用 pandas 绘制一维多线图 [英] 1D multiple lines plot with pandas

问题描述

我有一个包含 x1 和 x2 列的数据框.我想将每一行绘制为一维线，其中 x1 是起点，x2 是终点.下面我有我的解决方案，它不是很酷.此外，在同一图中绘制 900 条线时速度很慢.

I have a dataframe with x1 and x2 columns. I want to plot each row as an unidimensional line where x1 is the start and x2 is the end. Follows I have my solution which is not very cool. Besides it is slow when plotting 900 lines in the same plot.

创建一些示例数据:

import numpy as np
import pandas as pd    
df_lines = pd.DataFrame({'x1': np.linspace(1,50,50)*2, 'x2': np.linspace(1,50,50)*2+1})

我的解决方案:

import matplotlib.pyplot as plt
def plot(dataframe):
    plt.figure()
    for item in dataframe.iterrows():
        x1 = int(item[1]['x1'])
        x2 = int(item[1]['x2'])
        plt.hlines(0,x1,x2)

plot(df_lines)

它确实有效，但我认为它可以改进.提前致谢.

It actually works but I think it could be improved. Thanks in advance.

推荐答案

Matplotlib 可以节省大量绘制线条的时间，当它们以 LineCollection 进行组织时.不是像其他答案那样绘制 50 个单独的 hlines，而是创建一个对象.

Matplotlib can save a lot of time drawing lines, when they are organized in a LineCollection. Instead of drawing 50 individual hlines, like the other answers do, you create one single object.

这样的 LineCollection 需要一个线顶点数组作为输入，它的形状需要 (行数，每行点数，2).所以在这种情况下 (50,2,2).

Such a LineCollection requires an array of the line vertices as input, it needs to be of shape (number of lines, points per line, 2). So in this case (50,2,2).

import numpy as np
import pandas as pd    
import matplotlib.pyplot as plt
from matplotlib.collections import LineCollection

df_lines = pd.DataFrame({'x1': np.linspace(1,50,50)*2, 
                         'x2': np.linspace(1,50,50)*2+1})

segs = np.zeros((len(df_lines), 2,2))
segs[:,:,0] = df_lines[["x1","x2"]].values


fig, ax = plt.subplots()

line_segments = LineCollection(segs)
ax.add_collection(line_segments)

ax.set_xlim(0,102)
ax.set_ylim(-1,1)
plt.show()

这篇关于用 pandas 绘制一维多线图的文章就介绍到这了，希望我们推荐的答案对大家有所帮助，也希望大家多多支持IT屋！