How can we change the values of certain columns based on conditions that are determined by other columns?

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One way to change the values of certain columns based on conditions that are determined by other columns is to use conditional statements in programming.

Using Python as an example, we could start by importing a library such as pandas, which is commonly used for data manipulation. We would then read in the data that we want to modify.

Next, we can use the .loc function to select certain rows and columns based on conditions. For example, we could write:

df.loc[df['Column 1'] > 10, 'Column 2'] = 'New Value'

This would update the values in 'Column 2' for all rows where the value in 'Column 1' is greater than 10, setting them to 'New Value'.

We could also write more complex conditions using logical operators such as AND ( & ), OR ( | ), and NOT ( ~ ). For example:

df.loc[(df['Column 1'] > 10) & (df['Column 3'] == 'Condition'), 'Column 2'] = 'New Value'

This would update the values in 'Column 2' for all rows where the value in 'Column 1' is greater than 10 and the value in 'Column 3' is 'Condition', setting them to 'New Value'.

By using conditional statements like these, we can modify the values in certain columns based on the conditions that are determined by other columns, allowing us to manipulate and transform our data to meet our needs.