使用matplotlib从CSV文件绘制数据

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问题描述

我在e:\dir1\datafile.csv处有一个CSV文件.它包含三列，需要跳过10条标题行和尾随行.我想用numpy.loadtxt()绘制它，但我没有找到任何严格的文档.

I have a CSV file at e:\dir1\datafile.csv.It contains three columns and 10 heading and trailing lines need to be skipped.I would like to plot it with numpy.loadtxt(), for which I haven't found any rigorous documentation.

这是我在网上找到的几次尝试中开始写的东西.

Here is what I started to write from the several tries I found on the web.

import matplotlib as mpl
import numpy as np
import matplotlib.pyplot as plt
import matplotlib.cbook as cbook

def read_datafile(file_name):
    # the skiprows keyword is for heading, but I don't know if trailing lines
    # can be specified
    data = np.loadtxt(file_name, delimiter=',', skiprows=10)
    return data

data = read_datafile('e:\dir1\datafile.csv')

x = ???
y = ???

fig = plt.figure()

ax1 = fig.add_subplot(111)

ax1.set_title("Mains power stability")
ax1.set_xlabel('time')
ax1.set_ylabel('Mains voltage')

ax1.plot(x,y, c='r', label='the data')

leg = ax1.legend()

plt.show()

推荐答案

根据 docs numpy.loadtxt是

因此只有少数选项可以处理更复杂的文件.如前所述， numpy.genfromtxt 具有更多选项.因此，举例来说，您可以使用

so there are only a few options to handle more complicated files.As mentioned numpy.genfromtxt has more options. So as an example you could use

import numpy as np
data = np.genfromtxt('e:\dir1\datafile.csv', delimiter=',', skip_header=10,
                     skip_footer=10, names=['x', 'y', 'z'])

读取数据并为列分配名称(或使用names=True从文件中读取标题行)，然后使用

to read the data and assign names to the columns (or read a header line from the file with names=True) and than plot it with

ax1.plot(data['x'], data['y'], color='r', label='the data')

我认为numpy现在已被很好地记录下来.您可以从 ipython 或使用IDE轻松检查文档字符串例如 spider ，如果您希望阅读以HTML格式呈现的内容.

I think numpy is quite well documented now. You can easily inspect the docstrings from within ipython or by using an IDE like spider if you prefer to read them rendered as HTML.

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