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DailyTrends 6.0

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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.

Installation

pip install DailyTrends

Or with uv:

uv add DailyTrends

Quick Start

from 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.
  • end defaults to "TODAY".
  • start defaults to "2004-01-01".
  • geo defaults to "" (worldwide). Use country codes like "US", "DE".

Plotting

ax = data.rolling(10).mean().plot()
data.rolling(25).mean().plot(ax=ax)
data.rolling(50).mean().plot(ax=ax)

image.png

Multiple Queries

data = collect_data(["Intel", "AMD"], start="2004-01-01", end="TODAY",
                    geo="DE", save=False, verbose=False)

Combine with Your Own Data

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()

image.png

Development

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 build

Disclaimer

This API is not supported by Google and is for experimental purposes only.

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Python package to get the full time series for any search query with daily frequency.

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