There is no automatic feature to do such a thing, but you could loop through each point and put text in the appropriate location: import matplotlib.pyplot as plt import numpy as np data = np.random.rand(5, 4) heatmap = plt.pcolor(data) for y in range(data.shape[0]): for x in range(data.shape[1]): plt.text(x + 0.5, y + 0.5, ‘%.4f’ % … Read more
I present two ways. The first is probably cleaner: it loops through once, and within each loop, gets the next color, and then does two plotting commands with that color. In the second, it loops through and does all the markers and then it resets the colors and loops through again and does the lines. … Read more
You can use the set_label_coords method. import matplotlib.pylab as plt import random import matplotlib.gridspec as gridspec random.seed(20) data1 = [random.random() for i in range(10)] data2 = [random.random()*1000 for i in range(10)] gs = gridspec.GridSpec(2,1) fig = plt.figure() ax = fig.add_subplot(gs[0]) ax.plot(data1) ax.set_ylabel(r’Label One’, size =16) ax.get_yaxis().set_label_coords(-0.1,0.5) ax = fig.add_subplot(gs[1]) ax.plot(data2) ax.set_ylabel(r’Label Two’, size =16) ax.get_yaxis().set_label_coords(-0.1,0.5)
You can change the tick size using: font_size = 14 # Adjust as appropriate. cb.ax.tick_params(labelsize=font_size) See the docs for ax.tick_params here for more parameters that can be modified.
set useOffset to False: ax = plt.gca() ax.ticklabel_format(useOffset=False)
To fix this problem, I added to the top: import matplotlib matplotlib.use(‘Agg’) I have a CentOS7, Anaconda3-4.5.0, python3.5 pyqt version 5.6.0 and qt version 5.6.0 If you want to use the plot in a Tkinter window for visualisation then use: matplotlib.use(‘TkAgg’)
Having the same ValueError, this is just the result of some testing and little research on my own, without the claim to be complete or professional about it. Please comment or answer whoever finds something wrong. Of course, your data should be in the right order of the index values, which you would assure with … Read more
When plotting a normalized histogram, the area under the curve should sum to 1, not the height. In [44]: import matplotlib.pyplot as plt k=(3,3,3,3) x, bins, p=plt.hist(k, density=True) # used to be normed=True in older versions from numpy import * plt.xticks( arange(10) ) # 10 ticks on x axis plt.show() In [45]: print bins [ … Read more
You can use StrMethodFormatter, which uses the str.format() specification mini-language. import numpy as np import pandas as pd import matplotlib.pyplot as plt import matplotlib.ticker as mtick df = pd.DataFrame({‘A’: [‘A’, ‘B’], ‘B’: [1000,2000]}) fig, ax = plt.subplots(1, 1, figsize=(2, 2)) df.plot(kind=’bar’, x=’A’, y=’B’, align=’center’, width=.5, edgecolor=”none”, color=”grey”, ax=ax) fmt=”${x:,.0f}” tick = mtick.StrMethodFormatter(fmt) ax.yaxis.set_major_formatter(tick) plt.xticks(rotation=25) plt.show()
You can create a double-headed arrow using the annotate method with blank text annotation and setting the arrowprops dict to include arrowstyle=”<->” as shown below: import matplotlib.pyplot as plt plt.annotate(s=””, xy=(1,1), xytext=(0,0), arrowprops=dict(arrowstyle=”<->”)) plt.show()