Top-Level Functions
===================

.. currentmodule:: pandasCore

These functions are available directly from the pandasCore Python module.

.. code-block:: python

   import pandasCore as pd

   df = pd.DataFrame({'A': [1, 2]})
   dates = pd.date_range('2023-01-01', periods=5)
   merged = pd.merge(df1, df2, on='key')

Date/Time
---------

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   * - Function
     - Description
   * - ``date_range()``
     - Return a fixed frequency DatetimeIndex.
   * - ``bdate_range()``
     - Return a fixed frequency DatetimeIndex with business day ...
   * - ``period_range()``
     - Return a fixed frequency PeriodIndex.
   * - ``timedelta_range()``
     - Return a fixed frequency TimedeltaIndex.
   * - ``to_datetime()``
     - Convert argument to datetime.
   * - ``to_timedelta()``
     - Convert argument to timedelta.

Combining
---------

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   * - Function
     - Description
   * - ``concat()``
     - Concatenate pandas objects along a particular axis.
   * - ``merge()``
     - Merge DataFrame objects by performing a database-style join.
   * - ``merge_asof()``
     - Perform an asof merge (merge on nearest key rather than e...
   * - ``merge_ordered()``
     - Perform merge with optional filling/interpolation.

Reshaping
---------

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   * - Function
     - Description
   * - ``pivot()``
     - Return reshaped DataFrame organized by given index/column...
   * - ``pivot_table()``
     - Create a spreadsheet-style pivot table.
   * - ``melt()``
     - Unpivot a DataFrame from wide to long format.
   * - ``wide_to_long()``
     - Unpivot a DataFrame from wide to long format.
   * - ``crosstab()``
     - Compute a cross-tabulation of two factors.
   * - ``get_dummies()``
     - Convert categorical variable into dummy/indicator variables.
   * - ``factorize()``
     - Encode the object as an enumerated type.
   * - ``cut()``
     - Bin values into discrete intervals.
   * - ``qcut()``
     - Quantile-based discretization function.

I/O
---

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   * - Function
     - Description
   * - ``read_csv()``
     - Read a comma-separated values (CSV) file into DataFrame.
   * - ``read_excel()``
     - Read an Excel file into DataFrame.
   * - ``read_json()``
     - Read a JSON file into DataFrame.
   * - ``read_parquet()``
     - Read a Parquet file into DataFrame. (Not implemented)
   * - ``read_pickle()``
     - Read a pickle file into DataFrame. (Not implemented)
   * - ``read_sql()``
     - Read SQL query into DataFrame. (Not implemented)
   * - ``read_table()``
     - Read a table file into DataFrame. (Not implemented)
   * - ``read_fwf()``
     - Read a fixed-width file into DataFrame. (Not implemented)
   * - ``read_html()``
     - Read HTML tables into list of DataFrame. (Not implemented)

Missing Data
------------

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   * - Function
     - Description
   * - ``isna()``
     - Detect missing values.
   * - ``isnull()``
     - Alias for isna().
   * - ``notna()``
     - Detect non-missing values.
   * - ``notnull()``
     - Alias for notna().

Type Conversion
---------------

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   * - Function
     - Description
   * - ``to_numeric()``
     - Convert argument to a numeric type.

Utility
-------

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   * - Function
     - Description
   * - ``array()``
     - Create an array.
   * - ``unique()``
     - Return unique values based on a hash table.
   * - ``value_counts()``
     - Return a Series containing counts of unique values.
   * - ``infer_freq()``
     - Infer the most likely frequency given the input index.
   * - ``show_versions()``
     - Print version information about the library and dependenc...

Other Functions
---------------

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   * - Function
     - Description
   * - ``PeriodIndex_from_fields()``
     - Create PeriodIndex from temporal field arrays.
   * - ``PeriodIndex_from_ordinals()``
     - Create PeriodIndex from ordinal values.
   * - ``describe_option()``
     - Print description of options matching pattern.
   * - ``eval()``
     - Evaluate a Python expression as a string.
   * - ``from_dummies()``
     - Create a categorical DataFrame from a DataFrame of dummy ...
   * - ``get_option()``
     - Get the value of a pandas option.
   * - ``interval_range()``
     - Return a fixed frequency IntervalIndex.
   * - ``json_normalize()``
     - Normalize semi-structured JSON data into a flat table.
   * - ``lreshape()``
     - Reshape wide-format data to long format.
   * - ``option_context()``
     - Context manager for temporarily setting options.
   * - ``read_clipboard()``
     - Read content from clipboard. (Not implemented)
   * - ``read_feather()``
     - Read a Feather file into DataFrame. (Not implemented)
   * - ``read_gbq()``
     - Read Google BigQuery into DataFrame. (Not implemented)
   * - ``read_hdf()``
     - Read an HDF5 file into DataFrame.
   * - ``read_orc()``
     - Read an ORC file into DataFrame. (Not implemented)
   * - ``read_sas()``
     - Read a SAS file into DataFrame. (Not implemented)
   * - ``read_spss()``
     - Read an SPSS file into DataFrame. (Not implemented)
   * - ``read_sql_query()``
     - Read SQL query into DataFrame. (Not implemented)
   * - ``read_sql_table()``
     - Read SQL table into DataFrame. (Not implemented)
   * - ``read_stata()``
     - Read a Stata file into DataFrame. (Not implemented)
   * - ``read_xml()``
     - Read an XML file into DataFrame. (Not implemented)
   * - ``reset_option()``
     - Reset option to default value.
   * - ``set_eng_float_format()``
     - Set float format for engineering notation.
   * - ``set_option()``
     - Set the value of a pandas option.
   * - ``to_pickle()``
     - Write object to pickle file. (Not implemented)