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luisgdelafuente/geographical.ipynb

Last active August 31, 2023 16:48
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geographical.ipynb
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"source": [
"# Find the interest for certain term across the US and display the results as an interactive map\n",
"\n",
"import pytrends as pt\n",
"from pytrends.request import TrendReq\n",
"import pandas as pd\n",
"import plotly.express as px\n",
"\n",
"# Initialize the Google Trends object\n",
"pytrends = TrendReq()\n",
"\n",
"# Define the primary keyword, timeframe, and geo\n",
"keyword = \"car wash near me\"\n",
"timeframe = \"today 12-m\"\n",
"geo = 'US' # Search across all states in the USA\n",
"\n",
"# Build the payload with the keyword, timeframe, and geo\n",
"pytrends.build_payload(kw_list=[keyword], timeframe=timeframe, geo=geo)\n",
"\n",
"# Get interest by region data for the keyword\n",
"interest_by_region = pytrends.interest_by_region()\n",
"\n",
"# Mapping of state names to their abbreviations\n",
"state_abbreviations = {\n",
" 'Alabama': 'AL', 'Alaska': 'AK', 'Arizona': 'AZ', 'Arkansas': 'AR', \n",
" 'California': 'CA', 'Colorado': 'CO', 'Connecticut': 'CT', 'Delaware': 'DE',\n",
" 'Florida': 'FL', 'Georgia': 'GA', 'Hawaii': 'HI', 'Idaho': 'ID',\n",
" 'Illinois': 'IL', 'Indiana': 'IN', 'Iowa': 'IA', 'Kansas': 'KS',\n",
" 'Kentucky': 'KY', 'Louisiana': 'LA', 'Maine': 'ME', 'Maryland': 'MD',\n",
" 'Massachusetts': 'MA', 'Michigan': 'MI', 'Minnesota': 'MN', 'Mississippi': 'MS',\n",
" 'Missouri': 'MO', 'Montana': 'MT', 'Nebraska': 'NE', 'Nevada': 'NV',\n",
" 'New Hampshire': 'NH', 'New Jersey': 'NJ', 'New Mexico': 'NM', 'New York': 'NY',\n",
" 'North Carolina': 'NC', 'North Dakota': 'ND', 'Ohio': 'OH', 'Oklahoma': 'OK',\n",
" 'Oregon': 'OR', 'Pennsylvania': 'PA', 'Rhode Island': 'RI', 'South Carolina': 'SC',\n",
" 'South Dakota': 'SD', 'Tennessee': 'TN', 'Texas': 'TX', 'Utah': 'UT',\n",
" 'Vermont': 'VT', 'Virginia': 'VA', 'Washington': 'WA', 'West Virginia': 'WV',\n",
" 'Wisconsin': 'WI', 'Wyoming': 'WY', 'District of Columbia': 'DC'\n",
"}\n",
"\n",
"# Convert state names to abbreviations\n",
"interest_by_region['State'] = interest_by_region.index.map(state_abbreviations)\n",
"\n",
"# Create a DataFrame in the format similar to the dummy data\n",
"df = pd.DataFrame({\n",
" 'State': interest_by_region['State'],\n",
" 'Interest': interest_by_region[keyword]\n",
"})\n",
"\n",
"# Plotting the data using Plotly\n",
"fig = px.choropleth(df, \n",
" locations='State', \n",
" color='Interest',\n",
" locationmode='USA-states',\n",
" scope=\"usa\",\n",
" color_continuous_scale=\"Viridis\",\n",
" title=f\"Interest by State for '{keyword}'\")\n",
"\n",
"fig.update_layout(width=600)\n",
" \n",
"fig.show()\n",
"\n"
]
}
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