Python in algorithmic trading - page 6

[MetaQuotes]

How to collect detailed symbol information with Python and MetaTrader 5

COMO COLETAR INFORMAÇÕES DETALHADAS DE ATIVOS FINANCEIROS COM PYTHON E MT5

The video demonstrates how to collect detailed information on a specific financial asset using Python and the MT5 platform. The information collected includes various details about the asset's trading volume, pip values, and bid/ask prices, among other things. This section of the video also covers the conversion of the collected information into dictionary format for easier analysis. The video provides insights into how to collect and analyze financial data using Python programming.

• 00:00:00 In this section of the video, the presenter demonstrates how to collect detailed information on a specific asset using Python and the MT5 platform. Previously, the presenter had shown how to use the "get symbols" command to collect all available assets from a broker, but in this case, the focus is on collecting specific information for one asset, Petrobras preferred shares. The presenter uses the "Simple E" function to collect this information, and demonstrates how to convert the resulting variable into a dictionary format for easier analysis. The information collected includes details about the asset's trading volume, digit and pip values, and bid/ask prices, among other things.
  
  
• 00:05:00 In this section, the video covers detailed information that can be collected from financial assets, such as last trade, real volume, opening of the day, derivatives market information, and more. The speaker also demonstrates how to collect this information using Python and MT5 platform. They also show how to access the retrieved information by creating a dictionary and using a for loop to print it. Overall, this section provides insights into how to collect and analyze financial data using Python programming.

[MetaQuotes]

HOW TO TRANSFORM ASSET INFORMATION INTO PYTHON AND MT5 DATAFRAMES

COMO TRANSFORMAR AS INFORMAÇÕES DE ATIVOS EM DATAFRAMES PYTHON E MT5

This YouTube video highlights the process of converting asset information from dictionaries into data frames in Python and MT5. The instructor explains how to use the select statement to collect information and then convert it to a list of tuples, which can later transform into a data frame using the pandas library. They provide step-by-step guidance on creating a list, naming the columns and transforming it into a data frame. The tutorial aims to encourage viewers to utilize Python and MQL5 for creating investment strategies and robots by connecting all these ideas.

• 00:00:00 In this section, the video tutorial explains how to transform information about assets from dictionaries to data frames in Python and MT5. The instructor demonstrates how to collect information using the select statement and how to transform the variable into a list of tuples, which allows the conversion into a data frame. The pandas library, which is pre-installed in the Anaconda environment, is used to transform the variable into a data frame. The instructor shows the steps to create a list and then convert it into a data frame with specific column names.
  
  
• 00:05:00 In this section, the speaker demonstrates how to transform assets information into Python dataframes and MetaTrader 5. They show how to execute the code to establish the columns of the neto Femme and how to work with Zeta films. The speaker encourages the viewer to continue connecting all their ideas for creating investment strategies and robots using Python and mql5.

[MetaQuotes]

HOW TO COLLECT THE CLOSE PRICES OF VARIOUS ASSETS IN DATAFRAME - Python and MetaTrader 5

COMO COLETAR OS CLOSES DE VÁRIOS ATIVOS EM DATAFRAME - PYTHON E MetaTrader 5

The video teaches how to automate the process of collecting and storing the closing prices of multiple assets into a Pandas DataFrame using Python and MetaTrader 5. The process involves creating a portfolio of assets, using a for loop to collect their closing prices based on a specific date range, and transforming the collected data into a DataFrame. The tutorial provides an excellent example for traders interested in automating their data collection process. The presenter also shows how to select only the desired values and address errors during data collection, demonstrating a useful troubleshooting process. The resulting DataFrame contains the date and closing price for each asset, which is useful for creating asset trading robots.

• 00:00:00 In this section, the video explains how to collect and store closing prices of multiple assets into a Pandas DataFrame using Python and MetaTrader 5. The process involves creating a portfolio of assets and using a for loop to collect their closing prices based on a specific date range. The video also covers how to transform the collected data into a DataFrame and manipulate its columns. The tutorial provides a useful example for traders interested in automating their data collection process.
  
  
• 00:05:00 In this section of the video, the presenter explains how to transform a timestamp format column to a date-time format one using Python and MetaTrader 5. The transformed data is then stored in a dataframe, and the presenter shows how to select only the desired values (in this case, the closing values) to create a new dataframe containing only the selected data. The presenter encounters an error during data collection, which he then identifies and addresses, demonstrating a useful troubleshooting process.
  
  
• 00:10:00 In this section of the video, the speaker demonstrates how to collect and organize the closing prices for multiple assets into a pandas dataframe using Python and MetaTrader 5. The speaker emphasizes the importance of understanding the logic behind the code and studying the pandas library to be able to modify and manipulate the data. The resulting dataframe contains the date and closing price for each asset, which will be used in future videos to collect real-time price data for asset trading robots. The speaker encourages viewers to like the video and leave comments about their progress and learning experience.

