how to plot a graph using matplotlib
from matplotlib import pyplot as plt
plt.plot([0, 1, 2, 3, 4, 5], [0, 1, 4, 9, 16, 25])
plt.show()how to plot a graph using matplotlib
from matplotlib import pyplot as plt
plt.plot([0, 1, 2, 3, 4, 5], [0, 1, 4, 9, 16, 25])
plt.show()how to plotting points on matplotlib
import matplotlib.pyplot as plt
import numpy as np
data = np.random.rand(1024,2)
plt.scatter(data[:,0],data[:,1])
plt.show()
// Don't be
// fooled by this simplicity— plt.scatter() is a rich command.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()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()Copyright © 2021 Codeinu
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