Hello everyone. My matplotlib figure is too big, and I can’t change its size. I tried passing the figsize parameter both when creating the fig object and in the st.pyplot method. The figure size does not change.
Reproduce:
import matplotlib.pyplot as plt
fig, ax = plt.subplots(figsize=(5, 5))
st.pyplot(fig, figsize=(5, 5))I’d like to know this too, it’s frustrating to not have control over this.
Hi @Zylatis, I’m sorry to hear you’re having trouble with resizing matplotlib figures. 
Could you share a working example or code a snippet where you are trying unsuccessfully to resize a figure? We could try figuring it out together.
In the meantime, I put together a minimal example based on a matplotlib tutorial. I vary the values of the width and height parameters in figsize using sliders:
import streamlit as st
import matplotlib.pyplot as plt
cat = ["bored", "happy", "bored", "bored", "happy", "bored"]
dog = ["happy", "happy", "happy", "happy", "bored", "bored"]
activity = ["combing", "drinking", "feeding", "napping", "playing", "washing"]
width = st.sidebar.slider("plot width", 1, 25, 3)
height = st.sidebar.slider("plot height", 1, 25, 1)
fig, ax = plt.subplots(figsize=(width, height))
ax.plot(activity, dog, label="dog")
ax.plot(activity, cat, label="cat")
ax.legend()
st.pyplot(fig)
Click on the GIF below to see resizing in action:
Happy Streamlit-ing! 
Snehan
According to the streamlit docs we can only pass key word arguments for Matplotlib’s savefig function to st.pyplot.
However, this table indicates savefig does not have a figsize key word.
Here is a code snippet that demonstrate where resizing works (i.e. tabular data) and where it does not work (i.e. array data)
EDIT: I just discovered st.image, I guess probably should use that for arrays in streamlit. Will leave matplotlib array example below…
import streamlit as st
import matplotlib.pyplot as plt
import numpy as np
# tabular data
table = {
'cat':["bored", "happy", "bored", "bored", "happy", "bored"],
'dog':["happy", "happy", "happy", "happy", "bored", "bored"],
'activity':["combing", "drinking", "feeding", "napping", "playing", "washing"]
}
# array data
array = np.zeros((100,100))
# visualization algorithms
def display_table(table, figsize=(5,5)):
"example of displaying a table in streamlit"
fig, ax = plt.subplots(figsize=figsize)
ax.plot(table['activity'], table['dog'], label="dog")
ax.plot(table['activity'], table['cat'], label="cat")
st.pyplot(fig)
def display_array(array, figsize=(5,5)):
"example of displaying an array in streamlit"
fig, ax = plt.subplots(figsize=figsize)
_ = ax.imshow(array)
st.pyplot(fig)
# this works
display_table(table, figsize=(10,5))
# this does not work properly
display_array(array, figsize=(2,4))
Here is an example displaying a numpy array using st.image
import streamlit as st
import matplotlib
import numpy as np
def display_array(arr, colormap='viridis', width=None):
""" display a 2D array in streamlit with a color map"""
# color map
cm = matplotlib.cm.get_cmap(colormap)
# rgb visualization
rgb = cm(arr)
# display in app
st.image(rgb, width=width)
# numpy array
arr = np.random.rand(300,300)
# display numpy array in streamlit app
display_array(arr)
One thing to note is that even in @snehankekre 's excellent example showing matplotlib resizing in action, the final displayed width can’t be changed. The image always fills 100% of the width allotted in the column it lives in. Is there any way around that so that i.e. a 3-inch wide image is actually 3 inches wide instead of being widened to 100% after matplotlib’s rendering of the image?
Hey @benlindsay, 
Thanks for your patience! Here’s a workaround with 2 additional lines of code. Instead of using st.pyplot, you can convert the matplotlib.figure.Figure object into an image that’s held temporarily in memory, and then display it using st.image like so:
import streamlit as st
import matplotlib.pyplot as plt
from io import BytesIO
cat = ["bored", "happy", "bored", "bored", "happy", "bored"]
dog = ["happy", "happy", "happy", "happy", "bored", "bored"]
activity = ["combing", "drinking", "feeding", "napping", "playing", "washing"]
width = st.sidebar.slider("plot width", 0.1, 25., 3.)
height = st.sidebar.slider("plot height", 0.1, 25., 1.)
fig, ax = plt.subplots(figsize=(width, height))
ax.plot(activity, dog, label="dog")
ax.plot(activity, cat, label="cat")
ax.legend()
buf = BytesIO()
fig.savefig(buf, format="png")
st.image(buf)
Happy Streamlit-ing!
Snehan
Awesome, thanks for the workaround! Is there a reason st.image respects the image width but st.pyplot doesn’t, or is that something I could submit an issue for? It would be nice to either have a width kwarg in st.pyplot just like st.image and/or change st.pyplot’s default behavior to not expand to 100% width, just like st.image
I agree! Feel free to submit a new issue 
This worked for me very well. You can also change the position of the graph by playing around with the columns.
col1, col2, col3, col4, col5= st.columns([1,1, 2, 1, 1])
with col3:
df = pd.read_csv('dataframe.csv')
fig, ax = plt.subplots(figsize=(5,4))
ax = plt.plot(x, y)
plt.xticks(rotation = 45)
st.pyplot(fig)
Is this workaround still supposed to work? It doesn’t work for me on Streamlit 1.11. 
I am trying to display a figure object via st.pyplot or st.image within st.expander and the image always gets resized to the full width of the expander.
Edit: If I remove the expander the image is still exanded to the surrounding column width.
Edit 2: Also doesn’t work if I remove both the surrounding expander and the column.
Based on @gulcinvardar 's clever workaround, here’s arbitrary resizing:
input_resize = st.slider("Resize", min_value=0.1, max_value=1.0, step=0.05, value=1.0)
resize = input_resize * 0.999
col1, _ = st.columns((resize / (1 - resize), 1), gap="small")
col1.pyplot(fig)
when fig, axs = plt.subplots(3, 2,figsize=(width, height) )
The parameters are no use again