#jubilantfoodworks
low risk entry setup entry abv 3320 SL 3190 let it ride towards 4800
#AhmedabadNest #relativestrength #outperformance #investing #india
More from NISHSHKUMAR JAANI
More from Jublfood
#JUBLFOOD-4362
As the stock price trying to enter in to
new Orbit (#Fibonacci extension6.857%(4491)
Further Fibonacci extension projection ploted on chart.
Long term perspective.
#Probability https://t.co/fPSLKLDxln
As the stock price trying to enter in to
new Orbit (#Fibonacci extension6.857%(4491)
Further Fibonacci extension projection ploted on chart.
Long term perspective.
#Probability https://t.co/fPSLKLDxln
#JUBLFOOD -3940
— Waves_Perception(Dinesh Patel) \u092e\u0948\u0902Schedule Tribes) (@idineshptl) August 17, 2021
Moving higher towards objective
6.857%(4491)#Probability https://t.co/oKppKL59mG
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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.