blog oofdev

In this blog post, we will discuss 10 commonly used Pandas DataFrame methods, along with examples of how to use them. 1. fillna() The fillna() method fills missing values in a DataFrame with a specified value or method. # Fill missing values in the 'age' column with the mean age df['age'].fillna(df['age'].mean(), inplace=True) Output: name age 0 Alice 20.0 1 Bob 30.0 2 Charlie 40.0 2. dropna() The dropna() method removes rows or columns with missing values from a DataFrame. # Remove rows with missing values in the 'name' column df.dropna(subset=['name'], inplace=True) Output: name age 0 Alice 20.0 1 Bob 30.0 2 Charlie 40.0 3. unique() The unique() method returns the unique values in a DataFrame column. # Get the unique values in the 'city' column unique_cities = df['city'].unique() print(unique_cities) Output: ['New York', 'Boston', 'Chicago'] 4. value_counts()...