Matplotlib Default Title Font Size It seems that the set xticks is not working in log scale from matplotlib import pyplot as plt fig1 ax1 plt subplots ax1 plot 10 100 1000 1 2 3 ax1 set xscale log
Thanks I ve edited it But maybe you re right and I m just misunderstanding something with how matplotlib places these legends in general do you know which corner of the legend is placed In a matplotlib figure how can I make the font size for the tick labels using ax1 set xticklabels smaller Further how can one rotate it from horizontal to vertical
Matplotlib Default Title Font Size
Matplotlib Default Title Font Size
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Python matplotlib graph colorbar colormap edited Oct 5 2023 at 16 04 Trenton McKinney 63k 41 169 205 Adding a y axis label to secondary y axis in matplotlib Asked 12 years 4 months ago Modified 3 years 7 months ago Viewed 622k times
Given that today was not available when this question was made lots of people use Jupyter Notebook as python console there is an extremely easy way to save the plots as matplotlib inline sets the backend of matplotlib to the inline backend With this backend the output of plotting commands is displayed inline within frontends like the Jupyter
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30 This worked at least in matplotlib version 2 2 2 plt axis None None 0 100 Probably this is a nice way to set up for example xmin and ymax only etc I have used Matplotlib to plot lines on a figure Now I would now like to set the style specifically the marker for individual points on the line How do I do this To clarify my
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It seems that the set xticks is not working in log scale from matplotlib import pyplot as plt fig1 ax1 plt subplots ax1 plot 10 100 1000 1 2 3 ax1 set xscale log
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Thanks I ve edited it But maybe you re right and I m just misunderstanding something with how matplotlib places these legends in general do you know which corner of the legend is placed
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Matplotlib Default Title Font Size - matplotlib inline sets the backend of matplotlib to the inline backend With this backend the output of plotting commands is displayed inline within frontends like the Jupyter
