Datascience

finance

pyensae.finance.StockPrices (self, tick, url = ‘google’, folder = ‘cache’, begin = None, end = None, sep = ‘,’, intern = False, use_dtime = False)

Defines a class containing stock prices, provides basic functions, the class uses :epkg:`pandas` to load the data.

graphs

pyensae.graphhelper.Corrplot (self, data, na = 0)

An implementation of correlation plotting tools (corrplot). the class requires scipy.

Here is a simple example with a correlation matrix as an input (stored in a pandas dataframe)…

pyensae.graphhelper.graphviz_helper.dot_exe ()

retrieve graphivz executable

pyensae.graphhelper.draw_diagram (graph, module = ‘blockdiag’, format = ‘pillow’, options)

Draws a graph based on module blockdiag.

pyensae.graphhelper.matplotlib_helper.mpl_switch_style (style = ‘ggplot’)

changes the graph style

pyensae.graphhelper.run_dot (dot_file, outimg)

calls graphivz on a dot file and produces an image

notebooks and magic command helpers

pyensae.notebookhelper.folium_html_map (mapf, width = None, height = None, asobj = True)

Embeds the HTML source of the map directly into the IPython notebook.

pyensae.graphhelper.magic_graph.MagicGraph (self, shell = None, kwargs)

Defines magic commands about graphs

dataframes

pyensae.mlhelper.TableFormula (self, args, kwargs)

Extends class :epkg:`pandas:DataFrame` or proposes extensions to existing functions using lambda functions.