def plot_product(name):
new_data, date = readFile()
data = [go.Scatter(x=date, y=new_data[name], mode='lines+markers')]
layout = go.Layout(
title=go.layout.Title(
text='Historical Trend Graph for {}'.format(name),
xref='paper',
x=0),
xaxis=go.layout.XAxis(title=go.layout.xaxis.Title(
text='Months',
font=dict(family='Roboto', size=18, color='#7f7f7f'))),
yaxis=go.layout.YAxis(title=go.layout.yaxis.Title(
text='Sale Qty',
font=dict(family='Roboto', size=18, color='#7f7f7f'))))
fig = go.Figure(data=data, layout=layout)
fig.layout.plot_bgcolor = 'rgba(230, 236, 245, 0.1)'
fig.layout.paper_bgcolor = 'rgba(230, 236, 245, 0.1)'
graph = json.dumps(fig, cls=plotly.utils.PlotlyJSONEncoder)
return graph
import json
import plotly
import plotly.graph_objs as go
import matplotlib.pyplot as plt
from statsmodels.tsa.seasonal import seasonal_decompose
from processing import readFile
new_data, date = readFile()
def plot_trend(name):
a = seasonal_decompose(new_data[name], model="add")
# plot = a.seasonal.plot();
# print(a.seasonal.values)
data = [go.Scatter(x=date, y=a.trend.values, mode='lines+markers')]
layout = go.Layout(
title=go.layout.Title(text='Trend Graph for {}'.format(name),
xref='paper',
x=0),
xaxis=go.layout.XAxis(title=go.layout.xaxis.Title(
text='Months',
font=dict(family='Roboto', size=18, color='#7f7f7f'))),
yaxis=go.layout.YAxis(title=go.layout.yaxis.Title(
text='Sale Qty',
font=dict(family='Roboto', size=18, color='#7f7f7f'))))
fig = go.Figure(data=data, layout=layout)
fig.layout.plot_bgcolor = 'rgba(230, 236, 245, 0.1)'
fig.layout.paper_bgcolor = 'rgba(230, 236, 245, 0.1)'