# Applying a Function to Each Element in a Column
import pandas as pd

data = {
    ''''temperature_celsius'''': [0, 20, 30, 40]
}
df = pd.DataFrame(data)
#######################################
def celsius_to_fahrenheit(celsius):
    return (celsius * 9/5) + 32
#######################################
df[''''temperature_fahrenheit''''] = df[''''temperature_celsius''''].apply(celsius_to_fahrenheit)
print(df)

# Applying a Lambda Function
import pandas as pd

data = {
    ''''names'''': [''''Alice'''', ''''Bob'''', ''''Charlie'''', ''''David'''']
}
df = pd.DataFrame(data)
df[''''name_length''''] = df[''''names''''].apply(lambda x: len(x))
print(df)

# Applying a Function to Rows
import pandas as pd

data = {
    ''''math'''': [90, 80, 70, 60],
    ''''science'''': [85, 75, 65, 55],
    ''''english'''': [88, 78, 68, 58]
}
df = pd.DataFrame(data)
#######################################
def total_score(row):
    return row[''''math''''] + row[''''science''''] + row[''''english'''']
#######################################
df[''''total_score''''] = df.apply(total_score, axis=1)
print(df)

# Using apply with Additional Arguments
import pandas as pd

data = {
    ''''values'''': [1, 2, 3, 4]
}
df = pd.DataFrame(data)
######################################
def add_constant(x, constant):
    return x + constant
######################################
df[''''values_plus_10''''] = df[''''values''''].apply(add_constant, constant=10)
print(df)