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Feat: Adding a tutorial for the Iowa Liquor dataset#419

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happyhuman merged 9 commits into
GoogleCloudPlatform:mainfrom
edkrizo:main
Aug 3, 2022
Merged

Feat: Adding a tutorial for the Iowa Liquor dataset#419
happyhuman merged 9 commits into
GoogleCloudPlatform:mainfrom
edkrizo:main

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@edkrizo

@edkrizo edkrizo commented Jul 19, 2022

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Description

Note: If you are adding or editing a dataset, please specify the dataset folder involved, e.g. datasets/google_trends

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Use the sections below based on what's applicable to your PR and delete the rest:

Feature

  • I'm adding or editing a feature
  • I have updated the README accordingly
  • I have added/revised tests for the feature

Data Onboarding

  • I'm adding or editing a dataset
  • The Google Cloud Datasets team is aware of the proposed dataset
  • I put all my code inside datasets/<DATASET_NAME> and nothing outside of that directory

Documentation

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Bug fix

  • I'm submitting a bugfix
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Code cleanup or refactoring

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@edkrizo edkrizo changed the title iowa_liquor_sale tutorial datasets/iowa_liquor_sale/docs Jul 19, 2022
@happyhuman happyhuman changed the title datasets/iowa_liquor_sale/docs Feat: Adding a tutorial for the Iowa Liquor dataset Jul 19, 2022
@@ -0,0 +1,1026 @@
{

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Line #2.    from datetime import datetime

I am not sure if you actually made use of datetime in your code. If not, flake8 will warn you and you can delete this line.


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Comment thread datasets/iowa_liquor_sales/docs/tutorials/liquor_sales_prediction/tutorial.ipynb Outdated

artifact:
title: "Iowa Liquor sales predictions"
description: "Predict a liquor sales price based previous years sales data using a tree based ML estimators such as Random Forest"

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lint is complaining about line 17: 17:16 [colons] too many spaces after colon

import pandas as pd
mock_client = mock.MagicMock()
mock_df = pd.DataFrame()
mock_df['week'] = range(50)

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You want to change mock_df. These lines are added, so our test code does not make an actual request to BigQuery. Instead, we "mock" the BQ call, and create a mock object (in this case, mock_df) to be the object we pretend that our BQ call returned. You want it to be a dataframe that you expect the BQ call returns, so the rest of your code can function and work properly.

dataframe = tb.get("dataframe")
assert dataframe.shape == (50, 3)

train_pred_plot = tb.get("train_pred_plot")

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You want to pick an object from your code (ideally something from the end of your code) and replace train_pred_plot with it, and test whether it exists or not. That way, we are testing whether your notebook runs all the way to the end during the test.

edkrizo and others added 3 commits July 21, 2022 14:32
reducing the librarires
reducing spaces after columns
@happyhuman happyhuman merged commit b619b71 into GoogleCloudPlatform:main Aug 3, 2022
vijay-google pushed a commit to vijay-google/public-datasets-pipelines that referenced this pull request Aug 17, 2022
…orm#419)

* putting my files with docs

* changing my project id

* flake8 passed on notebook & test

* reducing spaces in files names

* reformatting the artifact

* Update artifact.yaml

reducing the librarires

* Update artifact.yaml

reducing spaces after columns

* Adding test file and notebook

Co-authored-by: Edouard Gahou <edouardg@google.com>
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2 participants