Returns the output of a function that takes pandas dataframe as a parameter

Question

I have a pandas framework that looks like this:

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

To perform several tasks in my work, the same tasks in pandas are required. I am starting to write standardized functions that will take data 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 am looking for a function to return a series. Thus, you can add a column to an existing data frame:

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

However, at present, this function will correctly return a series, but will also modify an existing column. How do you do this so that the original column is not modified?

Answer 1

, dataframe , params , python pandas .

, df, :

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]

. : pandas dataframe,