By default you can edit the value of a Pandas Series using the DataFrame.apply() method.

This method can perform row by row or column by column operations.

And you can either work with lambda functions or apply a method directly.

Here is the code

# To work with dataframes
import pandas as pd

# We create a sample dataframe
df = pd.DataFrame({"col1" : [0, 10, 3, 11, 3, 12]})

# How to change the values of a DataFrame Series
df["col1"] = df["col1"].apply(lambda x: x + 2)

print(df["col1"])

def multiply_by_two(x):
    """Multiplies x by two"""
    return x * 2

# Now we apply the method by specifying the method
# directly instead of a lambda
df["col1"] = df["col1"].apply(multiply_by_two)

print(df["col1"])

def multiply_by_n(x, n):
    """Multiplies x by n"""
    return x * n

# Now we pass a method along with an argument required 
# by the multiply_by_n method
df["col1"] = df["col1"].apply(multiply_by_n, n=2)

print(df["col1"])

Here you are! You now know how to change the values of a DataFrame Column with Pandas using Python!

More on DataFrames

If you want to know more about DataFrame and Pandas. Check out the other articles I wrote on the topic, just here :

Pandas - The Python You Need

We gathered the only Python essentials that you will probably ever need.

The Python You Need

How to iterate over columns in a DataFrame in Pandas

How to iterate over rows in a DataFrame in Pandas

How to change the values of a DataFrame column with Pandas using Python

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