Errore di tipo nella visualizzazione di dataframe panda come heatmap

Question

Sto provando a visualizzare un dataframe panda come heatmap, e sto ottenendo strani errori con tutte le funzioni di tracciamento che provo (ho provato con l'oggetto DataFrame e l'array DataFrame.values e niente i cambiamenti). Non capisco quale potrebbe essere la ragione per questo. Questo è il dataframe:

 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 

Ho provato diversi modi per tracciarlo. Ad esempio, 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' 

O 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 

E seaborn.heatmap dà questo:

--------------------------------------------------------------------------- 
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'' 

Quindi, è una specie di tipo problema, ma non riesco a vedere dove viene da. Ho provato a inserire entrambi i valori int e float nello DF, ma non cambia nulla.

Answer 1

L'ho capito dopo un po ': viene visualizzato che il tipo di DF.values è stato impostato su object. Può essere riparato dalla seguente riga:

DF = DF[DF.columns].astype(float) # or int 

Dopo che tutto funziona!

Answer 2

La modifica del tipo di valori del frame di dati non ha funzionato per me. Tuttavia, questo ha aiutato, non so perché salta il problema tipo:

plt.figure() 
    plt.pcolor(dataframe) 
    plt.colorbar() 
    plt.savefig("myheatmap.png") 
    plt.close()