Time series analysis involves identifying attributes of your time series data, such as trend and seasonality, by measuring statistical properties.

Pandas makes it easy to quickly load, manipulate, align, merge, and even visualize data tables directly in Python.

It is very common to analyze time series data, and the date and time stamp values can come in many different formats. Python supports converting from dates to strings and back.

However, in recent years the open source community has developed increasingly-sophisticated data manipulation, statistical analysis, and machine learning libraries for Python. We are now at the point ...

Showing speed and precision, one of Google’s latest experimental models, Exp-1206, shows potential to alleviate one of the most grueling aspects of any analyst’s job.

Learn the basics of producing time series forecasts in RStudio from your Google Search Console click data.

Google’s data science agent does just that: The new, free, Gemini 2.0-powered AI assistant that automates data analysis is now available to users age 18-plus in select countries and languages.