geetashankar

def sub_brand_finder(subcategory):
    temp=cscp[cscp['PrimaryCategory']=='Makeup Products (non-permanent)']
    df=temp[temp['SubCategory']==subcategory].groupby('brandname').agg({'ChemicalCount':np.mean,'BrandName':'first'}).sort_values('ChemicalCount').reset_index()
    least=str(np.array(df.head(3)['BrandName']))[1:-1]
    most=str(np.array(df.tail(3)['BrandName']))[1:-1]
    text1 = "\033[32m"
    text2 = "\033[31m"
    print("\033[1m",text1,'The three most chemical-safe brands in '+subcategory+' are '+least)
    print("\033[1m",text2,'The three least chemical-safe brands in '+subcategory+' are '+most)
for i in makeup_subcategories:

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def brand_finder(category):
    df=cscp[cscp['PrimaryCategory']==category].groupby('BrandName').agg(np.mean).sort_values('ChemicalCount').reset_index()
    least=str(np.array(df.head(3)['BrandName']))[1:-1]
    most=str(np.array(df.tail(3)['BrandName']))[1:-1]
    text1 = "\033[32m"
    text2 = "\033[31m"
    print("\033[1m",text1,'The three most chemical-safe brands in '+category+' are '+least)
    print("\033[1m",text2,'The three least chemical-safe brands in '+category+' are '+most)

geetashankar

cscp.groupby('ChemicalName').size().to_frame().rename({0:'count'},axis=1).sort_values('count',ascending=False).head(5)

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most_chemical_brands=chemical_count.sort_values('ChemicalCount',ascending=False).query('ChemicalCount>2')
most_chemical_brands.head(5)

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cscp['BrandName']=cscp['BrandName'].str.lower().str.replace('.','').str.replace(' ','').str.replace('�','')
cscp['ProductName']=cscp['ProductName'].str.lower()
cscp['ChemicalName']=cscp['ChemicalName'].str.lower()

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