How to filter for dates in dataframe?

Question

I have a pandas dataframe like this called data_daily and it is created using this code

ts = TimeSeries (key=api_key, output_format = "pandas")
data_daily, meta_data = ts.get_daily_adjusted(symbol=stock_ticker, outputsize ='full')

             1. open   2. high  ...  7. dividend amount  8. split coefficient
date                            ...                                          
2020-09-21  325.7000  327.1300  ...              0.0000                   1.0
2020-09-18  335.3700  335.4900  ...              1.3392                   1.0
2020-09-17  333.5600  337.6996  ...              0.0000                   1.0
2020-09-16  341.5100  343.0600  ...              0.0000                   1.0
2020-09-15  341.1200  342.0200  ...              0.0000                   1.0
...              ...       ...  ...                 ...                   ...
1999-11-05  138.6250  139.1093  ...              0.0000                   1.0
1999-11-04  136.7500  137.3593  ...              0.0000                   1.0
1999-11-03  136.0000  136.3750  ...              0.0000                   1.0
1999-11-02  135.9687  137.2500  ...              0.0000                   1.0
1999-11-01  136.5000  137.0000  ...              0.0000                   1.0

[5256 rows x 8 columns]

To iterate trough the rows and select date I had to use the word index. Not sure if this will help with finding the solution. I tried to ask on stack overflow but it has been a few days and nobody seems to know what is wrong haha

for index, row in data_daily.iterrows():
    print(index, row['1. open'])

I want to set a date filters like this

start_date = '2000-01-01'
end_date = '2019-12-31'
number_of_years = end_date - start_date

This is my code for the main section

start_date = '2000-01-01'
end_date = '2019-12-31'
number_of_years = end_date - start_date 


    # Step 1
date_filter = data_daily

initial_investment = 10000
monthly_deposit = 1000

    # Start Price
start_adjusted_close_price = date_filter['5. adjusted close'][-1]
starting_shares = initial_investment / start_adjusted_close_price
start_reported_date = date_filter['date'][-1] #not working

    # End Price
end_adjusted_close_price = date_filter['5. adjusted close'][0]
end_reported_date = date_filter['date'][0] #not working

    # Final Math
step1_final_value = round((starting_shares * end_adjusted_close_price), 2)
step1_profit = round((step1_final_value - initial_investment), 2)
step1_roi = round((((step1_final_value - initial_investment) / initial_investment)* 100), 2)
step1_cagr = round((((math.log(step1_final_value/initial_investment)) / (math.log(1 + number_of_years)))* 100), 2)

    # Print out results
print("Starting Date : {} ".format(start_reported_date))
print("Start Share Price : ${} ".format(start_adjusted_close_price))
print("Starting Shares : {} ".format(starting_shares))
print("")
print("Ending Date : {} ".format(start_reported_date))
print("Ending Share Price : ${} ".format(end_adjusted_close_price))
print("")
print("Total Deposits : ${} ".format(initial_investment))
print("Portfolio Value : ${} ".format(step1_final_value))
print("Investment Profit : ${} ".format(step1_profit))
print("ROI : {}% ".format(step1_roi))
print("CAGR : {}% ".format(step1_cagr))

I have tried this one that was most recommended and a few others

data_daily.loc[datetime.date(year=2014,month=1,day=1):datetime.date(year=2015,month=2,day=1)]

But I keep getting empty dataframe

Empty DataFrame
Columns: [1. open, 2. high, 3. low, 4. close, 5. adjusted close, 6. volume, 7. dividend amount, 8. split coefficient]
Index: []

Any help is much appreciated! :)

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Jakub Mozdzierz

Jakub Mozdzierz

How to filter for dates in dataframe?