Change one value based on another value in pandas

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One option is to use Python’s slicing and indexing features to logically evaluate the places where your condition holds and overwrite the data there.

Assuming you can load your data directly into pandas with pandas.read_csv then the following code might be helpful for you.

import pandas
df = pandas.read_csv("test.csv")
df.loc[df.ID == 103, 'FirstName'] = "Matt"
df.loc[df.ID == 103, 'LastName'] = "Jones"

As mentioned in the comments, you can also do the assignment to both columns in one shot:

df.loc[df.ID == 103, ['FirstName', 'LastName']] = 'Matt', 'Jones'

Note that you’ll need pandas version 0.11 or newer to make use of loc for overwrite assignment operations.

Another way to do it is to use what is called chained assignment. The behavior of this is less stable and so it is not considered the best solution (it is explicitly discouraged in the docs), but it is useful to know about:

import pandas
df = pandas.read_csv("test.csv")
df['FirstName'][df.ID == 103] = "Matt"
df['LastName'][df.ID == 103] = "Jones"

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