MQL5 ReferencePython Integrationcopy_rates_from_pos

copy_rates_from_pos

Get bars from the MetaTrader 5 terminal starting from the specified index.

copy_rates_from_pos(
   symbol,       // symbol name
   timeframe,    // timeframe
   start_pos,    // initial bar index
   count         // number of bars
   )

Parameters

symbol

[in] Financial instrument name, for example, "EURUSD". Required unnamed parameter.

timeframe

[in] Timeframe the bars are requested for. Set by a value from the TIMEFRAME enumeration. Required unnamed parameter.

start_pos

[in] Initial index of the bar the data are requested from. The numbering of bars goes from present to past. Thus, the zero bar means the current one. Required unnamed parameter.

count

[in] Number of bars to receive. Required unnamed parameter.

Return Value

Returns bars as the numpy array with the named time, open, high, low, close, tick_volume, spread and real_volume columns. Returns None in case of an error. The info on the error can be obtained using last_error().

Note

See the CopyRates() function for more information.

MetaTrader 5 terminal provides bars only within a history available to a user on charts. The number of bars available to users is set in the "Max. bars in chart" parameter.

Example:

from datetime import datetime
import MetaTrader5 as mt5
# display data on the MetaTrader 5 package
print("MetaTrader5 package author: ",mt5.__author__)
print("MetaTrader5 package version: ",mt5.__version__)

# import the 'pandas' module for displaying data obtained in the tabular form
import pandas as pd
pd.set_option('display.max_columns', 500) # number of columns to be displayed
pd.set_option('display.width', 1500)      # max table width to display

# establish connection to MetaTrader 5 terminal
if not mt5.initialize():
    print("initialize() failed, error code =",mt5.last_error())
    quit()

# get 10 GBPUSD D1 bars from the current day
rates = mt5.copy_rates_from_pos("GBPUSD", mt5.TIMEFRAME_D1, 0, 10)

# shut down connection to the MetaTrader 5 terminal
mt5.shutdown()
# display each element of obtained data in a new line
print("Display obtained data 'as is'")
for rate in rates:
    print(rate)

# create DataFrame out of the obtained data
rates_frame = pd.DataFrame(rates)
# convert time in seconds into the datetime format
rates_frame['time']=pd.to_datetime(rates_frame['time'], unit='s')

# display data
print("\nDisplay dataframe with data")
print(rates_frame)

Result:
MetaTrader5 package author:  MetaQuotes Software Corp.
MetaTrader5 package version:  5.0.29

Display obtained data 'as is'
(1581552000, 1.29568, 1.30692, 1.29441, 1.30412, 68228, 0, 0)
(1581638400, 1.30385, 1.30631, 1.3001, 1.30471, 56498, 0, 0)
(1581897600, 1.30324, 1.30536, 1.29975, 1.30039, 49400, 0, 0)
(1581984000, 1.30039, 1.30486, 1.29705, 1.29952, 62288, 0, 0)
(1582070400, 1.29952, 1.3023, 1.29075, 1.29187, 57909, 0, 0)
(1582156800, 1.29186, 1.29281, 1.28489, 1.28792, 61033, 0, 0)
(1582243200, 1.28802, 1.29805, 1.28746, 1.29566, 66386, 0, 0)
(1582502400, 1.29426, 1.29547, 1.28865, 1.29283, 66933, 0, 0)
(1582588800, 1.2929, 1.30178, 1.29142, 1.30037, 80121, 0, 0)
(1582675200, 1.30036, 1.30078, 1.29136, 1.29374, 49286, 0, 0)

Display dataframe with data
        time     open     high      low    close  tick_volume  spread  real_volume
0 2020-02-13  1.29568  1.30692  1.29441  1.30412        68228       0            0
1 2020-02-14  1.30385  1.30631  1.30010  1.30471        56498       0            0
2 2020-02-17  1.30324  1.30536  1.29975  1.30039        49400       0            0
3 2020-02-18  1.30039  1.30486  1.29705  1.29952        62288       0            0
4 2020-02-19  1.29952  1.30230  1.29075  1.29187        57909       0            0
5 2020-02-20  1.29186  1.29281  1.28489  1.28792        61033       0            0
6 2020-02-21  1.28802  1.29805  1.28746  1.29566        66386       0            0
7 2020-02-24  1.29426  1.29547  1.28865  1.29283        66933       0            0
8 2020-02-25  1.29290  1.30178  1.29142  1.30037        80121       0            0
9 2020-02-26  1.30036  1.30078  1.29136  1.29374        49286       0            0