Play With Your Data

Data can be stored in many formats, tables, texts, images, sounds, videos, and so on. Most of the time, the information for our business needs is stored in tabular format, which is basically a two-dimensional table. Horizontal elements are called rows, and vertical elements are called columns.

Two-dimensional table

Manipulating data in Octai generally involves a series of data preprocessing steps. 

Here's an outline of the common steps to manipulate data in Octai:

Merging datasets is often a part of the data preprocessing step. To merge datasets in Octai, you generally follow these steps:

  1. Import datasets: First, import both datasets into the platform. This typically involves uploading the datasets in a supported format (e.g., CSV, Excel, or JSON) or connecting to a database.
  2. Identify common keys or columns: Determine the columns or keys that are common between the two datasets. This will serve as the basis for merging the datasets. Ensuring that the common keys have consistent values and data types is essential.
  3. Merge the datasets: This section often requires you to specify the datasets to be merged, the common keys or columns to be used for merging, and the type of merge (inner, outer, left, or right).
  4. Review the merged dataset: After merging the datasets, review the result to ensure that the merge was successful and the data is accurate. This may include checking for duplicate rows, missing values, or any inconsistencies.



Sorting and filtering columns in Octai is usually part of the data preprocessing step.

  1. Access data manipulation tools: on Octai, you will have access to visual data manipulation tools, data preprocessing modules or SQL-like query interfaces that allow you to sort and filter columns in your dataset.
  2. Column filter: To filter columns, you will need to use Octai's function to keep only the columns or rows that meet specific criteria. This can be done by defining conditions or applying a logical expression to the columns in question.
  3. Sort: To sort a column, you will need to use the platform's function to order the values in the column in ascending or descending order.
  4. Review the sorted and filtered dataset: After applying the filtering and sorting operations, review the resulting dataset to ensure that the data manipulation was successful and the data is accurate.