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.