在 python 中使用不同时间索引在同一 x 轴上绘制多个直方图

Question

I have three lists of probabilities of three events (s, c, i) that I have obtained over time 1-1000 , ie, pr_s, pr_c, pr_i . At time t , only one event is true. I want to plot the values of all three events (pr_s, pr_c, pr_i) with different coloring on time-indexed x-axis but I am not sure how to do that. I want to know at time slot t , which event occurred and with what probability.

As an examples, let's say the events occur from time t to t+5 as follow:

pr_c(t) = 0.4; 
pr_i(t+1) = 0.3; 
pr_c(t+2) = 0.8; 
pr_s(t+3) = 0.65; 
pr_i(t+4) = 0.6; 
pr_s(t+5) = 0.9;

I would like to plot these probabilities on y-axis with time as x-axis. For now, I have a list of probabilities as they occur. For instance, pr_i = [0.3, 0.6] in above example that occured at time t+1 and t+4 .

EDIT: It probably will require me to use a loop and if else statement for plotting but I am not sure if I can do that and how

Answer 1

It is still not entirely clear to me how you want to provide the connection between t and the events pr_s, pr_c, pr_i but here are two solutions. One purely with base Python and matplotlib, the other with pandas/seaborn as higher libraries.

from matplotlib import pyplot as plt

pr_i = [0.3, 0.6]
pr_c = [0.4, 0.8]
pr_s = [0.65, 0.9]

t = ["c", "i", "c", "s", "i", "s"]

event_dict = {"c": pr_c, "i": pr_i, "s": pr_s}

fig, (ax1, ax2) = plt.subplots(2, figsize=(6, 10))

for key in event_dict.keys():
    ind = [i for i, x in enumerate(t) if x==key]
    ax1.bar(ind, event_dict[key], label=key)
    
ax1.legend()
ax1.set_title("List solution")


import pandas as pd
import seaborn as sns

df = pd.DataFrame({"t": t, "vals": 0})

for key in event_dict.keys():
    df.loc[df.t==key, "vals"] = event_dict[key]

sns.barplot(x=df.index, y=df.vals, hue=df.t, dodge=False, ax=ax2, palette="bright")
ax2.set_title("Pandas/seaborn solution")

plt.show()

Sample output:

Answer 2

maybe this will help.Sounds like you need a line plot possibly. You need to look up documentation for the rest. But this code will put the data into a dataframe then you will be able to plot like a time series.Seaborn a lot of features that might help you.

https://matplotlib.org/
https://stackoverflow.com/questions/28931224/adding-value-labels-on-a-matplotlib-bar-chart

import pandas as pd
import matplotlib.pyplot as plt

pr_s = [10,21,33]
pr_c = [20,11,16]
pr_i = [30,31,42]

df = pd.DataFrame(np.reshape(list(zip(pr_s, pr_c, pr_i)),(-1,3)))

plt.xticks(range(0, len(df.columns)))

plt.legend(loc='upper left')
plt.plot(df,marker='o')
plt.xlabel('Time')
plt.ylabel('Probabilities')