Split dataframe based on pandas groupby and generate multiple PDFs-CodePudding

There's a table containing a list of 3 employees and 3-4 courses they are supposed to take respectively. I want to create individual PDFs for every employee in this table. First PDF will have list of 3 courses to be taken by Emp1, 2nd PDF will have list of 3 courses to be taken by Emp2 and so on.

The below code is creating just 1 PDF and contains list of all courses for all employees together.

My idea is to initially split/ group the data based on EmpNo and then create individual PDF and to do this I need to create a For Loop for iterating. However, I am unable to figure this...

DataFrame Code

pip install fpdf #To generate PDF

import pandas as pd
data = {'EmpNo': ['123','123','123','456','456', '456','456','789','789','789'],
  'First Name': ['John', 'John', 'John', 'Jane', 'Jane', 'Jane', 'Jane', 'Danny', 'Danny', 'Danny'],
  'Last Name': ['Doe', 'Doe' ,'Doe', 'Doe' ,'Doe', 'Doe', 'Doe', 'Roberts', 'Roberts', 'Roberts'],
  'Activity Code': ['HR-CONF-1', 'HR-Field-NH-ONB','COEATT-2021','HR-HBK-CA-1','HR-WD-EMP','HR-LIST-1','HS-Guide-3','HR-WD-EMP','HR-LIST-1','HS-Guide-3'],
  'RegistrationDate': ['11/22/2021', '11/22/2021', '11/22/2021', '11/22/2021', '11/22/2021', '11/22/2021','11/22/2021', '11/22/2021', '11/22/2021','11/22/2021']}


df = pd.DataFrame(data = data, columns = ['EmpNo','First Name', 'Last Name', 'Activity Code', 'RegistrationDate'])
employees = data['EmpNo']
employees = data.drop_duplicates(subset=['EmpNo'])

print(df)

Input looks like this,

PDF Generation Code

from fpdf import FPDF

class PDF(FPDF):
def header(self):

    # Arial bold 15
    self.set_font('Helvetica', 'B', 15)
    # Move to the right
    self.cell(80)            
    # Title
    self.cell(42, 2, 'Plan', 0, 0, 'C')
    # Line break
    self.ln(20)
    
    # Page footer
def footer(self):
    # Position at 1.5 cm from bottom
    self.set_y(-15)
    # Arial italic 8
    self.set_font('Helvetica', 'I', 8)
    # Page number
    self.cell(0, 10, 'Page '   str(self.page_no())   '/{nb}', 0, 0, 'C')
    # Footer image First is horizontal, second is vertical, third is size
    
for EmpNo in employees['EmpNo']:
print (EmpNo)

    # Instantiation of inherited class
pdf = PDF()
pdf.alias_nb_pages()
pdf.add_page()
pdf.set_font('Helvetica', '', 11)
pdf.cell(80, 6, 'Employee ID: '   str(data.loc[0]['EmpNo']), 0, 1, 'L')
pdf.ln(2.5)
pdf.multi_cell(160, 5, 'Dear '   str(data.loc[0]['First Name'])   ' '   str(data.loc[0]['Last Name'])   ', Please find below your Plan.', 0, 1, 'L')
pdf.cell(80, 6, '', 0, 1, 'C')
pdf.set_font('Helvetica', 'B', 13)
pdf.cell(80, 6, 'Name', 0, 0, 'L')
pdf.cell(40, 6, 'Date', 0, 0, 'L')
pdf.cell(40, 6, 'Link', 0, 1, 'L')
pdf.cell(80, 6, '', 0, 1, 'C')
pdf.set_font('Helvetica', '', 8)
for i in range (len(data)):
    pdf.set_font('Helvetica', '', 8)
    pdf.cell(80, 6, data.loc[0 i]['Activity Code'], 0, 0, 'L')
    #pdf.cell(40, 6, data.loc[0 i]['Activity Link'], 0, 1, 'L')
    pdf.cell(40, 6, data.loc[0 i]['RegistrationDate'], 0, 0, 'L')
    pdf.set_font('Helvetica', 'U', 8)
    pdf.cell(40, 6, 'Click Here', 0, 1, 'L', link = 'www.google.com')
pdf.set_font('Helvetica', 'B', 10)
pdf.cell(80, 6, '', 0, 1, 'C')
pdf.cell(80, 6, 'IF YOU REQUIRE ANY HELP, PLEASE CONTACT US', 0, 0, 'L')
pdf.output(str(data.loc[0]['First Name'])   ' '   str(data.loc[0]['Last Name'])  '.pdf', 'F')

Here's a snap of PDF generated.

I can split the data using below code, but I am stuck at how to call out individual splits and then further create multiple PDF

splits = list(data.groupby('EmpNo'))

Any help would be greatly appreciated. Thanks.

