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pytrends's Introduction

pytrends

About

Pseudo API for Google Trends

  • Allows simple interface for automating downloads of csv reports from Google Trends.

  • Main feature is to help trick google into thinking the script is actually a browser.

  • Only good until Google changes their backend again :-P

Installation

pip install pytrends

Requirements

  • Written for both Python 2.7+ and Python 3.3+
  • Requires a google account to use.
  • Requires fake-useragent python library (installed automatically with pip)

Caveats

  • This is not an official or supported API
  • Google may change aggregation level for items with very large or very small search volume

Connect to Google

pyGTrends(google_username, google_password)

Parameters

  • google_username
    • a valid gmail address
  • google_password
    • password for the gmail account

Request a Report

request_report(keywords, hl='en-US', cat=None, geo=None, date=None, gprop=None)

Parameters

  • Keywords
    • the words to get data for
    • Example "Pizza"
    • Up to five terms with a comma and space: "Pizza, Italian, Spaghetti, Breadsticks, Sausage"
  • Advanced Keywords
    • When using Google Trends dashboard Google may provide suggested narrowed search terms.
    • For example "iron" will have a drop down of "Iron Chemical Element, Iron Cross, Iron Man, etc".
    • Find the encoded topic by using the get_suggestions() function and choose the most relevant one for you.
    • For example: https://www.google.com/trends/explore#q=%2Fm%2F025rw19&cmpt=q
    • "%2Fm%2F025rw19" is the topic "Iron Chemical Element" to use this with pytrends
  • hl
    • Language to return result headers in
    • Two letter language abbreviation
    • For example English is "en"
    • Defaults to english
  • cat
    • Category to narrow results
    • Find available cateogies by inspecting the url when manually using Google Trends. The category starts after cat= and ends before the next &
    • For example: "https://www.google.com/trends/explore#q=pizza&cat=0-71"
    • "0-71" is the category
    • Defaults to no category
  • geo
    • Two letter country abbreviation
    • For example United States is "US"
    • Defaults to World
    • More detail available for States/Provinces by specifying additonal abbreviations
    • For example: Alabama would be US-AL
    • For example: England would be GB-ENG
  • tz
    • Timezone using Etc/GMT
    • For example US CST is "Etc/GMT+5"
  • date
    • Date to start from
    • Defaults to all available data, 2004 - present.
    • Custom Timeframe Pattern:
      • By Month: "MM/YYYY #m" where # is the number of months from that date to pull data for
        • For example: "10/2009 61m" would get data from October 2009 to October 2014
        • Less than 4 months will return Daily level data
        • More than 36 months will return monthly level data
        • 4-36 months will return weekly level data
    • Current Time Minus Time Pattern:
      • By Month: "today #-m" where # is the number of months from that date to pull data for
        • For example: "today 61-m" would get data from today to 61months ago
        • 1-3 months will return daily intervals of data
        • 4-36 months will return weekly intervals of data
        • 36+ months will return monthly intervals of data
        • NOTE Google uses UTC date as 'today'
      • Daily: "today #-d" where # is the number of days from that date to pull data for
        • For example: "today 7-d" would get data from the last week
        • 1 day will return 8min intervals of data
        • 2-8 days will return Hourly intervals of data
        • 8-90 days will return Daily level data
      • Hourly: "now #-H" where # is the number of hours from that date to pull data for
        • For example: "now 1-H" would get data from the last hour
        • 1-3 hours will return 1min intervals of data
        • 4-26 hours will return 8min intervals of data
        • 27-34 hours will return 16min intervals of data
  • gprop
    • What search data we want
    • Defaults to web searches
    • Can be images, news, youtube or froogle (for Google Shopping results)

Save a Report to file

save_csv(path, trend_name)

Parameters

  • path
    • Output path
  • trend_name
    • Human readable name for file

Get Google Term Suggestions

get_suggestions(keyword)

Parameters

  • keyword
    • keyword to get suggestions for

Returns JSON {"default": {"topics": [{"mid": "/m/0663v","title": "Pizza","type": "Dish"}]}}

  • Use the mid value for the keyword in future searches for a more refined trend set

Credits

pytrends's People

Contributors

bdewilde avatar dreyco676 avatar jczerwinski avatar nwillems avatar petersonnek avatar srepho avatar tiesdekok avatar

Stargazers

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Watchers

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