Using PyFolio Next To Pandas

I am going to analyze the time series of financial data. Since I work on the Pakistan Stock Exchange (PSX), data is not available on yahoo. When I looked at some Quantopian tutorials, the first step is data extraction through yahoo finance. Now when I use the PyFolio module and read in csv (Panda Function) containing the data, there is a problem with the Pandas and PyFolio datetime format. Below is the code of what I am doing.

import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
import pyfolio as pf
import datetime
from datetime import datetime
from datetime import timedelta

start_date = '2015-02-01'
end_date = '2017-03-20'
live_date = '2017-03-15'
symbols = ['KEL']

def converter(start_date):
    convert=datetime.strptime(start_date, "%Y-%m-%d")
    return convert

def data(symbols):
    dates=pd.date_range(start_date,end_date) 
    df=pd.DataFrame(index=dates)
    df_temp=pd.read_csv('/home/furqan/Desktop/python_data/{}.csv'.format(str(symbols[0])),usecols=['Date','Close'],
                            parse_dates=True,index_col='Date',na_values=['nan'])
    df_temp = df_temp.rename(columns={'Close': symbols[0]})
    df=df.join(df_temp)
    df=df.fillna(method='ffill')
    df=df.fillna(method='bfill')
    return df
new_date = converter (live_date)
df= data(symbols)
sheet = pf.create_returns_tear_sheet(df, live_start_date=new_date)

The above code results in the following error

TypeError: Cannot compare tz-naive and tz-aware timestamps

Given the above information, I have two questions.

1) Can Quantopian be good for my analysis if I have data on my PC? Because the data is not available for financing yahoo.

2) ? .

PyFolio Pandas. https://quantopian.imtqy.com/pyfolio/notebooks/single_stock_example/#fetch-the-daily-returns-for-a-stock

http://pandas.pydata.org/pandas-docs/stable/

+4
1

, TZ . datetime, :

df.tz_localize('UTC')

, .

0

Source: https://habr.com/ru/post/1673205/


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