💻 Usage¶
Even though some investpy usage examples are presented on the docs, some basic functionality will be sorted out with sample Python code blocks. Additionally, more usage examples can be found under examples/ directory, which contains a collection of Jupyter Notebooks on how to use investpy and handle its data.
📌 Note that investpy.search_quotes is the only function that ensures that the data is updated and aligned 1:1 with
the data provided by Investing.com!
📈 Recent/Historical Data Retrieval¶
investpy allows the user to download both recent and historical data from any financial product indexed (stocks, funds, ETFs, currency crosses, certificates, bonds, commodities, indices, and cryptos). In the example presented below, the historical data from the past years of a stock is retrieved.
import investpy
df = investpy.get_stock_historical_data(stock='AAPL',
country='United States',
from_date='01/01/2010',
to_date='01/01/2020')
print(df.head())
Open High Low Close Volume Currency
Date
2010-01-04 30.49 30.64 30.34 30.57 123432176 USD
2010-01-05 30.66 30.80 30.46 30.63 150476160 USD
2010-01-06 30.63 30.75 30.11 30.14 138039728 USD
2010-01-07 30.25 30.29 29.86 30.08 119282440 USD
2010-01-08 30.04 30.29 29.87 30.28 111969192 USD
To get to know all the available recent and historical data extraction functions provided by investpy, and also, parameter tuning, please read the docs.
🔍 Search Live Data¶
Investing.com search engine is completely integrated with investpy, which means that any available financial product (quote) can be easily found. The search function allows the user to tune the parameters to adjust the search results to their needs, where both product types and countries from where the products are, can be specified. All the search functionality can be easily used, for example, as presented in the following piece of code:
import investpy
search_result = investpy.search_quotes(text='apple', products=['stocks'],
countries=['united states'], n_results=1)
print(search_result)
{"id_": 6408, "name": "Apple Inc", "symbol": "AAPL", "country": "united states", "tag": "/equities/apple-computer-inc", "pair_type": "stocks", "exchange": "NASDAQ"}
Retrieved search results will be a list of investpy.utils.search_obj.SearchObj class instances, unless
n_results is set to 1, when just a single investpy.utils.search_obj.SearchObj class instance will be returned.
To get to know which are the available functions and attributes of the returned search results, please read the related
documentation at Search Engine Documentation. So on, those
search results let the user retrieve both recent and historical data, its information, the technical indicators,
the default currency, etc., as presented in the pieces of code below:
Recent Data¶
recent_data = search_result.retrieve_recent_data()
print(recent_data.head())
Open High Low Close Volume Change Pct
Date
2021-05-13 124.58 126.15 124.26 124.97 105861000 1.79
2021-05-14 126.25 127.89 125.85 127.45 81918000 1.98
2021-05-17 126.82 126.93 125.17 126.27 74245000 -0.93
2021-05-18 126.56 126.99 124.78 124.85 63343000 -1.12
2021-05-19 123.16 124.92 122.86 124.69 92612000 -0.13
Historical Data¶
historical_data = search_result.retrieve_historical_data(from_date='01/01/2019', to_date='01/01/2020')
print(historical_data.head())
Open High Low Close Volume Change Pct
Date
2020-01-02 74.06 75.15 73.80 75.09 135647008 2.28
2020-01-03 74.29 75.14 74.13 74.36 146536000 -0.97
2020-01-06 73.45 74.99 73.19 74.95 118579000 0.80
2020-01-07 74.96 75.22 74.37 74.60 111511000 -0.47
2020-01-08 74.29 76.11 74.29 75.80 132364000 1.61
Information¶
information = search_result.retrieve_information()
print(information)
{"prevClose": 126.11, "dailyRange": "126.1-127.44", "revenue": 325410000000, "open": 126.53, "weekRange": "83.14-145.09", "eps": 4.46, "volume": 53522373, "marketCap": 2130000000000, "dividend": "0.88(0.70%)", "avgVolume": 88858729, "ratio": 28.58, "beta": 1.2, "oneYearReturn": "50.35%", "sharesOutstanding": 16687631000, "nextEarningDate": "03/08/2021"}
Currency¶
default_currency = search_result.retrieve_currency()
print(default_currency)
'USD'
Technical Indicators¶
technical_indicators = search_result.retrieve_technical_indicators(interval="daily")
print(technical_indicators)
indicator signal value
0 RSI(14) neutral 52.1610
1 STOCH(9,6) buy 63.7110
2 STOCHRSI(14) overbought 100.0000
3 MACD(12,26) sell -0.6700
4 ADX(14) neutral 21.4750
5 Williams %R buy -20.9430
6 CCI(14) buy 67.1057
7 ATR(14) less_volatility 1.7871
8 Highs/Lows(14) buy 0.4279
9 Ultimate Oscillator sell 47.3620
10 ROC buy 1.5150
11 Bull/Bear Power(13) buy 1.3580
💸 Crypto Currencies Data Retrieval¶
Cryptocurrencies support has recently been included, to let the user retrieve data and information from any available crypto at Investing.com. Please note that some cryptocurrencies do not have available data indexed at Investing.com so that it can not be retrieved using investpy either, even though they are just a few, consider it.
As already presented previously, historical data retrieval using investpy is really easy. The piece of code presented below shows how to retrieve the past years of historical data from Bitcoin (BTC).
import investpy
data = investpy.get_crypto_historical_data(crypto='bitcoin',
from_date='01/01/2014',
to_date='01/01/2019')
print(data.head())
Open High Low Close Volume Currency
Date
2014-01-01 805.9 829.9 771.0 815.9 10757 USD
2014-01-02 815.9 886.2 810.5 856.9 12812 USD
2014-01-03 856.9 888.2 839.4 884.3 9709 USD
2014-01-04 884.3 932.2 848.3 924.7 14239 USD
2014-01-05 924.7 1029.9 911.4 1014.7 21374 USD