Python 使用日期格式化X轴格式Matplotlib

我编写了一段代码，用于绘制用户确定的股票市场过去七天的股票价值。 我遇到的问题是，我想以YYMMDD格式格式化x轴。 我也不明白x轴末端的

2.014041e7

是什么意思

x的值为：

20140421.0, 20140417.0, 20140416.0, 20140415.0, 20140414.0, 20140411.0, 20140410.0

531.17, 524.94, 519.01, 517.96, 521.68, 519.61, 523.48

y的值为：

20140421.0, 20140417.0, 20140416.0, 20140415.0, 20140414.0, 20140411.0, 20140410.0

531.17, 524.94, 519.01, 517.96, 521.68, 519.61, 523.48

我的代码如下：

mini = min(y)
maxi = max(y)
minimum = mini - 75
maximum = maxi + 75
mini2 = int(min(x))
maxi2 = int(max(x))

plt.close('all')
fig, ax = plt.subplots(1)
pylab.ylim([minimum,maximum])
pylab.xlim([mini2,maxi2])

ax.plot(x, y)
ax.plot(x, y,'ro')
ax.plot(x, m*x + c)
ax.grid()
ax.plot()

---

使用您的方法绘制数据时，您只需根据

x

中的数字（浮动）绘制

y

数据，例如

20140421.0

（我假设您希望指的是2014年4月21日）

您需要将这些浮动中的数据转换为适当的格式，以便matplotlib理解。下面的代码获取两个列表（x，y）并转换它们

import numpy as np

import matplotlib.pyplot as plt
import matplotlib.dates as mdates

import datetime as dt

# Original data

raw_x = [20140421.0, 20140417.0, 20140416.0, 20140415.0, 20140414.0, 20140411.0, 20140410.0]
y = [531.17, 524.94, 519.01, 517.96, 521.68, 519.61, 523.48]

# Convert your x-data into an appropriate format.

# date_fmt is a string giving the correct format for your data. In this case
# we are using 'YYYYMMDD.0' as your dates are actually floats.
date_fmt = '%Y%m%d.0'

# Use a list comprehension to convert your dates into datetime objects.
# In the list comp. strptime is used to convert from a string to a datetime
# object.
dt_x = [dt.datetime.strptime(str(i), date_fmt) for i in raw_x]

# Finally we convert the datetime objects into the format used by matplotlib
# in plotting using matplotlib.dates.date2num
x = [mdates.date2num(i) for i in dt_x]

# Now to actually plot your data.
fig, ax = plt.subplots()

# Use plot_date rather than plot when dealing with time data.
ax.plot_date(x, y, 'bo-')

# Create a DateFormatter object which will format your tick labels properly.
# As given in your question I have chosen "YYMMDD"
date_formatter = mdates.DateFormatter('%y%m%d')

# Set the major tick formatter to use your date formatter.
ax.xaxis.set_major_formatter(date_formatter)

# This simply rotates the x-axis tick labels slightly so they fit nicely.
fig.autofmt_xdate()

plt.show()

整个代码都有注释，因此应该很容易解释。有关各个模块的详细信息，请参见以下内容：

---

使用您的方法绘制数据时，您只需将

y

数据与

x

中的数字（浮动）进行绘制，例如

20140421.0

（我假设您希望的日期是2014年4月21日）

您需要将这些浮动中的数据转换为适当的格式，以便matplotlib理解。下面的代码获取两个列表（x，y）并转换它们

import numpy as np

import matplotlib.pyplot as plt
import matplotlib.dates as mdates

import datetime as dt

# Original data

raw_x = [20140421.0, 20140417.0, 20140416.0, 20140415.0, 20140414.0, 20140411.0, 20140410.0]
y = [531.17, 524.94, 519.01, 517.96, 521.68, 519.61, 523.48]

# Convert your x-data into an appropriate format.

# date_fmt is a string giving the correct format for your data. In this case
# we are using 'YYYYMMDD.0' as your dates are actually floats.
date_fmt = '%Y%m%d.0'

# Use a list comprehension to convert your dates into datetime objects.
# In the list comp. strptime is used to convert from a string to a datetime
# object.
dt_x = [dt.datetime.strptime(str(i), date_fmt) for i in raw_x]

# Finally we convert the datetime objects into the format used by matplotlib
# in plotting using matplotlib.dates.date2num
x = [mdates.date2num(i) for i in dt_x]

# Now to actually plot your data.
fig, ax = plt.subplots()

# Use plot_date rather than plot when dealing with time data.
ax.plot_date(x, y, 'bo-')

# Create a DateFormatter object which will format your tick labels properly.
# As given in your question I have chosen "YYMMDD"
date_formatter = mdates.DateFormatter('%y%m%d')

# Set the major tick formatter to use your date formatter.
ax.xaxis.set_major_formatter(date_formatter)

# This simply rotates the x-axis tick labels slightly so they fit nicely.
fig.autofmt_xdate()

plt.show()

整个代码都有注释，因此应该很容易解释。有关各个模块的详细信息，请参见以下内容：

看看这里：看看这里：