313def _count_consecutive(data):
314    """Counts consecutive data (like cumsum() with reset on zeroes)"""
315
316    def _count(data):317        return data * (data.groupby((data != data.shift(1)).cumsum()).cumcount() + 1)
318
319    if isinstance(data, _pd.DataFrame):

232    return data
233
234
235def download_returns(ticker, period="max", proxy=None):236    params = {
237        "tickers": ticker,
238        "proxy": proxy,

 50    return df[df.index.isin(dates)]
 51
 52
 53def _pandas_current_month(df): 54    n = _dt.datetime.now()
 55    daterange = _pd.date_range(_dt.date(n.year, n.month, 1), n)
 56    return df[df.index.isin(daterange)]

 44    return df[df.index >= _dt.datetime.now().strftime("%Y-01-01")]
 45
 46
 47def _pandas_date(df, dates): 48    if not isinstance(dates, list):
 49        dates = [dates]
 50    return df[df.index.isin(dates)]

 40    return df[df.index >= date.strftime("%Y-%m-01")]
 41
 42
 43def _ytd(df): 44    return df[df.index >= _dt.datetime.now().strftime("%Y-01-01")]
 45
 46

 28from . import stats as _stats
 29
 30
 31def _mtd(df): 32    return df[df.index >= _dt.datetime.now().strftime("%Y-%m-01")]
 33
 34

1631        iDisplay(iHTML(jscode))
1632
1633
1634def _embed_figure(figfiles, figfmt):1635    if isinstance(figfiles, list):
1636        embed_string = "\n"
1637        for figfile in figfiles:

1618        iDisplay(iHTML(jscode.replace("{{filename}}", filename)))
1619
1620
1621def _open_html(html):1622    jscode = _regex.sub(
1623        " +",
1624        " ",

1600    return obj
1601
1602
1603def _download_html(html, filename="quantstats-tearsheet.html"):1604    jscode = _regex.sub(
1605        " +",
1606        " ",

1586    return dd_stats.T
1587
1588
1589def _html_table(obj, showindex="default"):1590    obj = _tabulate(
1591        obj, headers="keys", tablefmt="html", floatfmt=".2f", showindex=showindex
1592    )

1502            )
1503
1504
1505def _calc_dd(df, display=True, as_pct=False):1506    dd = _stats.to_drawdown_series(df)
1507    dd_info = _stats.drawdown_details(dd)
1508

1233    return metrics
1234
1235
1236def plots(1237    returns,
1238    benchmark=None,
1239    grayscale=False,

 723    )
 724
 725
 726def metrics( 727    returns,
 728    benchmark=None,
 729    rf=0.0,

 645    )
 646
 647
 648def basic( 649    returns,
 650    benchmark=None,
 651    rf=0.0,

 496        f.write(tpl)
 497
 498
 499def full( 500    returns,
 501    benchmark=None,
 502    rf=0.0,

  59    return returns, benchmark
  60
  61
  62def html(  63    returns,
  64    benchmark=None,
  65    rf=0.0,

  48    return periods_per_year, half_year
  49
  50
  51def _match_dates(returns, benchmark):  52    if isinstance(returns, _pd.DataFrame):
  53        loc = max(returns[returns.columns[0]].ne(0).idxmax(), benchmark.ne(0).idxmax())
  54    else:

  43    from IPython.core.display import display as iDisplay
  44
  45
  46def _get_trading_periods(periods_per_year=252):  47    half_year = _ceil(periods_per_year / 2)
  48    return periods_per_year, half_year
  49

1197    return res.replace(".0", "")
1198
1199
1200def format_pct_axis(x, _):1201    x *= 100  # lambda x, loc: "{:,}%".format(int(x * 100))
1202    if x >= 1e12:
1203        res = "%1.1fT%%" % (x * 1e-12)

1180    return None
1181
1182
1183def format_cur_axis(x, _):1184    if x >= 1e12:
1185        res = "$%1.1fT" % (x * 1e-12)
1186        return res.replace(".0T", "T")

1089    return None
1090
1091
1092def plot_table(1093    tbl,
1094    columns=None,
1095    title="",

 977    return None
 978
 979
 980def plot_distribution( 981    returns,
 982    figsize=(10, 6),
 983    fontname="Arial",

 863    return None
 864
 865
 866def plot_longest_drawdowns( 867    returns,
 868    periods=5,
 869    lw=1.5,

 717    return None
 718
 719
 720def plot_rolling_beta( 721    returns,
 722    benchmark,
 723    window1=126,

 589    return None
 590
 591
 592def plot_rolling_stats( 593    returns,
 594    benchmark=None,
 595    title="",