Python: Generate pandas plot in function but do not show it

Question

I want to plot columns of a pandas dataframe by a calling a function. A data frame is passed to a function and manipulated. A plot and the manipulated data frame is returned:

from matplotlib import pyplot as plt
import pandas as pd

def custom_plot(df):
    tmp = df.plot(kind = 'bar')
    plt.legend(title = "Test")
    return  [tmp,df]

df = pd.DataFrame( {'x' : [1,2,3]})
p,d = custom_plot(df)

Executing this code displays this plot although I do not want it to be displayed:

I want to plot the returned object p in the Jupyter notebook by calling something like p.show(). There are 2 problems:

The plot is always displayed when custom_plot() is called although I do not want it to be plotted.
When I want to plot p by calling p.show() this does not work. I am told AttributeError: 'AxesSubplot' object has no attribute 'show'

How can this behavior be achieved?

Why do you need the plot data, when you can call df.plot() wherever you need and get the plot? If you want to plot in a specific figure/subplot, that can be achieved using the ax argument in pandas' plot — gionni
– gionni, Commented Sep 6, 2021 at 7:28
I need this function because this plot is generated 20 times with different data frames. This minimal example does not represent the complexity of the problem at all. — HOSS_JFL
– HOSS_JFL, Commented Sep 6, 2021 at 8:22
The link you posted does not help. None of the suggestions there change the output. — HOSS_JFL
– HOSS_JFL, Commented Sep 6, 2021 at 8:23
@HOSS_JFL Oh sorry given a wrong link, I have deleted above comment as well. Please check stackoverflow.com/questions/30878666/… — Rinshan Kolayil
– Rinshan Kolayil, Commented Sep 6, 2021 at 8:33

René · Accepted Answer · 2021-09-06 08:27:00Z

1

Perhaps this (partly) solves the issue:

from matplotlib import pyplot as plt
import pandas as pd

def custom_plot(df):
    tmp = df.plot(kind = 'bar')
    plt.legend(title = 'Test')
    fig = tmp.get_figure()
    plt.close()
    return fig, df

df = pd.DataFrame( {'x' : [1, 2, 3]})

p, d = custom_plot(df)

Closing the figure prevents it from showing. You can use p without the .show() to display the figure.

edited Sep 6, 2021 at 8:27

answered Sep 6, 2021 at 8:15

René

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Comments

Rinshan Kolayil · Accepted Answer · 2021-09-06 09:01:27Z

0

You can try using plt.ioff()

from matplotlib import pyplot as plt
import pandas as pd

def custom_plot(df):
    plt.ioff()
    df.plot(kind = 'bar')
    plt.legend(title = "Test")
    return  [plt,df]

df = pd.DataFrame( {'x' : [1,2,3]})
p,d = custom_plot(df)

p.show()

Output (There was no image after the first cell)

EDIT

from matplotlib import pyplot as plt
import pandas as pd
def custom_plot(df):
    f1 = plt.figure()
    ax1 = f1.add_subplot(111)
    df.plot(kind = 'bar',ax=ax1)
    ax1.legend(title='TEST')
    plt.close()
    return  [f1,df]

df = pd.DataFrame( {'x' : [1,2,3]})
p,d = custom_plot(df)

Now you can call p as well instead of p.show()

edited Sep 6, 2021 at 9:01

answered Sep 6, 2021 at 8:12

Rinshan Kolayil

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2 Comments

HOSS_JFL Over a year ago

Thank you, but in my case the plot is shown also when p.show() is not called. This is the case both in Jupyter and Spyder. I do not know why.

Rinshan Kolayil Over a year ago

@HOSS_JFL Please check the updated answer, also you can try to restart the kernel

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