Calculate how many days passed since the last played match for each team

import pandas as pd
def calculatedaysdiff(df: pd.DataFrame) -> pd.DataFrame:
    result = df.copy()
    result["Date"] = pd.todatetime(result["Date"])
    result["row"] = range(len(result))
    longdf = result.melt(
        idvars=["row", "Date"],
        valuevars=["teamhome", "teamaway"],
        varname="side",
        valuename="team",
    )
    longdf["daysdiff"] = (
        longdf.sortvalues(["team", "Date", "row"])
        .groupby("team", sort=False)["Date"]
        .diff()
        .dt.days.fillna(0)  # fillna can be removed if you want to use NaN for the first occurrence
        .astype(int)
    )
    diffdf = longdf.pivot(index="row", columns="side", values="daysdiff").rename(
        columns={"teamhome": "homediff", "teamaway": "awaydiff"}
    )[["homediff", "awaydiff"]]
    return result.join(diffdf, on="row").drop(columns="row")
def main() -> None:
    import io
    data = """\
Date,teamhome,teamaway
2026-05-10,Tottenham,Arsenal
2026-05-11,Liverpool,West Ham
2026-05-13,West Ham,Chelsea
2026-05-13,Arsenal,Liverpool
"""
    df = pd.readcsv(io.StringIO(data))
    resultdf = calculatedaysdiff(df)
    print(resultdf)
    """\
        Date  teamhome  teamaway  homediff  away_diff
0 2026-05-10  Tottenham    Arsenal          0          0
1 2026-05-11  Liverpool   West Ham          0          0
2 2026-05-13   West Ham    Chelsea          2          0
3 2026-05-13    Arsenal  Liverpool          3          2
"""
if name == "main":
    main()