Final Exam: Data Visualization for Web Apps Using Python
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- Includes Assessment
- Earns a Badge
Final Exam: Data Visualization for Web Apps Using Python will test your knowledge and application of the topics presented throughout the Data Visualization for Web Apps Using Python track of the Skillsoft Aspire Pythonista to Python Master Journey.
WHAT YOU WILL LEARN
accept user input using Dash componentsapply logistic regressions to categorical datacompare and contrast date inputs using date pickerscompare and contrast date inputs using date pickers and stringscompare and contrast date inputs using strings and date pickersconfigure a multi-tab Dash applicationcontrast strip plots and swarm plotscontrast swarm plots and strip plotscreate a basic bar chart with Altaircreate a callback to add interactivity to chartscreate a Dash appcreate a gauge updated using a spin buttoncreate a map of the United States and plot state-specific information using markers and choropleth mapscreate an HTML button to embed in appscreate an ordinary bar chart using the Plotly Express librarycreate a user input form with validationcreate Boolean toggle switchescreate custom figure-level and axis-level strip plotscreate figure-level and axis-level KDE curvescreate histograms for univariate datacreate univariate KDE curves and cumulative distributionscreate various customized area chartscreate various customized area charts such as area charts with multiple categories, streamgraphs, and trellis area chartscustomize callbacks for more complex interactivitycustomize dropdowns using multi-selectcustomize histograms using the distplot() functioncustomize various aspects of a chart such as the axis ticks, legend, and title using various functionscustomize various aspects of a chart such as the axis ticks, legend, and title using various functions such as configure_title() and configure_legend()define gauge propertiesenhance bar charts by adding rules representing the mean or median of a distribution, conditional formatting, and creating stacked bar charts
execute operations on time series datagenerate a variety of box plots such as plain box plots, box plots with categorical color bars, and box plots with continuous color barsgenerate heat maps to visualize data in the form of a grididentify attributes of a strip plotillustrate some of the interactive features in line chartsimplement bar charts, KDE curves, and rug plotsimplement figure-level and axis-level scatter plotsinstall Dash using the pip package installerinstall the necessary Python modules to work with Seabornperform operations based on user inputperform operations on time series dataproduce basic bar charts such as bar charts with labels and bar charts with the bars sorted in an ascending or descending orderproduce Gantt chartsproduce Gantt charts to visualize activities, tasks, or events against timeproduce world maps using data in the topo JSON formatproduce world maps using data in the topo JSON format and plot points on the map by specifying the latitude and longitude coordinatesremove limits on dataset size set by Altairremove limits on dataset size set by Altair by defaultrepresent bivariate visualizations with color coding and grouped chartsselect values using basic dropdownsuse basic dropdowns to select valuesuse the distplot() function for customizing histogramsuse the pip package installer to install Dashverify the correct Python version is installed on your system, run Jupyter notebook, and install Altairvisualize bivariate histograms and KDE curvesvisualize data and identify the relationships between variables using scatter plotsvisualize data and identify the relationships between variables using scatter plots and create a scatter plot where the color of the data points represent a variablevisualize data using grouped bar charts and stacked bar chartsvisualize data using line charts and customize various aspects of the chart such as the interpolation and by adding rules to the chartvisualize time series data using figure-level and axis-level line charts
IN THIS COURSE
1.Data Visualization for Web Apps Using Python36sUP NEXT
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