from pytrends.request import TrendReq
# Define your keywords in a list
keywords = ['Travel Management']
# Create a dictionary with 'kw_list' as key and your keywords list as value
kw_list = {'kw_list': keywords}
# Initialize pytrends and build payload using the defined kw_list and specify the country as Kenya
pytrend = TrendReq(hl='en-KE') # 'hl' parameter sets the language to English and 'geo' parameter sets the region to Kenya
# Build payload with the defined kw_list and the geo parameter for Kenya
pytrend.build_payload(kw_list['kw_list'], geo='US')
# Fetch interest by region for Kenya
Travel_df = pytrend.interest_by_region()
# Display the top 10 rows
Travel_df.head(10)
| Travel Management | |
|---|---|
| geoName | |
| Alabama | 44 |
| Alaska | 69 |
| Arizona | 44 |
| Arkansas | 30 |
| California | 38 |
| Colorado | 47 |
| Connecticut | 36 |
| Delaware | 47 |
| District of Columbia | 100 |
| Florida | 44 |
import matplotlib.pyplot as plt
# Sort the DataFrame in descending order based on the 'Travel Management' column
sorted_df = Travel_df.sort_values(by='Travel Management', ascending=False)
# Select the top ten rows
top_ten = sorted_df.head(10)
# Display the top ten regions
print("Top Ten Regions with Highest Interest in Travel Management:")
print(top_ten)
# Create a pie chart using the 'top_ten' DataFrame
plt.figure(figsize=(8, 6)) # Adjust the figure size if needed
top_ten['Travel Management'].plot(kind='pie', autopct='%1.1f%%', startangle=140)
# Add title and labels
plt.title('Top Ten Regions with Highest Interest in Travel Management in USA')
plt.ylabel('') # No need for y-label, as it's redundant in a pie chart
# Display the pie chart
plt.axis('equal') # Equal aspect ratio ensures that pie is drawn as a circle
plt.show()
Top Ten Regions with Highest Interest in Travel Management:
Travel Management
geoName
District of Columbia 100
Hawaii 94
New York 69
Alaska 69
Virginia 58
Montana 58
Oregon 55
North Carolina 50
Kansas 47
Maryland 47