Media, mediana y moda

Before you analyze anything, you ask where the data sits. A measure of center answers that with one number that stands in for the whole column. 🎯

The mean adds up every value and divides by how many there are. It is the balance point of your data, the classic average you already know.

In pandas you never loop to average. One method call on a column gives you the mean instantly.

One huge value can drag the mean far from where most points sit. The mean is sensitive to outliers, so it is not always the honest center.

The median is the value sitting exactly in the middle once you sort the data. Half the points fall below it and half fall above.

Because it only cares about position, the median barely moves when a wild value appears. For skewed data like income, it often tells a fairer story.

The mode is simply the value that shows up most often. It is the only center that also works for text categories, not just numbers.

Data can tie for most frequent, giving you two or more peaks. That is why mode in pandas returns a Series, never a single guaranteed number.

When mean and median drift far apart, your data is skewed. A big gap is your first hint that one tail is stretching the average.

Use the mean for tidy symmetric data, the median when outliers lurk, and the mode for categories. The shape of your data decides for you.

You rarely compute these alone. The describe method hands you mean and more for every numeric column in a single line.

A salary column has a few extremely high earners pulling the average up.

You now know three ways to find the center: mean for the average, median for the middle, and mode for the most common. Match the tool to your data's shape. 👏