How to plot various data in different frequencies in the same graph?

Question

My problem is to plot two different csv files with different frequencies and value intervals. I just want to make a comparison on heartRate and motionData in unit time.

I use matplotlib to achieve that.

Following code gives me such a graph:

import numpy as np 
import pandas 
import matplotlib.pyplot as plt 

# fake data 
x = np.genfromtxt('/Users/yusufkamilak/Desktop/motionData.csv', delimiter=',', skip_header=10,
                     skip_footer=0, names=['TimeStamp', 'AccelerationX']) 
y = np.genfromtxt('/Users/yusufkamilak/Desktop/heartRate.csv', delimiter=',', skip_header=2,
                     skip_footer=0, names=['TimeStamp', 'Value'])

# data frames 
xdf = pandas.DataFrame(x) 
ydf = pandas.DataFrame(y) 

# plot x data, get an MPL axes object 
ax = xdf.plot() 

# plot y data, using the axes already created 
ydf.plot(ax=ax) 



plt.show() 

Heart Rate frequency should be extended to motionData

This is how HeartRate normally looks in ~1/6 Hz

Since motionData has over 60,000 lines of values, heartRate looks as if it never exists. But time intervals of both values are the same. Getting heart rate in each 5-6 seconds and motionData 10 times per second.

Any help will be appreciated, I've checked many questions before asking that but I couldn't find one that helps me to solve my problem. Thanks!

Answer 1

You need some data for the x-axis as well.
Either your dataframe already has this data in a column or you need to create that column. Then

ax = xdf.plot(x='TimeStamp', y=['AccelerationX', 'AccelerationY'])
ydf.plot(x='TimeStamp', y='Value', ax=ax)

would show all curves with what TimeStamp is on the x axis.

Using linear interpolation is sure possible, but may not make much sense, since the lines of a lineplot do exactly that: they connect two points linearly.