Auto-generated documentation

docs/health.html

@@ -61,10 +61,12 @@ <h1 class="title">Module <code>pydbsmgr.health</code></h1>
     def fix(self, cols_upper_case: bool = False, drop_empty_cols: bool = True) -&gt; None:
         &#34;&#34;&#34;Performs the clean of the data and validation
 
-        Args:
-        -----
-            cols_upper_case (`bool`, optional): Indicates whether to convert column names to uppercase. Defaults to `False`.
-            drop_empty_cols (`bool`, optional): Variable indicating whether columns with all their values empty should be removed. Defaults to `True`.
+        Parameters
+        ----------
+        cols_upper_case : `bool`, `optional`
+            Indicates whether to convert column names to uppercase. Defaults to `False`.
+        drop_empty_cols : `bool`, `optional`
+            Variable indicating whether columns with all their values empty should be removed. Defaults to `True`.
         &#34;&#34;&#34;
         if drop_empty_cols:
             for count, df in enumerate(self._dfs):
@@ -88,14 +90,20 @@ <h1 class="title">Module <code>pydbsmgr.health</code></h1>
     ) -&gt; None:
         &#34;&#34;&#34;Generate a `.html` health check report.
 
-        Args:
-        -----
-            report_name (`str`, optional): Name of the quality assessment report. Defaults to `./report.html`.
-            yaml_name (`str`, optional): Indicates the name of the `.yaml` file that will serve as a template for the creation of the SQL table. Defaults to `./output.yaml`.
-            database_name (`str`, optional): The header of the `.yaml` file. Default value is `database`
-            directory_name (`str`, optional): Folder in which the reports will be saved. Defaults to `summary`.
-            concat_vertically: (`bool`, optional), Variable indicating whether the list of dataframes should be vertically concatenated into a single one. Default value is `False`.
-            encoding (`str`, optional): The encoding of dataframes. Defaults to `utf-8`.
+        Parameters
+        ----------
+        report_name : `str`, `optional`
+            Name of the quality assessment report. Defaults to `./report.html`.
+        yaml_name : `str`, `optional`
+            Indicates the name of the `.yaml` file that will serve as a template for the creation of the SQL table. Defaults to `./output.yaml`.
+        database_name : `str`, `optional`
+            The header of the `.yaml` file. Default value is `database`
+        directory_name : `str`, `optional`
+            Folder in which the reports will be saved. Defaults to `summary`.
+        concat_vertically : `bool`, `optional`
+            Variable indicating whether the list of dataframes should be vertically concatenated into a single one. Default value is `False`.
+        encoding : `str`, `optional`
+            The encoding of dataframes. Defaults to `utf-8`.
         &#34;&#34;&#34;
         self.df_files_info = pd.DataFrame()
         self.yaml_name = yaml_name
@@ -239,10 +247,12 @@ <h2 class="section-title" id="header-classes">Classes</h2>
     def fix(self, cols_upper_case: bool = False, drop_empty_cols: bool = True) -&gt; None:
         &#34;&#34;&#34;Performs the clean of the data and validation
 
-        Args:
-        -----
-            cols_upper_case (`bool`, optional): Indicates whether to convert column names to uppercase. Defaults to `False`.
-            drop_empty_cols (`bool`, optional): Variable indicating whether columns with all their values empty should be removed. Defaults to `True`.
+        Parameters
+        ----------
+        cols_upper_case : `bool`, `optional`
+            Indicates whether to convert column names to uppercase. Defaults to `False`.
+        drop_empty_cols : `bool`, `optional`
+            Variable indicating whether columns with all their values empty should be removed. Defaults to `True`.
         &#34;&#34;&#34;
         if drop_empty_cols:
             for count, df in enumerate(self._dfs):
@@ -266,14 +276,20 @@ <h2 class="section-title" id="header-classes">Classes</h2>
     ) -&gt; None:
         &#34;&#34;&#34;Generate a `.html` health check report.
 
