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Checks whether the supplied data object is a pandas Series or dask Series type, with lazy loading support for dask.

Purpose

This utility function provides a unified way to check if data is a Series type across both pandas and dask dataframe libraries. It handles optional dask dependency gracefully by checking if dask.dataframe is already loaded in sys.modules before attempting to import it, making it safe to use in environments where dask may or may not be available.

Source Code

def is_series(data):
    """
    Checks whether the supplied data is of Series type.
    """
    dd = None
    if 'dask.dataframe' in sys.modules:
        import dask.dataframe as dd
    return((pd is not None and isinstance(data, pd.Series)) or
          (dd is not None and isinstance(data, dd.Series)))

Parameters

Parameter Details

data: Any Python object to be checked. Typically expected to be a pandas Series, dask Series, or other data structure. No type constraints are enforced - the function will return False for non-Series types.

Return Value

Returns a boolean value: True if the data is an instance of pandas.Series or dask.dataframe.Series (when dask is available), False otherwise. The function uses short-circuit evaluation, checking pandas first, then dask if available.

Dependencies

• sys
• pandas
• dask.dataframe

Required Imports

import sys
import pandas as pd

Conditional/Optional Imports

These imports are only needed under specific conditions:

import dask.dataframe as dd

Usage Example

import sys
import pandas as pd

# Assuming is_series function is available

# Test with pandas Series
pd_series = pd.Series([1, 2, 3, 4, 5])
print(is_series(pd_series))  # Output: True

# Test with pandas DataFrame
pd_df = pd.DataFrame({'a': [1, 2, 3]})
print(is_series(pd_df))  # Output: False

# Test with list
my_list = [1, 2, 3]
print(is_series(my_list))  # Output: False

# Test with dask Series (if dask is available)
try:
    import dask.dataframe as dd
    dask_series = dd.from_pandas(pd_series, npartitions=2)
    print(is_series(dask_series))  # Output: True
except ImportError:
    print("Dask not available")

Best Practices

• This function uses lazy importing for dask to avoid forcing dask as a hard dependency - only checks for dask Series if dask.dataframe is already loaded
• The function assumes 'pd' is already imported as pandas in the global scope - ensure pandas is imported before using this function
• Returns False for any non-Series types rather than raising exceptions, making it safe for defensive programming
• Use this function when you need to handle both pandas and dask Series uniformly in code that may work with either library
• The function checks sys.modules to determine if dask is available, which is more efficient than try-except import blocks

Tags

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