Algorithmic trading is revolutionizing financial markets, and Python is at the heart of this transformation. Whether you’re a quantitative trader in Singapore, an investor exploring crypto trading strategies, or searching for the best algorithmic trading software in the USA, mastering Pandas is essential. This video delves into quantitative analysis for trading, exploring OHLC data, market manipulation, and backtesting strategies. Learn how to use Freqtrade strategy and Python to streamline your trading decisions.
Know that you will have to deal with the pandas always because even while data analysis data manipulation time series analysis data cleaning and preparation statistical analysis performance and scalability visualization data integration back testing and strategy development whether it’s a red candle or a green candle so for that what you will do so you will check whether the open price is greater than the closed price or not if the open price is greater I want to print only the initial five rows and up to the market cap I don’t want these columns right so the First Column company name sector industry and market cap so for that what you will do here welcome back to the day 25 of the 100 days of hell with python algo trading in previous session we have covered Panda series and today we’ll be covering the pandas data frame and you know that you will have to deal with the pandas always because even while data analysis data manipulation time series analysis data cleaning and preparation statistical analysis performance and scalability visualization data integration back testing and strategy development so in order to efficiently work with all of these things you have to know the Deep concepts of pandas series and data frame so today.
We will be diving very deep into the pendas data frame and you will realize after this session that how how important it is and once you have attempted all the multiple choice questions and the task questions you will feel so powerful and just with the help of few more libraries like very easy the matlo Li and cbone you will see that how amazing things we can do with the pandas Library so let me quickly show you that what you can achieve with the pandas data frame so without the further Ado let’s Deep dive in The Amazing World of pandas data frame so before starting with the coding examples let me tell you what is ohlc so ohlc stands for open high low and close and sometimes we also use wi along with ohlc so wi stands for volume so generally whenever we fetch data from any Source be it a crypto exchange a Forex exchange or a traditional stock market you will always get the same data and that is O LC V right and that is what needed for your trading or algo trading right so as I have used the ohlc data in previous videos so before going further let me first clearly explain you how does this ohlc works okay so let’s get started with ohlc so here on the screen you can see that we have two candles one is green and another is red right so if you can see it is clearly written that we have a low a high on the green candle similarly a low and high on the red candle right similarly.
We have a open and a close on green candle but in red candle it is different the open is on the top and the close is on the bottom so how does we Define this o lcv so let me show you so generally so whenever you see any trading chart you will see these type of data it can be a Candlestick chart it can be a bar or it can be any other type of bar or candlesticks but more or less you will have this kind of structure right so here if you can see you will observe that from here this place the price is going up this phase is known as the manipulation right so along with olcv you will also learn something else again this price will increase from here to here and this phase is known as the distribution right distribution and again here it comes the manipulation and and this will also the distribution correct and here you can say it is manipulation and this little bit phase known as the accumulation right okay then what else we have in this chart okay let’s focus on one candle so I’ll remove this for now you will see that this one candle dropped from this place to this place right so we can say that this candle started from this this point and closed at this point right so you can say this is known as the open of this red candle and this is the close correct then let’s say if this candle was of the 1 hour chart okay 1 hour so means we can say in 1 hour there were multiple 1 minutes or 5 minutes scandles right so what happened in that particular 1 hour this candle reached at this point the top this point right so you can draw a line here and you can mark it as the high high of that particular candle and also this candle reached the low of this point right so you can mark it as the low hope now.
You’re able to understand that this candle opened at this point which is the open and closed at this which is known as the close and in that particular 1 hour it reached to this highest point this highest point and this lowest point so these are known as the high and low so let’s say let’s give it some value so opened at 100 right and closed at 80 and we can consider high as 120 and low as 60 right hope it’s clear so this ohlc data is for this red candle we can say ohlc and this is the volume so sometime we also need a volume also so we say o LC V correct similarly when we check about the green candle so what happened here this green candle opened at this place this point O closed at this point which is C and in this 1 hour it reachs to the highest point of this right and the lowest point of this one this this is lowest this is highest correct so again you can give some values here so opened at let’s say 80 and close at let’s say 855 correct highest you can give it as 90 and lowest you can give it as let’s say 75 so this is the O LC data of this green candle correct the only thing you need to notice here is that in red candle the open is at the top and in green candle the open is at the bottom right similarly in red candle the close is at the bottom but the Clos in green candle is at the top right hope it’s clear and if you still have any doubt you can let me know in the comments and I can repeat this again in any other video right okay now.
Let me compare this with a data frame so now if you can see on the screen that we have data of one day right you can see here this is 1st January 2015 this is 2nd January 2015 right so let’s suppose these old candles are one day chart so let’s suppose these all candles are one day chart means each one candle represents a single day right so you can say here that open is 101 right so let me just remove this one first so now how you can identify from a data frame that whether it’s a red candle or a green candle so for that what you will do so you will check whether the open price is greater than the close price or not if the open price is greater than the close price so means if the open price is greater than the Clos price means that is a red candle correct and if the open price is less than the Clos price means that is a green candle as simple as that let me show you how again so let’s see on this first row this one you can see here open is 10 1.03 and close is 10119 means open is less than the close means that is the green candle and we can also represent that in a candle let’s say open means this open is 101 right then close is 101 so let’s suppose this is the close correct so open is below the close means that is the green candle again let’s check on the next row and here the open is 100 and low is 99 means now the open is greater than the close right so we can say means this open is greater than the close which is here and this is a red candle I hope you are able to understand what I’m trying to say and this volume is this candle this one this bar is the volume bar don’t worry.
We will understand this in DET dail in further videos but for now as we are using this o lcv data that’s why I thought it’s important to explain you the O lcv data right hope it’s uh crystal clear for you now but if you still have any doubt please let us know in the comments and we’ll be happy to help you and you can also let us know that which kind of explanation you like and how we can improve the explanation for you and what else you need for your better understanding so with that being said let’s dive into the coding part okay so let’s create a data frame so we have seen that a data frame is nothing but a combination of multiple series or we can say a series is nothing but a single column or a single row of a data frame and we know that the pendas consider a table as a data frame right so let’s quickly go and create a data frame with the help of a list so let’s say I’ll create a 2 list right and inside that I’ll give some price data so let’s say one let’s take 100 200 3 400 and 600 right and inside that I’ll pass Multiple List so what I’ll do I’ll just give here a comma then again a list comma then again a list a comma and again my list so means we have a 2d list right and now what we can do we can simply write the PD data frame class and inside that we can pass this price data list so when we hit shift enter it says PD is not defined why because we have to run this cell and we have seen that whenever we import Panda’s Library please import numpy also along with the pendas so I’ll go here and hit shift enter And now when I run this you will see that we have a data frame created so what I’ll do here.
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