Challenge #332: The more ice cream, the better!

[nkinsey]

Spoiler

What about Breyers?!

[PhilipMannering]

My attempt at doing it in the Python Tool,

Spoiler

import pandas as pd
from ayx import Alteryx
df = Alteryx.read('#1')


#################################
rows = (~df.ingredients.isna()) & (df.brand != 'breyers')
cols = ['brand', 'name', 'rating', 'ingredients']
df = df.loc[rows, cols]


#################################
rename_brand = {'bj': "Ben and Jerry's", 'hd': "Häagen-Dazs", 'talenti': 'Talenti Gelato'}
df['brand'] = df.brand.map(rename_brand)


#################################
df.rating = df.rating.astype(float)


#################################
df.groupby('brand').mean().sort_values('rating', ascending=False)


#################################
def filter_allergens(df):
    '''Get all the ice cream without allergens cream and peanuts'''
    mask = ~df.ingredients.str.contains('cream|peanuts', case=False)
    return (
        df.loc[mask]
        .drop(columns='rating')
        .rename(columns=lambda col:col.title())
        .reset_index(drop=True)
    )

filter_allergens(df)


#################################
def get_best_and_worst(df):
    return (
        df.sort_values('rating')
        .groupby('brand')
        .agg(('first', 'last'))
        .rename(columns={'first':'Worst', 'last':'Best', 'name':'Ice Cream'})
        .rename(columns=lambda col:col.title())
        .swaplevel(0, 1, axis=1)
        .sort_index(axis=1)
    )

get_best_and_worst(df)

[TapasTR]

Here's my solution. Good one to brush up the knowledge of some tools not used since long.

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[amosteller]

[SeanMc_Westpac]

[kelvin_law1]

Here is my solution:

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[Reesetrain2]

All,

Spoiler

My submission:
1 Find/Replace
2 Joins
1 Multi Join

 

[DanFlint]

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[FloSchoch]

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[Brando]

All that alteryx work makes me hungry for ice cream. I personally like cookie dough at Andy's, a local ice cream shop in the Kansas City metro!