Plot panda series in separate subplots using matplotlib

Question

Hoping to get some help please, I'm trying plot simulation data in separate subplots using pandas and matplotlib my code so far is:

import matplotlib.pylab as plt
import pandas as pd
fig, ax = plt.subplots(2, 3)
for i in range(2):
    for j in range(50, 101, 10):
        for e in range(3):
            Var=(700* j)/ 100
            Names1 = ['ig','M_GZ']
            Data1 = pd.read_csv('~/File/JTL_'+str(Var)+'/GZ.csv', names=Names1)
            ig = Data1['ig']
            M_GZ=Data1['M_GZ']
            MGZ = Data1[Data1.M_GZ != 0]
            ax[i, e].plot(MGZ['ig'][:4], MGZ['M_GZ'][:4], '--v', linewidth=1.75)
plt.tight_layout()
plt.show()

But the code gives me 6 duplicate copies of the same plot: enter image description here instead of each iteration of Var having its own plot, I've tried changing the loop and using different variations like:

fig = plt.figure()
for i in range(1, 7):
      ax = fig.add_subplot(2, 3, i)
            for j in range(50, 101, 10):                
                     Var=(700* j)/ 100
                     Names1 = ['ig','M_GZ']
                     Data1 = pd.read_csv('~/File/JTL_'+str(Var)+'/GZ.csv', names=Names1)
                     ig = Data1['ig']
                     M_GZ=Data1['M_GZ']
                     MGZ = Data1[Data1.M_GZ != 0]
                     ax.plot(MGZ['ig'][:4], MGZ['M_GZ'][:4], '--v', linewidth=1.75)
plt.tight_layout()
plt.show()

but that changes nothing I still get the same plot as above. Any help would be appreciated, I'm hoping that each subplot contains one set of data instead of all six

This is a Link to one of the Dataframes each subdirectory ~/File/JTL_'+str(Var)+'/ contains a copy of this file there are 6 in total

@user3645626 I've added a link to an example of how one of the Data frames would look like would that be enough or do you think all 6 would be more helpful? — user3191569
– user3191569, Commented Feb 5, 2015 at 11:19

knightofni · Accepted Answer · 2015-02-06 03:36:21Z

2

The problem is in your loop

for i in range(2):  # Iterating rows of the plot
    for j in range(50, 101, 10): # Iterating your file names
        for e in range(3): # iterating the columns of the plot

The end result is that you iterate all the columns for each file name

For it two work, you should have only two nesting levels in your loop. Potential code (updated) :

import matplotlib.pylab as plt
import pandas as pd
fig, ax = plt.subplots(2, 3)
for row in range(2):
    for col in range(3):
        f_index = range(50, 101, 10)[row+1 * col]
        print row, col, f_index
        Var=(700* f_index)/ 100
        Names1 = ['ig','M_GZ']
        Data1 = pd.read_csv('~/File/JTL_'+str(Var)+'/GZ.csv', names=Names1)
        ig = Data1['ig']
        M_GZ=Data1['M_GZ']
        MGZ = Data1[Data1.M_GZ != 0]
        ax[row, col].plot(MGZ['ig'][:4], MGZ['M_GZ'][:4], '--v',linewidth=1.75)
plt.tight_layout()
plt.show()

edited Feb 6, 2015 at 3:36

answered Feb 5, 2015 at 5:38

knightofni

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2 Comments

user3191569 Over a year ago

I tried your suggestion but I keep getting IndexError: index 3 is out of bounds for axis 1 with size 3 however when i change the line fig, ax to fig, ax = plt.subplots(2, 6) a plot is produced where the top row is exactly the same as the bottom row, when print row, col is added I get 0,0 0,1 0,2 0,3 instead the loop should be giving 0,0 0,1 0,2 1,0 1,1 1,2

knightofni Over a year ago

haha, sorry, i read too fast, for some reason i thought there was only 3 files. Have a look at the updated code.

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