Data Processing and Python Optimization for Bank Nifty
Budget: ₹1,500 – ₹12,500 INR
I need a skilled Python developer to assist with optimizing and consolidating my Bank Nifty 1-minute raw data from November 2020 to July 2024. The final goal is to create a single, streamlined Python script that processes the data from January 2024 onwards and merges all necessary calculations from Jupyter Notebook into one file.
Key Requirements:
- The raw data is in CSV format and includes the fields: Datetime, Open, High, Low, Close.
- The final merged file must include all original raw data fields.
- You will need to clean and optimize the existing code, removing unnecessary parts and renaming functions for clarity.
- Calculate all fields: Prep_1Min, Previous Candle, Consolidation, Time Weight, HH_LL, RSI, MA, BB, ST.
- Validate that the recent data from June and July matches the original merged file.
- Identify and store HH_LL data in a CSV for real-time calculations.
Ideal Skills and Experience:
- Strong proficiency in Python, particularly with data processing and optimization.
- Experience with financial data analysis.
- Familiarity with Jupyter Notebook.
- Excellent attention to detail for data validation.
Please note that I already have code in Jupyter Notebook to calculate the required fields. The main task is to merge all code into a single file and execute it.
The optimization should aim to significantly reduce execution time.
Key Requirements:
- The raw data is in CSV format and includes the fields: Datetime, Open, High, Low, Close.
- The final merged file must include all original raw data fields.
- You will need to clean and optimize the existing code, removing unnecessary parts and renaming functions for clarity.
- Calculate all fields: Prep_1Min, Previous Candle, Consolidation, Time Weight, HH_LL, RSI, MA, BB, ST.
- Validate that the recent data from June and July matches the original merged file.
- Identify and store HH_LL data in a CSV for real-time calculations.
Ideal Skills and Experience:
- Strong proficiency in Python, particularly with data processing and optimization.
- Experience with financial data analysis.
- Familiarity with Jupyter Notebook.
- Excellent attention to detail for data validation.
Please note that I already have code in Jupyter Notebook to calculate the required fields. The main task is to merge all code into a single file and execute it.
The optimization should aim to significantly reduce execution time.