-        Args:
-        -----
-            report_name (`str`, optional): Name of the quality assessment report. Defaults to `./report.html`.
-            yaml_name (`str`, optional): Indicates the name of the `.yaml` file that will serve as a template for the creation of the SQL table. Defaults to `./output.yaml`.
-            database_name (`str`, optional): The header of the `.yaml` file. Default value is `database`
-            directory_name (`str`, optional): Folder in which the reports will be saved. Defaults to `summary`.
-            concat_vertically: (`bool`, optional), Variable indicating whether the list of dataframes should be vertically concatenated into a single one. Default value is `False`.
-            encoding (`str`, optional): The encoding of dataframes. Defaults to `utf-8`.
+        Parameters
+        ----------
+        report_name : `str`, `optional`
+            Name of the quality assessment report. Defaults to `./report.html`.
+        yaml_name : `str`, `optional`
+            Indicates the name of the `.yaml` file that will serve as a template for the creation of the SQL table. Defaults to `./output.yaml`.
+        database_name : `str`, `optional`
+            The header of the `.yaml` file. Default value is `database`
+        directory_name : `str`, `optional`
+            Folder in which the reports will be saved. Defaults to `summary`.
+        concat_vertically : `bool`, `optional`
+            Variable indicating whether the list of dataframes should be vertically concatenated into a single one. Default value is `False`.
+        encoding : `str`, `optional`
+            The encoding of dataframes. Defaults to `utf-8`.
         &#34;&#34;&#34;
         self.df_files_info = pd.DataFrame()
         self.yaml_name = yaml_name
@@ -383,21 +399,26 @@ <h3>Methods</h3>
 </code></dt>
 <dd>
 <div class="desc"><p>Performs the clean of the data and validation</p>
-<h2 id="args">Args:</h2>
-<pre><code>cols_upper_case (&lt;code&gt;bool&lt;/code&gt;, optional): Indicates whether to convert column names to uppercase. Defaults to &lt;code&gt;False&lt;/code&gt;.
-drop_empty_cols (&lt;code&gt;bool&lt;/code&gt;, optional): Variable indicating whether columns with all their values empty should be removed. Defaults to &lt;code&gt;True&lt;/code&gt;.
-</code></pre></div>
+<h2 id="parameters">Parameters</h2>
+<dl>
+<dt><strong><code>cols_upper_case</code></strong> :&ensp;<code>bool<code>,</code>optional</code></dt>
+<dd>Indicates whether to convert column names to uppercase. Defaults to <code>False</code>.</dd>
+<dt><strong><code>drop_empty_cols</code></strong> :&ensp;<code>bool<code>,</code>optional</code></dt>
+<dd>Variable indicating whether columns with all their values empty should be removed. Defaults to <code>True</code>.</dd>
+</dl></div>
 <details class="source">
 <summary>
 <span>Expand source code</span>
 </summary>
 <pre><code class="python">def fix(self, cols_upper_case: bool = False, drop_empty_cols: bool = True) -&gt; None:
     &#34;&#34;&#34;Performs the clean of the data and validation
 
