Plot a graph by reading coulmns from CSV

Question

I have a csv file which contains four columns. The first column in time, the second, third and fourth columns are Accelerometer readings. I want to plot Time on X-Axis and the Accelerometer reading on Y-Axis.
Sample Data:

0   1.0969  9.7721  0.614 
20  1.1146  9.7501  0.7444 
40  1.1146  9.7501  0.7444 
60  1.0124  9.7151  0.7169 
79  1.0124  9.7151  0.7169 
100 1.0927  9.7324  0.7356
120 1.0927  9.7324  0.7356 

Here is what I have so far.

from numpy import genfromtxt
import csv
import matplotlib.pyplot as plt
#import numpy as np

# Open the desired file for reading
f = open('walk-shoe.csv', "rb")

# create a object of csv class and read the file
# use ',' as a delimiter 
reader = csv.reader(f, delimiter=',')

time_row = 0
accel_1_row = 0
accel_2_row = 0
accel_3_row = 0

time = []
accel_1 = []
accel_2 = []
accel_3 = []

# create a list of 'Time in ms'
for row in reader: 
    # Skip the first row
    time_row = time_row + 1
if time_row == 1:
    continue
time.append(row[0])
accel_1.append(row[1])
accel_2.append(row[2])
accel_3.append(row[3])

# print the contents of the list
# print time
#print accel_1
#print accel_2
#print accel_3

# append all the list accelerometer list together
final_accel = []
final_accel.append(accel_1)
final_accel.append(accel_2)
final_accel.append(accel_3)

#print final_accel

# plot the graph
for i in range(len(final_accel)):
    plt.plot(time,[pt[i] for pt in final_accel],label = 'id %s'%i)
plt.legend()
plt.show()

I want to plot all the sensor readings on one graph on y axis and time in x axis

Answer 1

You seem to be importing numpy in the code you give, therefore I will take that to mean that library is available to you. Numpy lets you read in data very easily using numpy.loadtxt().

You can then create a for loop which goes through columns 1 to 3 and plots data against column 0 (time).

import numpy as np
import matplotlib.pyplot as plt

data = np.loadtxt('walk-shoe.csv', delimiter=',', dtype=float)
print (data)
#[[   0.        1.0969    9.7721    0.614 ]
# [  20.        1.1146    9.7501    0.7444]
# [  40.        1.1146    9.7501    0.7444]
# [  60.        1.0124    9.7151    0.7169]
# [  79.        1.0124    9.7151    0.7169]
# [ 100.        1.0927    9.7324    0.7356]
# [ 120.        1.0927    9.7324    0.7356]]

for i in range(1,data.shape[1]):
    plt.plot(data[:,0], data[:,i], label='id %s' %i)

plt.legend()
plt.show()