diff --git a/position_score_calculator.py b/position_score_calculator.py
index 7a703c0..06c3872 100644
--- a/position_score_calculator.py
+++ b/position_score_calculator.py
@@ -1,7 +1,19 @@
import pandas as pd
import argparse
-def load_data(filepath: str) -> pd.DataFrame:
+# Define Player attributes
+
+goalkeeper = {
+ "role_name": "goalkeeper",
+ "primary_multiplier": 5,
+ "primary_attributes": ["Agi", "Ref"],
+ "secondary_multiplier": 3,
+ "secondary_attributes": ["1v1", "Ant", "Cmd", "Cnt", "Kic", "Pos"],
+ "tertiary_multiplier": 1,
+ "tertiary_attributes": ["Acc", "Aer", "Cmp", "Dec", "Fir", "Han", "Pas", "Thr", "Vis"]
+}
+
+def load_html_data_to_dataframe(filepath: str) -> pd.DataFrame:
"""Read HTML file exported by FM into a Dataframe
Keyword arguments:
@@ -14,6 +26,37 @@ def load_data(filepath: str) -> pd.DataFrame:
player_df = player_df.map(lambda x: str(x).split("-")[0])
return player_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)
+
# TODO: Do I even want this?
def calc_composite_scores(player_df: pd.DataFrame) -> pd.DataFrame:
"""Calculate Speed, Workrate and Set Piece scores
@@ -38,38 +81,37 @@ def sum_attributes(player_df: pd.DataFrame, role: str, attribute_type: str, attr
player_df[f'{role}_{attribute_type}'] = 0
for attribute in attributes:
player_df[f'{role}_{attribute_type}'] += pd.to_numeric(player_df[attribute])
+ player_df[f'{role}_{attribute_type}'] = round(player_df[f'{role}_{attribute_type}'] / len(attributes), 2)
return player_df
-def calc_role_scores(player_df: pd.DataFrame, role: str, primary_attributes: [str], secondary_attributes: [str], tertiary_attributes: [str]) -> pd.DataFrame:
+def calc_role_scores(player_df: pd.DataFrame, role: dict) -> pd.DataFrame:
"""Calculate Player Role scores based on selected attributes.
Keyword arguments:
player_df: Dataframe of Players and Attributes
- role: Name of role to be used as additional column in dataframe
- primary_attributes: List of Most important attributes for a role
- secondary_attributes: List of Most secondary attributes for a role
- tertiary_attributes: List of Most tertiary attributes for a role
+ role: Dictionary containing role name, role attributes and role attribute weightings
"""
- player_df = sum_attributes(player_df, role, "primary", primary_attributes)
- player_df = sum_attributes(player_df, role, "secondary", secondary_attributes)
- player_df = sum_attributes(player_df, role, "tertiary", tertiary_attributes)
- divisor = (len(primary_attributes) * 5) + (len(secondary_attributes) * 3) + (len(tertiary_attributes) * 1)
- player_df[f'{role}'] = (((player_df[f'{role}_primary'] * 5) + (player_df[f'{role}_secondary'] * 3) + (player_df[f'{role}_tertiary'] * 1)) / divisor )
+ player_df = sum_attributes(player_df, role["role_name"], "primary", role["primary_attributes"])
+ player_df = sum_attributes(player_df, role["role_name"], "secondary", role["secondary_attributes"])
+ player_df = sum_attributes(player_df, role["role_name"], "tertiary", role["tertiary_attributes"])
+ divisor = role["primary_multiplier"] + role["secondary_multiplier"] + role["tertiary_multiplier"]
+ player_df[f'{role["role_name"]}'] = round((((player_df[f'{role["role_name"]}_primary'] * 5) + (player_df[f'{role["role_name"]}_secondary'] * 3) + (player_df[f'{role["role_name"]}_tertiary'] * 1)) / divisor ), 2)
return player_df
def calc_player_scores(player_df: pd.DataFrame):
# TODO: Create objects for each role that can be used here.
- player_df = calc_role_scores(player_df, "goalkeeper", primary_attributes=["Agi", "Ref"],
- secondary_attributes=["1v1", "Ant", "Cmd", "Cnt", "Kic", "Pos"],
- tertiary_attributes=["Acc", "Aer", "Cmp", "Dec", "Fir", "Han", "Pas", "Thr", "Vis"])
+ player_df = calc_role_scores(player_df, goalkeeper)
# TODO: Add roles.
- print(player_df)
+ return player_df
if __name__ == "__main__":
parser = argparse.ArgumentParser()
- parser.add_argument("-f", "--filepath", type=str)
+ parser.add_argument("-i", "--input-filepath", type=str)
+ parser.add_argument("-o", "--output-filepath", type=str)
args = parser.parse_args()
- filepath = args.filepath
+ input_filepath = args.input_filepath
+ output_filepath = args.output_filepath
- player_df = load_data(filepath)
- calc_player_scores(player_df)
+ player_df = load_html_data_to_dataframe(input_filepath)
+ player_df = calc_player_scores(player_df)
+ export_html_from_dataframe(player_df, output_filepath)