I will communicate useful insights, performing eda

Before jumping to more complex techniques like models, or summarizing your data through a dashboard, a thorough exploratory analysis should always be done to better understand the data and understand hidden (or explicit) characteristics about it.

What's included:

1. Descriptive statistics: central tendency, spread,...
2. Univariate and bivariate analysis across key variables
3. Correlation analysis and relationship mapping
4. Distribution visualizations: histograms, boxplots, ...
5. Categorical breakdowns and group comparisons
6. Outlier identification and anomaly flagging
7. Any other that may seem useful for the given data

All code is clean, commented and fully reproducible with all of the findings. For the report, not every analysis executed might be present, but only those which reflect important information.

Every specific analysis will take into consideration the context of the data and the future expected use for that data.

Specific requests are available with no extra charge.