How to Visualize LINE 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 LINE-connected Python applications and scripts for visualizing LINE data. This article shows how to use the pandas, SQLAlchemy, and Matplotlib built-in functions to connect to LINE data, execute queries, and visualize the results.

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

Connecting to LINE Data

Connecting to LINE 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.

Start by setting the Profile connection property to the location of the LINE Profile on disk (e.g. C:\profiles\LINE.apip). Next, set the ProfileSettings connection property to the connection string for LINE (see below).

LINE API Profile Settings

The LINE Messaging API uses Channel Access Token authentication. To obtain a Channel Access Token:

1. Log in to the LINE Developers Console at https://developers.line.biz
2. Select your provider and open your Messaging API channel.
3. Navigate to the Messaging API tab.
4. Under Channel access token, click Issue to generate a long-lived token.
5. Copy the generated token.

After obtaining your Channel Access Token, set the following connection properties:

• AuthScheme: Set this to APIKey.

Set the following in the ProfileSettings connection property:

• APIKey: Set this to your LINE Channel Access Token.

Follow the procedure below to install the required modules and start accessing LINE 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 LINE Data in Python

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

engine = create_engine("api:///?Profile=C:\profiles\LINE.apip&ProfileSettings='APIKey=your_channel_access_token&'&AuthScheme=APIKey")

Execute SQL to LINE

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

df = pandas.read_sql("SELECT DeliveryDate, DeliveredCount FROM ReplyMessageDelivery WHERE DeliveryDate = '20240115'", engine)

Visualize LINE Data

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

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

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 LINE data. Reach out to our Support Team if you have any questions.

Full Source Code

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

engine = create_engine("api:///?Profile=C:\profiles\LINE.apip&ProfileSettings='APIKey=your_channel_access_token&'&AuthScheme=APIKey")
df = pandas.read_sql("SELECT DeliveryDate, DeliveredCount FROM ReplyMessageDelivery WHERE DeliveryDate = '20240115'", engine)

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