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Seaborn lmplot annotate correlation
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Closed 4 days ago.
ax = sns.lmplot(x=i, y="Y_Quality", data=X_train, hue="Y_Class")
I want to print the slope values of the lines, but I only found that lmplot just doing line visualizes.
How do I print gradient values with Seaborn's lmplot?
np.arctan(Y,X)
I tried archan, archan2 but it didn't
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I'm plotting a seaborn plot, for example:
sns.pointplot (x=[1,2,3,10], y=[2,3,4,5])
How can I make the X ticks to have spcaing that represents their values? 10 should be further apart but the spacing is equal.
ax.xaxis.set_ticks([1,2,3,10]) does not work
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Bar labels in matplotlib/Seaborn
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Closed 5 months ago.
Image
The attached image shows the image of the seaborn plot. The values shown on the top of the graph are already rounded in the dataframe but the plot does not show the rounded values.
How can I do that?
Rounded with:
data["Marks (%)"] = data["Marks (%)"].apply(lambda x: round(x,1))
Seaborn code to showcase these values on top of the bar:
for i in ax.containers:
ax.bar_label(i, fontsize = 14)
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seaborn boxplot and stripplot points aren't aligned over the x-axis by hue
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Closed 7 months ago.
I'm trying to make a box plot and a strip plot from the following dataframe, but I think I'm not putting the arguments or maybe the df should be re-arranged but I don't know how.
the dataframe is here
I'm hopping to have a strip plot and a box for each color (column) in the same plot.
I'd be grateful if you could help
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Closed 10 months ago.
I am using the Wisconsin Breast Cancer dataset for a class project and I am attempting to display 10 KDE plots in 5 x 2 layout. Unfortunately,the plots are displayed in scrollable window which is definitely not what I would like.
features = ['radius_mean', 'texture_mean', 'perimeter_mean', 'area_mean', 'smoothness_mean', 'compactness_mean', 'concavity_mean', 'concave_points_mean', 'symmetry_mean', fractal_dimension_mean']
for feature in features:
df[feature].plot.kde(title=feature)
plt.show()
Any help would be appreciated.
Thank you.
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I used sns.distplot, but it is a deprecated function.
Is there any good alternative that have 'fit'?
sns.distplot(y, kde=False, fit=stats.norm)
Right now I'm using this
s1, loc2, scale2 = lognorm.fit(y)
r2 = lognorm.rvs(s1, loc2, scale2, size=r_size)
sns.histplot(data=r2, kde='True', ax=axes[1], alpha = 0)
sns.histplot(data=y, ax=axes[1])
axes[1].set_title('Log Normal')