Used for spreadsheet and SQL like operations, like grouping or joining data.
Overview
SpreadSheet Helper is a tool designed for performing operations similar to spreadsheets and SQL like operations, such as data grouping and joining. You need to specify the data you want to work with by referencing it.
Infer data types
To keep data type consistent, you can choose whether to enable data type inference or leave it disabled (it's turned off by default).
Infer data types option in all relevant actions
If this option is turned on, the Helper will try to automatically infer the data type of each column. This might cause unexpected results when working with zip codes and other numbers that can start with 0.
Otherwise, the data types will be left as provided by the source.
Actions
1. Group columns by
Group a spreadsheet or CSV file and apply different aggregates and properties.
The available aggregation functions are:
mean
sum
size
count
std
var
sem
first
last
min
max
median
For example, let's find the lowest price among devices. To do this we need to group columns by Product
Result columns must use the following syntax:
<column name or index>;<aggregation function><new column name (optional)>
In the example
Price - column name
min - aggregation function
lowest_price - new column name (optional)
2. Insert column
Insert a column into a spreadsheet - Pandas Docs for further details
3. Join
Join multiple spreadsheets or tables with a common column (VLookup) - Pandas Docs for further details.
This comes in handy if you want to map different tables based on common column data.
4. Query spreadsheet
The database is purely in memory and SQLite is used. See SQLite functions here.
