Return output of function that takes pandas dataframe as a parameter

Question

I have a pandas dataframe that looks like:

d = {'some_col' : ['A', 'B', 'C', 'D', 'E'],
     'alert_status' : [1, 2, 0, 0, 5]}
df = pd.DataFrame(d)

Quite a few tasks at my job require the same tasks in pandas. I'm beginning to write standardized functions that will take a dataframe as a parameter and return something. Here's a simple one:

def alert_read_text(df, alert_status=None):
    if (alert_status is None):
        print 'Warning: A column name with the alerts must be specified'
    alert_read_criteria = df[alert_status] >= 1
    df[alert_status].loc[alert_read_criteria] = 1
    alert_status_dict = {0 : 'Not Read',
                         1 : 'Read'}
    df[alert_status] = df[alert_status].map(alert_status_dict)
    return df[alert_status]

I'm looking to have the function return a series. This way, one could add a column to an existing data frame:

df['alert_status_text'] = alert_read_text(df, alert_status='alert_status')

However, currently, this function will correctly return a series, but also modifies the existing column. How do you make it so the original column passed in does not get modified?

Answer 1

As you've discovered the passed in dataframe will be modified as params are passed by reference, this is true in python and nothing to do with pandas as such.

So if you don't want to modify the passed df then take a copy:

def alert_read_text(df, alert_status=None):
    if (alert_status is None):
        print 'Warning: A column name with the alerts must be specified'
    copy = df.copy()
    alert_read_criteria = copy[alert_status] >= 1
    copy[alert_status].loc[alert_read_criteria] = 1
    alert_status_dict = {0 : 'Not Read',
                         1 : 'Read'}
    copy[alert_status] = copy[alert_status].map(alert_status_dict)
    return copy[alert_status]

Also see related: pandas dataframe, copy by value