尝试从数据集创建散点图时，TypeError：无法散列的类型：'numpy.ndarray'

Question

I am trying to create a scatter plot using a dataset on movies. The goal is to look at the correlation between the different categories and the target variable, whether or not the movie won an award. I have tried doing a type call on my variables, and neither of them appear to be of type numpy.ndarray as they are both pandas dataframes, yet I still get the following error when I try to create a scatter plot:

TypeError: unhashable type: 'numpy.ndarray'

My code is as follows:

import pandas as pd
import matplotlib.pyplot as plt

file=pd.read_csv('academy_awards.csv',sep=',',error_bad_lines=False,encoding="ISO 8859-1")
print(file)
df=pd.DataFrame(file)

#df=df.dropna(axis=0,how='any')
target=df.Category
X=pd.DataFrame(df.Won)

y=target
#print(type(X))
#print(type(y))

plt.scatter(X,y)

The following are the first 5 lines of the dataset I am using:

Year,Category,Nominee,Additional Info,Won
2010 (83rd),Actor -- Leading Role,Javier Bardem,Biutiful 
{'Uxbal'},NO
2010 (83rd),Actor -- Leading Role,Jeff Bridges,True Grit {'Rooster 
Cogburn'},NO
2010 (83rd),Actor -- Leading Role,Jesse Eisenberg,The Social 
Network {'Mark Zuckerberg'},NO
2010 (83rd),Actor -- Leading Role,Colin Firth,The King's Speech 
{'King George VI'},YES
2010 (83rd),Actor -- Leading Role,James Franco,127 Hours {'Aron 
Ralston'},NO
2010 (83rd),Actor -- Supporting Role,Christian Bale,The Fighter 
{'Dicky Eklund'},YES

Any help or suggestions are greatly appreciated!

Edit: The following is the full traceback--

-----------------------------------------------------------------------
TypeError                                 Traceback (most recent call 
last)
<ipython-input-211-efcb7c41bca1> in <module>
     14 print(y.shape)
     15 
---> 16 plt.scatter(X,y)

/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site- 
packages/matplotlib/pyplot.py in scatter(x, y, s, c, marker, cmap, 
norm, vmin, vmax, alpha, linewidths, verts, edgecolors, data, **kwargs)
   2862         vmin=vmin, vmax=vmax, alpha=alpha, 
linewidths=linewidths,
   2863         verts=verts, edgecolors=edgecolors, **({"data": data} 
if data
-> 2864         is not None else {}), **kwargs)
   2865     sci(__ret)
   2866     return __ret

/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site- 
packages/matplotlib/__init__.py in inner(ax, data, *args, **kwargs)
   1808                         "the Matplotlib list!)" % (label_namer, 
func.__name__),
   1809                         RuntimeWarning, stacklevel=2)
-> 1810             return func(ax, *args, **kwargs)
   1811 
   1812         inner.__doc__ = _add_data_doc(inner.__doc__,

/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site- 
packages/matplotlib/axes/_axes.py in scatter(self, x, y, s, c, marker, 
cmap, norm, vmin, vmax, alpha, linewidths, verts, edgecolors, **kwargs)
   4170             edgecolors = 'face'
   4171 
-> 4172         self._process_unit_info(xdata=x, ydata=y, 
kwargs=kwargs)
   4173         x = self.convert_xunits(x)
   4174         y = self.convert_yunits(y)

/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site- 
packages/matplotlib/axes/_base.py in _process_unit_info(self, xdata, 
ydata, kwargs)
   2133             return kwargs
   2134 
-> 2135         kwargs = _process_single_axis(xdata, self.xaxis, 
'xunits', kwargs)
   2136         kwargs = _process_single_axis(ydata, self.yaxis, 
'yunits', kwargs)
   2137         return kwargs

/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site- 
packages/matplotlib/axes/_base.py in _process_single_axis(data, axis, 
unit_name, kwargs)
   2116                 # We only need to update if there is nothing 
set yet.
   2117                 if not axis.have_units():
-> 2118                     axis.update_units(data)
   2119 
   2120             # Check for units in the kwargs, and if present 
update axis

/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site- 
packages/matplotlib/axis.py in update_units(self, data)
   1471         neednew = self.converter != converter
   1472         self.converter = converter
-> 1473         default = self.converter.default_units(data, self)
   1474         if default is not None and self.units is None:
   1475             self.set_units(default)

/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site- 
packages/matplotlib/category.py in default_units(data, axis)
    101         # default_units->axis_info->convert
    102         if axis.units is None:
--> 103             axis.set_units(UnitData(data))
    104         else:
    105             axis.units.update(data)

/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site- 
packages/matplotlib/category.py in __init__(self, data)
    167         self._counter = itertools.count()
    168         if data is not None:
--> 169             self.update(data)
    170 
    171     def update(self, data):

/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site- 
packages/matplotlib/category.py in update(self, data)
    184         data = np.atleast_1d(np.array(data, dtype=object))
    185 
--> 186         for val in OrderedDict.fromkeys(data):
    187             if not isinstance(val, (str, bytes)):
    188                 raise TypeError("{val!r} is not a 
string".format(val=val))

TypeError: unhashable type: 'numpy.ndarray'

Answer 1

Arrays are unhashable because they're mutable. You can hash it by converting it to an immutable tuple (by wrapping it with tuple() ) but you usually shouldn't be trying to hash arrays anyways. Your data is probably of the wrong shape.

Answer 2

First, you don't need to: df=pd.DataFrame(file) . After opening the CSV file with pandas and saved in the file variable, you already get the data as dataFrame.

Then, you can easily call the scatter and choose the x-axis and y-axis with

df.plot(kind ="scatter", x= "Won", y = "Category")

You don't need to preprocess the data, because of it's already preprocessed after opened the file with pandas.