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docs: add the first sample for the Single time-series forecasting from Google Analytics data tutorial #623

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Original file line number Diff line number Diff line change
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# Copyright 2024 Google LLC
#
# Licensed under the Apache License, Version 2.0 (t
# you may not use this file except in compliance wi
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in
# distributed under the License is distributed on a
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, eit
# See the License for the specific language governi
# limitations under the License.


def test_create_single_timeseries():

# [START bigquery_dataframes_single_timeseries_forecasting_model_tutorial]
import bigframes.pandas as bpd

# Start by loading the historical data from BigQuerythat you want to analyze and forecast.
# This clause indicates that you are querying the ga_sessions_* tables in the google_analytics_sample dataset.
# Read and visualize the time series you want to forecast.
df = bpd.read_gbq("bigquery-public-data.google_analytics_sample.ga_sessions_*")
parsed_date = bpd.to_datetime(df.date, format="%Y%m%d", utc=True)
visits = df["totals"].struct.field("visits")
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total_visits = visits.groupby(parsed_date).sum()

# Expected output: total_visits.head()
# date
# 2016-08-01 00:00:00+00:00 1711
# 2016-08-02 00:00:00+00:00 2140
# 2016-08-03 00:00:00+00:00 2890
# 2016-08-04 00:00:00+00:00 3161
# 2016-08-05 00:00:00+00:00 2702
# Name: visits, dtype: Int64

total_visits.plot.line()

# [END bigquery_dataframes_single_timeseries_forecasting_model_tutorial]
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