ValueError:视图限制最小值-35738.3640567小于1，并且是无效的Matplotlib日期值

问题描述

是matplotlib的初学者.我正在尝试使用matplotlib.pyplot绘制数据框.问题是，每次我尝试绘制它时，都会出现以下错误:

im a beginner in matplotlib. Im trying to plot a dataframe using matplotlib.pyplot. The problem is that everytime I try to plot it i get the following error:

ValueError: view limit minimum -35738.3640567 is less than 1 and is an invalid Matplotlib date value. This often happens if you pass a non-datetime value to an axis that has datetime units.

根据该错误，看来好像datetime列中有一个非datetime值，但没有.

According to the error, it seems to be like theres a non-datetime value in the datetime column, but there isnt.

我尝试使用pd.to_datetime()并尝试将时间戳的格式更改为pd.to_datetime(df_google['datetime'], format = '%d/%m/%Y')，但没有任何改变.

Ive tried using pd.to_datetime() and try to change the format of the timestamp to pd.to_datetime(df_google['datetime'], format = '%d/%m/%Y') but nothing changes.

这是我要使用的代码:

import matplotlib.pyplot as plt

df_google.plot()
plt.show()

df_google是具有列['datetime','price']的数据框，其中一些值如下:

df_google is a dataframe with columns ['datetime','price'] and some of the values are the following:

     datetime        price
0  2018-05-15  1079.229980
1  2018-05-16  1081.770020
2  2018-05-17  1078.589966
3  2018-05-18  1066.359985
4  2018-05-21  1079.579956
5  2018-05-22  1069.729980
6  2018-05-23  1079.689941
7  2018-05-24  1079.239990
8  2018-05-25  1075.660034
9  2018-05-29  1060.319946

有人可以帮助我理解这种类型的错误吗?当每个值都是日期时间类型值时，为什么会显示非日期时间值?如何绘制此数据框?

Can someone try to help me understand this type of error? Why does it says theres a non-datetime value when every value is a datetime type value? How can I plot this dataframe?

推荐答案

给出以下数据:

   datetime        price
 2018-05-15  1079.229980
 2018-05-16  1081.770020
 2018-05-17  1078.589966
 2018-05-18  1066.359985
 2018-05-21  1079.579956
 2018-05-22  1069.729980
 2018-05-23  1079.689941
 2018-05-24  1079.239990
 2018-05-25  1075.660034
 2018-05-29  1060.319946

将datetime列设置为Datetime格式并设置为索引:

如果列标题中没有空格，则可以使用.访问
• 列名称
  • df_google.datetime而不是df_google['datetime']

  Set the datetime column to a Datetime format and set as index:

  • Column names can be accessed with a ., if there are no spaces in the column header
    • df_google.datetime instead of df_google['datetime']

    import pandas as pd
    import matplotlib.pyplot as plt
    
    df_google.datetime = pd.to_datetime(df.datetime)
    df_google.set_index('datetime', inplace=True)
    

    print(df_google.info())
    
    <class 'pandas.core.frame.DataFrame'>
    DatetimeIndex: 10 entries, 2018-05-15 to 2018-05-29
    Data columns (total 1 columns):
    price    10 non-null float64
    dtypes: float64(1)
    memory usage: 160.0 bytes
    

    情节:

    df_google.plot()
    plt.show()
    

    • 有大量替代绘图工具的生态系统，但是df.plot()适合查看数据.
      • PyViz
      • There's a substantial ecosystem of alternative plotting tools, but df.plot() is fine for getting a look at the data.
        • PyViz

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