Interactive Data Visualization

Project Category

• Exploratory Data Analysis
• Data Visualization

Description

Interactive data visualization refers to the use of software that enables direct actions to modify elements on a graphical plot. Data visualization is the discipline of trying to understand data by placing it in a visual context so that patterns, trends and correlations that might not otherwise be detected can be exposed.

Live Interaction: Flower Data at Heroku

Logins: un(alphateds) and pw(alpha@heroku)

Data Visualization is more of Storytelling rather than complex programming. Being leading Data Science Company in Nepal, we know how to provide meaning from any raw data. With interactive visualization, you can change the views of data and make decisions in accordance.

We used following technology for Data Visualization.

• Matplotlib: low level, provides lots of freedom
• Pandas Visualization: easy to use interface, built on Matplotlib
• Seaborn: high-level interface, great default styles
• ggplot: based on R’s ggplot2, uses Grammar of Graphics
• Plotly: can create interactive plots

Benefits of Interactive Data Visualization

An interactive data visualization allows users to engage with data in ways not possible with static graphs, such as big data interactive visualizations.

1. Identify Trends Faster
2. Clear view of relationship between data
3. Useful data storytelling
4. Data Driven Decision Making
5. Simplify Complex Data

Technology Stack

• Streamlit
• Python
• Plotly
• Matplotlib
• Pandas
• GGplot