#CDSL -1305
After almost attained 4.618%
Correction likely retracement level shown in chart.
#Possibility

More from MaRkET WaVES (DINESH PATEL ) Stock Market FARMER
#ASIANPAINT-2853
What a beautiful picture
#Wow
एक कलर #लाल भी है
#ASIANPAINT-2931
— Waves_Perception(Dinesh Patel) \u092e\u0948\u0902Schedule Tribe) (@idineshptl) March 3, 2022
Trend down.
Weekly chart. Fibonacci retracement level shown in chart.
Near term 0.236% and 0.382% Fibonacci retracement level likely to be tested.#Perspective pic.twitter.com/cWJ0qaqDhK
What a beautiful picture
#Wow
एक कलर #लाल भी है

More from Cdsl
#cdsl now trading at 817 from 789..
More fireworks yet to come above 827 BO
This is power of AOV analysis feature.
More fireworks yet to come above 827 BO
This is power of AOV analysis feature.
#Areaofvalue analysis#CDSL
— SSStockAlerts (@ssstockalerts) May 6, 2021
Buy near 21 SMA support. This stock respects 21 SMA for 84% time. Backtested for last 1 year.
Candle size is getting smaller and volume also less then avg volume.
Any time it can reverse from here.
Help/Supporthttps://t.co/rRCfjf3KIi pic.twitter.com/KGyyAAQ1tV
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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.
