import numpy as np import matplotlib.pyplot as plt from matplotlib.patches import Polygon def func(x): return (x - 3) * (x - 5) * (x - 7) + 85 a, b = 2, 9 # integral limits x = np.linspace(0, 10) y = func(x) fig, ax = plt.subplots() plt.plot(x, y, 'r', lin...
log10(population), cmap='viridis', s=area, linewidth=0, alpha=0.5) plt.axis('equal') plt.xlabel('longitude') plt.ylabel('latitude') plt.colorbar(label='log_{10}(population)') plt.clim(3, 7) # Here we create a legend: # we'll plot empty lists with the desired size and label...
ax[1].plot(well_data['GR'],well_data['DEPTH'],color='green')ax[1].set_title('GR (Gamma Ray)')ax[1].set_xlim(0,150)# Typical scaleforGRax[1].grid()# PlottingDTon the thirdtrack(excludingNaNvalues) ax[2].plot(well_data['DT'].dropna(),well_data['DEPTH'].loc[well_data['...
# plt.grid(True)plt.grid(False)# Legendforthe plot.plt.legend()# Saving the figure on disk.'dpi'and'quality'can be adjusted according to the required image quality.plt.savefig('Line_plot.jpeg',dpi=400,quality=100)# Displays the plot.plt.show()# Clears the current figure contents.plt....
A gradient-filled area plot is like coloring the space under a curve with a smooth transition of colors. It helps emphasize the shape of the curve and how it changes.ExampleIn the following example, we are creating a smooth curve representing the sine function using numpy. We are then ...
months in 2025. Thenp.cumsumfunction computes the running total of monthly sales, transforming [20, 25, 30, 28, 35] into [20, 45, 75, 103, 138]. Theplt.fill_betweenfunction then fills the area under this cumulative curve, with a line plot overlaying it to show the growth trajectory....
plt.plot_date() 绘制数据日期 Matplotlib绘制直方图,使用plt.hist()这个函数,函数参数如下: Matplotlib.pyplot.hist(x,bins=None,range=None,density=None,weights=None, cumulative=False, bottom=None, histtype='bar', align='mid', orientation='vertical', rwidth=None, log=False, color=None, label=None...
[.5, y, w, h]) # Resize & move plot to the lower right (South East; SE) # corner of the original Axes area ax2.set_aspect('equal', anchor='SE') ax2.set_title('equal aspect\nSE anchor') ax3 = fig.add_axes([.75, y, w, h]) # Resize & move plot to the lower right...
我希望在type的基础上绘制面积图,也就是说,对于日期,如果type=1, 2, 3,我将分别使用颜色gray、lightpink和skyblue。 我怎么能这么做?谢谢 预期的绘图如下所示: Reference code: year_n_1 = [1.5, 3, 10, 13, 22, 36, 30, 33, 24.5, 15, 6.5, 1.2] ...
In order to plot an entire region and not just a rectangular or circular area, set radius=False importprettymapsplot=prettymaps.plot('Bom Fim, Porto Alegre, Brasil',radius=False, ) You can access layers's GeoDataFrames directly like this: ...