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The rich ecosystem of Python modules lets you get to work quickly and integrate your systems more effectively. With the CData Python Connector for Instagram, the pandas & Matplotlib modules, and the SQLAlchemy toolkit, you can build Instagram-connected Python applications and scripts for visualizing Instagram data. This article shows how to use the pandas, SQLAlchemy, and Matplotlib built-in functions to connect to Instagram data, execute queries, and visualize the results.
With built-in optimized data processing, the CData Python Connector offers unmatched performance for interacting with live Instagram data in Python. When you issue complex SQL queries from Instagram, the driver pushes supported SQL operations, like filters and aggregations, directly to Instagram and utilizes the embedded SQL engine to process unsupported operations client-side (often SQL functions and JOIN operations).
Connecting to Instagram 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.
Instagram uses the OAuth 2 authentication standard. Obtain the OAuthClientId, OAuthClientSecret, and CallbackURL by registering an app with Instagram. See the help documentation for a guide.
Follow the procedure below to install the required modules and start accessing Instagram through Python objects.
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
You can now connect with a connection string. Use the create_engine function to create an Engine for working with Instagram data.
engine = create_engine("instagram:///?OAuthClientId=MyOAuthClientId&OAuthClientSecret=MyOAuthClientSecret&CallbackURL=http://localhost:portNumber&InitiateOAuth=GETANDREFRESH")
Use the read_sql function from pandas to execute any SQL statement and store the resultset in a DataFrame.
df = pandas.read_sql("SELECT Link, LikesCount FROM Media WHERE TagName = 'goldfish'", engine)
With the query results stored in a DataFrame, use the plot function to build a chart to display the Instagram data. The show method displays the chart in a new window.
df.plot(kind="bar", x="Link", y="LikesCount") plt.show()👁 Instagram data in a Python plot (Salesforce is shown).
Download a free, 30-day trial of the CData Python Connector for Instagram to start building Python apps and scripts with connectivity to Instagram data. Reach out to our Support Team if you have any questions.
import pandas
import matplotlib.pyplot as plt
from sqlalchemy import create_engin
engine = create_engine("instagram:///?OAuthClientId=MyOAuthClientId&OAuthClientSecret=MyOAuthClientSecret&CallbackURL=http://localhost:portNumber&InitiateOAuth=GETANDREFRESH")
df = pandas.read_sql("SELECT Link, LikesCount FROM Media WHERE TagName = 'goldfish'", engine)
df.plot(kind="bar", x="Link", y="LikesCount")
plt.show()
Download a Community License of the Instagram Connector to get started:
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👁 Instagram IconPython Connector Libraries for Instagram Data Connectivity. Integrate Instagram with popular Python tools like Pandas, SQLAlchemy, Dash & petl.