in -> 1 map_options = (lat=np.mean(df.values),Ģ lng =np. KeyError Traceback (most recent call last) get_loc (key ) 2647 except KeyError : pandas/_libs/index.pyx in pandas._圎ngine.get_loc () pandas/_libs/index.pyx in pandas._圎ngine.get_loc () pandas/_libs/hashtable_class_helper.pxi in pandas._item () pandas/_libs/hashtable_class_helper.pxi in pandas._item () KeyError: 'latitude_surface_hole' ~/miniconda/envs/book/lib/python3.8/site-packages/pandas/core/indexes/base.py in get_loc (self, key, method, tolerance) 2645 try : -> 2646 return self. head (n = 3 ) ~/miniconda/envs/book/lib/python3.8/site-packages/intake/catalog/base.py in _getattr_ (self, item) 339 return self # triggers reload_on_change 340 except KeyError : -> 341 raise AttributeError (item ) 342 raise AttributeError (item ) 343 AttributeError: well_columns in -> 1 df = cat.well_columns(columns='latitude_surface_hole,longitude_surface_hole',Ģ where="parent_ticker='PXD' AND basin_name='PERMIAN'").read().dropna() ģ df. ~/miniconda/envs/book/lib/python3.8/site-packages/intake/catalog/base.py in _getattr_ (self, item) 338 try : -> 339 return self # triggers reload_on_change 340 except KeyError : ~/miniconda/envs/book/lib/python3.8/site-packages/intake/catalog/base.py in _getitem_ (self, key) 409 return out ( ) -> 410 raise KeyError (key ) 411 KeyError: 'well_columns' read ( ) ~/miniconda/envs/book/lib/python3.8/site-packages/intake/catalog/base.py in _getattr_ (self, item) 339 return self # triggers reload_on_change 340 except KeyError : -> 341 raise AttributeError (item ) 342 raise AttributeError (item ) 343 AttributeError: production_by_api ~/miniconda/envs/book/lib/python3.8/site-packages/intake/catalog/base.py in _getattr_ (self, item) 338 try : -> 339 return self # triggers reload_on_change 340 except KeyError : ~/miniconda/envs/book/lib/python3.8/site-packages/intake/catalog/base.py in _getitem_ (self, key) 409 return out ( ) -> 410 raise KeyError (key ) 411 KeyError: 'production_by_api'ĭuring handling of the above exception, another exception occurred:ĪttributeError Traceback (most recent call last) HSpacer (), sizing_mode = 'stretch_width' ).
#Github python bokeh code
bind ( plot, x, y, n_clusters ),), ), ( 'CODE', code ), ( 'DESCRIPTION', description ), width = 800 ) pn. WidgetBox ( x, y, n_clusters, explanation, width = 175, margin = 10 ), pn. interactive_plot = pn.bind(plot, x, y, n_clusters) pn.Row( pn.WidgetBox(x, y, n_clusters, explanation), interactive_plot ) ``` """, width = 800 ) app = pn. Markdown ( """ ```python import panel as pn pn.extension() x = pn.widgets.Select(name='x', options=cols) y = pn.widgets.Select(name='y', options=cols, value='bill_depth_mm') n_clusters = pn.widgets.IntSlider(name='n_clusters', start=2, end=5, value=3) explanation = pn.pane.Markdown(.) def plot(x, y, n_clusters). """, sizing_mode = "stretch_width" ) explanation = pn. Additionally the center of each cluster is marked with an `X`. - Adelie, ■ - Chinstrap, ▲ - Gentoo By comparing the two we can assess the performance of the clustering algorithm.Each cluster is denoted by one color while the penguin species is indicated using markers: Markdown ( """ This app applies *k-means clustering* on the Palmer Penguins dataset using scikit-learn, parameterizing the number of clusters and the variables to plot. scatter ( x, y, marker = 'x', color = 'black', size = 400, padding = 0.1, line_width = 5 )) description = pn. scatter ( x, y, c = 'labels', hover_cols =, line_width = 1, size = 60, frame_width = 400, frame_height = 400 ). mean ( numeric_only = True ) return ( penguins. values, n_clusters ) centers = penguins.
astype ( 'str' ) def plot ( x, y, n_clusters ): penguins = cluster ( penguins. IntSlider ( name = 'n_clusters', start = 2, end = 5, value = 3, sizing_mode = "stretch_width", margin = 10 ) def cluster ( data, n_clusters ): kmeans = KMeans ( n_clusters = n_clusters, n_init = 'auto' ) est = kmeans. Select ( name = 'y', options = cols, value = 'bill_depth_mm', sizing_mode = "stretch_width" ) n_clusters = pn. Select ( name = 'x', options = cols, sizing_mode = "stretch_width", margin = 10 ) y = pn.
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