The filter will appear in the top right corner. Move the filter towards the right, so that it looks like part of the dashboard. Similarly, we are going to add filters for “States” and “Regions”. Select the Boxplot visualization and add the “States” filter. Go to the filter and...
Step 8 – compare static and interactive plot versions Step 9 – create the interactive boxplot figures Tables The last component type covered in this tutorial is tabular data. Tables can be included as simple, static displays or as interactive tables with capabilities for sorting, filtering, sear...
The filter will appear in the top right corner. Move the filter towards the right, so that it looks like part of the dashboard. Similarly, we are going to add filters for “States” and “Regions”. Select the Boxplot visualization and add the “States” filter. Go to the filter and...
The filter will appear in the top right corner. Move the filter towards the right, so that it looks like part of the dashboard. Similarly, we are going to add filters for “States” and “Regions”. Select the Boxplot visualization and add the “States” filter. Go to the filter and...
The filter will appear in the top right corner. Move the filter towards the right, so that it looks like part of the dashboard. Similarly, we are going to add filters for “States” and “Regions”. Select the Boxplot visualization and add the “States” filter. Go to the filter and...
sns.pairplot(my_data, diag_kind='kde', plot_kws={'alpha': 0.2}) # creates scatterplots of each variable pair, then has kernel density plots down the diaganol. Boxplots df['col1_groups'] = pd.qcut(df['col_1'], 2, labels=['label_1', 'label_2']) df.boxplot(column='col_...