尝试绘制 pandas 类型错误 [英] Pandas type error trying to plot

问题描述

我正在尝试基于Pandas数据框创建基本的散点图.但是，当我调用分散例程时，出现错误"TypeError:无效的类型升级".重现此问题的示例代码如下所示:

I'm trying to create a basic scatter plot based on a Pandas dataframe. But when I call the scatter routine I get an error "TypeError: invalid type promotion". Sample code to reproduce the problem is shown below:

t1 = pd.to_datetime('2015-11-01 00:00:00')
t2 = pd.to_datetime('2015-11-02 00:00:00')

Time = pd.Series([t1, t2])
r = pd.Series([-1, 1])

df = pd.DataFrame({'Time': Time, 'Value': r})
print(df)

print(type(df.Time))
print(type(df.Time[0]))

fig = plt.figure(figsize=(x_size,y_size))
ax = fig.add_subplot(111)
ax.scatter(df.Time, y=df.Value, marker='o')

结果输出是

        Time  Value
0 2015-11-01     -1
1 2015-11-02      1
<class 'pandas.core.series.Series'>
<class 'pandas.tslib.Timestamp'>

---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
<ipython-input-285-f4ed0443bf4d> in <module>()
     15 fig = plt.figure(figsize=(x_size,y_size))
     16 ax = fig.add_subplot(111)
---> 17 ax.scatter(df.Time, y=df.Value, marker='o')

C:\Anaconda3\lib\site-packages\matplotlib\axes\_axes.py in scatter(self, x,    y, s, c, marker, cmap, norm, vmin, vmax, alpha, linewidths, verts, **kwargs)
   3635             edgecolors = 'face'
   3636 
-> 3637         offsets = np.dstack((x, y))
   3638 
   3639         collection = mcoll.PathCollection(

C:\Anaconda3\lib\site-packages\numpy\lib\shape_base.py in dstack(tup)
    365 
    366     """
--> 367     return _nx.concatenate([atleast_3d(_m) for _m in tup], 2)
    368 
    369 def _replace_zero_by_x_arrays(sub_arys):

TypeError: invalid type promotion

四处搜寻，我发现了类似的帖子 Pandas Series TypeError和使用datetime时出现ValueError ，这表明该错误是由系列中的多种数据类型引起的.但这在我的示例中似乎不是问题，正如我正在打印的类型信息所证明的那样.

Searching around I've found a similar post Pandas Series TypeError and ValueError when using datetime which suggests that the error is caused by having multiple data types in the series. But that does not appear to be the issue in my example, as evidenced by the type information I'm printing.

请注意，如果我停止使用熊猫的datetime对象，并将时间"设置为浮点数，则可以正常工作，例如

Note that if I stop using pandas datetime objects and make the 'Time' a float instead this works fine, e.g.

t1 = 1.1 #
t2 = 1.2

Time = pd.Series([t1, t2])
r = pd.Series([-1, 1])

df = pd.DataFrame({'Time': Time, 'Value': r})
print(df)

print(type(df.Time))
print(type(df.Time[0]))

fig = plt.figure(figsize=(x_size,y_size))
ax = fig.add_subplot(111)
ax.scatter(df.Time, y=df.Value, marker='o')

有输出

   Time  Value
0   1.1     -1
1   1.2      1
<class 'pandas.core.series.Series'>
<class 'numpy.float64'>

，该图看起来很好.我不知道为什么使用datetime会导致无效的类型升级错误?我正在使用Python 3.4.3和pandas 0.16.2.

and the graph looks just fine. I'm at a loss as to why the use of a datetime is causing the invalid type promotion error? I'm using Python 3.4.3 and pandas 0.16.2.

推荐答案

感谢@martinvseticka.我认为根据您指出的numpy代码，您的评估是正确的.我能够进一步简化您的调整(并添加了第三个样本点)以获得

Thanks @martinvseticka. I think your assessment is correct based on the numpy code you pointed me to. I was able to simplify your tweaks a bit more (and added a third sample point) to get

t1 = pd.to_datetime('2015-11-01 00:00:00')
t2 = pd.to_datetime('2015-11-02 00:00:00')
t3 = pd.to_datetime('2015-11-03 00:00:00')

Time = pd.Series([t1, t2, t3])
r = pd.Series([-1, 1, 0.5])

df = pd.DataFrame({'Time': Time, 'Value': r})

fig = plt.figure(figsize=(x_size,y_size))
ax = fig.add_subplot(111)
ax.plot_date(x=df.Time, y=df.Value, marker='o')

键似乎在调用"plot_date"而不是"plot".这似乎通知mapplotlib不要尝试连接数组.

The key seems to be calling 'plot_date' rather than 'plot'. This seems to inform mapplotlib to not try to concatenate the arrays.

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