CodePudding user response：

I would write the groupby like this:

for EmpNo, data in df.groupby("EmpNo"):

For each group, the groupby will return the variable it groups on, and the dataframe which matches that variable.

Next, I would extract the first row of that dataframe. This is to make it easier to get the name and similar attributes.

first_row = data.iloc[0]

(What's the difference between iloc and loc?)

Since we have the employee ID already, we can skip looking it up in the dataframe. For other attributes, we can look it up like first_row['First Name'].

pdf.cell(80, 6, 'Employee ID: '   str(EmpNo), 0, 1, 'L')
# ...
pdf.multi_cell(160, 5, 'Dear '   str(first_row['First Name'])   ' '   str(first_row['Last Name'])   ', Please find below your Plan.', 0, 1, 'L')

Next, in this loop which loops over the subset, I would use .iterrows() to do the loop instead of using range() and .loc. This is easier and won't break if the index of your dataframe doesn't start with zero. (After grouping, the second group's index won't start with zero anymore.)

Here is the final source code after the changes:

import pandas as pd
data = {'EmpNo': ['123','123','123','456','456', '456','456','789','789','789'],
  'First Name': ['John', 'John', 'John', 'Jane', 'Jane', 'Jane', 'Jane', 'Danny', 'Danny', 'Danny'],
  'Last Name': ['Doe', 'Doe' ,'Doe', 'Doe' ,'Doe', 'Doe', 'Doe', 'Roberts', 'Roberts', 'Roberts'],
  'Activity Code': ['HR-CONF-1', 'HR-Field-NH-ONB','COEATT-2021','HR-HBK-CA-1','HR-WD-EMP','HR-LIST-1','HS-Guide-3','HR-WD-EMP','HR-LIST-1','HS-Guide-3'],
  'RegistrationDate': ['11/22/2021', '11/22/2021', '11/22/2021', '11/22/2021', '11/22/2021', '11/22/2021','11/22/2021', '11/22/2021', '11/22/2021','11/22/2021']}
df = pd.DataFrame(data = data, columns = ['EmpNo','First Name', 'Last Name', 'Activity Code', 'RegistrationDate'])


from fpdf import FPDF

class PDF(FPDF):
    def header(self):

        # Arial bold 15
        self.set_font('Helvetica', 'B', 15)
        # Move to the right
        self.cell(80)            
        # Title
        self.cell(42, 2, 'Plan', 0, 0, 'C')
        # Line break
        self.ln(20)

        # Page footer
    def footer(self):
        # Position at 1.5 cm from bottom
        self.set_y(-15)
        # Arial italic 8
        self.set_font('Helvetica', 'I', 8)
        # Page number
        self.cell(0, 10, 'Page '   str(self.page_no())   '/{nb}', 0, 0, 'C')
        # Footer image First is horizontal, second is vertical, third is size

for EmpNo, data in df.groupby("EmpNo"):
    # Get first row of grouped dataframe
    first_row = data.iloc[0]

    # Instantiation of inherited class
    pdf = PDF()
    pdf.alias_nb_pages()
    pdf.add_page()
    pdf.set_font('Helvetica', '', 11)
    pdf.cell(80, 6, 'Employee ID: '   str(EmpNo), 0, 1, 'L')
    pdf.ln(2.5)
    pdf.multi_cell(160, 5, 'Dear '   str(first_row['First Name'])   ' '   str(first_row['Last Name'])   ', Please find below your Plan.', 0, 1, 'L')
    pdf.cell(80, 6, '', 0, 1, 'C')
    pdf.set_font('Helvetica', 'B', 13)
    pdf.cell(80, 6, 'Name', 0, 0, 'L')
    pdf.cell(40, 6, 'Date', 0, 0, 'L')
    pdf.cell(40, 6, 'Link', 0, 1, 'L')
    pdf.cell(80, 6, '', 0, 1, 'C')
    pdf.set_font('Helvetica', '', 8)
    for _, row in data.iterrows():
        pdf.set_font('Helvetica', '', 8)
        pdf.cell(80, 6, row['Activity Code'], 0, 0, 'L')
        #pdf.cell(40, 6, row['Activity Link'], 0, 1, 'L')
        pdf.cell(40, 6, row['RegistrationDate'], 0, 0, 'L')
        pdf.set_font('Helvetica', 'U', 8)
        pdf.cell(40, 6, 'Click Here', 0, 1, 'L', link = 'www.google.com')
    pdf.set_font('Helvetica', 'B', 10)
    pdf.cell(80, 6, '', 0, 1, 'C')
    pdf.cell(80, 6, 'IF YOU REQUIRE ANY HELP, PLEASE CONTACT US', 0, 0, 'L')
    pdf.output(str(first_row['First Name'])   ' '   str(first_row['Last Name'])  '.pdf', 'F')

Tested, and it works.