如何在 matplolib python 上制作 jitterplot [英] How to make jitterplot on matplolib python

问题描述

这是我的代码(改编自

Here is my code (adapted from here):

df_1 = pd.DataFrame({'Cells' : np.arange(0,100), 'Delta_7' : np.random.rand(100,), 'Delta_10' : np.random.rand(100,), 'Delta_14' : np.random.rand(100,)}, columns = ['Cells','Delta_7', 'Delta_10', 'Delta_14'])



#figure
fig, ax1 = plt.subplots()
fig.set_size_inches(13, 10)



#c sequence
c = df_1['Delta_7']

#plot

plt.scatter(np.full((len(df_1), 1), 1), df_1['Delta_7'] , s = 50, c=c, cmap = 'viridis')
plt.scatter(np.full((len(df_1), 1), 2), df_1['Delta_10'] , s = 50, c=c, cmap = 'viridis')
plt.scatter(np.full((len(df_1), 1), 3), df_1['Delta_14'] , s = 50, c=c, cmap = 'viridis')
cbar = plt.colorbar()

I would like to make a beautiful jitterplot (like on R or seaborn) with matplotlib. The thing is that I would like to give each cell a color based on its 'Delta_7' value. And this color would be kept when plotting 'Delta_10' and 'Delta_14', that I didn't manage to do with seaborn. Please, could you let me know if you have any clue (python package, coding tricks …)?

Kindly,

解决方案

The positions of the dots can be obtained from the list returned by scatter. These positions can be jittered, for example only in the x-direction. Possibly the range of the x-axis needs to be extended a bit to show every displaced dot.

Here is some code to start experimenting:

import matplotlib.pyplot as plt
import pandas as pd
import numpy as np

def jitter_dots(dots):
    offsets = dots.get_offsets()
    jittered_offsets = offsets
    # only jitter in the x-direction
    jittered_offsets[:, 0] += np.random.uniform(-0.3, 0.3, offsets.shape[0])
    dots.set_offsets(jittered_offsets)

df_1 = pd.DataFrame({'Cells': np.arange(0, 100),
                     'Delta_7': np.random.rand(100),
                     'Delta_10': np.random.rand(100),
                     'Delta_14': np.random.rand(100)})
fig, ax1 = plt.subplots()

columns = df_1.columns[1:]
c = df_1['Delta_7']
for i, column in enumerate(columns):
    dots = plt.scatter(np.full((len(df_1), 1), i), df_1[column], s=50, c=c, cmap='plasma')
    jitter_dots(dots)
plt.xticks(range(len(columns)), columns)
xmin, xmax = plt.xlim()
plt.xlim(xmin - 0.3, xmax + 0.3)  # make some room to show the jittered dots
cbar = plt.colorbar()
plt.show()

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