-    Args:
-    -----
-        cols_upper_case (`bool`, optional): Indicates whether to convert column names to uppercase. Defaults to `False`.
-        drop_empty_cols (`bool`, optional): Variable indicating whether columns with all their values empty should be removed. Defaults to `True`.
+    Parameters
+    ----------
+    cols_upper_case : `bool`, `optional`
+        Indicates whether to convert column names to uppercase. Defaults to `False`.
+    drop_empty_cols : `bool`, `optional`
+        Variable indicating whether columns with all their values empty should be removed. Defaults to `True`.
     &#34;&#34;&#34;
     if drop_empty_cols:
         for count, df in enumerate(self._dfs):
@@ -413,14 +434,21 @@ <h2 id="args">Args:</h2>
 </code></dt>
 <dd>
 <div class="desc"><p>Generate a <code>.html</code> health check report.</p>
-<h2 id="args">Args:</h2>
-<pre><code>report_name (&lt;code&gt;str&lt;/code&gt;, optional): Name of the quality assessment report. Defaults to `./report.html`.
-yaml_name (&lt;code&gt;str&lt;/code&gt;, optional): Indicates the name of the &lt;code&gt;.yaml&lt;/code&gt; file that will serve as a template for the creation of the SQL table. Defaults to `./output.yaml`.
-database_name (&lt;code&gt;str&lt;/code&gt;, optional): The header of the &lt;code&gt;.yaml&lt;/code&gt; file. Default value is &lt;code&gt;database&lt;/code&gt;
-directory_name (&lt;code&gt;str&lt;/code&gt;, optional): Folder in which the reports will be saved. Defaults to &lt;code&gt;summary&lt;/code&gt;.
-concat_vertically: (&lt;code&gt;bool&lt;/code&gt;, optional), Variable indicating whether the list of dataframes should be vertically concatenated into a single one. Default value is &lt;code&gt;False&lt;/code&gt;.
-encoding (&lt;code&gt;str&lt;/code&gt;, optional): The encoding of dataframes. Defaults to `utf-8`.
-</code></pre></div>
+<h2 id="parameters">Parameters</h2>
+<dl>
+<dt><strong><code>report_name</code></strong> :&ensp;<code>str<code>,</code>optional</code></dt>
+<dd>Name of the quality assessment report. Defaults to <code>./report.html</code>.</dd>
+<dt><strong><code>yaml_name</code></strong> :&ensp;<code>str<code>,</code>optional</code></dt>
+<dd>Indicates the name of the <code>.yaml</code> file that will serve as a template for the creation of the SQL table. Defaults to <code>./output.yaml</code>.</dd>
+<dt><strong><code>database_name</code></strong> :&ensp;<code>str<code>,</code>optional</code></dt>
+<dd>The header of the <code>.yaml</code> file. Default value is <code>database</code></dd>
+<dt><strong><code>directory_name</code></strong> :&ensp;<code>str<code>,</code>optional</code></dt>
+<dd>Folder in which the reports will be saved. Defaults to <code>summary</code>.</dd>
+<dt><strong><code>concat_vertically</code></strong> :&ensp;<code>bool<code>,</code>optional</code></dt>
+<dd>Variable indicating whether the list of dataframes should be vertically concatenated into a single one. Default value is <code>False</code>.</dd>
+<dt><strong><code>encoding</code></strong> :&ensp;<code>str<code>,</code>optional</code></dt>
+<dd>The encoding of dataframes. Defaults to <code>utf-8</code>.</dd>
+</dl></div>
 <details class="source">
 <summary>
 <span>Expand source code</span>
@@ -436,14 +464,20 @@ <h2 id="args">Args:</h2>
 ) -&gt; None:
     &#34;&#34;&#34;Generate a `.html` health check report.
 
-    Args:
-    -----
-        report_name (`str`, optional): Name of the quality assessment report. Defaults to `./report.html`.
-        yaml_name (`str`, optional): Indicates the name of the `.yaml` file that will serve as a template for the creation of the SQL table. Defaults to `./output.yaml`.
-        database_name (`str`, optional): The header of the `.yaml` file. Default value is `database`
-        directory_name (`str`, optional): Folder in which the reports will be saved. Defaults to `summary`.
-        concat_vertically: (`bool`, optional), Variable indicating whether the list of dataframes should be vertically concatenated into a single one. Default value is `False`.
-        encoding (`str`, optional): The encoding of dataframes. Defaults to `utf-8`.
+    Parameters
+    ----------
+    report_name : `str`, `optional`
+        Name of the quality assessment report. Defaults to `./report.html`.
+    yaml_name : `str`, `optional`
+        Indicates the name of the `.yaml` file that will serve as a template for the creation of the SQL table. Defaults to `./output.yaml`.
+    database_name : `str`, `optional`
+        The header of the `.yaml` file. Default value is `database`
+    directory_name : `str`, `optional`
+        Folder in which the reports will be saved. Defaults to `summary`.
+    concat_vertically : `bool`, `optional`
+        Variable indicating whether the list of dataframes should be vertically concatenated into a single one. Default value is `False`.
+    encoding : `str`, `optional`
+        The encoding of dataframes. Defaults to `utf-8`.
     &#34;&#34;&#34;
     self.df_files_info = pd.DataFrame()
     self.yaml_name = yaml_name

docs/lightest.html

@@ -37,13 +37,13 @@ <h1 class="title">Module <code>pydbsmgr.lightest</code></h1>
 
     Parameters
     ----------
-        x : `str`
-            character of type date.
+    x : `str`
+        character of type date.
 
