DataFrame

class amplpy.DataFrame(index, columns=(), **kwargs)

A DataFrame object, used to communicate data to and from the AMPL entities.

An object of this class can be used to do the following tasks: - Assign values to AMPL entities (once the DataFrame is populated, use set_data() / setData() to assign its values to the modelling entities in its columns) - Get values from AMPL, decoupling the values from the AMPL entities they originate via get_values() / getValues().

A DataFrame object can be created in various ways.

• Create a skeleton by specifiying manually the indexing columns and the column headers.

• Get values from AMPL, decoupling the values from the AMPL entities they originate from (via get_values() / getValues()).

Populating a DataFrame object can be done adding row by row to a pre-existing skeleton via addRow(), setting whole columns of a pre-existing skeleton via set_column() / setColumn() or adding columns (including indexing columns) via add_column() / addColumn().

Modifying a DataFrame object can be done via set_column() / setColumn() or, item by item, via set_values() / setValues().

Accessing data in a DataFrame can be done row by row using get_row() / getRow() or by column via get_column() / getColumn().

__init__(index, columns=(), **kwargs)

Create a new DataFrame with specifed index and column headers.

Args:

index: Index column;

columns: Column headers.

__iter__()

get_num_cols()

Get the total number of columns in this dataframe (indexarity + number of values).

Returns:

The number of columns.

get_num_rows()

Get the number of data rows in this dataframe.

Returns:

The number of rows.

get_num_indices()

Get the number of indices (the indexarity) of this dataframe.

Returns:

The number of indices needed to access one row of this dataframe.

add_row(*value)

Add a row to the DataFrame. The size of the tuple must be equal to the total number of columns in the dataframe.

Args:

value: A single argument with a tuple containing all the values for the row to be added, or multiple arguments with the values for each column.

add_column(header, values=None)

Add a new column with the corresponding header and values to the dataframe.

Args:

header: The name of the new column.

values: A list of size getNumRows() with all the values of the new column.

get_column(header)

Get the specified column as a view object.

Args:

header: The header of the column.

set_column(header, values)

Set the values of a column.

Args:

header: The header of the column to be set.

values: The values to set.

get_row(key)

Get a row by value of the indexing columns. If the index is not specified, gets the only row of a dataframe with no indexing columns.

Args:

key: Tuple representing the index of the desired row.

Returns:

The row.

get_row_by_index(index)

Get row by numeric index.

Args:

index: Zero-based index of the row to get.

Returns:

The corresponding row.

get_headers()

Get the headers of this DataFrame.

Returns:

The headers of this DataFrame.

set_values(values)

Set the values of a DataFrame from a dictionary.

Args:

values: Dictionary with the values to set.

to_dict()

Return a dictionary with the DataFrame data.

to_list()

Return a list with the DataFrame data.

to_pandas()

Return a pandas DataFrame with the DataFrame data.

classmethod from_dict(dic, index_names=None, column_names=None)

Create a DataFrame from a dictionary.

Args:

dic: dictionary to load. index_names: index names to use. column_names: column names to use.

classmethod from_pandas(df, index_names=None)

Create a DataFrame from a pandas DataFrame.

Args:

df: Pandas DataFrame to load. index_names: index names to use.

classmethod from_numpy(data)

Create a DataFrame from a numpy array or matrix.

addColumn(header, values=None)

Add a new column with the corresponding header and values to the dataframe.

Args:

header: The name of the new column.

values: A list of size getNumRows() with all the values of the new column.

addRow(*value)

Add a row to the DataFrame. The size of the tuple must be equal to the total number of columns in the dataframe.

Args:

value: A single argument with a tuple containing all the values for the row to be added, or multiple arguments with the values for each column.

classmethod fromDict(dic, index_names=None, column_names=None)

Create a DataFrame from a dictionary.

Args:

dic: dictionary to load. index_names: index names to use. column_names: column names to use.

classmethod fromNumpy(data)

Create a DataFrame from a numpy array or matrix.

classmethod fromPandas(df, index_names=None)

Create a DataFrame from a pandas DataFrame.

Args:

df: Pandas DataFrame to load. index_names: index names to use.

getColumn(header)

Get the specified column as a view object.

Args:

header: The header of the column.

getHeaders()

Get the headers of this DataFrame.

Returns:

The headers of this DataFrame.

getNumCols()

Get the total number of columns in this dataframe (indexarity + number of values).

Returns:

The number of columns.

getNumIndices()

Get the number of indices (the indexarity) of this dataframe.

Returns:

The number of indices needed to access one row of this dataframe.

getNumRows()

Get the number of data rows in this dataframe.

Returns:

The number of rows.

getRow(key)

Get a row by value of the indexing columns. If the index is not specified, gets the only row of a dataframe with no indexing columns.

Args:

key: Tuple representing the index of the desired row.

Returns:

The row.

getRowByIndex(index)

Get row by numeric index.

Args:

index: Zero-based index of the row to get.

Returns:

The corresponding row.

setColumn(header, values)

Set the values of a column.

Args:

header: The header of the column to be set.

values: The values to set.

setValues(values)

Set the values of a DataFrame from a dictionary.

Args:

values: Dictionary with the values to set.

toDict()

Return a dictionary with the DataFrame data.

toList()

Return a list with the DataFrame data.

toPandas()

Return a pandas DataFrame with the DataFrame data.

__module__ = 'amplpy.dataframe'

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