I have an excel file with different sections, each one with its header, of which i provide its names (they also have a number attached to it on second column). On a first approach, i want to read and print on screen each section's cells. Here is the code I used:

section_headers = [ 'LIBROS', 'CAPÍTULOS DE LIBROS','ARTÍCULOS CIENTÍFICOS (ORIGINALES Y DE REVISIÓN)', 'ARTÍCULOS DE DIVULGACIÓN','PONENCIAS PRESENTADAS','CARTELES PRESENTADOS EN CONGRESOS', 'CURSOS IMPARTIDOS','SEMINARIOS IMPARTIDOS','PROGRAMAS DE RADIO Y TV','PODCASTS','SOFTWARE', 'PATENTES', 'MODELOS DE UTILIDAD', 'PROTOTIPO', 'PRÁCTICAS PROFESIONALES', 'SERVICIO SOCIAL', 'TESIS','OTROS (Ej. Manuales, procesos)']

def process_excel(file_path, section_headers):
df = pd.read_excel(file_path, skiprows=2)


sections = {}
current_section = None
section_data = []


for idx, row in df.iterrows():

    if any(header in str(row[0]) for header in section_headers) and isinstance(row[1], (int, float)):
        if current_section is not None:
            sections[current_section] = pd.DataFrame(section_data)
        
        current_section = row[0]  # The first column is the section name
        section_data = []  # Reset data for the new section
        
    else:
        # Add row data to current section
        section_data.append(row)


if current_section is not None:
    sections[current_section] = pd.DataFrame(section_data)


for section, data in sections.items():
  print(f"\nSection: {section}")
  print(data)

Now, when I call the function:

process_excel(file_path='wherever the file is", section_headers)

i obtain nothing. I am running it on google colab. I already charged pandas and openpyxl. Any ideas on why i don't see anything (not even a error message)?

I have an excel file with different sections, each one with its header, of which i provide its names (they also have a number attached to it on second column). On a first approach, i want to read and print on screen each section's cells. Here is the code I used:

section_headers = [ 'LIBROS', 'CAPÍTULOS DE LIBROS','ARTÍCULOS CIENTÍFICOS (ORIGINALES Y DE REVISIÓN)', 'ARTÍCULOS DE DIVULGACIÓN','PONENCIAS PRESENTADAS','CARTELES PRESENTADOS EN CONGRESOS', 'CURSOS IMPARTIDOS','SEMINARIOS IMPARTIDOS','PROGRAMAS DE RADIO Y TV','PODCASTS','SOFTWARE', 'PATENTES', 'MODELOS DE UTILIDAD', 'PROTOTIPO', 'PRÁCTICAS PROFESIONALES', 'SERVICIO SOCIAL', 'TESIS','OTROS (Ej. Manuales, procesos)']

def process_excel(file_path, section_headers):
df = pd.read_excel(file_path, skiprows=2)


sections = {}
current_section = None
section_data = []


for idx, row in df.iterrows():

    if any(header in str(row[0]) for header in section_headers) and isinstance(row[1], (int, float)):
        if current_section is not None:
            sections[current_section] = pd.DataFrame(section_data)
        
        current_section = row[0]  # The first column is the section name
        section_data = []  # Reset data for the new section
        
    else:
        # Add row data to current section
        section_data.append(row)


if current_section is not None:
    sections[current_section] = pd.DataFrame(section_data)


for section, data in sections.items():
  print(f"\nSection: {section}")
  print(data)

Now, when I call the function:

process_excel(file_path='wherever the file is", section_headers)

i obtain nothing. I am running it on google colab. I already charged pandas and openpyxl. Any ideas on why i don't see anything (not even a error message)?

• python
• excel
• openpyxl

• Can you verify that what we see is what your current indentation looks like? The indentation around def process_excel(file_path, section_headers): looks incorrect. – JonSG Commented Nov 20, 2024 at 17:33
• Thank you. Copy paste of code wasn't right in here, but it does in code, it's right and consistent, it shows no error of that type. And yet, I obtain nothing at all. I can't find the source of error. – John Doe Commented Nov 21, 2024 at 18:55

2 Answers 2

import pandas as pd

section_headers = [
    'LIBROS', 'CAPÍTULOS DE LIBROS', 'ARTÍCULOS CIENTÍFICOS (ORIGINALES Y DE REVISIÓN)', 
    'ARTÍCULOS DE DIVULGACIÓN', 'PONENCIAS PRESENTADAS', 'CARTELES PRESENTADOS EN CONGRESOS', 
    'CURSOS IMPARTIDOS', 'SEMINARIOS IMPARTIDOS', 'PROGRAMAS DE RADIO Y TV', 'PODCASTS', 
    'SOFTWARE', 'PATENTES', 'MODELOS DE UTILIDAD', 'PROTOTIPO', 'PRÁCTICAS PROFESIONALES', 
    'SERVICIO SOCIAL', 'TESIS', 'OTROS (Ej. Manuales, procesos)'
]

def process_excel(file_path, section_headers):
    # Read the Excel file, skipping unnecessary rows
    df = pd.read_excel(file_path, skiprows=2)

    # Initialize storage for sections
    sections = {}
    current_section = None
    section_data = []

    for idx, row in df.iterrows():
        # Check if the row corresponds to a section header
        if any(header in str(row[0]) for header in section_headers) and isinstance(row[1], (int, float)):
            # Save the previous section's data
            if current_section is not None and section_data:
                sections[current_section] = pd.DataFrame(section_data, columns=df.columns)
            
            # Start a new section
            current_section = row[0]
            section_data = []  # Reset for new section
        else:
            # Add the row to the current section's data
            if not row.isnull().all():  # Skip completely empty rows
                section_data.append(row.tolist())

    # Save the last section
    if current_section is not None and section_data:
        sections[current_section] = pd.DataFrame(section_data, columns=df.columns)

    # Print each section
    for section, data in sections.items():
        print(f"\nSection: {section}")
        print(data)

# Example Usage
file_path = "your_excel_file.xlsx"
process_excel(file_path, section_headers)

df = pd.read_excel(file_path, skiprows=2)
for section in section headers:
   print(f"\nSection: {section}")
   # Remove print(df.filter(like=section, axis=0)
   # Update requires data frame column name Sections for section headers
   #Can add in excel row 2 and change from skiprows=2 to skiprows =1
   filter = df['Sections'].str.contains(section)
   print(df[filter])

This should simplify and achieve same goal