How to replace rows values on a DataFrame with Pandas using Python

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Replacing values is a core part of a Data Scientist's job.

When some of your values are inconsistent with the rest of the DataFrame and your statistics are wrong.

It usually happens when people give you a spreadsheet that they've been working on.

You can replace those values and fix those inconsistencies using the DataFrame.replace() method.

Here is the code

# To work with dataframes
import pandas as pd

# We create a sample dataframe
df = pd.DataFrame({"Country" : ["Germany", "USA", 
                                "germany", "france", 
                                "France"],
                   "Temperatures" : [24, 25, 23, 19, 23]})

# We replace the values germany and france 
# in the entire DataFrame
df = df.replace(to_replace={"germany":"Germany",
                       "france" :"France"})

# We check that all changes occured
print(df)

Here you are! You now know how to replace rows values on a DataFrame 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.
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A proven roadmap to prepare for $75K+ entry-level data roles. Perfect for Data Scientist ready to level up their career.

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Practice with real interview questions from tech companies
Access to the $100k/y Data Scientist Cheatsheet

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