正如我所说，pandas 会使这项任务比处理基本 Python 列表等更容易：
import matplotlib.pyplot as plt
import pandas as pd
#imports the text file assuming that your data are separated by space, as in your example above
df = pd.read_csv("test.txt", delim_whitespace=True, names=["X", "Y"])
#extracting the number in a separate column, assuming you do not have terms like NN1B3X5
df["N"] = df.X.str.replace(r"\D", "", regex=True).astype(int)
#this step is only necessary, if your file is not pre-sorted by Linux
df = df.sort_values(by="N")
fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(10, 6))
#categorical plotting
df.plot(x="X", y="Y", ax=ax1)
ax1.set_title("Evenly spaced")
#numerical plotting
df.plot(x="N", y="Y", ax=ax2)
ax2.set_xticks(df.N)
ax2.set_xticklabels(df.X)
ax2.set_title("Numerical spacing")
plt.show()
样本输出：
既然您问是否有非熊猫解决方案 - 当然。Pandas 让一些事情变得更加方便。在这种情况下，我将恢复为 numpy。Numpy 是一个 matplotlib 依赖项，因此与 pandas 相比，它必须安装，如果您使用 matplotlib：
import matplotlib.pyplot as plt
import numpy as np
import re
#read file as strings
arr = np.genfromtxt("test.txt", dtype="U15")
#remove trailing strings
Xnums = np.asarray([re.sub(r"\D", "", i) for i in arr[:, 0]], dtype=int)
#sort array
arr = arr[np.argsort(Xnums)]
#extract x-values as strings...
Xstr = arr[:, 0]
#...and y-values as float
Yvals = arr[:, 1].astype(float)
fig, (ax1, ax2) = plt.subplots(1, 2, figsize=(10, 6))
#categorical plotting
ax1.plot(Xstr, Yvals)
ax1.set_title("Evenly spaced")
#numerical plotting
ax2.plot(np.sort(Xnums), Yvals)
ax2.set_xticks(np.sort(Xnums))
ax2.set_xticklabels(Xstr)
ax2.set_title("Numerical spacing")
plt.show()
样本输出：
