To implement Cluster and Visitor Segmentation for Navigation patterns in Python.
- Read the CSV file: Use pd.read_csv to load the CSV file into a pandas DataFrame.
- Define Age Groups by creating a dictionary containing age group conditions using Boolean conditions.
- Segment Visitors by iterating through the dictionary and filter the visitors into respective age groups.
- Visualize the result using matplotlib.
# read the data
import pandas as pd
visitor_df = pd.read_csv('/content/clustervisitor.csv')
# Perform segmentation based on characteristics (e.g., age groups)
age_groups = {
'Young': visitor_df['Age'] <= 30,
'Middle-aged': (visitor_df['Age'] > 30) & (visitor_df['Age'] <= 50),
'Elderly': visitor_df['Age'] > 50
}
for group, condition in age_groups.items():
visitors_in_group = visitor_df[condition]
print(f"Visitors in {group} age group:")
print(visitors_in_group)
# read the data
import pandas as pd
visitor_df = pd.read_csv('/content/clustervisitor.csv')
# Perform segmentation based on characteristics (e.g., age groups)
age_groups = {
'Young': visitor_df['Age'] <= 30,
'Middle-aged': (visitor_df['Age'] > 30) & (visitor_df['Age'] <= 50),
'Elderly': visitor_df['Age'] > 50
}
for group, condition in age_groups.items():
visitors_in_group = visitor_df[condition]
print(f"Visitors in {group} age group:")
print(visitors_in_group)
Thus the Implementation of Cluster and Visitor Segmentation for Navigation patterns is executed successfully.