how to represent data in a graph using matplotlib plt.plot(df) by smoothening the curves?

Question

this is my question,can someone help

the second picture is my question and the first picture is what i was able to day with the following code. how can i plot graph using matplotlib as in the question?

enter code here

import matplotlib.pyplot as plt
%matplotlib inline
import numpy as np
import pandas as pd

maxi = [39, 41, 43, 47, 49, 51, 45, 38, 37, 29, 27, 25]
mini = [21, 23, 27, 28, 32, 35, 31, 28, 21, 19, 17, 18]
index=[i for i in range(0,len(maxi))]
list=[]
for i in range(0,len(maxi)):
   l=[]
   l.append(maxi[i])
   l.append(mini[i])
   l.append(index[i])
   list.append(l)

df=pd.DataFrame(list,columns=['maxi','mini','index'])
data=[tuple(df['maxi']),tuple(df['mini'])]


l=[]
for i in range(0,len(df.columns)-1):
   l.append(df.columns[i])


color=['r','b']
j=0
for y in l:
   plt.scatter(data=df,x='index', y=y, color=color[j])
   plt.plot(df[l[j]],color=color[j])
   j=j+1

Answer 1

If you're willing to use plotly, you can easily set up a figure using go.Figure() and go.Scatter(), and then set line = dict(shape='spline', smoothing= <factor>) where <factor> is a number between 0 and 1.3. From the docs you can also see that you'll have to set shape='spline' for this to take effect:

smoothing:

Parent: data[type=scatter].line Type: number between or equal to 0 and 1.3 Default: 1 Has an effect only if shape is set to "spline" Sets the amount of smoothing. "0" corresponds to no smoothing (equivalent to a "linear" shape).

Here's a very basic example:

Complete code:

# imports
import pandas as pd
import plotly.graph_objs as go

# data
df = pd.DataFrame({'value1':[10,40,20,5],
                   'value2':[20,30,10,10]})

# plotly setup
fig = go.Figure()

# value 1 with smoothing = 1.3
fig.add_trace(go.Scatter(x=df.index, y = df['value1'],
                          line = dict(shape='spline', smoothing= 1.3)
                          )
               )

# value 2 with smoothing = 0.8
fig.add_trace(go.Scatter(x=df.index, y = df['value2'],
                          line = dict(shape='spline', smoothing= 0.8)
                          )
               )

fig.show()