diff --git a/JupyterNotebooks/Alphavantage.ipynb b/JupyterNotebooks/Alphavantage.ipynb index 7abd8aa..af3d799 100644 --- a/JupyterNotebooks/Alphavantage.ipynb +++ b/JupyterNotebooks/Alphavantage.ipynb @@ -73,6 +73,13 @@ "key = \"AAUUBAYEDCI353AC\"" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Historic Stock Price and Volume" + ] + }, { "cell_type": "code", "execution_count": 27, @@ -244,7 +251,18 @@ } ], "source": [ - "data" + "data = {\n", + " \"function\": \"DIGITAL_CURRENCY_DAILY\", # WEEKLY, MONTHLY possible\n", + " \"symbol\": \"ETH\",\n", + " \"market\": 'CNY',\n", + " \"apikey\": key\n", + " }\n", + "r = requests.get(url, params=data)\n", + "data = r.json()\n", + "crypto_df = pd.DataFrame(data['Time Series (Digital Currency Daily)']).T.reset_index()\n", + "crypto_df = crypto_df.rename(columns={\"index\": \"Date\"})\n", + "crypto_df['Date'] = pd.to_datetime(crypto_df['Date'])\n", + "crypto_df " ] }, { @@ -367,7 +385,7 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "### Live Updates" + "### Realtime Data" ] }, { @@ -1236,6 +1254,24 @@ "data = r.json()\n" ] }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "data = {\n", + " \"function\": \"CURRENCY_EXCHANGE_RATE\", # WEEKLY, MONTHLY possible\n", + " \"from_currency\": \"ETH\",\n", + " \"to_currency\": 'USD',\n", + " \"apikey\": key\n", + " }\n", + "r = requests.get(url, params=data)\n", + "data = r.json()\n", + "crypto_df = pd.DataFrame(data['Realtime Currency Exchange Rate'], index=[0]).T\n", + "crypto_df" + ] + }, { "cell_type": "markdown", "metadata": {}, @@ -2314,377 +2350,21 @@ "cell_type": "markdown", "metadata": {}, "source": [ - "### Historic Data" + "### Treasury Yield" ] }, { "cell_type": "code", - "execution_count": 60, - "metadata": {}, - "outputs": [ - { - "data": { - "text/html": [ - "
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Date1a. open (CNY)1b. open (USD)2a. high (CNY)2b. high (USD)3a. low (CNY)3b. low (USD)4a. close (CNY)4b. close (USD)5. volume6. market cap (USD)
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0
1. From_Currency CodeETH
2. From_Currency NameEthereum
3. To_Currency CodeUSD
4. To_Currency NameUnited States Dollar
5. Exchange Rate4095.02000000
6. Last Refreshed2021-12-27 18:57:01
7. Time ZoneUTC
8. Bid Price4095.29000000
9. Ask Price4095.30000000
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" - ], - "text/plain": [ - " 0\n", - "1. From_Currency Code ETH\n", - "2. From_Currency Name Ethereum\n", - "3. To_Currency Code USD\n", - "4. To_Currency Name United States Dollar\n", - "5. Exchange Rate 4095.02000000\n", - "6. Last Refreshed 2021-12-27 18:57:01\n", - "7. Time Zone UTC\n", - "8. Bid Price 4095.29000000\n", - "9. Ask Price 4095.30000000" - ] - }, - "execution_count": 98, - "metadata": {}, - "output_type": "execute_result" - } - ], + "outputs": [], "source": [ - "data = {\n", - " \"function\": \"CURRENCY_EXCHANGE_RATE\", # WEEKLY, MONTHLY possible\n", - " \"from_currency\": \"ETH\",\n", - " \"to_currency\": 'USD',\n", + "treasury_yield = {\n", + " \"function\": \"TREASURY_YIELD\",\n", + " \"interval\": \"weekly\", # daily, monthly\n", + " \"maturity\": \"3month\", # OPTIONAL 5year, 10year, 30year\n", " \"apikey\": key\n", - " }\n", - "r = requests.get(url, params=data)\n", - "data = r.json()\n", - "crypto_df = pd.DataFrame(data['Realtime Currency Exchange Rate'], index=[0]).T\n", - "crypto_df" + "}" ] }, { @@ -2806,12 +2486,7 @@ " \"interval\": \"annual\", # quarterly\n", " \"apikey\": key\n", "}\n", - "treasury_yield = {\n", - " \"function\": \"TREASURY_YIELD\",\n", - " \"interval\": \"weekly\", # daily, monthly\n", - " \"maturity\": \"3month\", # OPTIONAL 5year, 10year, 30year\n", - " \"apikey\": key\n", - "}\n", + "\n", "federal_funds_rate = {\n", " \"function\": \"FEDERAL_FUNDS_RATE\",\n", " \"interval\": \"weekly\", # daily, monthly\n", @@ -2842,6 +2517,25 @@ "crypto_df" ] }, + { + "cell_type": "markdown", + "metadata": {}, + "source": [ + "### Financials" + ] + }, + { + "cell_type": "code", + "execution_count": null, + "metadata": {}, + "outputs": [], + "source": [ + "document = 'INCOME_STATEMENT' # BALANCE_SHEET, CASH_FLOW\n", + "url = 'https://www.alphavantage.co/query?function='+document+'&symbol=IBM&apikey=demo'\n", + "r = requests.get(url)\n", + "data = r.json()" + ] + }, { "cell_type": "markdown", "metadata": {}, diff --git a/Source/Alphavantage.rst b/Source/Alphavantage.rst index 145daa9..c8eba71 100644 --- a/Source/Alphavantage.rst +++ b/Source/Alphavantage.rst @@ -21,17 +21,17 @@ Fetching the data - `5. Many Stocks <#5>`_ - `6. Finanical Indices <#6>`_ - `7. Currencies <#7>`_ -- `8. Crypto <#8>`_ -- `9. Mutual Funds <#9>`_ -- `10. Treasury <#10>`_ -- `11. Stock Fundamentals <#11>`_ -- `12. Financials <#12>`_ -- `13. Put Call Options <#13>`_ -- `14. Stream Real Time Data <#14>`_ -- `15. Economic Indicators <#15>`_ -- `16. Technical Indicators <#16>`_ - -.. code:: ipython3 +- `8. Crypto <#8>`_ +- `9. Mutual Funds <#9>`_ +- `10. Treasury <#10>`_ +- `11. Stock Fundamentals <#11>`_ +- `12. Financials <#12>`_ +- `13. Put Call Options <#13>`_ +- `14. Stream Real Time Data <#14>`_ +- `15. Economic Indicators <#15>`_ +- `16. Technical Indicators <#16>`_ + +.. code-block:: ipython3 from alpha_vantage.timeseries import TimeSeries import pandas as pd @@ -42,6 +42,10 @@ Fetching the data Historical Price and Volume for 1 Stock --------------------------------------- +Link to the `historic price and volume of one stock`_ JupyterNB cell. + +.. _historic price and volume of one stock: Source/Alphavantage.ipynb#Historic-Stock-Price-and-Volume + .. code:: ipython3 data = { @@ -77,6 +81,9 @@ Adding Time Periods Frequency Setting ----------------- +Link to the `intraday data`_ JupyterNB cell. + +.. _intraday data: Source/Alphavantage.ipynb#Intraday-Data .. code:: ipython3 @@ -96,6 +103,9 @@ Frequency Setting Stock Split and dividends ------------------------- +Link to the `dividends`_ JupyterNB cell. + +.. _dividends: Source/Alphavantage.ipynb#Dividends .. code:: ipython3 @@ -108,6 +118,9 @@ Stock Split and dividends Financial Indices ----------------- +Link to the `financial indices`_ JupyterNB cell. + +.. _Financial Indices: Source/Alphavantage.ipynb#Indices .. code:: ipython3 @@ -120,6 +133,9 @@ Financial Indices Currencies --------------- +Link to the `currency exchange`_ JupyterNB cell. + +.. _Currency Exchange: Source/Alphavantage.ipynb#Currency-Exchange .. code:: ipython3 @@ -131,8 +147,11 @@ Currencies r = requests.get(url) data = r.json() -Crypto ---------------- +Cryptocurrencies +---------------- +Link to the `cryptocurrencies`_ JupyterNB cell. + +.. _Cryptocurrencies: Source/Alphavantage.ipynb#Cryptocurrencies .. code:: ipython3 @@ -146,6 +165,9 @@ Crypto Mutual Funds --------------- +Link to the `mutual funds`_ JupyterNB cell. + +.. _Mutual Funds: Source/Alphavantage.ipynb#Mutual-Funds .. code:: ipython3 @@ -159,6 +181,9 @@ Mutual Funds Treasury Rates --------------- +Link to the `treasury yield`_ JupyterNB cell. + +.. _Treasury Yield: Source/Alphavantage.ipynb#Treasury-Yield .. code:: ipython3 @@ -171,6 +196,9 @@ Treasury Rates Stock Fundamentals ------------------ +Link to the `intraday data`_ JupyterNB cell. + +.. _intraday data: Source/Alphavantage.ipynb#Intraday-Data .. code:: ipython3 @@ -181,6 +209,9 @@ Stock Fundamentals Import Financials ----------------- +Link to the `financials`_ JupyterNB cell. + +.. _Financials: Source/Alphavantage.ipynb#Financials .. code:: ipython3 @@ -191,6 +222,9 @@ Import Financials Stream Realtime Data -------------------- +Link to the `realtime data`_ JupyterNB cell. + +.. _Realtime Data: Source/Alphavantage.ipynb#Realtime-Data .. code:: ipython3 @@ -214,6 +248,9 @@ Stream Realtime Data Economic Indicators ------------------- +Link to the `economic indicators`_ JupyterNB cell. + +.. _Economic Indicators: Source/Alphavantage.ipynb#Economic-Indicators .. code:: ipython3 @@ -258,6 +295,9 @@ Economic Indicators Technical Indicators -------------------- +Link to the `technical indicators`_ JupyterNB cell. + +.. _Technical Indicators: Source/Alphavantage.ipynb#Technical-Indicators .. code:: ipython3