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How to add vertical lines for visual separation in pandas plot
MWE
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
df = pd.DataFrame(np.random.rand(9, 4), columns=['a', 'b', 'c', 'd'])
df.plot.bar()
plt.show()
Question
How do I add separating vertical lines between groups? Say these are
groups of three:
(0, 1, 2), LINE, (3, 4, 5), LINE, (6, 7, 8)
Notes
This really helps for recognizing patterns and tracking trends in a busy, but useful graph.
2 answers
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I don't think this is possible using just the Pandas plotting API. You can use the lower-level Matplotlib API to do just about anything you can imagine:
ax = df.plot.bar()
vlines = [2.5, 5.5] # x-positions of the group separators
ax.vlines(vlines, 0, 1,
transform=ax.get_xaxis_transform(), # [1]
color='black',
linewidths=0.8) # [2]
# [1]: This makes the above 0 and 1 refer to the top and bottom
# of the plot, regardless of the actual scale used for the data.
# [2]: 0.8 is the default width used for the axis frame
# (matplotlib.rcParams['axes.linewidth'], if you prefer).
plt.show()
ax here is a Matplotlib Axes object, and you can read about all the things you can do with it here.
The following users marked this post as Works for me:
| User | Comment | Date |
|---|---|---|
| mcp | (no comment) | Jul 26, 2022 at 21:39 |
One possibility with axvline:
import pandas as pd
import numpy as np
import matplotlib.pyplot as plt
df = pd.DataFrame(np.random.rand(9, 4), columns=['a', 'b', 'c', 'd'])
df.plot.bar()
plt.axvline(x=2.5, ymin=0, ymax=1)
plt.axvline(x=5.5, ymin=0, ymax=1)
plt.show()
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