quantstats: TypeError: Invalid comparison between dtype=datetime64[ns, America/New_York] and datetime

This is my code:

import quantstats as qs

qs.extend_pandas()

stock = qs.utils.download_returns('GLD', period="10y")

qs.reports.html(stock, title='PTL Investments', output='output/gld.html')

qs.reports.html(stock, "SPY", title="GLD vs. SPY", output='output/gld_vs_spy.html')

stock = qs.utils.download_returns('QQQ', period="10y")

qs.reports.html(stock, "SPY", title="QQQ vs. SPY", output='output/qqq_ovs_spy.html')

stock = qs.utils.download_returns('TQQQ', period="10y")

qs.reports.html(stock, "QQQ", title="TQQQ vs. QQQ", output='output/tqqq_vs_qqq.html')

tickers = {
    'FB': 0.2,
    'AAPL': 0.2, 
    'AMZN': 0.2,
    'MSFT': 0.2,
    'GOOG': 0.2 
}

fmaga = portfolio = qs.utils.make_index(tickers)

qs.reports.html(fmaga, "qqq", output="output/fmaga_vs_qqq.html")`

and this is my output:

TypeError: Cannot compare tz-naive and tz-aware datetime-like objects

The above exception was the direct cause of the following exception:

InvalidComparison                         Traceback (most recent call last)
...
     33     typ = type(right).__name__
---> 34     raise TypeError(f"Invalid comparison between dtype={left.dtype} and {typ}")
     35 return res_values

TypeError: Invalid comparison between dtype=datetime64[ns, America/New_York] and datetime

About this issue

Original URL
State: closed
Created 2 years ago
Comments: 20 (2 by maintainers)

Most upvoted comments

I did the above but I am now experiencing an issue with the tearsheets:

stock = qs.utils.download_returns(“SPY”) bench = qs.utils.download_returns(“SPY”)

stock.index = stock.index.tz_convert(None) bench.index = bench.index.tz_convert(None)

qs.reports.html(stock, bench)

when i run the above for the SAME underlying security(in this case the strategy and bench are both SPY) I do get a working plot but I do not get identical plots or identical output data…is anyone else experiencing this? They should be the same?

apachetrade on Dec 2, 2022

Not sure if this is what you’re after, but I download benchmark first, convert, and then add DataFrame to report

# adding benchmark
benchmark_SPY = pd.DataFrame(qs.utils.download_returns('SPY'))
benchmark_SPY.index = benchmark_SPY.index.tz_convert(None)
qs.reports.html(df, benchmark_SPY)

MidjoV on Dec 2, 2022

Finally got it to work with:

import quantstats as qs
import pandas as pd
stock = pd.DataFrame(qs.utils.download_returns('AAPL'))
stock.index = stock.index.tz_convert(None) # make timezone agnostic.
stock = stock.squeeze() # back to a series
benchmark = pd.DataFrame(qs.utils.download_returns('MSFT'))
benchmark.index = benchmark.index.tz_convert(None) # make timezone agnostic.
qs.reports.html(stock, benchmark)

jjphung on Feb 27, 2023

I have the same problem if my portfolio has a timezone-aware index, I can’t get it to work even without using a benchmark.

yes, this is because internally metrics() function is always creating default naive (no tz) dates, see my analysis above

drusakov778 on Jan 11, 2023