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Configure the Plot Style:
Set the background style using Seaborn.
sns.set(style="white")
2)Calculate the Correlation Matrix:
Compute the correlation values between features in data2.
corr = data2.corr()
3)Create an Upper Triangle Mask:
Initialize a matrix of zeros with the same shape as corr.
Convert it into a boolean type.
Set the upper triangle to True to mask it in the heatmap.
mask = np.zeros_like(corr, dtype=np.bool)
mask[np.triu_indices_from(mask)] = True
4)Set Up the Plot and Color Palette:
Create a figure with specified dimensions.
Define a diverging colormap for the heatmap.
f, ax = plt.subplots(figsize= (18, 15))
cmap = sns.diverging_palette(220, 10, as_cmap=True)
5)Generate the Heatmap:
Plot the heatmap with the correlation matrix.
Apply the mask to hide the upper triangle.
Use the diverging colormap, center it at 0, and set annotations, linewidths, and color bar properties.
sns.heatmap(corr, mask=mask, cmap=cmap, vmax=.3, center=0,
square=True, annot=True, linewidths=.5, cbar_kws= {"shrink": .5})
The error occurs because np.bool is deprecated in newer versions of NumPy. Instead, bool (the built-in Python type) should be used. The corrected line should be:
mask = np.zeros_like(corr, dtype=bool)
This change prevents the Attribute Error, ensuring compatibility with the latest NumPy versions.
The text was updated successfully, but these errors were encountered:
Set the background style using Seaborn.
sns.set(style="white")
2)Calculate the Correlation Matrix:
Compute the correlation values between features in data2.
corr = data2.corr()
3)Create an Upper Triangle Mask:
Initialize a matrix of zeros with the same shape as corr.
Convert it into a boolean type.
Set the upper triangle to True to mask it in the heatmap.
mask = np.zeros_like(corr, dtype=np.bool)
mask[np.triu_indices_from(mask)] = True
4)Set Up the Plot and Color Palette:
Create a figure with specified dimensions.
Define a diverging colormap for the heatmap.
f, ax = plt.subplots(figsize= (18, 15))
cmap = sns.diverging_palette(220, 10, as_cmap=True)
5)Generate the Heatmap:
Plot the heatmap with the correlation matrix.
Apply the mask to hide the upper triangle.
Use the diverging colormap, center it at 0, and set annotations, linewidths, and color bar properties.
sns.heatmap(corr, mask=mask, cmap=cmap, vmax=.3, center=0,
square=True, annot=True, linewidths=.5, cbar_kws= {"shrink": .5})
The error occurs because np.bool is deprecated in newer versions of NumPy. Instead, bool (the built-in Python type) should be used. The corrected line should be:
mask = np.zeros_like(corr, dtype=bool)
This change prevents the Attribute Error, ensuring compatibility with the latest NumPy versions.
The text was updated successfully, but these errors were encountered: