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PDF Report Generation -
Generate PDF reports from data included in several Pandas DataFrames
from __future__ import print_function
import pandas as pd
import numpy as np
import argparse
from jinja2 import Environment, FileSystemLoader
from weasyprint import HTML
def create_pivot(df, infile, index_list=["Manager", "Rep", "Product"], value_list=["Price", "Quantity"]):
Create a pivot table from a raw DataFrame and return it as a DataFrame
table = pd.pivot_table(df, index=index_list, values=value_list,
aggfunc=[np.sum, np.mean], fill_value=0)
return table
def get_summary_stats(df,product):
For certain products we want National Summary level information on the reports
Return a list of the average quantity and price
results = []
return results
if __name__ == "__main__":
parser = argparse.ArgumentParser(description='Generate PDF report')
parser.add_argument('infile', type=argparse.FileType('r'),
help="report source file in Excel")
parser.add_argument('outfile', type=argparse.FileType('w'),
help="output file in PDF")
args = parser.parse_args()
# Read in the file and get our pivot table summary
df = pd.read_excel(
sales_report = create_pivot(df,
# Get some national summary to include as well
manager_df = []
for manager in sales_report.index.get_level_values(0).unique():
manager_df.append([manager, sales_report.xs(manager, level=0).to_html()])
# Do our templating now
# We can specify any directory for the loader but for this example, use current directory
env = Environment(loader=FileSystemLoader('.'))
template = env.get_template("myreport.html")
template_vars = {"title" : "National Sales Funnel Report",
"CPU" : get_summary_stats(df, "CPU"),
"Software": get_summary_stats(df, "Software"),
"national_pivot_table": sales_report.to_html(),
"Manager_Detail": manager_df}
# Render our file and create the PDF using our css style file
html_out = template.render(template_vars)
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