More from Gurleen
HDFC Update
2715 📍
In Weekly; next in-line 2850.
In Monthly; Once ATH is taken out, A sight of 3000+ would be caught.
#StockMarket #StocksInFocus #HDFC https://t.co/VpM9Yvbq7l
2715 📍
In Weekly; next in-line 2850.
In Monthly; Once ATH is taken out, A sight of 3000+ would be caught.
#StockMarket #StocksInFocus #HDFC https://t.co/VpM9Yvbq7l

#HDFC Daily and Weekly TF's
— Gurleen (@GurleenKaur_19) August 3, 2021
Broken past the descending trendline; A follow-up beyond '2558' would bring in 2630 initially followed by 2850.
In Monthly; Once ATH is taken out, A sight of 3000+ would be caught.
[Will open position above 2558]#StockMarket #StocksToWatch pic.twitter.com/jRukw5Yh6d
#TATASTLBSL Weekly Update
Once again, approaching towards the zone of 98.35-101.05
A break-through would be a bullish indicative towards a new 52-week high.
#StockMarket #StocksToWatch https://t.co/vHfVB9asXk
Once again, approaching towards the zone of 98.35-101.05
A break-through would be a bullish indicative towards a new 52-week high.
#StockMarket #StocksToWatch https://t.co/vHfVB9asXk

#TATASTLBSL Weekly
— Gurleen (@GurleenKaur_19) August 6, 2021
Sustenance above 98.35 and a break-through at 101.05 will bring in a new 52-week high. #StockMarket #StocksToWatch #Metals pic.twitter.com/W5G6OeqQB9
More from Radico
#Radico reached our 1st target and is trading at 870 now.
@MD_ABNSTOCKS
@MD_ABNSTOCKS
#Radico #StockToWatch #Stock #Equity #StockMarket
— Team MD&ABN (@team_md_abn) July 10, 2021
CMP - 779
Entry - once price closes above 783 in the hourly chart
Pattern invalid below - 736.50
Possible upside Levels
Conservative - 866
Aggressive - 944@caniravkaria pic.twitter.com/6xD7oywkNC
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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.
