A quick guide to Pandas Concat to join two dataframes.
Data manipulation is the number one time sink of Data Science. On average, Data Scientists spend at least 60% of their time on data manipulation tasks, so in this series of data manipulation Einblick Tools, we will provide easy-to-use and prebuilt templates to manipulate your data.
Einblick hybrid approach to data manipulation allows you to mix code and no-code operators to manipulate your data quickly. This Einblick Tool shows the code and no-code version of a series of Concat, Sort, and Join operations.
The use case we will use in the following Tool is customer data enrichment and augmentation.
- In step 1), we take sales data from different months, namely August and September, and vertically concatenate them.
- In step 2), we proceed by augmenting our sales data with customer demographic information; we first sort the customer by their unique identifier and then horizontally concatenate them.
- In step 3), we finally join the data with information coming for a dealers table.
In this first Tool canvas, we used Pandas calls to run the data manipulation tasks.
In this second canvas, we utilized Einblick's built-in no-code operators to run the same series of operations.
Einblick is an agile data science platform that provides data scientists with a collaborative workflow to swiftly explore data, build predictive models, and deploy data apps. Founded in 2020, Einblick was developed based on six years of research at MIT and Brown University. Einblick customers include Cisco, DARPA, Fuji, NetApp and USDA. Einblick is funded by Amplify Partners, Flybridge, Samsung Next, Dell Technologies Capital, and Intel Capital. For more information, please visit www.einblick.ai and follow us on LinkedIn and Twitter.