def totalTogether(stockSymbol,Webster,currentInfo): #plots all the graphs together fig=go.create_candlestick(Webster.Open,Webster.High,Webster.Low,Webster.Close,dates=Webster.index) figure=obj.Trace(y=Webster.High,x=Webster.index,line=dict(color=('rgb(0,50,100)'))) currentFigure=obj.Trace(y=currentInfo[0]['LastTradePrice'],x=currentInfo[0]['LastTradeDateTime'],line=dict(color=('rgb(0,0,0)'))) fig['data'].extend([figure]) fig['data'].extend([currentFigure]) py.plot(fig, filename=stockSymbol+'_Line',validate=False)
def totalTogether(stockSymbol, Webster, currentInfo, Predict, Pointy, Rsi): #plots all the graphs together old_stdout = sys.stdout sys.stdout = open(os.devnull, "w") # Does not work in linux!!! temp = Webster.index temp = temp.tz_localize("UTC") figure = obj.Scatter(y=Webster.High, x=temp, line=dict(color=('rgb(0,50,100)')), name="Past Data for " + stockSymbol) #Past Data Line currentFigure = obj.Trace(y=currentInfo[0]['LastTradePrice'], x=currentInfo[0]['LastTradeDateTime'], line=dict(color=('rgb(0,0,0)')), name='Current Data for ' + stockSymbol) #Current Point Predicts = obj.Scatter(y=Predict, x=ArrayNCalc.getWorkDates(len(Predict)), line=dict(color=('rgb(255,165,0)')), name="Prediction " + stockSymbol) #Prediction Line point = obj.Trace(y=Pointy, x=datetime.now(pytz.utc) + timedelta(days=1), line=dict(color=pointColorMaker(Pointy, currentInfo)), name="Prediction " + stockSymbol) #point of prediciton RSI = obj.Scatter(y=Rsi, x=ArrayNCalc.getWorkDates(len(Rsi)), line=dict(color=('rgb(0,0,0)')), name="RSI for " + stockSymbol) #Prediction Line fig = tools.make_subplots(rows=2, cols=1) #data=Data([figure,currentFigure,Predicts, point]) #Data Array of Figures data = Data([Predicts, point, currentFigure, figure]) fig.append_trace(data[0], 1, 1) fig.append_trace(data[1], 1, 1) fig.append_trace(data[2], 1, 1) fig.append_trace(data[3], 1, 1) fig.append_trace(RSI, 2, 1) fig['layout']['yaxis1'].update(title='Dollars ($)', domain=[0, 0.7]) fig['layout']['yaxis2'].update(title='RSI percentage (%)', range=[0, 100], domain=[0.8, 1]) sys.stdout.close() sys.stdout = old_stdout return py.plot(fig, filename=stockSymbol + '_Line', auto_open=False) #Plot The Function
def make_trace(df, package, rgb): x_date = df["commit_date"] y_package = df[package] return go.Trace(x=x_date, y=y_package, name=package, marker=go.Marker(color=rgb))
def update_graph_scatter(): df1 = pd.read_csv(file_path+'df_ytd_week.csv',encoding='gbk') trace = [ go.Trace( x=df1['week'], # assign x as the dataframe column 'x' y=df1['净现金业绩'], name='净现金业绩' ), go.Trace( x=df1['week'], # assign x as the dataframe column 'x' y=df1['本期收款'], name='本期收款' ) ] layout = go.Layout( title='各周收款、净现金业绩', xaxis=dict(title='横坐标:周数'), yaxis=dict(title='金额(百万)') ) return {'data': trace, 'layout':layout}
def makeLineGraph( stockSymbol, Webster, currentInfo ): # Makes Line graph for both historic data (webster), current Stock Info (currentInfo) old_stdout = sys.stdout sys.stdout = open(os.devnull, "w") figure = obj.Scatter(y=Webster.High, x=Webster.index) # Line currentFigure = obj.Trace( y=currentInfo[0]['LastTradePrice'], x=currentInfo[0]['LastTradeDateTime'], line=dict(color=('rgb(0,0,0)'))) # Current Point Data data = [figure, currentFigure] py.plot(data, filename=stockSymbol + '_Line') sys.stdout.close() sys.stdout = old_stdout
"../data2/sauer/2.csv", "../data2/sauer/3.csv", "../data2/sauer/4.csv", "../data2/sauer/5.csv", "../data2/schale_morgen/1.csv", "../data2/schale_morgen/2.csv", "../data2/schale_morgen/3.csv", "../data2/schale_morgen/4.csv", "../data2/schale_morgen/5.csv", ]) data = [ go.Trace( x=group.wavelength, y=group.power, name="{} - {}".format(key[0], key[1]) ) for key, group in input_data.groupby(["label", "reading"]) ] ply.plot(go.Figure(data=data)) sensor_data_avg = input_data\ .drop("reading", axis=1)\ .groupby(["label", "wavelength"])\ .mean()\ .reset_index()