Add train loading and basic day filtering

src/analysis/filter.py

+from datetime import datetime
+
+import pandas as pd
+
+
+def date_filter(
+    df: pd.DataFrame, start_date: datetime | None, end_date: datetime | None
+) -> pd.DataFrame:
+    """Filter dataframe by date (day).
+
+    Args:
+        df (pd.DataFrame): the considered dataframe
+        start_date (datetime | None): the start date
+        end_date (datetime | None): the end date
+
+    Returns:
+        pd.DataFrame: the filtered dataframe
+    """
+    if isinstance(start_date, datetime):
+        df = df.loc[df.day >= start_date.date()]
+    if isinstance(end_date, datetime):
+        df = df.loc[df.day <= end_date.date()]
+    return df

src/analysis/load_data.py

@@ -27,6 +27,7 @@ def read_train_csv(file: Path) -> pd.DataFrame:
         infer_datetime_format=True,
     )
     df.client_code = df.client_code.apply(RailwayCompany.from_code)  # type: ignore
+    df.day = df.day.apply(lambda dt: dt.date())
     return df.loc[(df.phantom == False) & (df.trenord_phantom == False)].drop(
         ["phantom", "trenord_phantom"], axis=1
     )

src/analysis/main.py

 import argparse
+import logging
+import pathlib
 from datetime import datetime
 
+import pandas as pd
 from dateparser import parse
+from tqdm import tqdm
+
+from src.analysis.filter import date_filter
+from src.analysis.load_data import read_station_csv, read_train_csv
 
 
 def register_args(parser: argparse.ArgumentParser):
@@ -37,4 +44,24 @@ def main(args: argparse.Namespace):
     if args.end_date and not end_date:
         raise argparse.ArgumentTypeError("invalid end_date")
 
-    raise NotImplementedError()
+    # Load dataset
+    df = pd.DataFrame()
+    logging.info("Loading datasets...")
+    for train_csv in (
+        tqdm(args.trains_csv)
+        if logging.root.getEffectiveLevel() > logging.DEBUG
+        else args.trains_csv
+    ):
+        path = pathlib.Path(train_csv)
+        train_df: pd.DataFrame = read_train_csv(pathlib.Path(train_csv))
+        df = pd.concat([df, train_df], axis=0)
+        logging.debug(f"Loaded {len(train_df)} data points @ {path}")
+
+    stations: pd.DataFrame = read_station_csv(args.station_csv)
+    original_length: int = len(df)
+
+    # Apply filters
+    df = date_filter(df, start_date, end_date)
+
+    logging.info(f"Loaded {len(df)} data points ({original_length} before filtering)")
+    print(df)