Interactive python dashboards | Plotly Dash 2022| 3 Projects

Explore numpy basics for working with numerical data in Python, creating arrays with arange, zeros, and ones, indexing and slicing; learn mean, min, max, sum, and std.

Master pandas basics: create lists, series, and dictionaries; build data frames and read data from github or excel; use describe and info; index, select, update, and filter with loc/iloc.

Learn to use for and while loops to iterate over lists, strings, and ranges in Python, control flow with break and continue, and generate simple outputs like multiplication tables.

Learn how the Python range function works: default start at zero, end is exclusive, and how to use one, two, or three arguments with a specified step to generate sequences.

Build and compare two-line life-expectancy charts for India and the United States using plotly go dot scatter on the Gapminder dataset, with hover text, color, width, and axis titles.

Explore building choropleth maps with Plotly Express, using GeoJSON and ISO alpha codes to visualize Montreal election districts and global life expectancy data with interactive color scales.

Explore Plotly Dash by building a pandas dataframe from a csv URL and styling a data table with fixed headers, height, and odd/even row formatting.

Learn to implement a callback using a stimulus button in a dash app, updating a click counter via a button_update function and displaying the current count from zero.

Learn to read Covid-19 API data, parse global and country stats, and build three data cards showing total and last 24 hours for confirmed, recovered, and deaths.

Learn to build a dashboard that compares current and reference periods in retail sales using dropdowns. Visualize differences by month, week, stores, and top departments.

Build a dynamic sales card in a Plotly Dash dashboard by showing total current sales and the sales difference, format numbers as dollars in millions, and style for clarity.

Create a total stores card in a Python dash dashboard by counting distinct stores and computing the current period value and its difference from a prior period, and update variables.

Build a dataset from store sales to show the top 10 stores by weekly sales for the current month and a reference period, using two side-by-side bar charts.

Build an interface with two input boxes and a text area for context, a question field, a button to generate an answer based on the context, and a loading indicator.

Build an interactive question-answering feature in a Dash app by wiring a generate button callback to pass context and question to a transformers pipeline that returns an answer.