how effectively can we do one hot encoding in python code example

Example 1: python convert categorical data to one-hot encoding

# Basic syntax:
df_onehot = pd.get_dummies(df, columns=['col_name'], prefix=['one_hot'])
# Where:
#	- get_dummies creates a one-hot encoding for each unique categorical
#		value in the column named col_name
#	- The prefix is added at the beginning of each categorical value 
#		to create new column names for the one-hot columns

# Example usage:
# Build example dataframe:
df = pd.DataFrame(['sunny', 'rainy', 'cloudy'], columns=['weather'])
print(df)
  weather
0   sunny
1   rainy
2  cloudy

# Convert categorical weather variable to one-hot encoding:
df_onehot = pd.get_dummies(df, columns=['weather'], prefix=['one_hot'])
print(df_onehot)
	one_hot_cloudy	 one_hot_rainy   one_hot_sunny
0                0               0               1
1                0               1               0
2                1               0               0

Example 2: one hot encoding python pandas

y = pd.get_dummies(df.Countries, prefix='Country')
print(y.head())
# from here you can merge it onto your main DF