i have a 3 df's fro 3 machines(Machine1/Machine2/Machine3) .Each df with 3 columns. Day-shift and production. sample df:
Day-Shift Production Quality
Day 11-01 20 A
Night 11-01 45 A
Day 11-02 65 A
Night 11-02 12 B
Day 11-03 97 B
my code:
import numpy as np
import pandas as pd
from plotly.offline import iplot
import plotly.graph_objects as go
# Machine1: Create numpy arrays of values for the given quality.
b1 = np.where(df1['Quality'] == 'A', df1['Production'], None)
# Machine2: Same as above.
b2 = np.where(df2['Quality'] == 'A', df2['Production'], None)
# Machine3: Same as above.
b3 = np.where(df3['Quality'] == 'A', df3['Production'], None)
# Setup.
t = []
line = ['solid']
Quality = ['A']
t.append({'x': df1['Day-Shift'],
'y': b1,
'name': f'Machine1',
'line': {'color': 'red',
'dash': line[0]}})
t.append({'x': df2['Day-Shift'],
'y': b2,
'name': f'Machine1',
'line': {'color': 'blue',
'dash': line[0]}})
t.append({'x': df3['Day-Shift'],
'y': b3,
'name': f'Machine1',
'line': {'color': 'yellow',
'dash': line[0]}})
# Plot the graph.
layout = go.Layout(
title='Production meterage of Machine1/Machine2/Machine3 for Quality A',
template='plotly_dark',
xaxis=dict(
autorange=True
),
yaxis=dict(
autorange=True
)
)
fig = go.Figure(data=t, layout=layout)
iplot(fig)
Chart I got:
I created one line chart for all three machines. But the line chart looks messy. Need to do smoothing. I tried with gaussian_filter1d. But It does not work for me.
I think the best way of representing your data is with a histogram. I don't know much of ploty ofline module but you can do it (easily) with matplotlib.
Here is some documentation from matplotlib https://matplotlib.org/3.1.1/api/_as_gen/matplotlib.pyplot.hist.html
and an example: https://matplotlib.org/3.1.1/gallery/statistics/hist.html
and an example with multiply datasets for 1 chart https://matplotlib.org/3.1.1/gallery/statistics/histogram_multihist.html