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    <title>topic docs.azure.cn in Machine Learning</title>
    <link>https://community.databricks.com/t5/machine-learning/docs-azure-cn/m-p/23009#M1300</link>
    <description>&lt;P&gt;&lt;A href="https://docs.azure.cn/en-us/databricks/_static/notebooks/mlflow/mlflow-end-to-end-example-azure.html" target="test_blank"&gt;https://docs.azure.cn/en-us/databricks/_static/notebooks/mlflow/mlflow-end-to-end-example-azure.html&lt;/A&gt;&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;I imported the above notebook and try in Databricks community, but those subplots for Box plots are giving me errors as below:&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;AttributeError                            Traceback (most recent call last)&lt;/P&gt;&lt;P&gt;&amp;lt;command-1592399853593578&amp;gt; in &amp;lt;module&amp;gt;&lt;/P&gt;&lt;P&gt;      8   if col == 'is_red' or col == 'quality':&lt;/P&gt;&lt;P&gt;      9     continue # Box plots cannot be used on indicator variables&lt;/P&gt;&lt;P&gt;---&amp;gt; 10   sns.boxplot(x=high_quality, y=data[col], ax=axes[axis_i, axis_j])&lt;/P&gt;&lt;P&gt;     11   axis_j += 1&lt;/P&gt;&lt;P&gt;     12   if axis_j == dims[1]:&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;/databricks/python/lib/python3.8/site-packages/seaborn/_decorators.py in inner_f(*args, **kwargs)&lt;/P&gt;&lt;P&gt;     44             )&lt;/P&gt;&lt;P&gt;     45         kwargs.update({k: arg for k, arg in zip(sig.parameters, args)})&lt;/P&gt;&lt;P&gt;---&amp;gt; 46         return f(**kwargs)&lt;/P&gt;&lt;P&gt;     47     return inner_f&lt;/P&gt;&lt;P&gt;     48 &lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;/databricks/python/lib/python3.8/site-packages/seaborn/categorical.py in boxplot(x, y, hue, data, order, hue_order, orient, color, palette, saturation, width, dodge, fliersize, linewidth, whis, ax, **kwargs)&lt;/P&gt;&lt;P&gt;   2238 &lt;span class="lia-unicode-emoji" title=":disappointed_face:"&gt;😞&lt;/span&gt;&lt;/P&gt;&lt;P&gt;   2239 &lt;/P&gt;&lt;P&gt;-&amp;gt; 2240     plotter = _BoxPlotter(x, y, hue, data, order, hue_order,&lt;/P&gt;&lt;P&gt;   2241                           orient, color, palette, saturation,&lt;/P&gt;&lt;P&gt;   2242                           width, dodge, fliersize, linewidth)&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;/databricks/python/lib/python3.8/site-packages/seaborn/categorical.py in __init__(self, x, y, hue, data, order, hue_order, orient, color, palette, saturation, width, dodge, fliersize, linewidth)&lt;/P&gt;&lt;P&gt;    404                  width, dodge, fliersize, linewidth):&lt;/P&gt;&lt;P&gt;    405 &lt;/P&gt;&lt;P&gt;--&amp;gt; 406         self.establish_variables(x, y, hue, data, orient, order, hue_order)&lt;/P&gt;&lt;P&gt;    407         self.establish_colors(color, palette, saturation)&lt;/P&gt;&lt;P&gt;    408 &lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;/databricks/python/lib/python3.8/site-packages/seaborn/categorical.py in establish_variables(self, x, y, hue, data, orient, order, hue_order, units)&lt;/P&gt;&lt;P&gt;    154 &lt;/P&gt;&lt;P&gt;    155             # Figure out the plotting orientation&lt;/P&gt;&lt;P&gt;--&amp;gt; 156             orient = infer_orient(&lt;/P&gt;&lt;P&gt;    157                 x, y, orient, require_numeric=self.require_numeric&lt;/P&gt;&lt;P&gt;    158             )&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;/databricks/python/lib/python3.8/site-packages/seaborn/_core.py in infer_orient(x, y, orient, require_numeric)&lt;/P&gt;&lt;P&gt;   1302     """&lt;/P&gt;&lt;P&gt;   1303 &lt;/P&gt;&lt;P&gt;-&amp;gt; 1304     x_type = None if x is None else variable_type(x)&lt;/P&gt;&lt;P&gt;   1305     y_type = None if y is None else variable_type(y)&lt;/P&gt;&lt;P&gt;   1306 &lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;/databricks/python/lib/python3.8/site-packages/seaborn/_core.py in variable_type(vector, boolean_type)&lt;/P&gt;&lt;P&gt;   1220 &lt;/P&gt;&lt;P&gt;   1221     # Special-case all-na data, which is always "numeric"&lt;/P&gt;&lt;P&gt;-&amp;gt; 1222     if pd.isna(vector).all():&lt;/P&gt;&lt;P&gt;   1223         return "numeric"&lt;/P&gt;&lt;P&gt;   1224 &lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;AttributeError: 'bool' object has no attribute 'all'&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;However, when I run the same identical code in Spyder in my standalone PC, it gives those subplots of Box-plots perfectly. What are the causes of it? Python version?&lt;/P&gt;</description>
    <pubDate>Wed, 09 Nov 2022 12:49:17 GMT</pubDate>
    <dc:creator>THIAM_HUATTAN</dc:creator>
    <dc:date>2022-11-09T12:49:17Z</dc:date>
    <item>
      <title>docs.azure.cn</title>
