occurs when trying to run an example from the docs

stock_rets = pf.utils.get_symbol_rets('FB')
pf.create_returns_tear_sheet(stock_rets, live_start_date='2015-12-1')

---------------------------------------------------------------------------
AttributeError                            Traceback (most recent call last)
<ipython-input-40-feb97330a052> in <module>()
----> 1 pf.create_returns_tear_sheet(df, benchmark_rets=benchmark_rets)

~/.pyenv/versions/3.6.0/envs/pyfolio/lib/python3.6/site-packages/pyfolio/plotting.py in call_w_context(*args, **kwargs)
     50         if set_context:
     51             with plotting_context(), axes_style():
---> 52                 return func(*args, **kwargs)
     53         else:
     54             return func(*args, **kwargs)

~/.pyenv/versions/3.6.0/envs/pyfolio/lib/python3.6/site-packages/pyfolio/tears.py in create_returns_tear_sheet(returns, positions, transactions, live_start_date, cone_std, benchmark_rets, bootstrap, return_fig)
    455                              live_start_date=live_start_date)
    456 
--> 457     plotting.show_worst_drawdown_periods(returns)
    458 
    459     # If the strategy's history is longer than the benchmark's, limit strategy

~/.pyenv/versions/3.6.0/envs/pyfolio/lib/python3.6/site-packages/pyfolio/plotting.py in show_worst_drawdown_periods(returns, top)
   1686     """
   1687 
-> 1688     drawdown_df = timeseries.gen_drawdown_table(returns, top=top)
   1689     utils.print_table(drawdown_df.sort_values('Net drawdown in %',
   1690                                               ascending=False),

~/.pyenv/versions/3.6.0/envs/pyfolio/lib/python3.6/site-packages/pyfolio/timeseries.py in gen_drawdown_table(returns, top)
    995                                                                 recovery,
    996                                                                 freq='B'))
--> 997         df_drawdowns.loc[i, 'Peak date'] = (peak.to_pydatetime()
    998                                             .strftime('%Y-%m-%d'))
    999         df_drawdowns.loc[i, 'Valley date'] = (valley.to_pydatetime()

AttributeError: 'numpy.int64' object has no attribute 'to_pydatetime'

Hi I am new to using python and have been working with pyfolio to generate the graphs for portfolio returns. I am getting a the following figure. Any help would be appreciated. Thanks

update summary table to be of the format:

Summary statistics:
Annualized Specific Return (Alpha): x%
Annualized Common Return (Beta): y%
Total Annualized Return: A%

Specific Sharpe Ratio: x%/std.dev()

annualized cost to be added later on.

cc @joshpayne

This makes pos.get_long_short_pos return a dataframe that matches the gross leverage of the portfolio.

I removed the gross_lev argument since the leverage is dependent on positions dataframe.

This PR is addressing https://github.com/quantopian/pyfolio/issues/30

hi I am using pyfolio 0.9.0 and pandas 0.22

Got an error below(although the program continue running and plot graphs), does anyone have ideas?

Thanks a lot!

======== IndexErrorTraceback (most recent call last) in () ----> 1 pf.create_returns_tear_sheet(stock_rets, benchmark_rets=benchmark_rets)

/home/frank/Envs/quants/local/lib/python2.7/site-packages/pyfolio/plotting.pyc in call_w_context(*args, **kwargs) 50 if set_context: 51 with plotting_context(), axes_style(): ---> 52 return func(*args, **kwargs) 53 else: 54 return func(*args, **kwargs)

/home/frank/Envs/quants/local/lib/python2.7/site-packages/pyfolio/tears.pyc in create_returns_tear_sheet(returns, positions, transactions, live_start_date, cone_std, benchmark_rets, bootstrap, turnover_denom, header_rows, return_fig) 641 if ((bootstrap is not None) 642 and (benchmark_rets is not None)): --> 643 ax_bootstrap = plt.subplot(gs[i, :]) 644 plotting.plot_perf_stats(returns, benchmark_rets, 645 ax=ax_bootstrap)

/home/frank/Envs/quants/local/lib/python2.7/site-packages/matplotlib/gridspec.pyc in getitem(self, key) 159 raise ValueError("unrecognized subplot spec") 160 num1, num2 = np.ravel_multi_index( --> 161 [_normalize(k1, nrows), _normalize(k2, ncols)], (nrows, ncols)) 162 else: # Single key 163 num1, num2 = _normalize(key, nrows * ncols)

/home/frank/Envs/quants/local/lib/python2.7/site-packages/matplotlib/gridspec.pyc in _normalize(key, size) 151 if 0 <= key < size: 152 return key, key --> 153 raise IndexError("invalid index") 154 155 if isinstance(key, tuple):

IndexError: invalid index

This has two major negative consequences:

1. During development, an import-time error (e.g. a syntax error, or a missing package) anywhere in the repo causes all imports to fail.
2. Importing anything in the library takes an annoyingly long (almost 3 seconds on my machine) amount of time. Most of this time is spent in seaborn.__init__.

