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How to convert timezone of timeseries in python?
How to convert timezone of timeseries in python?
This recipe helps you convert timezone of timeseries in python
Recipe Objective
While operating with over timeseries, we might have time data of any country. Now we wish to change timeseries data with respect to other country. We can do it by add/subtracting specific time but it can be done in one go using pytz library.
So this recipe is a short example on how to convert timezone of timeseries in python. Let's get started.
Step 1 - Import the library
import pandas as pd
import pytz
Let's pause and look at these imports. Pandas is generally used for performing mathematical operation and preferably over arrays. pytz library allows accurate and cross platform timezone calculations.
Step 2 - Setup the Data and timezone
index = pd.date_range('20210101 00:00', freq='45S', periods=5)
df = pd.DataFrame(1, index=index, columns=['X'])
df.index = df.index.tz_localize('GMT')
print(df)
Here we have first set the index as 2021/01/01 00:00 and took 5 period with gap interval of 45 seconds. Nowe we have created a dataframe with given index and a column 'X' with values equal to 1. Finally using pytz library, we have set the timezone to 'GMT'
Step 3 - Coverting timezone to India
Indian = pytz.timezone('Asia/Kolkata')
df.index = df.index.tz_convert(Indian)
print(df)
Here, we have created a variable containing timezone of Kolkata (City in India) and finally resetting the index.
Step 4 - Let's look at our dataset now
Once we run the above code snippet, we will see:
Scroll down the ipython file to visualize the final output.
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