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update dist and docs
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mdancho84 committed Jul 18, 2024
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6 changes: 3 additions & 3 deletions docs/_freeze/reference/augment_holiday_signature/execute-results/html.json
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6 changes: 3 additions & 3 deletions docs/_freeze/reference/is_holiday/execute-results/html.json
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"markdown": "---\ntitle: is_holiday\n---\n\n\n\n`is_holiday(idx, country_name='UnitedStates', country=None, engine='pandas')`\n\nCheck if a given list of dates are holidays for a specified country.\n\nNote: This function requires the `holidays` package to be installed.\n\n## Parameters\n\n| Name | Type | Description | Default |\n|----------------|-------------------------------------------------------------------|-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|------------------|\n| `idx` | Union\\[str, datetime, List\\[Union\\[str, datetime\\]\\], pd.Series\\] | The dates to check for holiday status. | _required_ |\n| `country_name` | str | The name of the country for which to check the holiday status. Defaults to 'UnitedStates' if not specified. | `'UnitedStates'` |\n| `country` | str | An alternative parameter to specify the country for holiday checking, overriding country_name. | `None` |\n| `engine` | str | The `engine` parameter is used to specify the engine to use for generating the boolean series. It can be either \"pandas\" or \"polars\". - The default value is \"pandas\". - When \"polars\", the function will internally use the `polars` library for generating a boolean of holidays or not holidays. This can be faster than using \"pandas\" for long series. | `'pandas'` |\n\n## Returns:\n\npd.Series:\n Series containing True if the date is a holiday, False otherwise.\n\n\n\n## Raises:\n\nValueError:\n If the specified country is not found in the holidays package.\n\n\n\n## Examples:\n\n\n::: {.cell execution_count=1}\n``` {.python .cell-code}\nimport polars as pl\nimport pytimetk as tk\n\ntk.is_holiday('2023-01-01', country_name='UnitedStates')\n```\n\n::: {.cell-output .cell-output-display execution_count=1}\n```\n0 True\nName: is_holiday, dtype: bool\n```\n:::\n:::\n\n\n::: {.cell execution_count=2}\n``` {.python .cell-code}\n# List of dates\ntk.is_holiday(['2023-01-01', '2023-01-02', '2023-01-03'], country_name='UnitedStates')\n```\n\n::: {.cell-output .cell-output-display execution_count=2}\n```\n0 True\n1 True\n2 False\nName: is_holiday, dtype: bool\n```\n:::\n:::\n\n\n::: {.cell execution_count=3}\n``` {.python .cell-code}\n# Polars Series\ntk.is_holiday(pl.Series(['2023-01-01', '2023-01-02', '2023-01-03']), country_name='UnitedStates')\n```\n\n::: {.cell-output .cell-output-display execution_count=3}\n```\n0 True\n1 True\n2 False\nName: is_holiday, dtype: bool\n```\n:::\n:::\n\n\n",
"markdown": "---\ntitle: is_holiday\n---\n\n\n\n`is_holiday(idx, country_name='UnitedStates', country=None, engine='pandas')`\n\nCheck if a given list of dates are holidays for a specified country.\n\nNote: This function requires the `holidays` package to be installed.\n\n## Parameters\n\n| Name | Type | Description | Default |\n|----------------|-------------------------------------------------------------------|-----------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------------|------------------|\n| `idx` | Union\\[str, datetime, List\\[Union\\[str, datetime\\]\\], pd.Series\\] | The dates to check for holiday status. | _required_ |\n| `country_name` | str | The name of the country for which to check the holiday status. Defaults to 'UnitedStates' if not specified. | `'UnitedStates'` |\n| `country` | str | An alternative parameter to specify the country for holiday checking, overriding country_name. | `None` |\n| `engine` | str | The `engine` parameter is used to specify the engine to use for generating the boolean series. It can be either \"pandas\" or \"polars\". - The default value is \"pandas\". - When \"polars\", the function will internally use the `polars` library for generating a boolean of holidays or not holidays. This can be faster than using \"pandas\" for long series. | `'pandas'` |\n\n## Returns:\n\npd.Series:\n Series containing True if the date is a holiday, False otherwise.\n\n## Raises:\n\nValueError:\n If the specified country is not found in the holidays package.\n\n## Examples:\n\n\n::: {.cell execution_count=1}\n``` {.python .cell-code}\nimport polars as pl\nimport pytimetk as tk\n\ntk.is_holiday('2023-01-01', country_name='UnitedStates')\n```\n\n::: {.cell-output .cell-output-display execution_count=1}\n```\n0 True\nName: is_holiday, dtype: bool\n```\n:::\n:::\n\n\n::: {.cell execution_count=2}\n``` {.python .cell-code}\n# List of dates\ntk.is_holiday(['2023-01-01', '2023-01-02', '2023-01-03'], country_name='UnitedStates')\n```\n\n::: {.cell-output .cell-output-display execution_count=2}\n```\n0 True\n1 True\n2 False\nName: is_holiday, dtype: bool\n```\n:::\n:::\n\n\n::: {.cell execution_count=3}\n``` {.python .cell-code}\n# Polars Series\ntk.is_holiday(pl.Series(['2023-01-01', '2023-01-02', '2023-01-03']), country_name='UnitedStates')\n```\n\n::: {.cell-output .cell-output-display execution_count=3}\n```\n0 True\n1 True\n2 False\nName: is_holiday, dtype: bool\n```\n:::\n:::\n\n\n",
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38 changes: 33 additions & 5 deletions docs/_site/changelog-news.html
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<meta name="viewport" content="width=device-width, initial-scale=1.0, user-scalable=yes">


