条形图上的自定义 xticks 标签 (matplotlib)

Question

Im trying to plot the 95% confidence interval for the mean on a bar chart. The bar colors are set based on the horizontal line value. So bars is colored red if they are definitely above this value (given the confidence interval), blue if they are definitely below, or white if they contain this value.

The finished plot contains too many xticks labels. I tried using a few methods like xaxis.set_major_locator and plt.xticks(range(len(df.index)), df.index) but it all turned out bad. I think it's the problem with my color mask setting, but I cant figure how to fix it.

Really appreciate any help and advice. Thanks!

import pandas as pd
import numpy as np
from scipy import stats
import matplotlib.pyplot as plt

np.random.seed(12345)

df = pd.DataFrame([np.random.normal(32000,200000,3650), 
                   np.random.normal(43000,100000,3650), 
                   np.random.normal(43500,140000,3650), 
                   np.random.normal(48000,70000,3650)], 
                  index=[1992,1993,1994,1995])

mean = df.mean(axis = 1)
std = df.std(axis = 1)
n = len(df.columns)

yerr = []
for index, row in df.iterrows():
    yerr.append(stats.sem(row)*stats.t.ppf((1+0.95)/2, n-1))

theline = 42000
high_mask = theline > (mean+yerr)
low_mask = theline < (mean-yerr)
equal_mask = ((mean-yerr) <= theline) & (theline <= (mean+yerr))

plt.figure()
plt.bar(df.index[high_mask.values], mean.iloc[high_mask.values], alpha=0.5, color='blue')
plt.bar(df.index[low_mask.values], mean.iloc[low_mask.values], alpha=0.5, color='red')
plt.bar(df.index[equal_mask.values], mean.iloc[equal_mask.values], alpha=0.5, color='grey')
plt.errorbar(df.index, mean, yerr=yerr, fmt=".", color="k")
plt.axhline(y=theline, color="grey", alpha=0.7)
# plt.gca().set_xticklabels(df.index)
# plt.xticks(range(len(df.index)), df.index)
plt.show()

Answer 1

You can set the x-ticks to a custom array of x-axis values using the set_xticks method of the axis object.

ax = plt.gca()
ax.set_xticks([1992, 1993, 1994, 1995])