Final Exam: Data Visualization for Web Apps Using Python
Python 3.6+ | Intermediate
- 1 Video | 32s
- 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
create custom figure-level and axis-level strip plotsverify the correct Python version is installed on your system, run Jupyter notebook, and install Altairuse the pip package installer to install Dashcreate histograms for univariate datacustomize histograms using the distplot() functioncreate a basic bar chart with Altaircompare and contrast date inputs using date pickersproduce world maps using data in the topo JSON format and plot points on the map by specifying the latitude and longitude coordinatescustomize various aspects of a chart such as the axis ticks, legend, and title using various functions such as configure_title() and configure_legend()visualize bivariate histograms and KDE curvesapply logistic regressions to categorical datause basic dropdowns to select valuescompare and contrast date inputs using date pickers and stringscreate Boolean toggle switchesinstall the necessary Python modules to work with Seabornselect values using basic dropdownscreate a user input form with validationcreate univariate KDE curves and cumulative distributionsuse the distplot() function for customizing histogramsrepresent bivariate visualizations with color coding and grouped chartsimplement bar charts, KDE curves, and rug plotsidentify attributes of a strip plotcreate a map of the United States and plot state-specific information using markers and choropleth mapsimplement figure-level and axis-level scatter plotsproduce Gantt chartsproduce world maps using data in the topo JSON formatenhance bar charts by adding rules representing the mean or median of a distribution, conditional formatting, and creating stacked bar chartsvisualize data using line charts and customize various aspects of the chart such as the interpolation and by adding rules to the chartcompare and contrast date inputs using strings and date pickerscreate figure-level and axis-level KDE curves
create an HTML button to embed in appscreate a Dash appcreate a gauge updated using a spin buttondefine gauge propertiesexecute operations on time series dataperform operations on time series datacontrast swarm plots and strip plotscontrast strip plots and swarm plotsvisualize time series data using figure-level and axis-level line chartsremove limits on dataset size set by Altairgenerate a variety of box plots such as plain box plots, box plots with categorical color bars, and box plots with continuous color barsremove limits on dataset size set by Altair by defaultcreate various customized area chartsproduce basic bar charts such as bar charts with labels and bar charts with the bars sorted in an ascending or descending ordervisualize data and identify the relationships between variables using scatter plotscreate various customized area charts such as area charts with multiple categories, streamgraphs, and trellis area chartsvisualize data and identify the relationships between variables using scatter plots and create a scatter plot where the color of the data points represent a variablegenerate heat maps to visualize data in the form of a gridproduce Gantt charts to visualize activities, tasks, or events against timecustomize various aspects of a chart such as the axis ticks, legend, and title using various functionscreate a callback to add interactivity to chartscustomize callbacks for more complex interactivityinstall Dash using the pip package installerillustrate some of the interactive features in line chartscreate an ordinary bar chart using the Plotly Express libraryvisualize data using grouped bar charts and stacked bar chartsaccept user input using Dash componentsperform operations based on user inputconfigure a multi-tab Dash applicationcustomize dropdowns using multi-select
IN THIS COURSE
1.Data Visualization for Web Apps Using Python33sUP NEXT
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