Everything working pretty well.

This commit is contained in:
Landon Wark
2024-02-20 14:36:58 -06:00
parent a7e915995e
commit 1e711149f1
14 changed files with 62 additions and 37 deletions

View File

@@ -601,5 +601,3 @@ class PCRParser(object):
self.pcr['plugin'] = df.iloc[19][1]
self.pcr['exported_on'] = df.iloc[20][1]
self.pcr['imported_by'] = getuser()

View File

@@ -32,7 +32,6 @@ def make_report_xlsx(records:list[dict]) -> Tuple[DataFrame, DataFrame]:
df = df.sort_values(['Submitting Lab', "Submitted Date"])
return df, df2
def make_report_html(df:DataFrame, start_date:date, end_date:date) -> str:
"""
@@ -74,7 +73,6 @@ def make_report_html(df:DataFrame, start_date:date, end_date:date) -> str:
html = temp.render(input=dicto)
return html
def convert_data_list_to_df(input:list[dict], subtype:str|None=None) -> DataFrame:
"""
Convert list of control records to dataframe
@@ -104,7 +102,6 @@ def convert_data_list_to_df(input:list[dict], subtype:str|None=None) -> DataFram
df = df_column_renamer(df=df)
return df
def df_column_renamer(df:DataFrame) -> DataFrame:
"""
Ad hoc function I created to clarify some fields
@@ -123,7 +120,6 @@ def df_column_renamer(df:DataFrame) -> DataFrame:
"kraken_percent":"kraken2_read_percent_(top_50)"
})
def displace_date(df:DataFrame) -> DataFrame:
"""
This function serves to split samples that were submitted on the same date by incrementing dates.
@@ -182,7 +178,6 @@ def check_date(df:DataFrame, item:dict, previous_dates:list) -> Tuple[DataFrame,
df, previous_dates = check_date(df, item, previous_dates)
return df, previous_dates
def get_unique_values_in_df_column(df: DataFrame, column_name: str) -> list:
"""
get all unique values in a dataframe column by name
@@ -196,7 +191,6 @@ def get_unique_values_in_df_column(df: DataFrame, column_name: str) -> list:
"""
return sorted(df[column_name].unique())
def drop_reruns_from_df(ctx:Settings, df: DataFrame) -> DataFrame:
"""
Removes semi-duplicates from dataframe after finding sequencing repeats.
@@ -227,4 +221,4 @@ def make_hitpicks(input:List[dict]) -> DataFrame:
Returns:
DataFrame: constructed dataframe.
"""
return DataFrame.from_records(input)
return DataFrame.from_records(input)