CODEWITHSUNDEEP
pythonpython-3.xpandas
Jake Halopoff
Jake Halopoff

Reputation: 73

Is there a way to combine mapping with conditional statements?

If I have a dictionary like this, which I then assign to a data frame to use for mapping, is there a way to add conditional statements to the mapping so that they only happen if the condition is true?

mapping_pbm = {'Hospice': ['JOURNEY\'S HOSPICE', 'SALMON VALLEY HOSPICE', 'FIRST CHOICE HOSPICE',
                                   'CASTLE HILLS EDGEWOOD'], 'Tag': ['JOURNEYS',
                                                                     'SALMON VALLEY', 'FIRST CHOICE',
                                                                     'CASTLE HILLS, HOUSE STOCK']}
pbm_mapping_df = pd.DataFrame(data=mapping_pbm)
p = dict(zip(pbm_mapping_df.Tag, pbm_mapping_df.Hospice))
raw_direct_data['responsible_name'] = raw_direct_data['responsible_name'].map(p)

The above code is from elsewhere in my program, it takes the 'responsible_name' column and renames all the incorrectly named entries to what they should be.

        for index in data1f.index:
            price = float(data1f.loc[index, 44])
            id = data1f.loc[index, 36]
            if price > 0 & id != 1234:
                if data1f.loc[index, 28] in ("ACH1507", "CE11507", "CE21507", "CE51507", "LHH1507", "BBH1507", "DOC1507"):
                    if price + 2 < 19.99:
                        price = 19.99
                        data1f.loc[index, 44] = price
                    elif price + 2 > 19.99:
                        price = price + 2
                        data1f.loc[index, 44] = price
                elif data1f.loc[index, 28] in ("KEY1507", "FCH1507", "SVH1507", "JOU1507"):
                    price = (price * 1.3) + 2
                    data1f.loc[index, 44] = price
            elif price < 0:
                if data1f.loc[index, 28] in ("ACH1507", "CE11507", "CE21507", "CE51507", "LHH1507", "BBH1507", "DOC1507"):
                    if price - 2 > -19.99:
                        price = -19.99
                        data1f.loc[index, 44] = price
                    elif price - 2 < -19.99:
                        price = price - 2
                        data1f.loc[index, 44] = price
                elif data1f.loc[index, 28] in ("KEY1507", "FCH1507", "SVH1507", "JOU1507"):
                    price = (price * 1.3) - 2
                    data1f.loc[index, 44] = price

This code is what I'm currently using to set the prices in my data for a price plan we're using. Is there a way to combine these two concepts so I don't have to use a for loop/conditional statements?

Example Desired Input/Output

Input:

Hospice Price
JOURNEYS 7.99
FIRST CHOICE 19.99
SALMON VALLEY -7.99

Output:

Hospice Price
JOURNEY'S HOSPICE 19.99
FIRST CHOICE HOSPICE 21.99
SALMON VALLEY HOSPICE -19.99

Upvotes: 1

Views: 56

Answers (1)

wwnde
wwnde

Reputation: 26676

Say input is df.

Map df.Hospice to a dictionary of pbm_mapping_df['Tag']:pbm_mapping_df['Hospice']

Can create the dictionary using dict(zip(key:value))

df['Hospice']=df['Hospice'].map(dict(zip(pbm_mapping_df['Tag'],pbm_mapping_df['Hospice'])))

   

             Hospice       Price
0      JOURNEY'S HOSPICE   7.99
1   FIRST CHOICE HOSPICE  19.99
2  SALMON VALLEY HOSPICE  -7.99

Upvotes: 1

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