@twiecki is there a reason we're doing this in the module __init__?

from . import utils
from . import timeseries
from . import pos
from . import txn

from .tears import *  # noqa
from .plotting import *  # noqa

Fixes #379

We don't just want a multivariate regression, we want a rolling multivariate regression. Pandas used to support this sort of thing with pd.stats.ols.MovingOLS, but that has unfortunately been deprecated.

A solution is described on StackOverflow, but frustratingly this solution doesn't work since apply only works on Series data (see citynorman's comment on the top answer). So, we will have to write our own rolling multivariate regression...

This fixes a whole bunch of stuff that caused tests to break under more recent python and pandas. It also removes the bayesian module, it's just making tests slow, is difficult to install, and we don't have time to maintain it properly.

Hi, I am running the single stock example. As I run the line:

pf.create_returns_tear_sheet(stock_rets, live_start_date='2015-12-1')

I obtain the following error:

/lib/python3.4/site-packages/pandas/tseries/tools.py in _convert_listlike(arg, box, format, name) 329 arg = getattr(arg, 'values', arg) 330 result = tslib.array_with_unit_to_datetime(arg, unit, --> 331 errors=errors) 332 if box: 333 if errors == 'ignore': pandas/tslib.pyx in pandas.tslib.array_with_unit_to_datetime (pandas/tslib.c:38273)() pandas/tslib.pyx in pandas.tslib.array_with_unit_to_datetime (pandas/tslib.c:37194)() ValueError: non convertible value 2015-07-21with the unit 'D'

It looks like enough has changed on pyfolio to merit v0.8.0 (with risk and performance attribution, I think we might even want to call it v1.0.0!)

We are also seeing an increasing number of users running into bugs that have already been patched: upping the version would make it easier to diagnose errors (both ours, and open source users).

To-do:

• [ ] Performance attribution tear sheet #417 (still WIP, will definitely want to wait for this)
• [ ] Resolve any dependency issues with zipline/alphalens/empyrical
• [x] Do we want to outsource Fama-French functionality from pyfolio to empyrical? #56 on empyrical (Answer: yes. PR waiting: #416)
• [ ] Do we want to include returns decomposition from alphalens into pyfolio? #183 on alphalens

@twiecki @gusgordon @richafrank @Jstauth thoughts? If this sounds good I'll organize a milestone :)

New features

• Risk tear sheet: added a new tear sheet to analyze risk exposures to common factors, sector, market cap and illiquidity (#391)
• Simple tear sheet: added a new tear sheet that presents only the most important plots in the full tear sheet, for a quick general overview of a portfolio's performance (#389)
• Volatility plot: added a rolling annual volatility plot in the returns tear sheet (#390)

Bugfixes

• Fixed bug regarding Yahoo API and pandas data reader (#395)
• Removed information_ratio to remain compatible with empyrical
• Fama-French rolling multivariate regression bug fix (#406)

Maintenance

• Updated and improved jupyter notebook documentation (#411)

Referencing issue: #385

I have substituted out the yahoo backend for the google data using the pandas web.get_data_google(symbol, start=start, end=end) function

Problem Description

Please provide a minimal, self-contained, and reproducible example:

[Paste code here]

Please provide the full traceback:

[Paste traceback here]

Please provide any additional information below:

Versions

• Pyfolio version:
• Python version:
• Pandas version:
• Matplotlib version:

Modified create_full_tear_sheet() and create_simple_tear_sheet() to optionally return matplotlib figures based on the return_fig boolean parameter, in analogy to other tear sheet functions, such as create_returns_tear_sheet(), create_position_tear_sheet() etc. Now these two tear sheet functions can be used outside of IPython (%matplotlib inline) environments to capture these tear sheets and display them, convert them to pdf files etc.

If return_fig==True, create_full_tear_sheet() now returns the following dictionary containing all the matplotlib figures that were created internally:

{ 'returns': fig_returns, 'interesting_times': fig_interesting_times, 'position': fig_position, 'txn': fig_txn, 'round_trip': fig_round_trip, 'capacity': fig_capacity, 'perf_attrib': fig_perf_attrib }

And if return_fig==True, create_simple_tear_sheet() returns the matplotlib figure already created internally.

Problem Description

Please provide a minimal, self-contained, and reproducible example:

[Paste code here]

import pyfolio as pf Please provide the full traceback:

