src.utils.pandas module

helper methods for manipulation pandas dataframes. i.e. - merging tables - drop list entries - index by a certain feature

src.utils.pandas.concatOnPrefixes(table, prefixes, ident)

Partition columns by prefix and stack matches row-wise.

For each prefix in prefixes:

• take all columns starting with the prefix

• append all non-matching columns

• add a column ‘ident’ with the prefix label

Then concatenate these partitions along rows.

Parameters:

• table (DataFrame)

• prefixes (list[str])

• ident (str)

Return type:

DataFrame

src.utils.pandas.dropListEntries(dataframe)

this method drops all columns of a dataframe, that contain a list.

Parameters:

dataframe (pd.DataFrame) – a dataframe to format

Returns:

dataframe – the resulting dataframe with dropped lists

Return type:

pd.DataFrame

src.utils.pandas.indexByOneVariable(df, var)

this method uses one variable/feature and sets it as the new index variable.

Parameters:

• df (pd.DataFrame) – the dataframe, to change

• var (str) – the name of the feature/variable

Returns:

dataframe – the new dataframe indexed by var

Return type:

pd.DataFrame

src.utils.pandas.mergeTables(tables)

merges tables along the rows, but assumes unique colnames!

Parameters:

tables (list[DataFrame])

Return type:

DataFrame

Dependency Diagrams (without externals):

Mode: exportMode: importMode: neighborMode: neighbor_reduced

Range 1Range 2Range 3Range 4Range 5

Import dependencies (collapsed)

Dependency Diagrams:

Mode: exportMode: importMode: neighborMode: neighbor_reduced

Range 1Range 2Range 3Range 4Range 5

Import dependencies (collapsed)