Python: Functions-map()

The map()transform values in a Series or DataFrame based on a mapping or function. With it, we can apply custom transformations to our data.

Syntax:

Series.map(arg, na_action=None)

• arg: This parameter can take one of the following:

1. A dictionary: It maps current values to new values.

2. A Series: It uses the Series values to perform the mapping.

3. A function: It applies the function to each element in the Series.

• na_action (optional): This parameter specifies what to do with missing values (NaNs). It can be one of 'ignore' (default), 'raise', or None.

Mapping Values Using a Dictionary:

import pandas as pd
data = {'A':['apple','banana','cherry','apple']}
df=pd.DataFrame(data)
fruit_to_color= {'apple':'red', 'banana':'yellow', 'cherry':'red'}
df['color']=df['A'].map(fruit_to_color)

This code maps fruit names in the ‘A’ column to their corresponding colors using a dictionary and creates a new ‘Color’ column in the DataFrame.

Mapping Values Using a Series:

import pandas as pd
data = {'A':['apple','banana','cherry','apple']}
df=pd.DataFrame(data)
color_series=pd.Series(['red','yellow','red'], index=['apple','banana','cherry'])…