Fortunately, this issue can be easily fixed. The `.to_datetime()` method has `yearfirst` and `dayfirst` boolean parameters that define whether dates start with the year or day, respectively. By default, both parameters are set to `False`, which is why the first numbers were considered as months (if possible). Since the dates in our data start with the day, we just need to set the `dayfirst` parameter to `True`.

This hands-on course provides an opportunity to apply and consolidate your skills across a range of data analysis tasks using real-world dataset. You'll learn how to identify and address data issues, and then explore and visualize data using pandas, matplotlib, and seaborn to uncover insights and draw conclusions.

First, let's get acquainted with the data we will be working with. Throughout this section, we will perform the initial set of actions to prepare the data for further analysis.

In the second section, we will continue with the preparatory tasks started in the first section and ensure the data is ready for further exploration.

After preparing the data, we will move on to some exploratory analysis. Throughout this section, we will answer several questions and uncover interesting insights.

In the last section, we will use visualization tools to either confirm or reject the hypotheses we made in the previous section. We will also create visualizations of key indicators for the entire dataset.

Proper Converting

Oplossing