Symbols and key fields

The symbol parameter serves as the key for querying datasets in CloudQuant Data Liberator. The platform initially focused on US Equity Symbols, but its datasets have expanded to include diverse data types such as shipping, weather, and market research. These datasets use varied keys like zip codes and geographic locations. CloudQuant Data Liberator keeps the symbols parameter name for consistency with existing integrations. Default Value: None (returns all symbols/keys, including blanks/NaN values) symbols and keys are synonyms — use either name.

When setting your query parameters, consider the amount of data you may be requesting and start small until you understand data volume patterns for each symbol/date combination.

Determining unique symbols in a dataset

The most straightforward approach is to query and count the data. Here is an example using the daily_bars dataset:

df = liberator.get_dataframe(liberator.query(
    name = 'daily_bars',
    as_of = '2024-07-24',
    back_to = '2024-07-22',
    symbols = None))
df

This returns over 20,000 rows. To count unique symbols:

len(df.symbol.unique())
# Output: 10524

Storing and displaying symbols

To store symbols in a variable:

allsym = list(df.symbol.unique())

To display the complete list (with caution — lists can be lengthy):

print(list(df.symbol.unique()))

Query methods for all symbols

Either explicitly set symbols = None or omit the parameter entirely, as it defaults to None.

Pattern filters (2.4+)

In Liberator 2.4 and later, symbols / keys accept SQL LIKE patterns. An unescaped % matches any sequence of characters, so you can request a product family or naming pattern without listing every contract.

# All keys that start with PWR
df = liberator.get_dataframe(liberator.query(
    name='energy_contracts',
    symbols='PWR%',
    back_to='2026-08-01',
    as_of='2026-08-02',
))

# Mix exact keys and patterns
df = liberator.get_dataframe(liberator.query(
    name='energy_contracts',
    symbols=['AAPL', 'MSFT', 'PWR%'],
    back_to='2026-08-01',
    as_of='2026-08-02',
))

Pattern	Matches
`PWR%`	`PWR`, `PWR-H`, `PWR_CAL_26`
`G%GL`	`GOGL`, `GAGL`, `GOOGLE`
`A\%PL`	only the literal key `A%PL` (escaped percent)

Exact keys (no unescaped %) still use equality, including lists of tickers. Liberator only switches to LIKE for values that contain %.

Start with a short date range when you first use a pattern. A leading % on a large dataset can return far more rows than an exact-symbol query.

See the query parameters reference for symbols and keys.

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Symbols and Key Fields

Symbols and key fields

Determining unique symbols in a dataset

Storing and displaying symbols

Query methods for all symbols

Pattern filters (2.4+)

​Symbols and key fields

​Determining unique symbols in a dataset

​Storing and displaying symbols

​Query methods for all symbols

​Pattern filters (2.4+)

Symbols and key fields

Determining unique symbols in a dataset

Storing and displaying symbols

Query methods for all symbols

Pattern filters (2.4+)