Python &引用；KeyError 0.0“；当使用另一个包含标准偏差的数据帧作为y轴的误差条时

我有一些代码，我无法找到解决方案（尽管谷歌搜索了很多）。 基本上，我有一个scipt，它编译了两个来自相同数据的文件——一个文件是六组每个波长的平均值表，另一个是完全相同的，但包含标准偏差（两个表大小相同，标题相同，等等）。为平均值绘制文件（df2）生成图形，没有问题

然而，当我尝试使用包含标准偏差（df3）值的数据帧作为图形的误差条时，我得到了“KeyError 0.0”。 有人能帮我找出哪里出了问题吗？非常感谢

我的剧本在下面

wave = pd.read_csv("Wavelength_to_Index_Conversion.csv") #contains a list of wavelengths used to use later on
##
#GET AVERAGE VALUES OF DATA FROM EACH FILE
##
for filename in os.listdir(indir):
    print (i)
    df1 = pd.read_csv(indir + filename) #imports file
    print(filename)
    filename = filename[:-12] #removes extra filename and extension
    print(filename)
    if i == 0:
        df2 = pd.DataFrame(data=None, columns=None,index=df1.index)
    e = df1['Average']
    df2 = df2.assign(temp=e.values)
    print (filename)
    df2.rename(columns={'temp': str(filename)}, inplace=True)

    i = i+1

df2.set_index(wave['Wavelength'], inplace=True)
df2.to_csv("Total_Average.csv")
df2t = df2.T
df2t.to_csv("Total_Average_T.csv")

##
## GET STD DEV
##
i = 0
for filename in os.listdir(indir):
    print (i)
    df1 = pd.read_csv(indir + filename) #imports file
    print(filename)
    filename = filename[:-12]
    print(filename)
    if i == 0:
        df3 = pd.DataFrame(data=None, columns=None,index=df1.index)
    e = df1['Std Dev']
    df3 = df3.assign(temp=e.values)
    print (filename)
    df3.rename(columns={'temp': str(filename)}, inplace=True)

    i = i+1
df3.set_index(wave['Wavelength'], inplace=True)
df3.to_csv("Total_Std Dev.csv")

#plt.rc('font', family='serif', size=13)
#plt.rc('font', family='san-serif', size=13)


#plt.ylim(0, 60)    
#plt.xlim(400, 900)
plt.title('Title',fontsize=20)
plt.xlabel('Wavelength (nm)',fontsize=15)
plt.ylabel('Reflectance (%)',fontsize=15)
    #plt.autoscale(enable=True, axis=u'both', tight=False)
plt.grid(False)
df2.plot(x = wave['Wavelength'], xlim=(400,850), ylim=(0,60), yerr=df3) #ERROR HERE WHENEVER yerr=df3 IS USED

编辑：

这是我得到的错误

Traceback (most recent call last):

  File "<ipython-input-8-d121c6b80d76>", line 1, in <module>
    runfile('C:/Users/user/Documents/PhD/Data Manipulation and Graphs/Spectrometry/Plotting All Files into a Graph [X]/Plotting Spectral.py', wdir='C:/Users/user/Documents/PhD/Data Manipulation and Graphs/Spectrometry/Plotting All Files into a Graph [X]')

  File "C:\Anaconda3\lib\site-packages\spyder\utils\site\sitecustomize.py", line 880, in runfile
    execfile(filename, namespace)

  File "C:\Anaconda3\lib\site-packages\spyder\utils\site\sitecustomize.py", line 102, in execfile
    exec(compile(f.read(), filename, 'exec'), namespace)

  File "C:/Users/jdstam/Documents/PhD/Data Manipulation and Graphs/Spectrometry/Plotting All Files into a Graph [X]/Plotting Spectral.py", line 115, in <module>
    df2.plot(x = wave['Wavelength'], xlim=(400,850), ylim=(0,60), yerr=df3)

  File "C:\Anaconda3\lib\site-packages\pandas\tools\plotting.py", line 3671, in __call__
    sort_columns=sort_columns, **kwds)

  File "C:\Anaconda3\lib\site-packages\pandas\tools\plotting.py", line 2556, in plot_frame
    **kwds)

