fix some docs issues

plotly · LiamConnors · Dec 9, 2025 · Dec 9, 2025 · Dec 9, 2025 · Dec 9, 2025
commit b630ada5c1db5d94a0c6ec2b0678d982ecff6d26
diff --git a/doc/python/bar-charts.md b/doc/python/bar-charts.md
@@ -772,7 +772,7 @@ fig.show()
 
 ### Colored and Styled Bar Chart
 
-In this example several parameters of the layout as customized, hence it is convenient to use directly the `go.Layout(...)` constructor instead of calling `fig.update`.
+In this example several parameters of the layout are customized, hence it is convenient to use directly the `go.Layout(...)` constructor instead of calling `fig.update`.
 
 ```python
 import plotly.graph_objects as go

diff --git a/doc/python/discrete-color.md b/doc/python/discrete-color.md
@@ -162,7 +162,7 @@ fig = px.bar(df, y="continent", x="pop", color="continent", orientation="h", hov
 fig.show()
 ```
 
-**_Warning_**: If your color sequence is has fewer colors than the number of unique values in the column you are mapping to `color`, the colors will cycle through and repeat, possibly leading to ambiguity:
+**_Warning_**: If your color sequence has fewer colors than the number of unique values in the column you are mapping to `color`, the colors will cycle through and repeat, possibly leading to ambiguity:
 
 ```python
 import plotly.express as px

diff --git a/doc/python/ml-knn.md b/doc/python/ml-knn.md
@@ -264,6 +264,7 @@ import plotly.express as px
 import plotly.graph_objects as go
 import numpy as np
 from sklearn.neighbors import KNeighborsClassifier
+from sklearn.model_selection import train_test_split
 
 mesh_size = .02
 margin = 1

diff --git a/doc/python/ml-pca.md b/doc/python/ml-pca.md
@@ -222,6 +222,7 @@ For more details about the linear algebra behind eigenvectors and loadings, see
 
 ```python
 import plotly.express as px
+import numpy as np
 from sklearn.decomposition import PCA
 from sklearn import datasets
 from sklearn.preprocessing import StandardScaler

diff --git a/doc/python/splom.md b/doc/python/splom.md
@@ -256,7 +256,7 @@ fig.show()
 Diabetes dataset is downloaded from [kaggle](https://www.kaggle.com/uciml/pima-indians-diabetes-database/data). It is used to predict the onset of diabetes based on 8 diagnostic measures. The diabetes file contains the diagnostic measures for 768 patients, that are labeled as non-diabetic (Outcome=0), respectively diabetic (Outcome=1). The splom associated to the 8 variables can illustrate the strength of the relationship between pairs of measures for diabetic/nondiabetic patients.
 
 ```python
-import plotly.graph_objs as go
+import plotly.graph_objects as go
 import pandas as pd
 
 dfd = pd.read_csv('https://raw.githubusercontent.com/plotly/datasets/master/diabetes.csv')

diff --git a/doc/python/subplots.md b/doc/python/subplots.md
@@ -22,7 +22,7 @@ jupyter:
     pygments_lexer: ipython3
     version: 3.11.10
   plotly:
-    description: How to make subplots in with Plotly's Python graphing library. Examples
+    description: How to make subplots with Plotly's Python graphing library. Examples
       of stacked, custom-sized, gridded, and annotated subplots.
     display_as: file_settings
     language: python

diff --git a/doc/python/templates.md b/doc/python/templates.md
@@ -37,7 +37,7 @@ jupyter:
 
 The Plotly Python library comes pre-loaded with several themes that you can get started using right away, and it also provides support for creating and registering your own themes.
 
-> Note on terminology: Theming generally refers to the process of defining default styles for visual elements. Themes in plotly are implemented using objects called templates. Templates are slightly more general than traditional themes because in addition to defining default styles, templates can pre-populate a figure with visual elements like annotations, shapes, images, and more. In the documentation we will refer to the overall process of defining default styles as theming, and when in comes to the plotly API we will talk about how themes are implemented using templates.
+> Note on terminology: Theming generally refers to the process of defining default styles for visual elements. Themes in plotly are implemented using objects called templates. Templates are slightly more general than traditional themes because in addition to defining default styles, templates can pre-populate a figure with visual elements like annotations, shapes, images, and more. In the documentation we will refer to the overall process of defining default styles as theming, and when it comes to the plotly API we will talk about how themes are implemented using templates.
 
 ### Using built-in themes