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To fill null or missing values in a Pandas DataFrame column with the mode of that column, follow these steps:

1. Import the Pandas library:

   import pandas as pd
   

2. Create a DataFrame object or read a CSV file into a DataFrame:

   df = pd.read_csv('data.csv')
   

3. Use the fillna() method of the DataFrame object to fill null or missing values with the mode of the column:

   df['column_name'].fillna(df['column_name'].mode()[0], inplace=True)
   

   Here, column_name is the name of the column we want to fill null or missing values, mode()[0] returns the mode value of the column, and inplace=True ensures that the changes are made to the original DataFrame.

4. Finally, we can check the DataFrame for any missing values using the isnull() method:

   df.isnull().sum()
   

   This will return the number of missing values in each column of the DataFrame, which should be 0 for the column we just filled with the mode.