pandas Series' 对象没有属性 'find'

Question

我正在尝试绘制简单的数据图并收到以下错误。非常感谢任何帮助

AttributeError:“系列”对象没有“查找”属性

版本： 蟒蛇3， matplotlib (2.0.2) , 熊猫（0.20.3）， jupyter (1.0.0)。

代码：

import pandas as pd
import matplotlib.pyplot as plt
pd_hr_data = pd.read_csv("/Users/pc/Downloads/HR_comma_sep.csv")

#print(pd_hr_data['average_montly_hours'],pd_hr_data['sales'])
take_ten_data = pd_hr_data[0:19]
x = take_ten_data['average_montly_hours'].astype(int)
y = take_ten_data['sales'].astype(str)
print(type(x[0]))
print(type(y[0]))
#print(x,y) ---- this gives me all the 20 values
#print(type(y[0]))
plt.plot(x,y)
plt.show()

输出/错误：

-

-------------------------------------------------- ------------------------- AttributeError Traceback（最近一次调用最后一次） 在 （） 9 #print(类型(y[0])) 10 ---> 11 plt.plot(x,y) 12 plt.show()

       /Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/matplotlib/pyplot.py
   in plot(*args, **kwargs)
          3315                       mplDeprecation)
          3316     try:
       -> 3317         ret = ax.plot(*args, **kwargs)
          3318     finally:
          3319         ax._hold = washold

       /Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/matplotlib/__init__.py
   in inner(ax, *args, **kwargs)
          1896                     warnings.warn(msg % (label_namer, func.__name__),
          1897                                   RuntimeWarning, stacklevel=2)
       -> 1898             return func(ax, *args, **kwargs)
          1899         pre_doc = inner.__doc__
          1900         if pre_doc is None:

       /Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/matplotlib/axes/_axes.py
   in plot(self, *args, **kwargs)
          1404         kwargs = cbook.normalize_kwargs(kwargs, _alias_map)
          1405 
       -> 1406         for line in self._get_lines(*args, **kwargs):
          1407             self.add_line(line)
          1408             lines.append(line)

       /Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/matplotlib/axes/_base.py
   in _grab_next_args(self, *args, **kwargs)
           405                 return
           406             if len(remaining) <= 3:
       --> 407                 for seg in self._plot_args(remaining, kwargs):
           408                     yield seg
           409                 return

       /Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/matplotlib/axes/_base.py
   in _plot_args(self, tup, kwargs)
           355         ret = []
           356         if len(tup) > 1 and is_string_like(tup[-1]):
       --> 357             linestyle, marker, color = _process_plot_format(tup[-1])
           358             tup = tup[:-1]
           359         elif len(tup) == 3:

       /Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/matplotlib/axes/_base.py
   in _process_plot_format(fmt)
            92     # handle the multi char special cases and strip them from the
            93     # string
       ---> 94     if fmt.find('--') >= 0:
            95         linestyle = '--'
            96         fmt = fmt.replace('--', '')

       /Library/Frameworks/Python.framework/Versions/3.6/lib/python3.6/site-packages/pandas/core/generic.py
   in __getattr__(self, name)
          3079             if name in self._info_axis:
          3080                 return self[name]
       -> 3081             return object.__getattribute__(self, name)
          3082 
          3083     def __setattr__(self, name, value):

       AttributeError: 'Series' object has no attribute 'find'

Answer 1

我认为您可以使用 DataFrame.plot 来定义 x 和 y 通过列名，因为它更好地支持绘制非数值：

take_ten_data = pd_hr_data[0:19]
x = take_ten_data['average_montly_hours'].astype(int)
y = take_ten_data['sales'].astype(str)

take_ten_data.plot(x='average_montly_hours', y='sales')
#working without x,y also, but less readable
#take_ten_data.plot('average_montly_hours','sales')
plt.show()

示例：

take_ten_data = pd.DataFrame({'average_montly_hours':[3,10,12], 'sales':[10,20,30]})
x = take_ten_data['average_montly_hours'].astype(int)
y = take_ten_data['sales'].astype(str)

take_ten_data.plot(x='average_montly_hours', y='sales')
plt.show()

---

但如果所有值都是数字，它会很好用：

take_ten_data = pd.DataFrame({'average_montly_hours':[3,10,12], 'sales':['10','20','30']})

x = take_ten_data['average_montly_hours'].astype(int)
#convert to int if necessary
y = take_ten_data['sales'].astype(int)

plt.plot(x,y)
plt.show()

Answer 2

以下对我有用，希望对您有所帮助....问题是混合不同的数据类型进行绘图。

    import pandas as pd
    import matplotlib.pyplot as plt
    pd_hr_data = pd.read_csv("/Users/pc/Downloads/HR_comma_sep.csv")
    take_ten_data = pd_hr_data[0:4]
    y = take_ten_data['average_montly_hours'].astype(int)
    x = [1,2,3,4] ----this is can be autogenerated based on the series/matrix size
    names = take_ten_data['sales']
    plt.bar(x,y, align='center')
    #plt.plot(x,y) ---- use this if you want 
    plt.xticks(x, names)
    plt.show()