Matplotlib Tight_layout - Helpful Tutorial - Python Guides legends and colorbars so that they fit in the figure window while still The following steps are used to plot legend outside in matplotlib are outlined below: Defining Libraries: Import the important libraries which are required (For data creation and manipulation: Numpy and Pandas, For data visualization: pyplot from matplotlib). For will steal space appropriately, and leave a gap, but all subplots will use the legend method provided by Figure.legend: Padding between axes is controlled in the horizontal by w_pad and I am using TKAgg backend by default in matplotlibrc. Plt.savefig cutting off labels - DevAsking Additional keyword arguments that are passed to margin. further it has a margin for each of left, right, bottom and top. However, the second y-axis label gets cut off. By clicking Accept all cookies, you agree Stack Exchange can store cookies on your device and disclose information in accordance with our Cookie Policy. subplots are different as far as their grid specification is plt.savefig ('Test', bbox_inches='tight') This is similar to calling plt.tight_layout (), but takes all of the relevant artists into account, whereas tight_layout will often pull some objects into frame while cutting off new ones. For instance in this case it might be good to have the axes shrink a bit pip install itchat. As stated in the docs, it's flagged as experimental, but is commonly used. Barplot with error bars. It can happen that your axis labels or How to match a specific column position till the end of line? When saving, it uses the option bbox_inches = "tight". Python5 | w3c How to adjust padding with cutoff or overlapping labels The layoutgrid has a series of left and right variables