erikaris

# taken from Coursera

import mpl_toolkits.axes_grid1.inset_locator as mpl_il

plt.figure()
plt.boxplot([ df['normal'], df['random'], df['gamma'] ], whis='range')

# overlay axis on top of another 
# create an inset using .inset_axes()
ax2 = mpl_il.inset_axes(plt.gca(), width='60%', height='40%', loc=2)  #loc 5 (center right) = loc 7 (right)

erikaris

import matplotlib.pyplot as plt
k = np.array([1, 4, 9, 16, 25, 36, 49, 64])
plt.figure()
y,bins,p=plt.hist(k, edgecolor='black')
print("", y, "\n", bins, "\n", p)

erikaris

import numpy as np

a = np.array([1,2,3,5,8,13,21,34])
b = np.array([1, 4, 9, 16, 25, 36, 49, 64])
c = np.linspace(0, 40, 8)
d = np.sin(c)

plt.figure()
plt.plot(a)
plt.plot(a, 'go') # 1

erikaris

# modified from: https://matplotlib.org/gallery/userdemo/demo_gridspec02.html#sphx-glr-gallery-userdemo-demo-gridspec02-py
import matplotlib.pyplot as plt
from matplotlib.gridspec import GridSpec

Y = np.random.normal(loc=0.0, scale=1.0, size=10000)
X = np.random.random(size=10000)
a = np.array([1,2,3,5,8,13,21,34])
b = np.array([1, 4, 9, 16, 25, 36, 49, 64])

fig = plt.figure()

erikaris

# from matplotlib

import matplotlib.pyplot as plt
from matplotlib.gridspec import GridSpec


def make_ticklabels_invisible(fig):
    for i, ax in enumerate(fig.axes):
        ax.text(0.5, 0.5, "ax%d" % (i+1), va="center", ha="center")
        ax.tick_params(labelbottom=False, labelleft=False)

erikaris

# from matplotlib.org
import matplotlib.pyplot as plt
from matplotlib.gridspec import GridSpec


def make_ticklabels_invisible(fig):
    for i, ax in enumerate(fig.axes):
        ax.text(0.5, 0.5, "ax%d" % (i+1), va="center", ha="center")
        ax.tick_params(labelbottom=False, labelleft=False)

erikaris

# create 2x2 grid of axis subplots
fig, ((ax1, ax2, ax3), (ax4, ax5, ax6), (ax7, ax8, ax9)) = plt.subplots(3, 3, sharex=True)
axs = [ax1,ax2,ax3,ax4,ax5,ax6,ax7,ax8,ax9]

# draw n = 10, 100, 1000, and 10000 samples from the normal distribution and plot corresponding histograms
for n in range(0,len(axs)):
    axs[n].plot(x, y)
    .....<continue your script >

erikaris

# modified from Coursera

# figure 2: Creates two subplots and unpacks the output array immediately
# 1st subplot
plt.subplot(2,2,1)
plt.plot(x, y)
plt.title('Sharing Y axis')   # set_title() is owned by axes, not plt. 
# 2nd subplot
plt.subplot(2, 2, 4)
plt.scatter(x, y)

erikaris

# modified from Coursera

# figure 2: Creates two subplots and unpacks the output array immediately
f, ax = plt.subplots(2, 2, sharey=True)
ax[0,0].plot(x, y)
ax[0,0].set_title('Sharing Y axis')
ax[1,1].scatter(x, y)

erikaris

# Modified from Coursera.org

%matplotlib notebook
import numpy as np
import matplotlib.pyplot as plt

x = np.linspace(0, 2*np.pi, 400)
y = np.sin(x**2)

# figure 2: Creates two subplots and unpacks the output array immediately