1.2 Getting Data: TMY in your local timezone

We are going to retrieve some air temperature TMY data from the Solcast API and plot it.

In [1]:

from solcast import tmy

from solcast import tmy

To test the API you can use unmetered locations, in the SDK:

In [2]:

from solcast.unmetered_locations import UNMETERED_LOCATIONS

site = UNMETERED_LOCATIONS["Giza Pyramid Complex"]
site

from solcast.unmetered_locations import UNMETERED_LOCATIONS site = UNMETERED_LOCATIONS["Giza Pyramid Complex"] site

Out[2]:

{'latitude': 29.977296,
 'longitude': 31.132496,
 'resource_id': '8d10-f530-af85-5cbb'}

Let's retreive the TMY data for the Giza Pyramids in Cairo. The API lets you specify the timezone in the request by adding a time_zone parameter:

In [3]:

res = tmy.radiation_and_weather(
    latitude=site["latitude"],
    longitude=site["longitude"],
    output_parameters=["ghi", "air_temp"],
    time_zone=2  # in January there are 2h between the Cairo timezone and UTC
)

res = tmy.radiation_and_weather( latitude=site["latitude"], longitude=site["longitude"], output_parameters=["ghi", "air_temp"], time_zone=2 # in January there are 2h between the Cairo timezone and UTC )

The Response object in the SDK lets you easliy transform the data received from the API to a Pandas DataFrame. Make sure that Pandas is installed if you want to use this functionality:

In [9]:

df = res.to_pandas()
df.head()

df = res.to_pandas() df.head()

Out[9]:

	ghi	air_temp
period_end
2059-01-01 01:00:00+02:00	0	11
2059-01-01 02:00:00+02:00	0	11
2059-01-01 03:00:00+02:00	0	10
2059-01-01 04:00:00+02:00	0	10
2059-01-01 05:00:00+02:00	0	10

For visualization purposes we can create a copy shifted to UTC:

In [6]:

import matplotlib.pyplot as plt

df.plot()

import matplotlib.pyplot as plt df.plot()

Out[6]:

<Axes: xlabel='period_end'>

In [8]:

df[:50].plot()

df[:50].plot()

Out[8]:

<Axes: xlabel='period_end'>

In [ ]: