How Can I Modify Specific Values in Pandas DataFrame Columns Based on a Condition?

Altering Values Based on Conditions in Pandas

This question presents a situation where specific values in two columns, FirstName and LastName, need to be modified based on the condition of the ID column matching a particular value. In Stata, this can be achieved using simple replace commands.

In Pandas, a powerful Python library for data manipulation, one approach is to leverage the loc function with the indexing feature. This enables logical evaluation and subsequent data modification. For instance:

<code class="python">import pandas as pd

df = pd.read_csv("test.csv")
df.loc[df.ID == 103, 'FirstName'] = "Matt"
df.loc[df.ID == 103, 'LastName'] = "Jones"</code>

Alternatively, the assignment to both columns can be done in one step:

<code class="python">df.loc[df.ID == 103, ['FirstName', 'LastName']] = 'Matt', 'Jones'</code>

Note that Pandas version 0.11 or higher is required for loc overwrite assignment operations. For older versions, chained assignment is a viable solution:

<code class="python">df['FirstName'][df.ID == 103] = "Matt"
df['LastName'][df.ID == 103] = "Jones"</code>

While chained assignment should generally be avoided in modern Pandas versions, it remains a useful technique to be aware of for compatibility with older versions.

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