bucky.viz package

Submodules

bucky.viz.geoid module

bucky.viz.geoid.read_geoid_from_graph(graph_file=None)

Creates a dataframe relating geographic administration levels, e.g. admin2 values in a given admin1.

Parameters

graph_file (string or None) – Location of graph file. If None, uses most recently created graph in data/input_graphs/

Returns

df – Dataframe with names and values for admin0, admin1, and admin2 levels

Return type

Pandas DataFrame

bucky.viz.geoid.read_lookup(geofile, country='US')

Creates a dataframe relating geographic administration levels e.g. admin2 values in a given admin1 based on a lookup table.

Parameters

  • geofile (string) – Location of lookup table

  • country (string (default: 'US')) – Country name

Returns

df – Dataframe with names and values for admin0, admin1, and admin2

Return type

Pandas DataFrame

bucky.viz.map module

bucky.viz.map.get_dates(df, frequency='weekly')

Given a DataFrame of simulation data, this method returns dates based on the requested frequency.

Parameters

  • df (Pandas DataFrame) – Dataframe of simulation data

  • frequency ({'daily', 'monthly', 'weekly' (default)}) – Frequency of selected dates

Returns

date_list – List of dates

Return type

list of strings

bucky.viz.map.get_map_data(data_dir, adm_level, use_mean=False)

Reads requested simulation data.

Maps are created using one level down from the requested map level. For example, a national map is created using state-level data.

Parameters

  • data_dir (string) – Location of preprocessed simulation data

  • adm_level ({'adm0', adm1'}) – Admin level of requested map

  • use_mean (boolean) – If true, uses mean data. Otherwise, uses median quantile

Returns

df – Requested preprocessed simulation data

Return type

Pandas DataFrame

bucky.viz.map.get_state_outline(adm2_data, adm1_data)

Given admin2 shape data, finds matching admin1 shape data in order to get the admin1 outline.

Parameters

  • adm2_data (Geopandas GeoDataFrame) – Admin2-level shape data

  • adm1_data (Geopandas GeoDataFrame) – Admin1-level shape data

Returns

outline_df – Admin1-level shape data that match values in admin2

Return type

Geopandas GeoDataFrame

bucky.viz.map.make_adm1_maps(adm2_shape_df, adm1_shape_df, df, lookup_df, dates, cols, adm1_list, output_dir, log_scale=True, colormap='Reds', add_outline=False)

Creates adm1 maps.

Parameters

  • adm2_shape_df (Geopandas GeoDataFrame) – Shapefile information at the admin2 level

  • adm1_shape_df (Geopandas GeoDataFrame) – Shapefile information at the admin1 level

  • df (Pandas DataFrame) – Simulation data to plot

  • lookup_df (Pandas DataFrame) – Dataframe containing mapping between admin levels

  • dates (list of strings) – List of dates to make maps for

  • cols (list of strings) – List of columns to make maps for

  • adm1_list (list of strings or None) – List of explicit admin1 names to create names for. If None, a map is made for each unique admin1 in the lookup table

  • output_dir (string) – Directory to place created maps

  • log_scale (boolean (default: True)) – If true, uses log scaling

  • colormap (string, (default: 'Reds')) – Colormap to use; must be a valid Matplotlib colormap

  • add_outline (boolean (default: False)) – Add a thicker outline to the map

bucky.viz.map.make_map(shape_df, df, dates, adm_key, cols, output_dir, title_prefix=None, log_scale=True, colormap='Reds', outline_df=None)

Creates a map for each date and column.

Parameters

  • shape_df (Geopandas GeoDataFrame) – Shapefile information at the required admin level

  • df (Pandas DataFrame) – Simulation data to plot

  • dates (list of strings) – List of dates to make maps for

  • cols (list of strings) – List of columns to make maps for

  • output_dir (string) – Directory to place created maps

  • title_prefix (string or None) – String to add to map prefix

  • log_scale (boolean) – If true, uses log scaling

  • colormap (string (default: 'Reds')) – Colormap to use; must be a valid Matplotlib colormap

  • outline_df (Geopandas GeoDataFrame or None) – Shapefile for outline

bucky.viz.plot module

Bucky Plotting Tools (bucky.viz.plot)

TODO

bucky.viz.plot.interval(mean, sem, conf, N)
bucky.viz.plot.make_plots(adm_levels, input_dir, output_dir, lookup, plot_hist, plot_columns, quantiles, window_size, end_date, hist_file, min_hist_points, admin1=None, hist_start=None)

Wrapper function around plot. Creates plots, aggregating data if necessary.

Parameters

  • adm_levels (list of strings) – List of ADM levels to make plots for

  • input_dir (string) – Location of simulation data

  • output_dir (string) – Parent directory to place created plots.

  • lookup (Pandas DataFrame) – Lookup table for geographic mapping information

  • plot_hist (boolean) – If true, will plot historical data

  • plot_columns (list of strings) – List of columns to plot from data

  • quantiles (list of floats (or None)) – List of quantiles to plot. If None, will plot all available quantiles in data.

  • window_size (int) – Size of window (in days) to apply to historical data

  • end_date (string, formatted as YYYY-MM-DD) – Plot data until this date. If None, uses last date in simulation

  • hist_file (string) – Path to historical data file. If None, uses either CSSE or Covid Tracking data depending on columns requested.

  • min_hist_points (int) – Minimum number of historical data points to plot.

  • admin1 (list of strings, or None) – List of admin1 values to make plots for. If None, a plot will be created for every unique admin1 values. Otherwise, plots are only made for those requested.

  • hist_start (string, formatted as YYYY-MM-DD) – Plot historical data from this point. If None, aligns with simulation start date

bucky.viz.plot.plot(output_dir, lookup_df, key, sim_data, hist_data, plot_columns, quantiles)

Given a dataframe and a key, creates plots with requested columns.

For example, a DataFrame with state-level data would create a plot for each unique state. Simulation data is plotted as a line with shaded confidence intervals. Historical data is added as scatter points if requested.

Parameters

  • output_dir (string) – Location to place created plots.

  • lookup_df (Pandas DataFrame) – Dataframe containing information relating different geographic areas

  • key (string) – Key to use to relate simulation data and geographic areas. Must appear in lookup and simulation data (and historical data if applicable)

  • sim_data (Pandas DataFrame) – Simulation data to plot

  • hist_data (Pandas DataFrame) – Historical data to add to plot

  • plot_columns (list of strings) – Columns to plot

  • quantiles (list of floats (or None)) – List of quantiles to plot. If None, will plot all available quantiles in data.

Module contents