Tables is a library for manipulating tabular data inside Robot Framework.

It can import data from various sources and apply different operations to it. Common use-cases are reading and writing CSV files, inspecting files in directories, or running tasks using existing Excel data.

Import types

The data from which a table can be created can be of two main types:

  1. An iterable of individual rows, like a list of lists, or list of dictionaries
  2. A dictionary of columns, where each dictionary value is a list of values

For instance, these two input values:

data1 = [
    {"name": "Mark", "age": 58},
    {"name": "John", "age": 22},
    {"name": "Adam", "age": 67},

data2 = {
    "name": ["Mark", "John", "Adam"],
    "age":  [    58,     22,     67],

Would both result in the following table:

Index Name Age
1 Mark 58
2 John 22
3 Adam 67


Robot Framework

The Tables library can load tabular data from various other libraries and manipulate it inside Robot Framework.

*** Settings ***
Library    RPA.Tables

*** Keywords ***
Files to Table
    ${files}=    List files in directory    ${CURDIR}
    ${files}=    Create table    ${files}
    Filter table by column    ${files}    size  >=  ${1024}
    FOR    ${file}    IN    @{files}
        Log    ${file}[name]
    Write table to CSV    ${files}    ${OUTPUT_DIR}${/}files.csv


The library is also available directly through Python, where it is easier to handle multiple different tables or do more bespoke manipulation operations.

from RPA.Tables import Tables

library = Tables()
orders = library.read_table_from_csv(
    "orders.csv", columns=["name", "mail", "product"]

customers = library.group_table_by_column(rows, "mail")
for customer in customers:
    for order in customer: