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Update core.py & utils.py #382

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Update core.py & utils.py #382

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3412333
Update utils.py - enable start-end date
finiya Nov 21, 2024
811ba43
Update core.py - add pandas3.0 compatibility
finiya Nov 21, 2024
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14 changes: 6 additions & 8 deletions quantstats/_plotting/core.py
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Original file line number Diff line number Diff line change
Expand Up @@ -290,11 +290,9 @@ def plot_timeseries(
benchmark = benchmark.cumsum()

if resample:
returns = returns.resample(resample)
returns = returns.last() if compound is True else returns.sum(axis=0)
returns = returns.resample(resample).last() if compound else returns.resample(resample).sum()
if isinstance(benchmark, _pd.Series):
benchmark = benchmark.resample(resample)
benchmark = benchmark.last() if compound is True else benchmark.sum(axis=0)
benchmark = benchmark.resample(resample).last() if compound else benchmark.resample(resample).sum()
# ---------------

fig, ax = _plt.subplots(figsize=figsize)
Expand Down Expand Up @@ -1013,16 +1011,16 @@ def plot_distribution(
apply_fnc = _stats.comp if compounded else _np.sum

port["Weekly"] = port["Daily"].resample("W-MON").apply(apply_fnc)
port["Weekly"].ffill(inplace=True)
port["Weekly"] = port["Weekly"].ffill()

port["Monthly"] = port["Daily"].resample("ME").apply(apply_fnc)
port["Monthly"].ffill(inplace=True)
port["Monthly"] = port["Monthly"].ffill()

port["Quarterly"] = port["Daily"].resample("QE").apply(apply_fnc)
port["Quarterly"].ffill(inplace=True)
port["Quarterly"] = port["Quarterly"].ffill()

port["Yearly"] = port["Daily"].resample("YE").apply(apply_fnc)
port["Yearly"].ffill(inplace=True)
port["Yearly"] = port["Yearly"].ffill()

fig, ax = _plt.subplots(figsize=figsize)
ax.spines["top"].set_visible(False)
Expand Down
6 changes: 6 additions & 0 deletions quantstats/utils.py
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Original file line number Diff line number Diff line change
Expand Up @@ -236,6 +236,10 @@ def _prepare_returns(data, rf=0.0, nperiods=None):


def download_returns(ticker, period="max", proxy=None):
"""
Period parse in as yfinance format "max" or
as pd.DatetimeIndex([...]) array.
"""
params = {
"tickers": ticker,
"proxy": proxy,
Expand All @@ -245,6 +249,8 @@ def download_returns(ticker, period="max", proxy=None):
}
if isinstance(period, _pd.DatetimeIndex):
params["start"] = period[0]
if len(period) > 1:
params["end"] = period[-1]
else:
params["period"] = period
df = _yf.download(**params)["Close"].pct_change()
Expand Down