Without setting figure size post-plotting, the resulting figure is too small: import random, pandas as pdįrom import seasonal_decomposeĭata = pd.Series(, index=pd. Plt.gcf().set_size_inches(15,5) # set figure size afterwardsĪnother example where a time series decomposition plot is handled by statsmodels. This data is from the King County House Sales dataset. In particular, > fig, ax plt.subplots (1, 1) is essentially equivalent to > fig plt.figure () > ax fig.addsubplot (1, 1) But plt. plt.subplots(figsize(6, 2)) plt.text(0.5, 0.5, 600px x 200px, textkwargs) plt. To broaden the plot, set the width greater than 1. When creating plots using Matplotlib, you get a default figure size of 6.4 for the width and 4.8 for the height (in inches). So, the syntax is something like this- (figsize (float,float)) Parameters- Width Here, we have to input the width in inches. For example, here is a figure containing six subplots. plt.subplots () is basically a (very nice) shortcut for initializing a figure and subplot axes. Also, figsize is an attribute of figure () class of pyplot submodule of matplotlib library. pyplot.subplots creates a figure and a grid of subplots with a single call, while providing reasonable control over how the individual plots are created. Ys = for _ in range(2)] for _ in range(2)] Using subplots simply means putting more than one plot in the same figure. If for whatever reason, the figsize of subplots needs to be changed after plotting (perhaps because its creation is handled by an external library such as statsmodels etc.), then you can call set_size_inches() on the figure object to set the figure size.
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