weiß kaum, wo ich hier überhaupt anfangen soll; so viele fucking Strohmänner auf einmal.
Die Verteidigung spielt random Clips, in denen Demokraten “fight” sagen, fast zehn Minuten lang. Weil Trump 20mal am 6. Januar “fight” gesagt hat. Dies ist kein Witz. Komisch, dass sonst die Folge nie war, dass ein Mob das Kapitol gestürmt hat und Pence hängen wollte
“Dieser Fall geht um politischen Hass” Ich mein, ja. “Die House Managers hassen Donald Trump.”
So close.
Michael van der Veen begins Trump's defense: "The article of impeachment now before the Senate is an unjust and blatantly unconstitutional act of political vengeance" pic.twitter.com/xRaZHEPIaC
— Aaron Rupar (@atrupar) February 12, 2021
Es wird argumentiert, dass Trump nur habe sicherstellen wollen, dass die Wahl fair abgelaufen sei. Die Verteidigung zeigt Clips einzelner Demokraten, die der Zertifizierung von Trumps Stimmen 2016 widersprechen. (Dass es 2016 keinen von Obama gesandten Mob aufs Kapitol gab?Egal!)
Die intellektuelle Unehrlichkeit ist so unfassbar, ich weiß kaum, wo ich hier überhaupt anfangen soll; so viele fucking Strohmänner auf einmal.
Die Verteidigung spielt random Clips, in denen Demokraten “fight” sagen, fast zehn Minuten lang. Weil Trump 20mal am 6. Januar “fight” gesagt hat. Dies ist kein Witz. Komisch, dass sonst die Folge nie war, dass ein Mob das Kapitol gestürmt hat und Pence hängen wollte
WATCH: Trump's defense plays nearly 10 minutes of clips showing Democrats using the word "fight," to defend Trump using the word "fight" about 20 times in his speech to supporters before the Capitol riot began https://t.co/YUg7sgxuDX pic.twitter.com/3eMNp7E2S2
— CBS News (@CBSNews) February 12, 2021
“Dieser Fall geht um politischen Hass” Ich mein, ja. “Die House Managers hassen Donald Trump.”
So close.
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Nano Course On Python For Trading
==========================
Module 1
Python makes it very easy to analyze and visualize time series data when you’re a beginner. It's easier when you don't have to install python on your PC (that's why it's a nano course, you'll learn python...
... on the go). You will not be required to install python in your PC but you will be using an amazing python editor, Google Colab Visit https://t.co/EZt0agsdlV
This course is for anyone out there who is confused, frustrated, and just wants this python/finance thing to work!
In Module 1 of this Nano course, we will learn about :
# Using Google Colab
# Importing libraries
# Making a Random Time Series of Black Field Research Stock (fictional)
# Using Google Colab
Intro link is here on YT: https://t.co/MqMSDBaQri
Create a new Notebook at https://t.co/EZt0agsdlV and name it AnythingOfYourChoice.ipynb
You got your notebook ready and now the game is on!
You can add code in these cells and add as many cells as you want
# Importing Libraries
Imports are pretty standard, with a few exceptions.
For the most part, you can import your libraries by running the import.
Type this in the first cell you see. You need not worry about what each of these does, we will understand it later.
==========================
Module 1
Python makes it very easy to analyze and visualize time series data when you’re a beginner. It's easier when you don't have to install python on your PC (that's why it's a nano course, you'll learn python...
... on the go). You will not be required to install python in your PC but you will be using an amazing python editor, Google Colab Visit https://t.co/EZt0agsdlV
This course is for anyone out there who is confused, frustrated, and just wants this python/finance thing to work!
In Module 1 of this Nano course, we will learn about :
# Using Google Colab
# Importing libraries
# Making a Random Time Series of Black Field Research Stock (fictional)
# Using Google Colab
Intro link is here on YT: https://t.co/MqMSDBaQri
Create a new Notebook at https://t.co/EZt0agsdlV and name it AnythingOfYourChoice.ipynb
You got your notebook ready and now the game is on!
You can add code in these cells and add as many cells as you want
# Importing Libraries
Imports are pretty standard, with a few exceptions.
For the most part, you can import your libraries by running the import.
Type this in the first cell you see. You need not worry about what each of these does, we will understand it later.