Time series

Articles tagged Time series

How to calculate month start and month end dates in Python

When creating business reports or running queries against a database or web analytics platform in a business setting, you’ll often need to know the start and end dates of the...

How to calculate ISO week numbers and start and end dates in Python

In ecommerce and marketing it’s relatively common to use ISO week numbers when reporting data. The ISO week system is a leap week calendar that forms part of the ISO...

How to forecast Google Trends search data with NeuralProphet

In ecommerce, it is often difficult to tell whether your search traffic is performing to expectations. What your boss perceives to be caused by an on-site or marketing-related issue may...

How to calculate the time difference between two dates in Pandas

Calculating the time difference between two dates in Pandas can yield useful information to aid your analysis, help you understand the data, and guide a machine learning model on making...

How to create Google Search Console time series forecasts using Neural Prophet

Time series forecasting uses machine learning to predict future values of time series data. In this project we’ll be using the Neural Prophet model to predict future values of Google...

How to infer the effects of marketing using the Causal Impact model

One common conundrum in e-commerce and marketing involves trying to ascertain whether a given change in marketing activity, product price, or site design or content, has had a statistically significant...

How to add days and subtract days from dates in Pandas

If you regularly work with time series data, one common thing you’ll need to do is add and subtract days from a date. If you tried doing this by hand,...

How to make time series forecasts with Neural Prophet

The Neural Prophet model is relatively new and was heavily inspired by Facebook’s earlier Prophet time series forecasting model. NeuralProphet is a neural network based model that uses a PyTorch...

How to perform time series decomposition

Time series data have a reputation for being somewhat complicated, partly because they’re made up of a number of different components that work together. At the most basic level these...

How to engineer customer purchase latency features

Purchase latency or customer latency is a measure of the number of days between a customer’s orders and is one of the most powerful features in many propensity and churn...

How to resample time series data in Pandas

When working with time series data, such as web analytics data or ecommerce sales, the time series format in your dataset might not be ideal for the analysis you’re performing...

How to reformat dates in Pandas

If you regularly work with time series data in Pandas it’s probable that you’ll sometimes need to convert dates or datetimes and extract additional features from them.

How to create ecommerce sales forecasts using Prophet

Time series forecasting models are notoriously tricky to master, especially in ecommerce, where you have seasonality, the weather, marketing promotions, and holidays to consider. Not to mention pandemics.

How to create an ecommerce trading calendar using Pandas

In both B2C and B2B ecommerce, special trading periods such as Christmas, Mothers’ Day, and Valentines’ Day can often greatly contribute to sales. Indeed, the introduction of Black Friday sales...

How to use GAPandas to view your Google Analytics data

Over the past decade I’ve written more Google Analytics API queries than I can remember. Initially, I favoured PHP for these (and still do for permanent web-based applications utilising GA...

How to engineer date features using Pandas

When dealing with temporal or time series data, the dates themselves often yield information that can vastly improve the performance of your model. However, to get the best from these...