<\/span><\/h2>\nThe primary method for value replacement in a pandas DataFrame is the replace()<\/b> function. This function allows us to replace given values with new values in selected columns or throughout the entire DataFrame. Let’s look at how to use it:<\/p>\n
“`python
\nimport pandas as pd<\/p>\n
# Create a sample DataFrame
\ndata = {‘Name’: [‘John’, ‘Emma’, ‘Connor’, ‘Emily’],
\n ‘Age’: [25, 28, 24, 30],
\n ‘City’: [‘New York’, ‘London’, ‘Paris’, ‘Sydney’]}
\ndf = pd.DataFrame(data)<\/p>\n
# Replace a specific value in a DataFrame
\ndf.replace(‘London’, ‘Berlin’, inplace=True) # Replace ‘London’ with ‘Berlin’<\/p>\n
print(df)
\n“`
\nOutput:
\n“`
\n Name Age City
\n0 John 25 New York
\n1 Emma 28 Berlin
\n2 Connor 24 Paris
\n3 Emily 30 Sydney
\n“`<\/p>\n
In the above example, we replaced the value ‘London’ with ‘Berlin’ in the ‘City’ column of the DataFrame using the replace()<\/b> method. Note that we used the inplace=True<\/b> parameter to modify the DataFrame directly; otherwise, the method would return a new DataFrame with the replaced values.<\/p>\n