pipeline.src.flows.activity_visualizations

Functions

extract_activity_overview_data(→ pandas.DataFrame)
get_time_range(→ list)
make_config(→ dict)
_df_to_dict(df)	Create an input dict for Kepler.gl using a DataFrame object
_normalize_data(data)
data_to_json(data)	Serialize a Python data object.
_repr_html_([data, config, read_only, center_map])
generate_html(→ str)
create_data_frame_to_load(→ pandas.DataFrame)
load_activity_visualization(df, truncate_table)
activity_visualizations_flow([start_months_ago, ...])

Module Contents

pipeline.src.flows.activity_visualizations.extract_activity_overview_data(from_datetime_utc: datetime.datetime, to_datetime_utc: datetime.datetime) → pandas.DataFrame

pipeline.src.flows.activity_visualizations.get_time_range(df: pandas.DataFrame) → list

pipeline.src.flows.activity_visualizations.make_config(time_range: list) → dict

pipeline.src.flows.activity_visualizations._df_to_dict(df)

Create an input dict for Kepler.gl using a DataFrame object

Inputs: - df: a DataFrame object

Returns: - dictionary: a dictionary variable that can be used in Kepler.gl

pipeline.src.flows.activity_visualizations._normalize_data(data)

pipeline.src.flows.activity_visualizations.data_to_json(data)

Serialize a Python data object. Attributes of this dictionary are to be passed to the JavaScript side.

pipeline.src.flows.activity_visualizations._repr_html_(data=None, config=None, read_only=False, center_map=False)

pipeline.src.flows.activity_visualizations.generate_html(df: pandas.DataFrame, config: dict) → str

pipeline.src.flows.activity_visualizations.create_data_frame_to_load(html: str, from_datetime_utc: datetime.datetime, to_datetime_utc: datetime.datetime) → pandas.DataFrame

pipeline.src.flows.activity_visualizations.load_activity_visualization(df: pandas.DataFrame, truncate_table: bool)

pipeline.src.flows.activity_visualizations.activity_visualizations_flow(start_months_ago: int = 12, end_months_ago: int = 0, truncate_table: bool = False, get_utcnow_fn=get_utcnow)