Performing Exploratory Data Analysis with AI

Exploratory Data Analysis (EDA) is a foundational step in data science that allows analysts to understand the underlying patterns of the data before delving into more complex analyses. Vizly has become a popular tool among students and professionals for its user-friendly interface and powerful EDA capabilities. You can begin by uploading your data source; for more detailed instructions, visit our Getting Started guide.

For the purposes of this example, we will use a social media dataset of Instagram profiles from December 2022. This dataset includes metrics like follower counts, profile categorization, and engagement rates, offering a comprehensive snapshot of social media dynamics.

Once the data is loaded, Vizly automatically offers insightful suggestions to help you quickly identify significant analytical pathways. For instance, you can click on "Top influencers by followers" to instantly rank profiles by their follower count, making it easier to identify key players in the social media landscape.

Automated suggestions like 'Top influencers by followers' streamline the identification of key profiles.

As a first step, let's get a better look at the data. I can ask Vizly to give me an overview of the data, as well as a more detailed description of each column.

Vizly can give you an overview of your data to help you make the best decisions about your data analysis.

At every step of your analysis, Vizly automatically generates suggestions for the next best step.

Suggestions can help you understand the next best step in your analysis.

Upon clicking the suggestion 'Show me the top influencers based on follower count', Vizly automatically generates the necessary code to filter and visualize the data.

Vizly can generate code to filter and visualize your data.