<title>pytimetk - Changelog for PyTimeTK</title>
<title>pytimetk - Changelog for Pytimetk</title>
<style>
code{white-space: pre-wrap;}
span.smallcaps{font-variant: small-caps;}
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<script src="//load.sumome.com/" data-sumo-site-id="070b24e7e068776f081d1a2a477c11bcfe804d8310bdfd4e44277194b8e41b07" async="async"></script>


<meta property="og:title" content="pytimetk - Changelog for PyTimeTK">
<meta property="og:title" content="pytimetk - Changelog for Pytimetk">
<meta property="og:description" content="">
<meta property="og:site-name" content="pytimetk">
<meta name="twitter:title" content="pytimetk - Changelog for PyTimeTK">
<meta name="twitter:title" content="pytimetk - Changelog for Pytimetk">
<meta name="twitter:description" content="">
<meta name="twitter:card" content="summary">
</head>
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<h2 id="toc-title">On this page</h2>

<ul>
<li><a href="#pytimetk-0.4.0" id="toc-pytimetk-0.4.0" class="nav-link active" data-scroll-target="#pytimetk-0.4.0">pytimetk 0.4.0</a>
<li><a href="#pytimetk-0.4.0.9000-development-version" id="toc-pytimetk-0.4.0.9000-development-version" class="nav-link active" data-scroll-target="#pytimetk-0.4.0.9000-development-version">pytimetk 0.4.0.9000 (Development Version)</a>
<ul class="collapse">
<li><a href="#pandas-and-polars-compatibility" id="toc-pandas-and-polars-compatibility" class="nav-link" data-scroll-target="#pandas-and-polars-compatibility">Pandas and Polars Compatibility:</a></li>
<li><a href="#improvements" id="toc-improvements" class="nav-link" data-scroll-target="#improvements">Improvements:</a></li>
</ul></li>
<li><a href="#pytimetk-0.4.0" id="toc-pytimetk-0.4.0" class="nav-link" data-scroll-target="#pytimetk-0.4.0">pytimetk 0.4.0</a>
<ul class="collapse">
<li><a href="#feature-engineering-module" id="toc-feature-engineering-module" class="nav-link" data-scroll-target="#feature-engineering-module">Feature Engineering Module:</a></li>
<li><a href="#finance-module-updates" id="toc-finance-module-updates" class="nav-link" data-scroll-target="#finance-module-updates">Finance Module Updates:</a></li>
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<header id="title-block-header" class="quarto-title-block default">
<div class="quarto-title">
<h1 class="title">Changelog for PyTimeTK</h1>
<h1 class="title">Changelog for Pytimetk</h1>
</div>


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</header>

<section id="pytimetk-0.4.0.9000-development-version" class="level1">
<h1>pytimetk 0.4.0.9000 (Development Version)</h1>
<section id="pandas-and-polars-compatibility" class="level2">
<h2 class="anchored" data-anchor-id="pandas-and-polars-compatibility">Pandas and Polars Compatibility:</h2>
<p>Upgrading to:</p>
<ul>
<li>pandas &gt;= 2.0.0</li>
<li>polars &gt;= 1.2.0</li>
</ul>
<p>Use pytimetk &lt;=0.4.0 to support:</p>
<ul>
<li>pandas &lt;2.0.0</li>
<li>polars &lt;1.0.0</li>
</ul>
</section>
<section id="improvements" class="level2">
<h2 class="anchored" data-anchor-id="improvements">Improvements:</h2>
<ul>
<li>Implement <code>sort_dataframe()</code>: This function is used internally to make sure Polars and Pandas engines perform grouped operations consistently and correctly. #286 #290</li>
<li><code>.augment_lags()</code> and <code>.augment_leads()</code>: value_column now accepts any dtype. #295</li>
</ul>
</section>
</section>
<section id="pytimetk-0.4.0" class="level1">
<h1>pytimetk 0.4.0</h1>
<section id="feature-engineering-module" class="level2">
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Expand Up @@ -651,15 +651,15 @@ <h2 class="anchored" data-anchor-id="examples">Examples</h2>
<span id="cb2-14"><a href="#cb2-14" aria-hidden="true" tabindex="-1"></a>df_ppo.glimpse()</span></code><button title="Copy to Clipboard" class="code-copy-button"><i class="bi"></i></button></pre></div>
<div class="cell-output cell-output-stdout">
<pre><code>&lt;class 'pandas.core.frame.DataFrame'&gt;: 16194 rows of 9 columns
symbol: object ['META', 'META', 'META', 'META' ...
symbol: object ['AAPL', 'AAPL', 'AAPL', 'AAPL' ...
date: datetime64[ns] [Timestamp('2013-01-02 00:00:00 ...
open: float64 [27.440000534057617, 27.8799991 ...
high: float64 [28.18000030517578, 28.46999931 ...
low: float64 [27.420000076293945, 27.5900001 ...
close: float64 [28.0, 27.770000457763672, 28.7 ...
volume: int64 [69846400, 63140600, 72715400, ...
adjusted: float64 [28.0, 27.770000457763672, 28.7 ...
close_ppo_line_12_26: float64 [0.0, -0.06556683019189882, 0.1 ...</code></pre>
open: float64 [19.779285430908203, 19.5671424 ...
high: float64 [19.821428298950195, 19.6310710 ...
low: float64 [19.343929290771484, 19.3214282 ...
close: float64 [19.608213424682617, 19.3607139 ...
volume: int64 [560518000, 352965200, 59433360 ...
adjusted: float64 [16.791179656982422, 16.5792407 ...
close_ppo_line_12_26: float64 [0.0, -0.10078442036791524, -0. ...</code></pre>
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30 changes: 15 additions & 15 deletions docs/_site/reference/augment_rolling.html
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