嘗試在matplotlib中繪制或直方圖熊貓數據時出現KeyError

Question

我從導入的csv文件生成基本分布直方圖時遇到問題。 該代碼適用於來自另一個csv的一組數據，但不適用於我感興趣的一組，這基本上是相同的。 這是我嘗試過的代碼：

import pandas as pd
import numpy as np
import matplotlib as plt
data = pd.read_csv("idcases.csv")
data1 = data[(data["Disease"] == "Amebiasis") & (data["County"] == "Marin")]
data2 = data[(data["Disease"] == "Amebiasis") & (data["County"] == "Sonoma")]

fig = plt.pyplot.figure()
ax = fig.add_subplot(111)
ax.hist(data1['Population'], bins =10, range = (data1['Population'].min(), data1['Population'].max()))
plt.pyplot.xlabel('Population')
plt.pyplot.ylabel('Count of Population')
plt.pyplot.show()

產生：

---------------------------------------------------------------------------
KeyError                                  Traceback (most recent call last)
<ipython-input-35-63303aa9d8a5> in <module>()
      1 fig = plt.pyplot.figure()
      2 ax = fig.add_subplot(111)
----> 3 ax.hist(data1['Population'], bins =10, range = (data1['Population'].min(), data1['Population'].max()))
  4 plt.pyplot.xlabel('Count')
  5 plt.pyplot.ylabel('Count of Population')

C:\Program Files (x86)\Anaconda\lib\site-packages\matplotlib\axes\_axes.py in hist(self, x, bins, range, normed, weights, cumulative, bottom, histtype, align, orientation, rwidth, log, color, label, stacked, **kwargs)
   5602         # Massage 'x' for processing.
   5603         # NOTE: Be sure any changes here is also done below to 'weights'
-> 5604         if isinstance(x, np.ndarray) or not iterable(x[0]):
   5605             # TODO: support masked arrays;
   5606             x = np.asarray(x)

C:\Program Files (x86)\Anaconda\lib\site-packages\pandas\core\series.py in __getitem__(self, key)
    549     def __getitem__(self, key):
    550         try:
--> 551             result = self.index.get_value(self, key)
    552 
    553             if not np.isscalar(result):

C:\Program Files (x86)\Anaconda\lib\site-packages\pandas\core\index.py in get_value(self, series, key)
   1721 
   1722         try:
-> 1723             return self._engine.get_value(s, k)
   1724         except KeyError as e1:
   1725             if len(self) > 0 and self.inferred_type in ['integer','boolean']:

pandas\index.pyx in pandas.index.IndexEngine.get_value (pandas\index.c:3204)()

pandas\index.pyx in pandas.index.IndexEngine.get_value (pandas\index.c:2903)()

pandas\index.pyx in pandas.index.IndexEngine.get_loc (pandas\index.c:3843)()

pandas\hashtable.pyx in pandas.hashtable.Int64HashTable.get_item (pandas\hashtable.c:6525)()

pandas\hashtable.pyx in pandas.hashtable.Int64HashTable.get_item (pandas\hashtable.c:6463)()

KeyError: 0L

我究竟做錯了什么？ 這是我正在讀取的數據的一部分。 該代碼不適用於任何字段，包括“計數”或“費率”

       Disease County  Year     Sex  Count  Population   Rate  CI.lower  \
882  Amebiasis  Marin  2001   Total     14      247731  5.651     3.090   
883  Amebiasis  Marin  2001  Female      0      125414  0.000     0.000   
884  Amebiasis  Marin  2001    Male      0      122317  0.000     0.000   
885  Amebiasis  Marin  2002   Total      7      247382  2.830     1.138   
886  Amebiasis  Marin  2002  Female      0      125308  0.000     0.000   
887  Amebiasis  Marin  2002    Male      0      122074  0.000     0.000   
888  Amebiasis  Marin  2003   Total      9      247280  3.640     1.664   
889  Amebiasis  Marin  2003  Female      0      125259  0.000     0.000   
890  Amebiasis  Marin  2003    Male      0      122021  0.000     0.000   

