DOC Fix FutureWarning in plot_linear_model_coefficient_interpretation
@@ -330,7 +330,7 @@ coefs = pd.DataFrame(
# %%
plt.figure(figsize=(9, 7))
-sns.stripplot(data=coefs, orient="h", color="k", alpha=0.5)
+sns.stripplot(data=coefs, orient="h", palette="dark:k", alpha=0.5)
sns.boxplot(data=coefs, orient="h", color="cyan", saturation=0.5, whis=10)
plt.axvline(x=0, color=".5")
plt.xlabel("Coefficient importance")
@@ -389,7 +389,7 @@ coefs = pd.DataFrame(
# %%
plt.figure(figsize=(9, 7))
-sns.stripplot(data=coefs, orient="h", color="k", alpha=0.5)
+sns.stripplot(data=coefs, orient="h", palette="dark:k", alpha=0.5)
sns.boxplot(data=coefs, orient="h", color="cyan", saturation=0.5)
plt.axvline(x=0, color=".5")
plt.title("Coefficient importance and its variability")
@@ -492,7 +492,7 @@ coefs = pd.DataFrame(
# %%
plt.figure(figsize=(9, 7))
-sns.stripplot(data=coefs, orient="h", color="k", alpha=0.5)
+sns.stripplot(data=coefs, orient="h", palette="dark:k", alpha=0.5)
sns.boxplot(data=coefs, orient="h", color="cyan", saturation=0.5, whis=10)
plt.axvline(x=0, color=".5")
plt.title("Coefficient variability")
@@ -699,7 +699,7 @@ coefs = pd.DataFrame(
# %%
plt.figure(figsize=(9, 7))
-sns.stripplot(data=coefs, orient="h", color="k", alpha=0.5)
+sns.stripplot(data=coefs, orient="h", palette="dark:k", alpha=0.5)
sns.boxplot(data=coefs, orient="h", color="cyan", saturation=0.5, whis=100)
plt.axvline(x=0, color=".5")
plt.title("Coefficient variability")
