Python/Jupyter - Parsing csv/text/xls file to python dataframe within a class
Budget: $30 – $250 AUD
Description
Parsing csv/text/xls file to python dataframe within a class
Language: Python (ideally Jupyter/VS code)
Given a csv, txt or spreadsheet file of stock execution data (example input.xls will be provided), I want a function that does the following:
i) Prompts the user:
a. “Please select which columns to use for:”
i. Executed price
ii. Executed volume
iii. Executed time
iv. Execution date
v. Buy/sell direction
vi. Security
vii. Executing broker (optional)
Ultimately this will be used as part of a UI, so the quality of the interface isn’t too important.
ii) Using the above selection, the function condenses the data into 5 minute intervals starting at 9:55am, 10am, 10:05am, 10:10am etc. At each 5 minute time slice, we need to display the volume traded over the previous 5m and the volume weighted average price. We need to do this for each security. Direction should be the same.
a. The output needs to be a class object containing two dataframes (i) price, and (ii) volume (example_output.xls will be provided for format).
More info/comments
The input in (i) can take many different formats and column headers, which is why the user needs to select the column.
In (i) sometimes the date and time may be combined. The code needs to be able to recognize this and differentiate date from time for the output.
There will be a third component, and that is for the class output to accommodate several days trading. We can chat about that in more detail and can be quoted separately if it's complex.
Parsing csv/text/xls file to python dataframe within a class
Language: Python (ideally Jupyter/VS code)
Given a csv, txt or spreadsheet file of stock execution data (example input.xls will be provided), I want a function that does the following:
i) Prompts the user:
a. “Please select which columns to use for:”
i. Executed price
ii. Executed volume
iii. Executed time
iv. Execution date
v. Buy/sell direction
vi. Security
vii. Executing broker (optional)
Ultimately this will be used as part of a UI, so the quality of the interface isn’t too important.
ii) Using the above selection, the function condenses the data into 5 minute intervals starting at 9:55am, 10am, 10:05am, 10:10am etc. At each 5 minute time slice, we need to display the volume traded over the previous 5m and the volume weighted average price. We need to do this for each security. Direction should be the same.
a. The output needs to be a class object containing two dataframes (i) price, and (ii) volume (example_output.xls will be provided for format).
More info/comments
The input in (i) can take many different formats and column headers, which is why the user needs to select the column.
In (i) sometimes the date and time may be combined. The code needs to be able to recognize this and differentiate date from time for the output.
There will be a third component, and that is for the class output to accommodate several days trading. We can chat about that in more detail and can be quoted separately if it's complex.