How to Convert the Unix Timestamp From UTC To Your Local Timezone

Jan. 11, 2023, 2:36 a.m.by CryptoDataDownload

What is meant by "Unix Timestamp" and "Epoch Time"?

A Unix timestamp is the number of seconds since January 1, 1970, at 00:00:00 UTC. It is commonly used in computer systems and other applications that use time representation internally.

Epoch time, on the other hand, is a more general term that refers to a point in time relative to some fixed reference point. The reference point for Unix timestamps is the Unix epoch, which is January 1, 1970, at 00:00:00 UTC. So in that sense, a Unix timestamp is a specific type of epoch time. But other systems and applications may use different reference points, such as the beginning of a particular year or the launch of a satellite, and these would be considered different types of epoch time.

Unix Timestamps and Cryptocurrency

Cryptocurrency transactions occur on market exchanges around the clock, a full 24/7. These crypto ecosystems are run by computers that are based in UTC time. When their data centers or APIs return OHLC or trade information, that timestamp / time interval is conveyed in computer time; which is likely different than your local time zone. For instance, the East coast of the US is considered UTC - 5 hours. When we write the files, our servers are likely (possibly) in a different time zone than you are located. The script we wrote is super short, and every line is documented. Basically we will download the BTC/USD hourly file from Bitstamp and add a new date column that will align with our local time zone, and save the resulting CSV file to our machine.

# CryptoDataDownload
# No Express Warranty
import pandas as pd
import ssl

# change the ssl state so we do not see an error for https:// content
ssl._create_default_https_context = ssl._create_unverified_context

# turn off pandas SettingWithCopyWarning
pd.options.mode.chained_assignment = None  # default='warn'

def main():
    """This is the main function of the script. What we are doing is quite basic but as follows:
       1) Pull the CSV file from website and read it as a Pandas DataFrame
       2) Drop the date column already in the file
       3) Re-write the date function to add date but it will use your computer's time
       4) save the file

"""
    url = 'https://www.cryptodatadownload.com/cdd/Bitstamp_BTCUSD_1h.csv'   # file url 
    df = pd.read_csv(url, skiprows=1)    # read csv file into dataframe
    df.drop(columns=['date'], inplace=True)  # drop the date column in place (modify current dataframe and 'save it')
    df['date'] = pd.to_datetime(df['unix'], unit='s')  # add new date column using the epoch/unix timestamp
    df.to_csv('date_in_local_timezone.csv')  # save CSV file to your machine

if __name__ == "__main__":
    """
    This is an example for how to change the "human time" in the OHLC timeseries files to your local timezone 
    using the unix timestamp column (also called epoch time)
    """
    main()

Notice: Information contained herein is not and should not be construed as an offer, solicitation, or recommendation to buy or sell securities. The information has been obtained from sources we believe to be reliable; however no guarantee is made or implied with respect to its accuracy, timeliness, or completeness. Author does not own the any crypto currency discussed. The information and content are subject to change without notice. CryptoDataDownload and its affiliates do not provide investment, tax, legal or accounting advice.

This material has been prepared for informational purposes only and is the opinion of the author, and is not intended to provide, and should not be relied on for, investment, tax, legal, accounting advice. You should consult your own investment, tax, legal and accounting advisors before engaging in any transaction. All content published by CryptoDataDownload is not an endorsement whatsoever. CryptoDataDownload was not compensated to submit this article. Please also visit our Privacy policy; disclaimer; and terms and conditions page for further information.

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