[FIXED] Loop n-times, adding a new y-data series (different scale) to the same x-axis plot (using ax.twinx())

Issue

I'm trying to follow these examples,

Using loops to create multiple matplotlib graphs with dual y-axes

How do you plot two different y-axes using a loop with twinx?

How to use "ax.twinx()" with a loop?

however they don't work for different reasons , for example, df2 or region is not defined, or no answers/comments. My goal is to read a csv file, and on the fly add columns to a single plot (They all share the same x-axis, but have different y-axes scales/ranges.)

But when I try to programmatically generate the axes, it has an error because I haven't declared an array of axes to hold the return of twinx():

import matplotlib.pyplot as plt

#Single canvas and axes in which to put all the data
fig, ax = plt.subplots(1, 1)

#Generate additional Y-axes and save into array for easy access
for i in range (5):
    axIdx [ i ] = ax.twinx()    #ERROR
        
#Loop thru each axis and add csv data, positioning the legend and spines appropriately
time = [0,1,2,3]
y1   = [10,11,12,13]
axIdx[0].plot(time,y1,color="green", label='y1')
axIdx[0].legend(loc='upper right', bbox_to_anchor=(1.2, 1),  ncol=2, borderaxespad=0)
axIdx[0].set_ylabel("y1",color="black")
axIdx[0].tick_params(axis='y',colors="black")
axIdx[0].spines['right'].set_color("black")      

y2   = [7.3,1.2,3.14,88.8]
axIdx[1].plot(time,y2,color="red", label='y2')
axIdx[1].legend(loc='upper right', bbox_to_anchor=(1.4, 1),  ncol=2, borderaxespad=0)
axIdx[1].set_ylabel("y1",color="black")
axIdx[1].tick_params(axis='y',colors="black")
axIdx[1].spines['right'].set_color("black")     

plt.tight_layout()
plt.show()
 

How is this normally done? I tried using a dictionary to import the csv data, but I still need a way to programmatically loop thru the axes.

Solution

You have problem with basic knowledge about Python.

You didn't create list.

To use axIdx[i] first you have to create list axIdx = [...] (with correct number of items).

axIdx = [None, None, None, None, None]   # list with 5 elements 

# Generate additional Y-axes and save into array for easy access
for i in range(5):
    axIdx[i] = ax.twinx() 

But it is more popular to create empty list and use append() to add items.

axIdx = []   # empty list

# Generate additional Y-axes and save into array for easy access
for i in range(5):
    axIdx.append( ax.twinx() )

---

Full working code:

import matplotlib.pyplot as plt

# Single canvas and axes in which to put all the data
fig, ax = plt.subplots(1, 1)

#axIdx = [None, None, None, None, None]

# Generate additional Y-axes and save into array for easy access
#for i in range (5):
#    axIdx[i] = ax.twinx()
        
axIdx = []

#Generate additional Y-axes and save into array for easy access
for i in range (5):
    axIdx.append(ax.twinx())
        
# Loop thru each axis and add csv data, positioning the legend and spines appropriately
time = [0,1,2,3]

y1   = [10,11,12,13]
axIdx[0].plot(time,y1,color="green", label='y1')
axIdx[0].legend(loc='upper right', bbox_to_anchor=(1.2, 1),  ncol=2, borderaxespad=0)
axIdx[0].set_ylabel("y1",color="black")
axIdx[0].tick_params(axis='y',colors="black")
axIdx[0].spines['right'].set_color("black")      

y2   = [7.3,1.2,3.14,88.8]
axIdx[1].plot(time,y2,color="red", label='y2')
axIdx[1].legend(loc='upper right', bbox_to_anchor=(1.4, 1),  ncol=2, borderaxespad=0)
axIdx[1].set_ylabel("y1",color="black")
axIdx[1].tick_params(axis='y',colors="black")
axIdx[1].spines['right'].set_color("black")     

plt.tight_layout()
plt.show()

Answered By - furas