cowidev.variants

cowidev.variants.__main__

cowidev.variants.__main__.run_step(step: str)[source]

cowidev.variants._parser

cowidev.variants._parser._parse_args()[source]

cowidev.variants.etl

class cowidev.variants.etl.VariantsETL[source]

Bases: object

property _parse_last_update_date
extract() dict[source]
json_to_df(data: dict) DataFrame[source]
load(df: DataFrame, output_path: str) None[source]
pipe_check_variants(df: DataFrame) DataFrame[source]
pipe_correct_excess_percentage(df: DataFrame) DataFrame[source]
pipe_cumsum(df: DataFrame) DataFrame[source]
pipe_date(df: DataFrame) DataFrame[source]
pipe_dtypes(df: DataFrame) DataFrame[source]
pipe_filter_by_num_sequences(df: DataFrame) DataFrame[source]
pipe_filter_locations(df: DataFrame) DataFrame[source]
pipe_group_by_variants(df: DataFrame) DataFrame[source]
pipe_location(df: DataFrame) DataFrame[source]
pipe_omicron(df: DataFrame) DataFrame[source]
pipe_out(df: DataFrame) DataFrame[source]
pipe_per_capita(df: DataFrame) DataFrame[source]
pipe_percent(df: DataFrame) DataFrame[source]
pipe_rename_columns(df: DataFrame) DataFrame[source]
pipe_variant_dominant(df)[source]
pipe_variant_non_who(df: DataFrame) DataFrame[source]
pipe_variant_others(df: DataFrame) DataFrame[source]
pipe_variant_totals(df: DataFrame) DataFrame[source]
pipe_variants(df: DataFrame) DataFrame[source]
run()[source]
transform(data: dict) DataFrame[source]
transform_seq(df: DataFrame) DataFrame[source]
property variants_mapping
property variants_who
cowidev.variants.etl.run_etl()[source]

cowidev.variants.grapher

cowidev.variants.grapher.filter_by_num_sequences(df: DataFrame) DataFrame[source]
cowidev.variants.grapher.run_db_updater(input_path: str)[source]
cowidev.variants.grapher.run_explorerizer()[source]
cowidev.variants.grapher.run_grapheriser()[source]
cowidev.variants.grapher.variant_url_frienldy_name(df: DataFrame) DataFrame[source]

python -m cowidev.variants etl python -m cowidev.variants grapher-file