一个python包，用于从coinmarketcap获取加密货币的历史市场数据，并计算和绘制不同的指标。
PriceIndices的Python项目详细描述
安装
PIP
pip install PriceIndics
从源（github）
git克隆https://github.com/dc-aichara/Price-Indices.git
CD价格指数
python3 setup.py安装
用法
fromPriceIndicesimportMarketHistory,Indices
示例
获取市场历史和收盘价
>>>history=MarketHistory()# Get Market History >>>df_history=history.get_history('bitcoin','20130428','20190624')>>>df_history.head()DateOpen*HighLowClose**VolumeMarketCap02019-06-2310696.6911246.1410556.1010855.372099832650219297009035512019-06-2210175.9211157.3510107.0410701.692999520486119021412482422019-06-219525.0710144.569525.0710144.562062400864318029324152832019-06-209273.069594.429232.489527.161784682378416930478479142019-06-199078.739299.629070.409273.5215546809946164780855869# Get closing price>>>price_data=history.get_price('bitcoin','20130428','20190624')>>>price_data.head()dateprice02019-06-2310855.3712019-06-2210701.6922019-06-2110144.5632019-06-209527.1642019-06-199273.52
计算波动率指数
>>>df_bvol=Indices.get_bvol_index(price_data)>>>df_bvol.head()datepriceBVOL_Index02019-06-2210701.690.63648212019-06-2110144.560.63641422019-06-209527.160.61988632019-06-199273.520.60840342019-06-189081.760.604174
绘制波动率指数
>>>Indices.get_bvol_graph(df_bvol)"""This will return a plot of BVOL index against time also save volatility index plot in your working directory as 'bvol_index.png'"""
计算相对强度指数（rsi）
>>>df_rsi=Indices.get_rsi(price_data)>>>print(df_rsi.tail())datepriceprice_changegainlossgain_averageloss_averageRSRSI_1RS_SmoothRSI_222172013-05-02105.217.467.460.001.5321432.5000000.61285737.9982290.56111735.94330622182013-05-01116.9911.7811.780.002.3735712.1757141.09093952.1745960.97531949.37525722192013-04-30139.0022.0122.010.003.9457141.9814291.99134866.5702581.86911065.14598122202013-04-29144.545.545.540.003.8785711.9814291.95746266.1872262.20642268.81259222212013-04-28134.21-10.330.0010.333.8785712.5064291.54744960.7450501.39715858.283931
绘制rsi
>>>Indices.get_rsi_graph(df_rsi)"""This will return a plot of RSI against time and also save RSI plot in your working directory as 'rsi.png'"""
获取bollinger谱带及其绘图
>>>df_bb=Indices.get_bollinger_bands(price_data,20)>>>df_bb.tail()datepriceSMASDpluseminus22432013-05-02105.21115.23456.339257127.913013-115.234522442013-05-01116.99114.94006.097587127.135174-114.940022452013-04-30139.00115.79008.016499131.822998-115.790022462013-04-29144.54116.917510.217936137.353372-116.917522472013-04-28134.21117.453010.842616139.138233-117.4530"""This will also save Bollingers bands plot in your working directory as 'bollinger_bands.png'"""
得到移动平均收敛散度（macd）及其图
>>>df_macd=Indices.get_moving_average_convergence_divergence(price_data)"""This will return a pandas DataFrame and save EMA plot as 'macd.png' in working directory. """">>>df_macd.head()datepriceEMA_12EMA_26MACD192019-06-189081.7610415.97934010886.327599-470.348259202019-06-179320.3510247.42098010770.329259-522.908279212019-06-168994.4910054.66236810638.785610-584.123242222019-06-158838.389867.54200410505.422231-637.880228232019-06-148693.839686.97092610371.230214-684.259288
获得简单移动平均值（SMA）及其曲线图
>>>df_sma=Indices.get_simple_moving_average(price_data,20)"""This will return a pandas DataFrame and save EMA plot as 'sma.png' in working directory. """">>>df_sma.head()datepriceSMA192019-06-189081.7610998.4180202019-06-179320.3510891.8930212019-06-168994.4910781.1900222019-06-158838.3810674.1860232019-06-148693.8310548.1055
得到指数移动平均值（ema）及其曲线
>>>df_ema=Indices.get_exponential_moving_average(price_data,[20,70])"""This will return a pandas DataFrame and save EMA plot as 'ema.png' in working directory. """">>>df_ema.head()datepriceEMA_20EMA_7002019-07-0711450.8511450.85000011450.85000012019-07-0611208.5511427.77381011444.02464822019-07-0510978.4611384.98201811430.91015132019-07-0411215.4411368.83515911424.84056942019-07-0311961.2711425.25752511439.951257
许可证
查看这个价格指数包的webpage。
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