将熊猫数据框可视化为热图时出现类型错误
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【中文标题】将熊猫数据框可视化为热图时出现类型错误【英文标题】：Type error in visualising pandas dataframe as heatmap 【发布时间】：2015-08-09 17:55:36 【问题描述】：我正在尝试将 pandas 数据框可视化为热图，但我尝试的所有绘图功能都出现了奇怪的错误（我尝试了 DataFrame 对象和 DataFrame.values 数组，但没有任何变化）。我不明白这可能是什么原因。这是数据框：
1 2 3 4 5 6 7 8 9 10 11 12 \
1 0 1163 986 1105 1315 1472 844 560 1033 867 610 703
2 1163 0 1774 803 1091 899 704 806 891 648 1082 1199
3 986 1774 0 679 880 798 1268 931 560 1128 774 481
4 1105 803 679 0 742 654 887 765 1113 1079 605 928
5 1315 1091 880 742 0 924 580 658 1073 1008 719 699
6 1472 899 798 654 924 0 619 991 1290 1002 1290 540
7 844 704 1268 887 580 619 0 639 611 717 812 469
8 560 806 931 765 658 991 639 0 788 1469 498 588
9 1033 891 560 1113 1073 1290 611 788 0 665 1172 621
10 867 648 1128 1079 1008 1002 717 1469 665 0 728 1060
11 610 1082 774 605 719 1290 812 498 1172 728 0 1146
12 703 1199 481 928 699 540 469 588 621 1060 1146 0
13 1193 1065 1163 458 364 741 713 663 777 529 492 548
14 909 902 894 369 439 768 1043 350 975 1058 630 558
15 877 957 1303 516 604 954 403 784 987 510 1126 617
16 1035 662 456 584 812 1049 856 856 684 358 1098 685
17 1191 496 770 1083 417 809 635 669 912 366 336 418
18 1118 1118 590 550 930 665 501 664 577 918 458 574
19 429 526 324 786 658 215 308 518 522 331 540 487
X 1333 1273 589 908 691 604 1243 1085 853 591 696 921
13 14 15 16 17 18 19 X
1 1193 909 877 1035 1191 1118 429 1333
2 1065 902 957 662 496 1118 526 1273
3 1163 894 1303 456 770 590 324 589
4 458 369 516 584 1083 550 786 908
5 364 439 604 812 417 930 658 691
6 741 768 954 1049 809 665 215 604
7 713 1043 403 856 635 501 308 1243
8 663 350 784 856 669 664 518 1085
9 777 975 987 684 912 577 522 853
10 529 1058 510 358 366 918 331 591
11 492 630 1126 1098 336 458 540 696
12 548 558 617 685 418 574 487 921
13 0 807 504 672 421 446 726 847
14 807 0 408 616 304 781 270 715
15 504 408 0 495 331 614 239 577
16 672 616 495 0 199 324 358 597
17 421 304 331 199 0 622 678 303
18 446 781 614 324 622 0 501 373
19 726 270 239 358 678 501 0 237
X 847 715 577 597 303 373 237 0
我尝试了不同的方法来绘制它。例如pcolor:
---------------------------------------------------------------------------
AttributeError Traceback (most recent call last)
<ipython-input-16-88566b82f0f0> in <module>()
1 inter_chr = a.make_intrachromosomal_map(BD.dataDict['26769'])
----> 2 plt.pcolor(inter_chr)
3 plt.show()
/usr/local/lib/python2.7/dist-packages/matplotlib/pyplot.pyc in pcolor(*args, **kwargs)
3016 ax.hold(hold)
3017 try:
-> 3018 ret = ax.pcolor(*args, **kwargs)
3019 draw_if_interactive()
3020 finally:
/usr/local/lib/python2.7/dist-packages/matplotlib/axes/_axes.pyc in pcolor(self, *args, **kwargs)
4965 collection.set_norm(norm)
4966 collection.set_clim(vmin, vmax)
-> 4967 collection.autoscale_None()
4968 self.grid(False)
4969
/usr/local/lib/python2.7/dist-packages/matplotlib/cm.pyc in autoscale_None(self)
333 if self._A is None:
334 raise TypeError('You must first set_array for mappable')
--> 335 self.norm.autoscale_None(self._A)
336 self.changed()
337
/usr/local/lib/python2.7/dist-packages/matplotlib/colors.pyc in autoscale_None(self, A)
952 ' autoscale only None-valued vmin or vmax'
953 if self.vmin is None and np.size(A) > 0:
--> 954 self.vmin = ma.min(A)
955 if self.vmax is None and np.size(A) > 0:
956 self.vmax = ma.max(A)
/usr/local/lib/python2.7/dist-packages/numpy/ma/core.pyc in min(obj, axis, out, fill_value)
6025 # If obj doesn't have a min method,
6026 # ...or if the method doesn't accept a fill_value argument
-> 6027 return asanyarray(obj).min(axis=axis, fill_value=fill_value, out=out)
6028 min.__doc__ = MaskedArray.min.__doc__
6029
/usr/local/lib/python2.7/dist-packages/numpy/ma/core.pyc in min(self, axis, out, fill_value)
