Axes from plt.subplots() is a "numpy.ndarray" object and has no attribute "plot"

Question

The information below may be superfluous if you are trying to understand the error message. Please start off by reading the answer by @user707650.

Using MatPlotLib, I wanted a generalizable script that creates the following from my data.

A window containing a subplots arranged so that there are b subplots per column. I want to be able to change the values of a and b.

If I have data for 2a subplots, I want 2 windows, each with the previously described "a subplots arranged according to b subplots per column".

The x and y data I am plotting are floats stored in np.arrays and are structured as follows:

The x data is always the same for all plots and is of length 5.
```
 'x_vector': [0.000, 0.005, 0.010, 0.020, 0.030, 0.040]
```
The y data of all plots are stored in y_vector where the data for the first plot is stored at indexes 0 through 5. The data for the second plot is stored at indexes 6 through 11. The third plot gets 12-18, the fourth 19-24, and so on.

In total, for this dataset, I have 91 plots (i.e. 91*6 = 546 values stored in y_vector).

Attempt:

import matplotlib.pyplot as plt

# Options:
plots_tot = 14 # Total number of plots. In reality there is going to be 7*13 = 91 plots.
location_of_ydata = 6 # The values for the n:th plot can be found in the y_vector at index 'n*6' through 'n*6 + 6'.
plots_window = 7 # Total number of plots per window.
rows = 2 # Number of rows, i.e. number of subplots per column.

# Calculating number of columns:
prim_cols = plots_window / rows
extra_cols = 0
if plots_window % rows > 0:
    extra_cols = 1
cols = prim_cols + extra_cols

print 'cols:', cols
print 'rows:', rows

# Plotting:
n=0
x=0
fig, ax = plt.subplots(rows, cols)
while x <= plots_tot:
    ax[x].plot(x_vector, y_vector[n:(n+location_of_ydata)], 'ro')
    if x % plots_window == plots_window - 1:
        plt.show() # New window for every 7 plots.
    n = n+location_of_ydata
    x = x+1

I get the following error:

cols: 4
rows: 2
Traceback (most recent call last):
  File "Script.py", line 222, in <module>
    ax[x].plot(x_vector, y_vector[n:(n+location_of_ydata)], 'ro')
AttributeError: 'numpy.ndarray' object has no attribute 'plot'

Importing numpy doesn't matter: matplotlib (pyplot) already does that behind the scenes, since it is a major dependency of matplotlib. — user707650
– user707650, Commented Jun 22, 2016 at 12:38
matplotlib and numpy really should work together here to throw a better error. This is one of those rare instances when I wish it was Matlab. :) — eric
– eric, Commented Dec 7, 2021 at 23:02

user707650 · Accepted Answer · 2016-06-22 12:37:16Z

If you debug your program by simply printing ax, you'll quickly find out that ax is a two-dimensional array: one dimension for the rows, one for the columns.

Thus, you need two indices to index ax to retrieve the actual AxesSubplot instance, like:

ax[1,1].plot(...)

If you want to iterate through the subplots in the way you do it now, by flattening ax first:

ax = ax.flatten()

and now ax is a one dimensional array. I don't know if rows or columns are stepped through first, but if it's the wrong around, use the transpose:

ax = ax.T.flatten()

Of course, by now it makes more sense to simply create each subplot on the fly, because that already has an index, and the other two numbers are fixed:

for x < plots_tot:
     ax = plt.subplot(nrows, ncols, x+1)

Note: you have x <= plots_tot, but with x starting at 0, you'll get an IndexError next with your current code (after flattening your array). Matplotlib is (unfortunately) 1-indexed for subplots. I prefer using a 0-indexed variable (Python style), and just add +1 for the subplot index (like above).

bluedroid · Accepted Answer · 2019-11-23 23:55:11Z

12

The problem here is with how matplotlib handles subplots. Just do the following:

fig, axes = plt.subplots(nrows=1, ncols=2)
for axis in axes:
    print(type(axis))

you will get a matplotlib object which is actually a 1D array which can be traversed using single index i.e. axis[0], axis[1]...and so on. But if you do

fig, axes = plt.subplots(nrows=2, ncols=2)
for axis in axes:
    print(type(axis))

you will get a numpy ndarray object which is actually a 2D array which can be traversed only using 2 indices i.e. axis[0, 0], axis[1, 0]...and so on. So be mindful how you incorporate your for loop to traverse through axes object.

answered Nov 23, 2019 at 23:55

bluedroid

3433 silver badges15 bronze badges

Comments

the Tin Man · Accepted Answer · 2020-04-21 22:45:28Z

2

The axes are in 2-d, not 1-d so you can't iterate through using one loop. You need one more loop:

 fig,axes=plt.subplots(nrows=2,ncols=2)
    plt.tight_layout()
    for ho in axes:
        for i in ho:
            i.plot(a,a**2)

This gives no problem but if I try:

for i in axes:
      i.plot(a,a**2)

the error occurs.

edited Apr 21, 2020 at 22:45

the Tin Man

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answered Apr 20, 2020 at 10:14

Devansh Chowdhury

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Comments

Cloud Cho · Accepted Answer · 2019-08-16 04:05:35Z

1

In case if you use N by 1 graphs, for example if you do like fig, ax = plt.subplots(3, 1) then please do likeax[plot_count].plot(...)

answered Aug 16, 2019 at 4:05

Cloud Cho

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