     Returns
     ----------
-        x : `str`
-            character after processing with format `YYYY-MM-DD`.
+    x : `str`
+        character after processing with format `YYYY-MM-DD`.
     &#34;&#34;&#34;
     # performing data type conversion
     x = str(x)
@@ -106,16 +106,17 @@ <h1 class="title">Module <code>pydbsmgr.lightest</code></h1>
 
         Parameters
         ----------
-        - sample_frac (`float`): The fraction of rows to use for date type inference. Default is 0.1 i.e., 10%.
-        - fast_execution (`bool`): If `False` use `applymap` pandas for extra text cleanup. Default is `True`.
+        sample_frac : `float`
+            The fraction of rows to use for date type inference. Default is 0.1 i.e., 10%.
+        fast_execution : `bool`
+            If `False` use `applymap` pandas for extra text cleanup. Default is `True`.
 
         Keyword Arguments:
         ----------
-        - no_emoji: (`bool`): By default it is set to `False`.
-        If `True`, removes all emojis from text data. Works only when `fast_execution` = `False`.
-        - title_mode: (`bool`): By default it is set to `True`.
-        If `False`, converts the text to lowercase. Works only when `fast_execution` = `False`.
-        By default, converts everything to `title`.
+        no_emoji : `bool`
+            By default it is set to `False`. If `True`, removes all emojis from text data. Works only when `fast_execution` = `False`.
+        title_mode : `bool`
+            By default it is set to `True`. If `False`, converts the text to lowercase. Works only when `fast_execution` = `False`. By default, converts everything to `title`.
         &#34;&#34;&#34;
         table = (self.df).copy()
         cols = table.columns
@@ -271,13 +272,15 @@ <h2 class="section-title" id="header-functions">Functions</h2>
 <dd>
 <div class="desc"><p>Auxiliary function in date type string processing</p>
 <h2 id="parameters">Parameters</h2>
-<pre><code>x : &lt;code&gt;str&lt;/code&gt;
-    character of type date.
-</code></pre>
+<dl>
+<dt><strong><code>x</code></strong> :&ensp;<code>str</code></dt>
+<dd>character of type date.</dd>
+</dl>
 <h2 id="returns">Returns</h2>
-<pre><code>x : &lt;code&gt;str&lt;/code&gt;
-    character after processing with format `YYYY-MM-DD`.
-</code></pre></div>
+<dl>
+<dt><strong><code>x</code></strong> :&ensp;<code>str</code></dt>
+<dd>character after processing with format <code>YYYY-MM-DD</code>.</dd>
+</dl></div>
 <details class="source">
 <summary>
 <span>Expand source code</span>
@@ -287,13 +290,13 @@ <h2 id="returns">Returns</h2>
 
     Parameters
     ----------
-        x : `str`
-            character of type date.
+    x : `str`
+        character of type date.
 
     Returns
     ----------
-        x : `str`
-            character after processing with format `YYYY-MM-DD`.
+    x : `str`
+        character after processing with format `YYYY-MM-DD`.
     &#34;&#34;&#34;
     # performing data type conversion
     x = str(x)
@@ -371,16 +374,17 @@ <h2 class="section-title" id="header-classes">Classes</h2>
 
         Parameters
         ----------
-        - sample_frac (`float`): The fraction of rows to use for date type inference. Default is 0.1 i.e., 10%.
-        - fast_execution (`bool`): If `False` use `applymap` pandas for extra text cleanup. Default is `True`.
+        sample_frac : `float`
+            The fraction of rows to use for date type inference. Default is 0.1 i.e., 10%.
+        fast_execution : `bool`
+            If `False` use `applymap` pandas for extra text cleanup. Default is `True`.
 