[Paste traceback here]
```---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
<ipython-input-11-1977abd82007> in <module>
----> 1 import pyfolio as pf

~\anaconda3\lib\site-packages\pyfolio\__init__.py in <module>
----> 1 from . import utils
      2 from . import timeseries
      3 from . import pos
      4 from . import txn
      5 from . import interesting_periods

~\anaconda3\lib\site-packages\pyfolio\utils.py in <module>
     26 import empyrical.utils
     27 
---> 28 from . import pos
     29 from . import txn
     30 

~\anaconda3\lib\site-packages\pyfolio\pos.py in <module>
     20 
     21 try:
---> 22     from zipline.assets import Equity, Future
     23     ZIPLINE = True
     24 except ImportError:

c:\users\home\src\zipline-trader\zipline\__init__.py in <module>
     27 from .utils.numpy_utils import numpy_version
     28 from .utils.pandas_utils import new_pandas
---> 29 from .utils.run_algo import run_algorithm
     30 from ._version import get_versions
     31 

c:\users\home\src\zipline-trader\zipline\utils\run_algo.py in <module>
     22 from trading_calendars import get_calendar
     23 
---> 24 from zipline.data import bundles
     25 from zipline.data.benchmarks import get_benchmark_returns_from_file
     26 from zipline.data.data_portal import DataPortal

c:\users\home\src\zipline-trader\zipline\data\bundles\__init__.py in <module>
      1 # These imports are necessary to force module-scope register calls to happen.
----> 2 from . import quandl  # noqa
      3 from . import csvdir  # noqa
      4 from . import alpaca_api
      5 from . import alpha_vantage_api

c:\users\home\src\zipline-trader\zipline\data\bundles\quandl.py in <module>
     14 from trading_calendars import register_calendar_alias
     15 
---> 16 from . import core as bundles
     17 import numpy as np
     18 

c:\users\home\src\zipline-trader\zipline\data\bundles\core.py in <module>
     11 from toolz import curry, complement, take
     12 
---> 13 from ..adjustments import SQLiteAdjustmentReader, SQLiteAdjustmentWriter
     14 from ..bcolz_daily_bars import BcolzDailyBarReader, BcolzDailyBarWriter
     15 from ..minute_bars import (

c:\users\home\src\zipline-trader\zipline\data\adjustments.py in <module>
     27 from zipline.utils.pandas_utils import empty_dataframe
     28 from zipline.utils.db_utils import group_into_chunks, coerce_string_to_conn
---> 29 from ._adjustments import load_adjustments_from_sqlite
     30 
     31 log = Logger(__name__)

c:\users\home\src\zipline-trader\zipline\data\_adjustments.pyx in init zipline.data._adjustments()

c:\users\home\src\zipline-trader\zipline\assets\__init__.py in <module>
     20     make_asset_array,
     21 )
---> 22 from .assets import (
     23     AssetFinder,
     24     AssetConvertible,

c:\users\home\src\zipline-trader\zipline\assets\assets.py in <module>
     65     OrderedContracts,
     66 )
---> 67 from .asset_writer import (
     68     check_version_info,
     69     split_delimited_symbol,

c:\users\home\src\zipline-trader\zipline\assets\asset_writer.py in <module>
    451 
    452 
--> 453 class AssetDBWriter(object):
    454     """Class used to write data to an assets db.
    455 

c:\users\home\src\zipline-trader\zipline\assets\asset_writer.py in AssetDBWriter()
    462 
    463     @preprocess(engine=coerce_string_to_eng(require_exists=False))
--> 464     def __init__(self, engine, asset_finder=None):
    465         self.asset_finder = asset_finder
    466         self.engine = engine

c:\users\home\src\zipline-trader\zipline\utils\preprocess.py in _decorator(f)
    107             )
    108 
--> 109         return _build_preprocessed_function(
    110             f, processors, args_defaults, varargs, varkw,
    111         )

c:\users\home\src\zipline-trader\zipline\utils\preprocess.py in _build_preprocessed_function(func, processors, args_defaults, varargs, varkw)
    244 
    245     args['co_firstlineno'] = original_code.co_firstlineno
--> 246     new_func.__code__ = CodeType(*map(getitem(args), _code_argorder))
    247     return new_func

TypeError: an integer is required (got type bytes)






**Please provide any additional information below:**


## Versions

* Pyfolio version:      3
* Python version:      3.8.5
* Pandas version:      1.1.3
* Matplotlib version:  3.32

Problem Description

Please provide a minimal, self-contained, and reproducible example:

f = pf.create_returns_tear_sheet(df, benchmark_rets=benchmark_rets,return_fig=True);
f.savefig('report.pdf')

Please provide the full traceback:

how we can export the full output? I use savefig(), but it saves only plots , and doesn't save  fists part of output

Please provide any additional information below:

saved filed didn't contain tabular part, for example these two tables , saved only plots.

Versions

• Pyfolio version: 0.9.4
• Python version: 3.7
• Pandas version:1.3.5
• Matplotlib version: 3.5.2

Any issues raised for in this Git are unlikely to be resolved, since Quantopian has folded and the staff that have moved to Robinhood have not been involved for a few years, so it's currently unlikely that anything will happen here.

However, thanks to the foresight of the Quantopian founders and devs who made this open source, other contributors have taken the banner and have improved this package from where Quantopian left it.

@Stefan-Jansen maintains a forked, updated version of this package here: https://github.com/stefan-jansen/pyfolio-reloaded

as part of his continuing development of Zipline (also developed by Quantopian) here: https://github.com/stefan-jansen/zipline-reloaded