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#Set up the matplotlib figure and a diverging colormap:
f, ax = plt.subplots(figsize=(18, 15))
cmap = sns.diverging_palette(220, 10, as_cmap=True)
#Draw the heatmap with the mask and correct aspect ratio:
sns.heatmap(corr, mask=mask, cmap=cmap, vmax=.3, center=0,square=True,annot = True, linewidths=.5, cbar_kws={"shrink": .5})
AttributeError Traceback (most recent call last)
Cell In[43], line 7
3 corr = data2.corr()
5 #Generate a mask for the upper triangle:
----> 7 mask = np.zeros_like(corr, dtype=np.bool)
8 mask[np.triu_indices_from(mask)] = True
10 #Set up the matplotlib figure and a diverging colormap:
File ~\anaconda3\Lib\site-packages\numpy_init_.py:305, in getattr(attr)
300 warnings.warn(
301 f"In the future np.{attr} will be defined as the "
302 "corresponding NumPy scalar.", FutureWarning, stacklevel=2)
304 if attr in former_attrs:
--> 305 raise AttributeError(former_attrs[attr])
307 # Importing Tester requires importing all of UnitTest which is not a
308 # cheap import Since it is mainly used in test suits, we lazy import it
309 # here to save on the order of 10 ms of import time for most users
310 #
311 # The previous way Tester was imported also had a side effect of adding
312 # the full numpy.testing namespace
313 if attr == 'testing':
AttributeError: module 'numpy' has no attribute 'bool'. np.bool was a deprecated alias for the builtin bool. To avoid this error in existing code, use bool by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, use np.bool_ here.
The aliases was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at: https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations@Pradnya1208
The text was updated successfully, but these errors were encountered:
#Set and compute the Correlation Matrix:
sns.set(style="white")
corr = data2.corr()
#Generate a mask for the upper triangle:
mask = np.zeros_like(corr, dtype=np.bool)
mask[np.triu_indices_from(mask)] = True
#Set up the matplotlib figure and a diverging colormap:
f, ax = plt.subplots(figsize=(18, 15))
cmap = sns.diverging_palette(220, 10, as_cmap=True)
#Draw the heatmap with the mask and correct aspect ratio:
sns.heatmap(corr, mask=mask, cmap=cmap, vmax=.3, center=0,square=True,annot = True, linewidths=.5, cbar_kws={"shrink": .5})
AttributeError Traceback (most recent call last)
Cell In[43], line 7
3 corr = data2.corr()
5 #Generate a mask for the upper triangle:
----> 7 mask = np.zeros_like(corr, dtype=np.bool)
8 mask[np.triu_indices_from(mask)] = True
10 #Set up the matplotlib figure and a diverging colormap:
File ~\anaconda3\Lib\site-packages\numpy_init_.py:305, in getattr(attr)
300 warnings.warn(
301 f"In the future
np.{attr}
will be defined as the "302 "corresponding NumPy scalar.", FutureWarning, stacklevel=2)
304 if attr in former_attrs:
--> 305 raise AttributeError(former_attrs[attr])
307 # Importing Tester requires importing all of UnitTest which is not a
308 # cheap import Since it is mainly used in test suits, we lazy import it
309 # here to save on the order of 10 ms of import time for most users
310 #
311 # The previous way Tester was imported also had a side effect of adding
312 # the full
numpy.testing
namespace313 if attr == 'testing':
AttributeError: module 'numpy' has no attribute 'bool'.
np.bool
was a deprecated alias for the builtinbool
. To avoid this error in existing code, usebool
by itself. Doing this will not modify any behavior and is safe. If you specifically wanted the numpy scalar type, usenp.bool_
here.The aliases was originally deprecated in NumPy 1.20; for more details and guidance see the original release note at:
https://numpy.org/devdocs/release/1.20.0-notes.html#deprecations @Pradnya1208
The text was updated successfully, but these errors were encountered: