Suppose I have the following code that plots something very simple using pandas:
import pandas as pd
values = [[1, 2], [2, 5]]
df2 = pd.DataFrame(values, columns=['Type A', 'Type B'],
index=['Index 1', 'Index 2'])
df2.plot(lw=2, colormap='jet', marker='.', markersize=10,
title='Video streaming dropout by category')
How do I easily set x and y-labels while preserving my ability to use specific colormaps? I noticed that the plot()
wrapper for pandas DataFrames doesn't take any parameters specific for that.
To set labels on the x-axis and y-axis, use the plt. xlabel() and plt. ylabel() methods.
The df.plot()
function returns a matplotlib.axes.AxesSubplot
object. You can set the labels on that object.
ax = df2.plot(lw=2, colormap='jet', marker='.', markersize=10, title='Video streaming dropout by category')
ax.set_xlabel("x label")
ax.set_ylabel("y label")
Or, more succinctly: ax.set(xlabel="x label", ylabel="y label")
.
Alternatively, the index x-axis label is automatically set to the Index name, if it has one. so df2.index.name = 'x label'
would work too.
You can use do it like this:
import matplotlib.pyplot as plt
import pandas as pd
plt.figure()
values = [[1, 2], [2, 5]]
df2 = pd.DataFrame(values, columns=['Type A', 'Type B'],
index=['Index 1', 'Index 2'])
df2.plot(lw=2, colormap='jet', marker='.', markersize=10,
title='Video streaming dropout by category')
plt.xlabel('xlabel')
plt.ylabel('ylabel')
plt.show()
Obviously you have to replace the strings 'xlabel' and 'ylabel' with what you want them to be.
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