Unofficial API for Google Trends
Allows simple interface for automating downloading of reports from Google Trends. Main feature is to allow the script to login to Google on your behalf to enable a higher rate limit. Only good until Google changes their backend again :-P. When that happens feel free to contribute!
pip install pytrends
- Written for both Python 2.7+ and Python 3.3+
- Requires Requests, lxml, Pandas
from pytrends.request import TrendReq
pytrends = TrendReq(hl='en-US', tz=360)
kw_list = ["Blockchain"]
pytrends.build_payload(kw_list, cat=0, timeframe='today 5-y', geo='', gprop='')
Parameters
-
kw_list- Required
- Keywords to get data for
The following API methods are available:
-
Interest Over Time: returns historical, indexed data for when the keyword was searched most as shown on Google Trends' Interest Over Time section.
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Interest by Region: returns data for where the keyword is most searched as shown on Google Trends' Interest by Region section.
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Related Topics: returns data for the related keywords to a provided keyword shown on Google Trends' Related Topics section.
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Related Queries: returns data for the related keywords to a provided keyword shown on Google Trends' Related Queries section.
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Trending Searches: returns data for latest trending searches shown on Google Trends' Trending Searches section.
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Top Charts: returns the data for a given topic shown in Google Trends' Top Charts section.
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Suggestions: returns a list of additional suggested keywords that can be used to refine a trend search.
Many API methods use the following:
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kw_list-
keywords to get data for
-
Example
['Pizza'] -
Up to five terms in a list:
['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- You can also use
pytrends.suggestions()to automate this.
-
-
-
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&or view this wiki page containing all available categories - For example:
"https://www.google.com/trends/explore#q=pizza&cat=71" '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 Offset
- For example US CST is
'360'
-
timeframe-
Date to start from
-
Defaults to last 5yrs,
'today 5-y'. -
Everything
'all' -
Specific dates, 'YYYY-MM-DD YYYY-MM-DD' example
'2016-12-14 2017-01-25' -
Specific datetimes, 'YYYY-MM-DDTHH YYYY-MM-DDTHH' example
'2017-02-06T10 2017-02-12T07'- Note Time component is based off UTC
-
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 3-m'would get data from today to 3months ago - NOTE Google uses UTC date as 'today'
- Seems to only work for 1, 2, 3 months only
- For example:
-
Daily:
'now #-d'where # is the number of days from that date to pull data for- For example:
'now 7-d'would get data from the last week - Seems to only work for 1, 7 days only
- For example:
-
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 - Seems to only work for 1, 4 hours only
- For example:
-
-
-
gprop- What Google property to filter to
- Example
'images' - Defaults to web searches
- Can be
images,news,youtubeorfroogle(for Google Shopping results)
pytrends.interest_over_time()
Returns pandas.Dataframe
pytrends.interest_by_region(resolution='COUNTRY')
Parameters
-
resolution- 'CITY' returns city level data
- 'COUNTRY' returns country level data
Returns pandas.DataFrame
pytrends.related_topics()
Returns dictionary of pandas.DataFrames
pytrends.related_queries()
Returns dictionary of pandas.DataFrames
pytrends.trending_searches(pn='p1') # in English
pytrends.trending_searches(pn='p4') # in Japanese
Returns pandas.DataFrame
pytrends.topcharts(date, cid, geo='US', cat='')
Parameters
-
date- Required
- YYYYMM integer or string value
- Example
'201611'for November 2016 Top Chart data
-
cid- Required
- Topic to get data for
- Only able to choose from those listed on https://www.google.com/trends/topcharts
- Example the chart 'Baseketball players
cidis'basketball_players'
Returns pandas.DataFrame
pytrends.suggestions(keyword)
Parameters
-
keyword- Required
- keyword to get suggestions for
Returns dictionary
pytrends.categories()
Returns dictionary
- This is not an official or supported API
- Google may change aggregation level for items with very large or very small search volume
- Google will send you an email saying that you had a new login after running this.
- Rate Limit is not publicly known, let me know if you have a consistent estimate.
- For certain configurations the dependency lib certifi requires the environment variable REQUESTS_CA_BUNDLE to be explicitly set and exported. This variable must contain the path where the ca-certificates are saved or a SSLError: [SSL: CERTIFICATE_VERIFY_FAILED] error is given at runtime.
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Major JSON revision ideas taken from pat310's JavaScript library
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Connecting to google code heavily based off Stack Overflow post
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With some ideas pulled from Matt Reid's Google Trends API