import argparse
import pandas as pd
def load_xlsx_data_to_dataframe(filepath: str) -> pd.DataFrame:
"""Read XLSX file into a Dataframe.
Keyword arguments:
filepath -- path to xlsx file
"""
df = pd.read_excel(filepath, engine="openpyxl", nrows=12)
return df
def load_html_data_to_dataframe(filepath: str) -> pd.DataFrame:
"""Read HTML file exported by FM into a Dataframe.
Keyword arguments:
filepath -- path to fm player html file
"""
df = pd.read_html(filepath, header=0, encoding="utf-8", keep_default_na=False)[0]
# Clean Dataframe to get rid of unknown values and ability ranges (takes the lowest value)
# This casts to a string to be able to split, so we have to cast back to an int later.
df = df.replace("-", 0)
df = df.map(lambda x: str(x).split("-")[0])
return df
def export_html_from_dataframe(player_df: pd.DataFrame, filepath: str) -> str:
"""Export Dataframe as html with jQuery Data Tables.
Taken from: https://www.thepythoncode.com/article/convert-pandas-dataframe-to-html-table-python.
Keyword arguments:
filepath -- path to fm player html file
"""
table_html = player_df.to_html(table_id="table", index=False)
html = f"""
{table_html}
"""
open(filepath, "w", encoding="utf-8").write(html)
def calc_role_scores(player_df: pd.DataFrame, attribute_df: pd.DataFrame) -> pd.DataFrame:
"""Calculate Player position scores based on selected attribute weightings.
Keyword arguments:
player_df: Dataframe of Players and their Attributes
attribute_df: Dataframe of Attributes and their Weightings
"""
for _, weightings in attribute_df.iterrows():
role = weightings["Ratings Weights"]
player_df[role] = 0
for attribute in weightings.index[1:]:
weighting = weightings[attribute]
try:
player_df[role] += round(pd.to_numeric(player_df[attribute]) * weighting / 20, 2)
except Exception as e: # Used to Nat being used twice (Nationality and Natural Fitness)
print(e)
continue
player_df.loc[player_df[role] < 10, role] = 0
return player_df
if __name__ == "__main__":
# Parse Input args
parser = argparse.ArgumentParser()
parser.add_argument("-i", "--input-filepath", type=str, help="Path to Input Html file")
parser.add_argument("-o", "--output-filepath", type=str, help="Path to Export resultant Html file")
parser.add_argument("-a", "--attribute-filepath", type=str, help="Path to Attribute XLSX file", default="./attribute_ratings.xlsx")
args = parser.parse_args()
input_filepath = args.input_filepath
output_filepath = args.output_filepath
attribute_filepath = args.attribute_filepath
# Inport data, calculate scores for role,
attribute_df = load_xlsx_data_to_dataframe(attribute_filepath)
player_df = load_html_data_to_dataframe(input_filepath)
player_df = calc_role_scores(player_df, attribute_df)
# trim attributes from final output
player_df = player_df.drop(player_df.columns[15:-11], axis=1)
# export results as html
export_html_from_dataframe(player_df, output_filepath)