      <link>https://community.databricks.com/t5/machine-learning/docs-azure-cn/m-p/23009#M1300</link>
      <description>&lt;P&gt;&lt;A href="https://docs.azure.cn/en-us/databricks/_static/notebooks/mlflow/mlflow-end-to-end-example-azure.html" target="test_blank"&gt;https://docs.azure.cn/en-us/databricks/_static/notebooks/mlflow/mlflow-end-to-end-example-azure.html&lt;/A&gt;&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;I imported the above notebook and try in Databricks community, but those subplots for Box plots are giving me errors as below:&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;AttributeError                            Traceback (most recent call last)&lt;/P&gt;&lt;P&gt;&amp;lt;command-1592399853593578&amp;gt; in &amp;lt;module&amp;gt;&lt;/P&gt;&lt;P&gt;      8   if col == 'is_red' or col == 'quality':&lt;/P&gt;&lt;P&gt;      9     continue # Box plots cannot be used on indicator variables&lt;/P&gt;&lt;P&gt;---&amp;gt; 10   sns.boxplot(x=high_quality, y=data[col], ax=axes[axis_i, axis_j])&lt;/P&gt;&lt;P&gt;     11   axis_j += 1&lt;/P&gt;&lt;P&gt;     12   if axis_j == dims[1]:&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;/databricks/python/lib/python3.8/site-packages/seaborn/_decorators.py in inner_f(*args, **kwargs)&lt;/P&gt;&lt;P&gt;     44             )&lt;/P&gt;&lt;P&gt;     45         kwargs.update({k: arg for k, arg in zip(sig.parameters, args)})&lt;/P&gt;&lt;P&gt;---&amp;gt; 46         return f(**kwargs)&lt;/P&gt;&lt;P&gt;     47     return inner_f&lt;/P&gt;&lt;P&gt;     48 &lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;/databricks/python/lib/python3.8/site-packages/seaborn/categorical.py in boxplot(x, y, hue, data, order, hue_order, orient, color, palette, saturation, width, dodge, fliersize, linewidth, whis, ax, **kwargs)&lt;/P&gt;&lt;P&gt;   2238 &lt;span class="lia-unicode-emoji" title=":disappointed_face:"&gt;😞&lt;/span&gt;&lt;/P&gt;&lt;P&gt;   2239 &lt;/P&gt;&lt;P&gt;-&amp;gt; 2240     plotter = _BoxPlotter(x, y, hue, data, order, hue_order,&lt;/P&gt;&lt;P&gt;   2241                           orient, color, palette, saturation,&lt;/P&gt;&lt;P&gt;   2242                           width, dodge, fliersize, linewidth)&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;/databricks/python/lib/python3.8/site-packages/seaborn/categorical.py in __init__(self, x, y, hue, data, order, hue_order, orient, color, palette, saturation, width, dodge, fliersize, linewidth)&lt;/P&gt;&lt;P&gt;    404                  width, dodge, fliersize, linewidth):&lt;/P&gt;&lt;P&gt;    405 &lt;/P&gt;&lt;P&gt;--&amp;gt; 406         self.establish_variables(x, y, hue, data, orient, order, hue_order)&lt;/P&gt;&lt;P&gt;    407         self.establish_colors(color, palette, saturation)&lt;/P&gt;&lt;P&gt;    408 &lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;/databricks/python/lib/python3.8/site-packages/seaborn/categorical.py in establish_variables(self, x, y, hue, data, orient, order, hue_order, units)&lt;/P&gt;&lt;P&gt;    154 &lt;/P&gt;&lt;P&gt;    155             # Figure out the plotting orientation&lt;/P&gt;&lt;P&gt;--&amp;gt; 156             orient = infer_orient(&lt;/P&gt;&lt;P&gt;    157                 x, y, orient, require_numeric=self.require_numeric&lt;/P&gt;&lt;P&gt;    158             )&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;/databricks/python/lib/python3.8/site-packages/seaborn/_core.py in infer_orient(x, y, orient, require_numeric)&lt;/P&gt;&lt;P&gt;   1302     """&lt;/P&gt;&lt;P&gt;   1303 &lt;/P&gt;&lt;P&gt;-&amp;gt; 1304     x_type = None if x is None else variable_type(x)&lt;/P&gt;&lt;P&gt;   1305     y_type = None if y is None else variable_type(y)&lt;/P&gt;&lt;P&gt;   1306 &lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;/databricks/python/lib/python3.8/site-packages/seaborn/_core.py in variable_type(vector, boolean_type)&lt;/P&gt;&lt;P&gt;   1220 &lt;/P&gt;&lt;P&gt;   1221     # Special-case all-na data, which is always "numeric"&lt;/P&gt;&lt;P&gt;-&amp;gt; 1222     if pd.isna(vector).all():&lt;/P&gt;&lt;P&gt;   1223         return "numeric"&lt;/P&gt;&lt;P&gt;   1224 &lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;AttributeError: 'bool' object has no attribute 'all'&lt;/P&gt;&lt;P&gt;&lt;/P&gt;&lt;P&gt;However, when I run the same identical code in Spyder in my standalone PC, it gives those subplots of Box-plots perfectly. What are the causes of it? Python version?&lt;/P&gt;</description>
      <pubDate>Wed, 09 Nov 2022 12:49:17 GMT</pubDate>
      <guid>https://community.databricks.com/t5/machine-learning/docs-azure-cn/m-p/23009#M1300</guid>
      <dc:creator>THIAM_HUATTAN</dc:creator>
      <dc:date>2022-11-09T12:49:17Z</dc:date>
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