Example 1: matplotlib plot
import matplotlib.pyplot as plt
fig = plt.figure(1)
plt.title("Y vs X", fontsize='16')
plt.plot([1, 2, 3, 4], [6,2,8,4])
plt.xlabel("X",fontsize='13')
plt.ylabel("Y",fontsize='13')
plt.legend(('YvsX'),loc='best')
plt.savefig('Y_X.png')
plt.grid()
plt.show()
Example 2: show graph matplotlib axes
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
df = pd.read_csv("filesc/file1.csv")
df.head()
BBox = ((df.x.min(), df.x.max(), df.y.min(), df.y.max()))
ruh_m = plt.imread('map.png')
print(BBox)
fig, ax = plt.subplots(figsize = (8,7))
ax.scatter(df.x, df.y, zorder=1, alpha= 0.2, c='b', s=10)
ax.set_title('Plotting Spatial Data on Map')
ax.set_xlim(BBox[0],BBox[1])
ax.set_ylim(BBox[2],BBox[3])
ax.imshow(ruh_m, zorder=0, extent = BBox, aspect= 'equal')
plt.show()
Example 3: plot using matplotlib
import matplotlib.pyplot as plt
plt.plot([1, 2, 3, 4])
plt.ylabel('some numbers')
plt.show()
Example 4: matplotlib plot
>>> rng = np.arange(50)
>>> rnd = np.random.randint(0, 10, size=(3, rng.size))
>>> yrs = 1950 + rng
>>> fig, ax = plt.subplots(figsize=(5, 3))
>>> ax.stackplot(yrs, rng + rnd, labels=['Eastasia', 'Eurasia', 'Oceania'])
>>> ax.set_title('Combined debt growth over time')
>>> ax.legend(loc='upper left')
>>> ax.set_ylabel('Total debt')
>>> ax.set_xlim(xmin=yrs[0], xmax=yrs[-1])
>>> fig.tight_layout()