How to Visualize OpenWeatherMap Data in Python with pandas

The rich ecosystem of Python modules lets you get to work quickly and integrate your systems more effectively. With the CData API Driver for Python, the pandas & Matplotlib modules, and the SQLAlchemy toolkit, you can build OpenWeatherMap-connected Python applications and scripts for visualizing OpenWeatherMap data. This article shows how to use the pandas, SQLAlchemy, and Matplotlib built-in functions to connect to OpenWeatherMap data, execute queries, and visualize the results.

With built-in optimized data processing, the CData Python Connector offers unmatched performance for interacting with live OpenWeatherMap data in Python. When you issue complex SQL queries from OpenWeatherMap, the driver pushes supported SQL operations, like filters and aggregations, directly to OpenWeatherMap and utilizes the embedded SQL engine to process unsupported operations client-side (often SQL functions and JOIN operations).

Connecting to OpenWeatherMap Data

Connecting to OpenWeatherMap data looks just like connecting to any relational data source. Create a connection string using the required connection properties. For this article, you will pass the connection string as a parameter to the create_engine function.

Using API Key Authentication

To obtain an API key, sign up for a free account at https://openweathermap.org/api and navigate to the API keys section of your dashboard. Copy your API key for use in the connection configuration.

After setting the following connection properties, you are ready to connect:

• AuthScheme: Set this to APIKey.
• APIKey: Set this to your OpenWeatherMap API key.

Follow the procedure below to install the required modules and start accessing OpenWeatherMap through Python objects.

Install Required Modules

Use the pip utility to install the pandas & Matplotlib modules and the SQLAlchemy toolkit:

pip install pandas
pip install matplotlib
pip install sqlalchemy

Be sure to import the module with the following:

import pandas
import matplotlib.pyplot as plt
from sqlalchemy import create_engine

Visualize OpenWeatherMap Data in Python

You can now connect with a connection string. Use the create_engine function to create an Engine for working with OpenWeatherMap data.

engine = create_engine("api:///?Profile=C:\path\to\OpenWeatherMap.apip&AuthScheme=APIKey&ProfileSettings="APIKey=your_openweathermap_api_key"")

Execute SQL to OpenWeatherMap

Use the read_sql function from pandas to execute any SQL statement and store the resultset in a DataFrame.

df = pandas.read_sql("SELECT , FROM AccumulatedPrecipitation WHERE Latitude = '40.7128'", engine)

Visualize OpenWeatherMap Data

With the query results stored in a DataFrame, use the plot function to build a chart to display the OpenWeatherMap data. The show method displays the chart in a new window.

df.plot(kind="bar", x="", y="")
plt.show()

👁 OpenWeatherMap data in a Python plot (Salesforce is shown).

Free Trial & More Information

Download a free, 30-day trial of the CData API Driver for Python to start building Python apps and scripts with connectivity to OpenWeatherMap data. Reach out to our Support Team if you have any questions.

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Full Source Code

import pandas
import matplotlib.pyplot as plt
from sqlalchemy import create_engin

engine = create_engine("api:///?Profile=C:\path\to\OpenWeatherMap.apip&AuthScheme=APIKey&ProfileSettings="APIKey=your_openweathermap_api_key"")
df = pandas.read_sql("SELECT , FROM AccumulatedPrecipitation WHERE Latitude = '40.7128'", engine)

df.plot(kind="bar", x="", y="")
plt.show()