I have some csv data in the following format.

Ln    Dr    Tag Lab    0:01    0:02    0:03    0:04    0:05    0:06    0:07    0:08   0:09
L0   St     vT  4R       0       0       0       0       0      0        0       0      0
L2   Tx     st  4R       8       8       8       8       8      8        8       8      8
L2   Tx     ss  4R       1       1       9       6       1      0        0       6      7

I want to plot a timeseries graph using the columns (Ln , Dr, Tg,Lab) as the keys and the 0:0n field as values on a timeseries graph.

I have the following code.

import pandas as pd
import matplotlib.pyplot as plt
import numpy as npplt.ylabel('time')
plt.xlabel('events')plt.grid(True)
plt.xlim((0,150))
plt.ylim((0,200))a=pd.read_csv('yourfile.txt',delim_whitespace=True)
for x in a.iterrows():x[1][4:].plot(label=str(x[1][0])+str(x[1][1])+str(x[1][2])+str(x[1][3]))plt.legend()
fig.savefig('test.pdf')

I have only shown a subset of my data here. I have around 200 entries (200 rows) in my full data set. the above code plots all graphs in a single figure. I would prefer each row to be plotted in a separate graph.

Use subplot()

import matplotlib.pyplot as pltfig = plt.figure()plt.subplot(221) # 2 rows, 2 columns, plot 1
plt.plot([1,2,3])plt.subplot(222) # 2 rows, 2 columns, plot 2
plt.plot([3,1,3])plt.subplot(223) # 2 rows, 2 columns, plot 3
plt.plot([3,2,1])plt.subplot(224) # 2 rows, 2 columns, plot 4
plt.plot([1,3,1])plt.show()fig.savefig('test.pdf')

https://matplotlib.org/stable/api/_as_gen/matplotlib.pyplot.subplot.html#matplotlib.pyplot.subplot