Map or Convert categorical to boolean.

[knageswara78]

How to convert target from categorical to boolean type.

[knageswara78]

Sol.1)

Making few values as 'others'

print(df['Name'].value_counts()) df['name'] = np.where(df['name'].isin(['A','B']), df['name'], 'others') print(df['Name'].value_counts())

Sol.2)

All Values Mapping.

Define Mapping

dmap = {0:'Mon',1:'Tue',2:'Wed',3:'Thu',4:'Fri',5:'Sat',6:'Sun'}

Mapping

df['Day of Week'] = df['Day of Week'].map(dmap)

Sol.3)

Convert target from categorical to boolean

categorical to boolean (Map 2 columns at a time.)

For 1 Variable

cleanup_nums = {"STATUS": {"four": 4, "two": 2}}

To convert the columns to numbers using replace

df.replace(cleanup_nums, inplace=True)

To see converted counts

df["STATUS"].value_counts()

For 2 variables:

Convert target from categorical to boolean

cleanup_nums = {"num_doors": {"four": 4, "two": 2}, "num_cylinders": {"four": 4, "six": 6 }}

To convert the columns to numbers using replace

df.replace(cleanup_nums, inplace=True)# To see converted counts df["num_doors"].value_counts() df["num_cylinders"].value_counts()