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    Drop Rows with Missing Values from a Pandas DataFrame

        A Drop Rows with Missing Values from a Pandas DataFrame
         
         Short Description of the Program:
         This program removes all rows from the DataFrame that contain missing (NaN) values.
       
          Explanation:

    • dropna()
      Automatically removes any row that has one or more NaN values.
       
    • Use inplace=True if you want to modify the original DataFrame:

      python
      CopyEdit

    Program:

    import pandas as pd

import numpy as np

data = {

    'Name': ['Alice', 'Bob', 'Charlie', 'Diana', 'Eva', 'Frank'],

    'Age': [25, np.nan, 22, 28, 26, 35],

    'Gender': ['Female', 'Male', 'Male', 'Female', 'Female', 'Male'],

    'City': ['New York', 'Los Angeles', np.nan, 'Houston', 'Phoenix', 'Seattle']

}

df = pd.DataFrame(data)

cleaned_df = df.dropna()

print(cleaned_df)

     

     

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