  File "C:\Anaconda3\lib\site-packages\pandas\tools\plotting.py", line 2384, in _plot
    plot_obj.generate()

  File "C:\Anaconda3\lib\site-packages\pandas\tools\plotting.py", line 987, in generate
    self._make_plot()

  File "C:\Anaconda3\lib\site-packages\pandas\tools\plotting.py", line 1664, in _make_plot
    **kwds)

  File "C:\Anaconda3\lib\site-packages\pandas\tools\plotting.py", line 1678, in _plot
    lines = MPLPlot._plot(ax, x, y_values, style=style, **kwds)

  File "C:\Anaconda3\lib\site-packages\pandas\tools\plotting.py", line 1293, in _plot
    return ax.errorbar(x, y, **kwds)

  File "C:\Anaconda3\lib\site-packages\matplotlib\__init__.py", line 1811, in inner
    return func(ax, *args, **kwargs)

  File "C:\Anaconda3\lib\site-packages\matplotlib\axes\_axes.py", line 2963, in errorbar
    iterable(yerr[0]) and len(yerr[0]) > 1))):

  File "C:\Anaconda3\lib\site-packages\pandas\core\series.py", line 557, in __getitem__
    result = self.index.get_value(self, key)

  File "C:\Anaconda3\lib\site-packages\pandas\core\index.py", line 3884, in get_value
    loc = self.get_loc(k)

  File "C:\Anaconda3\lib\site-packages\pandas\core\index.py", line 3942, in get_loc
    tolerance=tolerance)

  File "C:\Anaconda3\lib\site-packages\pandas\core\index.py", line 1759, in get_loc
    return self._engine.get_loc(key)

  File "pandas\index.pyx", line 137, in pandas.index.IndexEngine.get_loc (pandas\index.c:3979)

  File "pandas\index.pyx", line 157, in pandas.index.IndexEngine.get_loc (pandas\index.c:3843)

  File "pandas\hashtable.pyx", line 498, in pandas.hashtable.Float64HashTable.get_item (pandas\hashtable.c:9556)

  File "pandas\hashtable.pyx", line 504, in pandas.hashtable.Float64HashTable.get_item (pandas\hashtable.c:9494)

KeyError: 0.0

二,。df3.head（）的输出

---

你能显示完整的错误堆栈吗？将添加到main post只是一个猜测：看起来

df2

有一列名为

0.0

，而

df3

没有。所以我不知道这是否有帮助，但它们都只有“波长，Mon18th_C24_20%，Mon18th_C24_50%，Mon18th_C24_80%，Mon18th_Col0_20%，Mon18th_Col0_50%，Mon18th_Col0_80%”。这两个数据帧还表示它们有6列（索引称为波长）和2048行。感谢您迄今为止的帮助。您可以编辑您的问题以包括

df2.head（）

和

df3.head（）

？

            Mon18th_C24_20%  Mon18th_C24_50%  Mon18th_C24_80%  Mon18th_Col0_20%  Mon18th_Col0_50%  Mon18th_Col0_80%
Wavelength                                                                                                         
341.514           -1.963704        32.036429        13.413667         -1.396250            39.647        -23.480313
341.892           -1.963704        32.036429        13.413667         -1.396250            39.647        -23.480313
342.269           11.653704       -44.896786       180.915667         -6.503438            38.840         50.237812
342.646           18.801111       305.569286       532.147000        -27.857500           504.351         66.496562
343.024           28.421852        48.280000        65.551000        968.713437            79.782         63.419688

            Mon18th_C24_20%  Mon18th_C24_50%  Mon18th_C24_80%  Mon18th_Col0_20%  Mon18th_Col0_50%  Mon18th_Col0_80%
Wavelength                                                                                                         
341.514          103.027866       121.768024        98.039234         60.476486        101.865202        325.329848
341.892          103.027866       121.768024        98.039234         60.476486        101.865202        325.329848
342.269           59.441182       719.315230       643.463142         52.176211        606.273169        177.225557
342.646           41.717983       820.680259       922.506270         73.360823        689.563817         93.132120
343.024           47.129664        75.400200        73.011963       1728.405146         71.020783         52.873068