How do I count blank an filled cells in each column in a .csv file?

What I want is to count the filled and blank cells in each column of a .csv file.

This is my code:

import pandas as pd

file_path = r"C:\Users\andre\OneDrive\Documentos\Farmácia\Python\Cadastro_clientes\cadastro_cli.csv"  
df = pd.read_csv(file_path, sep='|', header=None)  # No names argument, read all columns

filled_counts = df.count()  # Count non-null entries for all columns
blank_counts = df.isnull().sum()  # Count null (blank) entries for all columns

summary = pd.DataFrame({
    'Filled': filled_counts,
    'Blank': blank_counts
})

print("\nFilled and Blank Counts:")
print(summary)

I only get this, which is not what I want at all:

Filled and Blank Counts:
   Filled  Blank
0   22318      0

I'm using Jupyter Notebook. Any help or tips are very appreciated!

If you want to tally the number of filled and blank cells for each column individually, use:

summary = pd.DataFrame({
    'Filled': df.notnull().sum(),   # Count non-null (filled) cells
    'Blank': df.isnull().sum()      # Count null (blank) cells
})
print(summary, "\n")

If you want to tally for the whole csv, use:

total_filled = summary['Filled'].sum()
total_blank = summary['Blank'].sum()
print(f"Filled: {total_filled}, \nBlank: {total_blank}"

Complete script:

import pandas as pd

file_path = r"C:\Users\andre\OneDrive\Documentos\Farmácia\Python\Cadastro_clientes\cadastro_cli.csv"
df = pd.read_csv(file_path, sep='|') #if csv does not have headers add 'header=None'


# Calculate filled and blank counts for each column
summary = pd.DataFrame({
    'Filled': df.notnull().sum(),   
    'Blank': df.isnull().sum()      
})
print(summary, "\n")

# Calculate totals for the entire CSV
total_filled = summary['Filled'].sum()
total_blank = summary['Blank'].sum()
print(f"Total filled: {total_filled} \nTotal blank: {total_blank}")