Answer 1

從matploblib-v1.4.3升級到matplotlib-v1.5.0 ，我注意到對pandas.Series繪制pandas.Series停止工作，例如：

ax.plot_date(df['date'], df['raw'], '.-', label='raw')

會導致KeyError: 0異常。

快速解決方案：

您需要將numpy.ndarray而不是pandas.Series傳遞給plot_date函數：

ax.plot_date(df['date'].values, df['raw'].values, '.-', label='raw')

更多細節：

讓我們看一下異常的完整回溯：

# ... PREVIOUS TRACEBACK MESSAGES OMITTED FOR BREVITY ...

C:\Users\pedromdu\AppData\Local\Continuum\Anaconda3\lib\site-packages\matplotlib\dates.py in default_units(x, axis)
   1562 
   1563         try:
-> 1564             x = x[0]
   1565         except (TypeError, IndexError):
   1566             pass

C:\Users\pedromdu\AppData\Local\Continuum\Anaconda3\lib\site-packages\pandas\core\series.py in __getitem__(self, key)
    555     def __getitem__(self, key):
    556         try:
--> 557             result = self.index.get_value(self, key)
    558 
    559             if not np.isscalar(result):

C:\Users\pedromdu\AppData\Local\Continuum\Anaconda3\lib\site-packages\pandas\core\index.py in get_value(self, series, key)
   1788 
   1789         try:
-> 1790             return self._engine.get_value(s, k)
   1791         except KeyError as e1:
   1792             if len(self) > 0 and self.inferred_type in ['integer','boolean']:

pandas\index.pyx in pandas.index.IndexEngine.get_value (pandas\index.c:3204)()

pandas\index.pyx in pandas.index.IndexEngine.get_value (pandas\index.c:2903)()

pandas\index.pyx in pandas.index.IndexEngine.get_loc (pandas\index.c:3843)()

pandas\hashtable.pyx in pandas.hashtable.Int64HashTable.get_item (pandas\hashtable.c:6525)()

pandas\hashtable.pyx in pandas.hashtable.Int64HashTable.get_item (pandas\hashtable.c:6463)()

KeyError: 0

請注意，該錯誤源於matploblib嘗試執行x=x[0] 。 如果您的pandas系列未使用從零開始的整數索引，則將失敗，因為這將查找索引值為0 ，而不是pandas.Series的0th元素。

為了解決這個問題，我們需要從numpy.ndarray中的數據中獲取一個pandas.Series ，然后將其用於繪圖：

ax.plot_date(df['date'].values, df['raw'].values, '.-', label='raw')

Answer 2

給我的情節：

import io
import matplotlib.pyplot as plt


s = """       Disease County  Year     Sex  Count  Population   Rate  CI.lower
 Amebiasis  Marin  2001   Total     14      247731  5.651     3.090   
 Amebiasis  Marin  2001  Female      0      125414  0.000     0.000   
Amebiasis  Marin  2001    Male      0      122317  0.000     0.000   
Amebiasis  Marin  2002   Total      7      247382  2.830     1.138   
Amebiasis  Marin  2002  Female      0      125308  0.000     0.000   
 Amebiasis  Marin  2002    Male      0      122074  0.000     0.000   
Amebiasis  Marin  2003   Total      9      247280  3.640     1.664   
Amebiasis  Marin  2003  Female      0      125259  0.000     0.000   
 Amebiasis  Marin  2003    Male      0      122021  0.000     0.000  """
fobj = io.StringIO(s)
data1 = pd.read_csv(fobj, delim_whitespace=True)
plt.hist(data1['Population'], bins =10, range = (data1['Population'].min(), data1['Population'].max()))
plt.xlabel('Population')
plt.ylabel('Count of Population')
plt.show()