5179 # No explicit output
5180 if out is None:
-> 5181 result = self.filled(fill_value).min(axis=axis, out=out).view(type(self))
5182 if result.ndim:
5183 # Set the mask
AttributeError: 'int' object has no attribute 'view'
或imshow:
---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
<ipython-input-17-1d4365bb4ce8> in <module>()
1 inter_chr = a.make_intrachromosomal_map(BD.dataDict['26769'])
----> 2 plt.imshow(inter_chr)
3 plt.show()
/usr/local/lib/python2.7/dist-packages/matplotlib/pyplot.pyc in imshow(X, cmap, norm, aspect, interpolation, alpha, vmin, vmax, origin, extent, shape, filternorm, filterrad, imlim, resample, url, hold, **kwargs)
2959 vmax=vmax, origin=origin, extent=extent, shape=shape,
2960 filternorm=filternorm, filterrad=filterrad,
-> 2961 imlim=imlim, resample=resample, url=url, **kwargs)
2962 draw_if_interactive()
2963 finally:
/usr/local/lib/python2.7/dist-packages/matplotlib/axes/_axes.pyc in imshow(self, X, cmap, norm, aspect, interpolation, alpha, vmin, vmax, origin, extent, shape, filternorm, filterrad, imlim, resample, url, **kwargs)
4642 filterrad=filterrad, resample=resample, **kwargs)
4643
-> 4644 im.set_data(X)
4645 im.set_alpha(alpha)
4646 if im.get_clip_path() is None:
/usr/local/lib/python2.7/dist-packages/matplotlib/image.pyc in set_data(self, A)
432 if (self._A.dtype != np.uint8 and
433 not np.can_cast(self._A.dtype, np.float)):
--> 434 raise TypeError("Image data can not convert to float")
435
436 if (self._A.ndim not in (2, 3) or
TypeError: Image data can not convert to float
seaborn.heatmap 给出了这个：
---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
<ipython-input-18-7ce156cf69d4> in <module>()
1 inter_chr = a.make_intrachromosomal_map(BD.dataDict['26769'])
----> 2 sns.heatmap(inter_chr)
3 plt.show()
/usr/local/lib/python2.7/dist-packages/seaborn/matrix.pyc in heatmap(data, vmin, vmax, cmap, center, robust, annot, fmt, annot_kws, linewidths, linecolor, cbar, cbar_kws, cbar_ax, square, ax, xticklabels, yticklabels, mask, **kwargs)
330 plotter = _HeatMapper(data, vmin, vmax, cmap, center, robust, annot, fmt,
331 annot_kws, cbar, cbar_kws, xticklabels, yticklabels,
--> 332 mask)
333
334 # Add the pcolormesh kwargs here
/usr/local/lib/python2.7/dist-packages/seaborn/matrix.pyc in __init__(self, data, vmin, vmax, cmap, center, robust, annot, fmt, annot_kws, cbar, cbar_kws, xticklabels, yticklabels, mask)
145 # Determine good default values for the colormapping
146 self._determine_cmap_params(plot_data, vmin, vmax,
--> 147 cmap, center, robust)
148
149 # Save other attributes to the object
/usr/local/lib/python2.7/dist-packages/seaborn/matrix.pyc in _determine_cmap_params(self, plot_data, vmin, vmax, cmap, center, robust)
159 cmap, center, robust):
160 """Use some heuristics to set good defaults for colorbar and range."""
--> 161 calc_data = plot_data.data[~np.isnan(plot_data.data)]
162 if vmin is None:
163 vmin = np.percentile(calc_data, 2) if robust else calc_data.min()
TypeError: ufunc 'isnan' not supported for the input types, and the inputs could not be safely coerced to any supported types according to the casting rule ''safe''
所以，这是某种类型问题，但我看不出它来自哪里。我尝试将int 和float 值都放入DF，但没有任何变化。
【问题讨论】：
【参考方案1】：过了一会才弄明白：好像DF.values的类型设置为object。它可以通过以下行修复：
DF = DF[DF.columns].astype(float) # or int
之后一切正常！
【讨论】：
【参考方案2】：更改数据框值的类型对我不起作用。但是，这有帮助，我不知道为什么它会跳过类型问题：
plt.figure()
plt.pcolor(dataframe)
plt.colorbar()
plt.savefig("myheatmap.png")
plt.close()
【讨论】：
【参考方案3】：我也有同样的问题。在将我的 2D 列表转换为 DataFrame 之前，我运行了一个 for 循环，使用以下代码将每个条目转换为浮点数 ...
test = [test[i].astype(float) for i in range(len(test))]
【讨论】：
【参考方案4】：除了@Phlya，你可以直接用dtype=np.float64初始化数据框
df = pd.Dataframe(index=[0,1,2,3], columns=['a','b','c','d'], dtype=np.float64)
【讨论】：
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