[MetaQuotes]

HOW TO GET REAL TIME ASSET PRICES WITH PYTHON AND METATRADER 5

COMO OBTER PREÇOS DE ATIVOS EM TEMPO REAL PYTHON E MT5

The YouTube video demonstrates how to use Python and MetaTrader 5 to obtain real-time asset prices by running a loop that continuously collects data on closing prices at two-second intervals. The speaker converts the collected data into a date and time format and shows how to extract the last five values of an asset's closing prices. While the asset's closing values do not fluctuate much in the example shown, the method can be used to collect data on any desired asset. Additionally, the video mentions the availability of a similar function that collects data on buy and sell prices for each execution moment in the market.

• 00:00:00 In this section of the video, the speaker demonstrates how to continuously collect real-time information on a particular asset's closing values using a never-ending loop in Python. They begin by converting the collected data into a Data Frame and then transform the time column into a date and time format. By running the necessary code, the speaker then shows how to collect the last five values of the asset's closing prices at two-second intervals and print the current value of the latest closing price in real-time. Although the asset's closing values are not fluctuating significantly in this example due to low liquidity, the speaker notes that one can collect any data desired using this method.
  
  
• 00:05:00 In this section, the speaker shows how to obtain real-time asset prices using Python and MT5. By running a loop that collects data from the latest line of Open High low Close volume, the function continuously collects real-time data on the price and volume of assets. By pressing 'Stop', the function is paused, and the data can then be used for further analysis. The speaker also mentions the availability of a similar function that can collect data on the buy and sell prices of assets for each execution moment within the market.

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HOW TO CONTINUOUSLY SAVE IN FILE DATA OBTAINED WITH METATRADER 5 AND PYTHON

COMO SALVAR EM ARQUIVO CONTINUAMENTE DADOS OBTIDOS COM PYTHON DO METATRADER 5

This video tutorial demonstrates the process of collecting and saving real-time financial data obtained through Python from MetaTrader 5 by using the Pandas library's DataFrame method to create a CSV file. The video covers how to modify the file into a row-based data structure for better organization and shows how to delete headers and indexes. It also explains how to save the data as an Excel file with a few tweaks.

• 00:00:00 In this section, the video explains how to save real-time information obtained through Python from MetaTrader 5 and save it to a CSV file. The video shows how to collect and save data in a CSV file and how to modify that file to have the data stored in rows instead of columns, thereby creating a more suitable data structure. The process involves using the Pandas library and its DataFrame method, and the video walks through each step, including how to name the file and specify the saving mode.
  
  
• 00:05:00 In this section, the video tutorial explains how to save continuously-obtained data from Python on MetaTrader 5 in a file using transposition. The data is transformed from rows to columns for easier organization and saved in a file. The tutorial also covers how to delete headers and indexes using a command and shows how the data can be saved as an Excel file with a few adjustments.

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HOW TO ADD SYMBOLS IN METATRADER 5 MARKET WATCH WITH PYTHON

COMO ADICIONAR ATIVOS NA OBSERVAÇÃO DE MERCADO MT5 COM PYTHON

This YouTube tutorial teaches users how to add new assets to the MetaTrader 5 market watch using Python. The tutorial explains how to gather information about an asset using Meta Trader and add it to the observation market. By adding an asset, users gain access to more detailed information such as opening and closing prices and volume. The tutorial emphasizes the importance of this feature for those programming their own trading bots.

• 00:00:00 In this section of the YouTube tutorial, the instructor explains how to add a new asset to the MetaTrader5 market watch using Python. By adding an asset to the observation market, the user gains access to more precise information such as opening and closing prices, volume, and other additional details. The tutorial discusses how to load an asset and gather its information using Meta Trader, and shows how to add the asset to the observation market using a command. The benefits of adding an asset and gaining access to more detailed information are also highlighted.
  
  
• 00:05:00 In this section, the video demonstrates how to add assets to the market observation panel in MT5 using Python. The host shows the viewers how to add and remove assets and modify their values in the panel. The host highlights the importance of this feature for those who are programming their own trading bo

[MetaQuotes]

HOW TO PLOT CANDLES CHARTS WITH PYTHON AND METATRADER5

COMO PLOTAR GRÁFICOS DE CANDLES COM PYTHON E MetaTrader 5

This video tutorial covers the process of plotting candlestick charts using Python and MetaTrader 5. The instructor uses the cufflinks library to import and manipulate data from MetaTrader 5, shows how to use pandas to generate interactive and customized charts, and explains how to transform the data into a dataframe to utilize the Pandas library functions for charting. Additionally, they demonstrate how to customize charts, transform data index to date and time, and provide code and commands for users to create their own customized charts for financial analysis.

