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Oracle Drags Its Feet in the JavaScript Trademark Dispute
Oracle seeks to dismiss fraud claims in the JavaScript trademark dispute, delaying the case and avoiding questions about its right to the name.
PyGoogalytics allows a user to quickly and simply download Google Analytics and Google Search Console data
PyGoogalytics can be installed using pip:
pip install -U pygoogalytics
Although PyGoogalytics is intended to be user-friendly it is still necessary to set up various accounts and credentials with Google. If you haven't yet setup API access for Universal Analytics, GA4, Search Console or Google Ads, follow our instructions to get started.
client.py
defines the class Client
which builds googleapiclient.discovery
resources for accessing
Google Search Console and Google Analytics 3 (UA) data from the respective APIs,
and also google.analytics.data_v1beta.BetaAnalyticsDataClient
resource for accessing GA4 data, although
currently this is only for testing.
Before using this python package you must create a service account and download a JSON key file following the instructions from Google. This process will also give you a service account email address, you need to add this email address to the user list for the Analytics or Search Console account for which you want to obtain data — you only need to give the service account "read" access.
A Client
class can create a GoogalyticsWrapper
object which has methods to access data
the Google services and return a pandas dataframe.
A typical implementation will look like:
from pygoogalytics.client import Client
googalytics_client = Client(key_file_path='<path-to-your-key-file>')
g_wrapper = googalytics_client.wrapper(
sc_domain='<search-console-domain>',
view_id='<ga3-view-id>',
ga4_property_id='<ga4-property-id>'
)
ga3_dataframe = g_wrapper.get_df(
result='GA3',
start_date='2023-01-01',
end_date='2023-01-07',
metrics=['ga:itemRevenue', 'ga:itemQuantity', 'ga:users'],
dimensions=['ga:dateHourMinute', 'ga:landingPagePath', 'ga:sourceMedium', 'ga:countryIsoCode']
)
The get_df
method accepts the following values for the result
argument:
sort_values
, groupby
, etc. to analyse your data.country_iso_code
, landing_page
,
ctr
and position
from GSC, and another from GA3 with country_iso_code
, landing_page
and transaction_revenue
,
then join on the dimensions (country_iso_code
, landing_page
) to get a single data frame with data from both GA3 and GSC.googlepandas.py
provides the classes GADataFrame
and GSCDataFrame
,
both children of pandas DataFrame
specific to storing
GA and GSC data with additional metadata fields
(e.g. dimensions
and metrics
) and methods for adding columns
and filtering by particular metrics.
FAQs
PyGoogalytics allows a user to quickly and simply download Google Analytics and Google Search Console data
We found that pygoogalytics demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
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