{
"cells": [
{
"cell_type": "markdown",
"metadata": {},
"source": [
"# Example use of pandas_ta\n",
"* Simple imports"
]
},
{
"cell_type": "code",
"execution_count": 1,
"metadata": {},
"outputs": [],
"source": [
"import pandas as pd\n",
"import matplotlib.pyplot as plt\n",
"\n",
"import pandas_ta as ta\n",
"from alphaVantageAPI.alphavantage import AlphaVantage # pip install alphaVantage-api\n",
"e = pd.DataFrame()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Help on Indicators (post an [issue](https://github.com/twopirllc/pandas-ta/issues) if the indicator doc needs updating)"
]
},
{
"cell_type": "code",
"execution_count": 2,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"pandas.ta - Technical Analysis Indicators\n",
"Total Indicators: 72\n",
"Abbreviations:\n",
" accbands, ad, adosc, adx, ao, apo, aroon, atr, bbands, bop, cci, cmf, cmo, coppock, decreasing, dema, donchian, dpo, efi, ema, eom, fwma, hl2, hlc3, hma, ichimoku, increasing, kc, kst, kurtosis, linreg, log_return, macd, mad, massi, median, mfi, midpoint, midprice, mom, natr, nvi, obv, ohlc4, percent_return, ppo, pvol, pvt, pwma, quantile, rma, roc, rsi, skew, sma, stdev, stoch, t3, tema, trima, trix, true_range, tsi, uo, variance, vortex, vp, vwap, vwma, willr, wma, zscore\n",
"Help on function accbands in module pandas_ta.volatility:\n",
"\n",
"accbands(high, low, close, length=None, c=None, drift=None, mamode=None, offset=None, **kwargs)\n",
" Acceleration Bands (ACCBANDS)\n",
" \n",
" Acceleration Bands created by Price Headley plots upper and lower envelope\n",
" bands around a simple moving average.\n",
" \n",
" Sources:\n",
" https://www.tradingtechnologies.com/help/x-study/technical-indicator-definitions/acceleration-bands-abands/\n",
" \n",
" Calculation:\n",
" Default Inputs:\n",
" length=10, c=4\n",
" EMA = Exponential Moving Average\n",
" SMA = Simple Moving Average\n",
" HL_RATIO = c * (high - low) / (high + low)\n",
" LOW = low * (1 - HL_RATIO)\n",
" HIGH = high * (1 + HL_RATIO)\n",
" \n",
" if 'ema':\n",
" LOWER = EMA(LOW, length)\n",
" MID = EMA(close, length)\n",
" UPPER = EMA(HIGH, length)\n",
" else:\n",
" LOWER = SMA(LOW, length)\n",
" MID = SMA(close, length)\n",
" UPPER = SMA(HIGH, length)\n",
" \n",
" Args:\n",
" high (pd.Series): Series of 'high's\n",
" low (pd.Series): Series of 'low's\n",
" close (pd.Series): Series of 'close's\n",
" length (int): It's period. Default: 10\n",
" c (int): Multiplier. Default: 4\n",
" mamode (str): Two options: None or 'ema'. Default: 'ema'\n",
" drift (int): The difference period. Default: 1\n",
" offset (int): How many periods to offset the result. Default: 0\n",
" \n",
" Kwargs:\n",
" fillna (value, optional): pd.DataFrame.fillna(value)\n",
" fill_method (value, optional): Type of fill method\n",
" \n",
" Returns:\n",
" pd.DataFrame: lower, mid, upper columns.\n",
"\n"
]
}
],
"source": [
"e.ta.indicators()\n",
"help(ta.accbands)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"### Load Daily EUR.USD from [AlphaVantage](http://www.alphavantage.com) and clean it up a little"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"Shape: (100, 14)\n"
]
},
{
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