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can we improve the latency in above code with defining data structure like 16 or 64 bit int

Sleepy Seal answered on July 20, 2023 Popularity 1/10 Helpfulness 1/10

answer can we improve the latency in above code with defining data structure like 16 or 64 bit int

can we improve the latency in above code with defining data structure like 16 or 64 bit int

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import pandas as pd
import numpy as np

def candlestick_analysis(time_series_data):
    # Convert the DataFrame to NumPy arrays with 16-bit integers for open and close prices
    open_prices = time_series_data['open'].to_numpy(dtype=np.float16)
    close_prices = time_series_data['close'].to_numpy(dtype=np.float16)

    # Rest of the code remains the same...

    return time_series_data

# Example usage:
# Assuming you have a DataFrame 'df' with timestamp as index and columns 'open', 'high', 'low', and 'close'
# df = pd.read_csv('time_series_data.csv', parse_dates=['timestamp'], index_col='timestamp')
# analyzed_data = candlestick_analysis(df)

Popularity 1/10 Helpfulness 1/10 Language python

Source: chat.openai.com

Tags: 64-bit int latency python structure

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Contributed on Jul 20 2023

Sleepy Seal

0 Answers Avg Quality 2/10

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can we improve the latency in above code with defining data structure like 16 or 64 bit int

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