A lightweight API to get full-range daily Google Trends data. Solves the problem of getting only monthly-based data for large time series. No login required.
pip install DailyTrendsOr with uv:
uv add DailyTrendsfrom DailyTrends import collect_data
data = collect_data("AMD stock", start="2004-01-01", end="2024-07-06",
geo="", save=False, verbose=False)data.info()
# <class 'pandas.core.frame.DataFrame'>
# DatetimeIndex: 7493 entries, 2004-01-01 to 2024-07-06
# Freq: D
# ...- The returned DataFrame is datetime-indexed and ready for storage/analysis.
enddefaults to"TODAY".startdefaults to"2004-01-01".geodefaults to""(worldwide). Use country codes like"US","DE".
ax = data.rolling(10).mean().plot()
data.rolling(25).mean().plot(ax=ax)
data.rolling(50).mean().plot(ax=ax)data = collect_data(["Intel", "AMD"], start="2004-01-01", end="TODAY",
geo="DE", save=False, verbose=False)import pandas as pd
price_data = pd.read_csv("price_data.csv")
merged = pd.merge(price_data, data, left_index=True, right_index=True)
merged[["AMD stock: (Worldwide)", "Open"]].rolling(30).mean().plot()This project uses uv for dependency management.
# Clone and set up
git clone https://github.com/le0x99/DailyTrends.git
cd DailyTrends
uv sync
# Run tests
uv run pytest -v
# Run linter
uv run ruff check .
# Build the package
uv buildThis API is not supported by Google and is for experimental purposes only.

