使用Matplotlib可视化CSV数据 [英] Using Matplotlib, visualize CSV data

问题描述

使用matplotlib/熊猫/python，我无法将数据可视化为每30分钟和每天的值是一个新问题，与该问题密切相关.

Using matplotlib/pandas/python, I cannot visualize data as values per 30mins and per days is a new question, which is strongly related to this question.

我想用Matplotlib可视化CSV数据.

I want to visualize CSV data with Matplotlib.

以下是我的代码，名为 1.30mins.py

Following is my code named 1.30mins.py

import matplotlib.pyplot as plt
from matplotlib import style
import numpy as np

style.use('ggplot')

x,y =np.loadtxt('total_watt.csv',
                unpack = True,
                delimiter = ',')

plt.plot(x,y)

plt.title('Example')
plt.ylabel('Y axis')
plt.xlabel('X axis')

plt.show()

当我故意 1.30mins.py 时，收到以下错误消息.

When I implemtented 1.30mins.py, I got a following error message.

(DataVizProj)Soma-Suzuki:Soma Suzuki$ python 1.30mins.py
Traceback (most recent call last):
  File "1.30mins.py", line 10, in <module>
    delimiter = ',')
  File "/Users/Suzuki/Envs/DataVizProj/lib/python2.7/site-packages/numpy/lib/npyio.py", line 856, in loadtxt
    items = [conv(val) for (conv, val) in zip(converters, vals)]
ValueError: invalid literal for float(): 2011-04-18 13:22:00

这是我的 total_watt.csv

2011-04-18 21:22:00 659.670303375527
2011-04-18 21:52:00 576.304871428571
2011-04-18 22:22:00 2,497.20620579196
2011-04-18 22:52:00 2,790.20392088608
2011-04-18 23:22:00 1,092.20906629318
2011-04-18 23:52:00 825.994417375886
2011-04-19 00:22:00 2,397.16672089666
2011-04-19 00:52:00 1,411.66659265233

据我自己搜索，我需要在程序中添加 converters 或％y-％m-％t .

As far as I searched by myself, I need to add converters or, %y-%m-%t　to my program.

我的python版本是2.76我的matpltlib版本是1.42

My python version is 2.76 My matpltlib version is 1.42

推荐答案

您的数据

2011-04-18 21:22:00 659.670303375527
2011-04-18 21:52:00 576.304871428571
...

不受空格或逗号分隔.可以认为它具有固定宽度但是列. np.genfromtxt 可以读取固定宽度的数据.而不是通过字符串到 delimiter ，传递一个表示每个字符串的宽度的整数序列字段.

is not delimited by spaces or commas. It could be regarded as having fixed-width columns however. np.genfromtxt can read fixed-width data. Instead of passing a string to delimiter, pass a sequence of ints representing the width of each field.

import numpy as np
import matplotlib.pyplot as plt
import matplotlib.dates as mdates
from matplotlib import style
style.use('ggplot')

x, y = np.genfromtxt('total_watt.csv',
                     unpack=True,
                     delimiter=[19, 10**6], dtype=None)

x = mdates.datestr2num(x)
y = np.array(np.char.replace(y, ',', ''), dtype=float)

fig, ax = plt.subplots()
ax.plot(x, y)

plt.title('Example')
plt.ylabel('Y axis')
plt.xlabel('X axis')
xfmt = mdates.DateFormatter('%Y-%m-%d %H:%M:%S')
ax.xaxis.set_major_formatter(xfmt)

fig.autofmt_xdate()
plt.show()

产量

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