Update heterogeneity.rst

doc/guide/heterogeneity.rst

@@ -345,7 +345,7 @@ Estimation is conducted via its ``fit()`` method:
             np.random.seed(3141)
             ml_g = RandomForestClassifier(n_estimators=100, max_features=20, max_depth=10, min_samples_leaf=2)
             ml_m = RandomForestClassifier(n_estimators=100, max_features=20, max_depth=10, min_samples_leaf=2)
-            data = make_iivm_data(theta=0.5, n_obs=1000, dim_x=20, return_type='DataFrame')
+            data = make_iivm_data(theta=0.5, n_obs=2000, dim_x=20, return_type='DataFrame')
             obj_dml_data = dml.DoubleMLData(data, 'y', 'd', z_cols='z')
             dml_lpq_obj = dml.DoubleMLLPQ(obj_dml_data, ml_g, ml_m, treatment=1, quantile=0.5)
             dml_lpq_obj.fit().summary