Summary  
The chapter explains how to use the pandas `resample()` method to change the frequency of time-indexed data by specifying a resampling rule (e.g., 'D', 'H', 'M') and applying aggregation functions.  

General domain of usage  
Time series data processing

In Python, the `resample()` method is used to resample time series data to a different frequency. The method is typically used on a pandas DataFrame or Series with a time-based index, and it is available through the `resample()` attribute of the DataFrame or Series.

The basic syntax for the `resample()` method is as follows:

```python
data.resample(rule)
```

Where  `rule` identigies the resampling rule, which defines the new frequency of the data. This can be a string or `pandas` offset, such as `'D'` for daily, `'H'` for hourly, `'M'` for monthly, etc.


Congratulations on completing your time series project! Your hard work and dedication have paid off. I am impressed with the results and am sure that your efforts will be valuable to the team. Keep up the great work!

In this project, we are going to understand what a Time Series is and which are its main features.

Time Series Essentials

Resample

Solution