         Keyword Arguments:
         ----------
-        - no_emoji: (`bool`): By default it is set to `False`.
-        If `True`, removes all emojis from text data. Works only when `fast_execution` = `False`.
-        - title_mode: (`bool`): By default it is set to `True`.
-        If `False`, converts the text to lowercase. Works only when `fast_execution` = `False`.
-        By default, converts everything to `title`.
+        no_emoji : `bool`
+            By default it is set to `False`. If `True`, removes all emojis from text data. Works only when `fast_execution` = `False`.
+        title_mode : `bool`
+            By default it is set to `True`. If `False`, converts the text to lowercase. Works only when `fast_execution` = `False`. By default, converts everything to `title`.
         &#34;&#34;&#34;
         table = (self.df).copy()
         cols = table.columns
@@ -541,18 +545,17 @@ <h3>Methods</h3>
 <dd>
 <div class="desc"><p><code>DataFrame</code> cleaning main function</p>
 <h2 id="parameters">Parameters</h2>
-<ul>
-<li>sample_frac (<code>float</code>): The fraction of rows to use for date type inference. Default is 0.1 i.e., 10%.</li>
-<li>fast_execution (<code>bool</code>): If <code>False</code> use <code>applymap</code> pandas for extra text cleanup. Default is <code>True</code>.</li>
-</ul>
+<dl>
+<dt><strong><code>sample_frac</code></strong> :&ensp;<code>float</code></dt>
+<dd>The fraction of rows to use for date type inference. Default is 0.1 i.e., 10%.</dd>
+<dt><strong><code>fast_execution</code></strong> :&ensp;<code>bool</code></dt>
+<dd>If <code>False</code> use <code>applymap</code> pandas for extra text cleanup. Default is <code>True</code>.</dd>
+</dl>
 <h2 id="keyword-arguments">Keyword Arguments:</h2>
-<ul>
-<li>no_emoji: (<code>bool</code>): By default it is set to <code>False</code>.
-If <code>True</code>, removes all emojis from text data. Works only when <code>fast_execution</code> = <code>False</code>.</li>
-<li>title_mode: (<code>bool</code>): By default it is set to <code>True</code>.
-If <code>False</code>, converts the text to lowercase. Works only when <code>fast_execution</code> = <code>False</code>.
-By default, converts everything to <code>title</code>.</li>
-</ul></div>
+<p>no_emoji : <code>bool</code>
+By default it is set to <code>False</code>. If <code>True</code>, removes all emojis from text data. Works only when <code>fast_execution</code> = <code>False</code>.
+title_mode : <code>bool</code>
+By default it is set to <code>True</code>. If <code>False</code>, converts the text to lowercase. Works only when <code>fast_execution</code> = <code>False</code>. By default, converts everything to <code>title</code>.</p></div>
 <details class="source">
 <summary>
 <span>Expand source code</span>
@@ -568,16 +571,17 @@ <h2 id="keyword-arguments">Keyword Arguments:</h2>
 
     Parameters
     ----------
-    - sample_frac (`float`): The fraction of rows to use for date type inference. Default is 0.1 i.e., 10%.
-    - fast_execution (`bool`): If `False` use `applymap` pandas for extra text cleanup. Default is `True`.
+    sample_frac : `float`
+        The fraction of rows to use for date type inference. Default is 0.1 i.e., 10%.
+    fast_execution : `bool`
+        If `False` use `applymap` pandas for extra text cleanup. Default is `True`.
 
     Keyword Arguments:
     ----------
-    - no_emoji: (`bool`): By default it is set to `False`.
-    If `True`, removes all emojis from text data. Works only when `fast_execution` = `False`.
-    - title_mode: (`bool`): By default it is set to `True`.
-    If `False`, converts the text to lowercase. Works only when `fast_execution` = `False`.
-    By default, converts everything to `title`.
+    no_emoji : `bool`
+        By default it is set to `False`. If `True`, removes all emojis from text data. Works only when `fast_execution` = `False`.
+    title_mode : `bool`
+        By default it is set to `True`. If `False`, converts the text to lowercase. Works only when `fast_execution` = `False`. By default, converts everything to `title`.
     &#34;&#34;&#34;
     table = (self.df).copy()
     cols = table.columns