RPA.Tables

Data can be a combination of various iterable containers, e.g. list of lists, list of dicts, dict of lists.

The filtering will be done in-place.

Remove all rows where the column values don't match the given condition.

Supported operators:

The filtering will be done in-place.

Examples:

*** Tasks ***
# Only accept prices that are non-zero
Filter table by column    ${table}   price  !=  ${0}

# Remove uwnanted product types
@{types}=    Create list    Unknown    Removed
Filter table by column    ${table}   product_type  not in  ${types}

Group table by column and return a list of grouped Tables.

By default rows from all tables are appended one after the other. Optionally a column name can be given with index, which is used to merge rows together.

Examples

For instance, a name column could be used to identify unique rows and the merge operation should overwrite values instead of appending multiple copies of the same name.

*** Tasks ***
${products}=    Merge tables    ${prices}    ${stock}    index=Name
FOR    ${product}    IN    @{products}
    Log many
    ...    Product: ${product}[Name]
    ...    Price: ${product}[Price]
    ...    Stock: ${product}[Stock]
END

By default attempts to deduce the CSV format and headers from a sample of the input file. If it's unable to determine the format automatically, the dialect and header will have to be defined manually.

Valid dialect values are excel, excel-tab, and unix, and header is boolean argument (True/False). Optionally a set of valid delimiters can be given as a string.

The columns argument can be used to override the names of columns in the resulting table. The amount of columns must match the input data.

If the source data has a header and rows have more fields than the header defines, the remaining values are put into the column given by column_unknown. By default it has the value "Unknown".

Examples:

*** Tasks ***
# Source dialect is deduced automatically
${table}=    Read table from CSV    export.csv
Log   Found columns: ${table.columns}

# Source dialect is known and given explicitly
${table}=    Read table from CSV    export-excel.csv    dialect=excel
Log   Found columns: ${table.columns}

Renames columns in the Table with given values. Columns with name as None will be use previous value.

Sort table in-place according to column.

Return first count rows from table.

Return last count rows from table.

Remove all rows from the end of the table which have only None values.

Valid dialect values are excel, excel-tab, and unix.