PDF file Table from Pandas DataFrame

PDF Pandas
DataFrame to PDF table

Adding pandas dataframe created from SLQite or MySQL database table to PDF file by Python ReportLab

Our main file table_pandas.py ( Copy source code at the end of this page ) only reads the data as a list ( my_data ) from the data file.

Inside the table_pandas.py we import the my_data variable containing data as a list.
from reportlab.pdfgen import canvas
my_path='G:\\My drive\\testing\\pypdf2\\my_pdf.pdf' 
from reportlab.lib.units import inch
from reportlab.lib.pagesizes import letter
from reportlab.platypus import SimpleDocTemplate
from reportlab.platypus.tables import Table,TableStyle,colors
from table_pandas_data import my_data # import the data 
my_doc = SimpleDocTemplate(my_path,pagesize=letter)

c_width=[1*inch] # width of the columns 
Basics of adding Table to PDF file

Creating DataFrame

Inside our table_pandas_data.py we will create the dataframe by using one dictionary as source of data.
import pandas as pd 
df = pd.DataFrame(data=my_dict) # dataframe 
my_data=df.values.tolist() # create a list using Dataframe
Here the last line creates our required data source my_data as a list.

Using Database table as datasource

In above code the variable my_data can be created by using data ( value ) from different data sources. Let us try SQLite database student as source for creating this variable. As SQLite is a file based database, the sample file with student table can be downloaded.

We used try except error handling to show error message.

Download sample SQLite database with student table
import pandas as pd 
from sqlalchemy import create_engine
from sqlalchemy.exc import SQLAlchemyError
db_file='G:\\My drive\\testing\\my_db.db'  
file1='sqlite:///'+ db_file 
my_conn = create_engine(file1)
#my_conn = create_engine("mysql+mysqldb://id:pw@localhost/my_tutorial")
    df = pd.read_sql("SELECT * FROM student",my_conn)
    my_data=df.values.tolist()   # add rows as list. 
    my_data.insert(0,df.columns) # add the columns at first row
except SQLAlchemyError as e:
    error = str(e.__dict__['orig'])
tolist() is used to create List from DataFrame

Using MySQL database

In above code we can create the connection object my_conn by using this connection string for MySQL.
from sqlalchemy import create_engine
my_conn = create_engine("mysql+mysqldb://userid:password@localhost/database_name")
Full student table with SQL Dump for MySQL database.


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