• 00:00:00 In this section, the video tutorial showcases how to plot candlestick charts with Python and MetaTrader 5. The instructor explains that the data from MetaTrader 5 can be brought into the Python/Jupyter platform using various libraries such as matplotlib or prole, but in this tutorial, they use the cufflinks library. The instructor walks through the installation and necessary configuration steps to use cufflinks and demonstrates how the pandas library is used to import and manipulate the necessary data for generating interactive and customised charts. Finally, the instructor shows how to transform the data into a dataframe and make use of the functions in the Pandas library for descriptive statistics before plotting the candlestick chart.
  
  
• 00:05:00 In this section, the video tutorial demonstrates how to plot candlestick charts using Python and MetaTrader 5. The tutorial utilizes a library called "ai pros" to create simple candlestick charts with high-low and close data from a dataframe. The tutorial also shows how to customize the charts and transform the data index to date and time. Code and commands are provided to help users create their own customized charts for financial analysis.

[MetaQuotes]

How to Host a Robot (Expert Advisor) on a MetaTrader 5 VPS

Como Hospedar um Robô (Expert Advisor) numa VPS do MetaTrader 5

The video provides guidance on how to host an Expert Advisor (robot) on a VPS machine using MetaTrader 5. Users must select and purchase a plan on the mql5.com website after logging into the platform, making sure that they have a configuration that is equal to or above version 3063 to use the service. This feature can help users avoid issues with power outages and internet connectivity when running the robot.

[MetaQuotes]

HOW TO FILTER DATES AND TIMES IN DATAFRAMES WITH PYTHON

COMO FILTRAR DATAS E HORAS EM DATAFRAMES COM PYTHON

In this YouTube video, the YouTuber demonstrates how to filter data and extract information based on time in a data frame using Python. They use MetaTrader 5 to import data and prices and then show how to use the pandas library to work with the data frame. The speaker explains how to transform the time columns into strings and how to filter the data frame based on specific hours using a lambda function applied row by row. This video is helpful for those who want to develop complex strategies and work with data analysis using Python and MetaTrader 5. It provides a good explanation of the apply function and filtering data frames based on conditions.

• 00:00:00 In this section, the YouTuber explains how to filter data and information based on time in a data frame using Python. The video demonstrates the use of MetaTrader 5 to import data and prices and then shows how to use the pandas library to work with the data frame. The YouTuber shows how to transform the array instance into a data frame and how to filter a particular hour to collect specific information from the open-highway close. The video is helpful for those who want to work with data analysis and develop complex strategies using Python and MetaTrader 5.
  
  
• 00:05:00 In this section, the speaker explains how to filter and manipulate dates and times in a DataFrame using Python. They demonstrate how to investigate a specific column in the DataFrame and retrieve information based on matching values. They also explain how to transform the time columns into strings and format the time according to the desired format. They use this formatting to filter and extract information from each row in the DataFrame, allowing for more precise data analysis.
  
  
• 00:10:00 In this section, the speaker explains how to filter data frames based on specific dates and times using Python. The apply function is used to apply a lambda function row by row to a particular column, with the lambda function taking in a single variable (represented as x) for each row. The speaker demonstrates how to extract only the hours for each row and format it as a string, and then filter the data frame based on specific hours using the obtained string. The concept of the apply function and filtering data frames based on certain conditions is important to understand when working with data in Pytho

[MetaQuotes]

HOW TO DOWNLOAD METATRADER 5 DATA AND OPEN WITH PYTHON

COMO BAIXAR DADOS DO METATRADER 5 E ABRIR COM PYTHON

The video tutorial explains how to download data from MetaTrader 5 and open it with Python. The process involves identifying the necessary data and downloading it, opening and manipulating the data in Python using libraries like Pandas, and resolving common errors such as proper data separation using tab separators.

• 00:00:00 In this section, the video explains how to download data from MetaTrader 5 and open it using Python. The tutorial starts by identifying the data needed and the specifications for the data download. Once data is downloaded, the video shows how to open it using Jupyter Notebook and import necessary libraries such as Pandas to manipulate the data. Additionally, the video highlights common errors and provides solutions to resolve them.
  
  
• 00:05:00 In this section, the video discusses the process of downloading data from MetaTrader 5 and opening it with Python. The data file captured from MetaTrader 5 may not be separated appropriately, but can be opened with free software such as Notepad++. The data is separated by tabs rather than commas, so in order to properly read the data with pandas, users need to specify the tab as a separator. Once the data is properly separated, it can be used in Python for further analysis.
  
  
• 00:10:00 This transcript excerpt does not contain any relevant information for a summary. It is a message from the speaker promoting his Telegram channel and encouraging viewers to like and subscribe to his videos.