import numpy as np
import matplotlib
import matplotlib.pyplot as plt
from dsutil.plotting import add_grid
from platform import python_version
python_version(), np.__version__,matplotlib.__version__
('3.6.9', '1.19.0', '3.2.2')
import matplotlib.pyplot as plt
import numpy as np
np.random.seed(42)
plt.clf()
# generate sample data for this example
xs = [1,2,3,4,5,6,7,8,9,10,11,12]
ys=np.random.normal(loc=10000,size=12, scale=20000.55) + 100000.05
# plot the data
plt.bar(xs,ys)
# after plotting the data, format the labels
current_values = plt.gca().get_yticks()
plt.gca().set_yticklabels(['{:,.0f}'.format(x) for x in current_values])
add_grid()
plt.show()
import matplotlib.pyplot as plt
import numpy as np
np.random.seed(42)
plt.clf()
# generate sample data for this example
xs = [1,2,3,4,5,6,7,8,9,10,11,12]
ys=np.random.normal(loc=0,size=12, scale=500000) + 1000000
# plot the data
plt.bar(xs,ys)
# after plotting the data, format the labels
current_values = plt.gca().get_yticks()
plt.gca().set_yticklabels(['{:.0f}'.format(x) for x in current_values])
add_grid()
plt.show()
import matplotlib.pyplot as plt
import numpy as np
np.random.seed(42)
plt.clf()
# generate sample data for this example
xs = [1,2,3,4,5,6,7,8,9,10,11,12]
ys= np.minimum(np.random.normal(loc=0.5,size=12,scale=0.4), np.repeat(1.0, 12))
# plot the data
plt.bar(xs,ys)
plt.ylim(0,1.05)
# after plotting the data, format the labels
current_values = plt.gca().get_yticks()
plt.gca().set_yticklabels(['{:,.0%}'.format(x) for x in current_values])
add_grid()
plt.show()