def main(csv, interactive, cjk_support, conf, yaml, package_yaml, sponsor_yaml,
output_path):
conf_singlet = report_generatorconfig.Configuration.get_instance()
conf_singlet.read_configuration(template)
if conf:
logger.debug("User customized conf is specified: %s" % conf_singlet)
conf_singlet.read_configuration(conf)
# welcome user, ask year of data
year = vtext.welcome_ask_year(interactive)
frames = []
for csv_single in csv:
csv_index = csv.index(csv_single)
df = report_generatorcsv.csv_to_dataframe(csv_single)
# select necessary columns from df
df = vtext.select_column(df, interactive, csv_index)
frames.append(df)
df_all = pd.concat(frames, join="outer", axis=0, ignore_index=True)
# all raw data is imported. let's call analyzer to do something
df_all = ag.add_cat_title(df_all)
df_all = df_all.fillna(value="No Record")
df_all = ag.get_sanity_data(df_all, cjk_support)
# all datafram general data object
df_all_g_data_obj = attendee.Attendee(df_all)
# analyzed data frame is ready. let's plot
figs = plotter.plot_counts(df_all, year, cjk_support)
# read the other report data
report_yaml = report_generatoryaml.read_yaml(yaml)
sponsors = apsponsor.get_all_sponsors(package_yaml, sponsor_yaml)
# generate the report
# general info (everyone could see it):
# figs: plots from attendee dataframe
# df_all_g_data_obj: numbers from attendee dataframe
# report_yaml: plot description of figs
# sponsors:
# sponsor specific information based on yaml descriptor
exporter_html.generate(figs, report_yaml, df_all_g_data_obj, sponsors,
output_path)
print("Analysis process finished completely.")
def main(
csv,
talks_csv,
proposed_talks_csv,
booth_csv,
interactive,
cjk_support,
conf,
yaml,
package_yaml,
sponsor_yaml,
output_path,
):
conf_singlet = report_generatorconfig.Configuration.get_instance()
conf_singlet.read_configuration(template)
if conf:
logger.debug("User customized conf is specified: %s" % conf_singlet)
conf_singlet.read_configuration(conf)
# welcome user, ask year of data
year = vtext.welcome_ask_year(interactive)
frames = []
for csv_single in csv:
csv_index = csv.index(csv_single)
df = report_generatorcsv.csv_to_dataframe(csv_single)
# select necessary columns from df
df = vtext.select_column(df, interactive, csv_index)
frames.append(df)
df_all = pd.concat(frames, join="outer", axis=0, ignore_index=True)
# all raw data is imported. let's call analyzer to do something
df_all = ag.add_cat_title(df_all)
df_all = df_all.fillna(value="No Record")
df_all = ag.get_sanity_data(df_all, cjk_support)
# all datafram general data object
df_all_g_data_obj = attendee.Attendee(df_all)
# analyzed data frame is ready. let's plot attendee data
figs = plotter.plot_attendee_counts(df_all, year, cjk_support)
# prepared the selected topic pie chart
talks_df = report_generatorcsv.csv_to_dataframe(talks_csv)
talks_fig = plotter.plot_talk_categories(talks_df)
figs.update(talks_fig)
# prepared the proposed topic pie chart
p_talks_df = report_generatorcsv.csv_to_dataframe(proposed_talks_csv)
p_talks_fig = plotter.plot_talk_categories(p_talks_df,
fig_title="Proposed_Topics")
figs.update(p_talks_fig)
booth_df = report_generatorcsv.csv_to_dataframe(booth_csv)
# TODO: if we want to enhance the issue #11 in the future like #23, we may start here by using the returned value
plotter.plot_booth(booth_df, "booth")
# read the other report data
report_yaml = report_generatoryaml.read_yaml(yaml)
sponsors = apsponsor.get_all_sponsors(package_yaml, sponsor_yaml)
accepted_talk_number = talks_df["category"].value_counts().sum()
all_talk_number = p_talks_df["category"].value_counts().sum()
talk_info_ratio = accepted_talk_number / all_talk_number
talk_info = "{:.1%}".format(talk_info_ratio)
# generate the report
# general info (everyone could see it):
# figs: plots from attendee dataframe and talks
# df_all_g_data_obj: numbers from attendee dataframe
# report_yaml: plot description of figs
# sponsors:
# sponsor specific information based on yaml descriptor
exporter_html.generate(figs,
report_yaml,
df_all_g_data_obj,
sponsors,
talk_info,
"sponsor.html",
output_path=output_path)
# summary for internal review
exporter_html.generate_summary(figs, report_yaml, df_all_g_data_obj,
sponsors, talk_info, "internal.html",
"internal-post-event", output_path)
print("Analysis process finished completely.")