diff --git a/doc/source/getting_started/intro_tutorials/03_subset_data.rst b/doc/source/getting_started/intro_tutorials/03_subset_data.rst
index 8476fee5e1eee..a718c39620ce5 100644
--- a/doc/source/getting_started/intro_tutorials/03_subset_data.rst
+++ b/doc/source/getting_started/intro_tutorials/03_subset_data.rst
@@ -27,14 +27,14 @@ This tutorial uses the Titanic data set, stored as CSV. The data
 consists of the following data columns:
 
 -  PassengerId: Id of every passenger.
--  Survived: This feature have value 0 and 1. 0 for not survived and 1
+-  Survived: This feature has value 0 and 1. 0 for not survived and 1
    for survived.
 -  Pclass: There are 3 classes: Class 1, Class 2 and Class 3.
 -  Name: Name of passenger.
 -  Sex: Gender of passenger.
 -  Age: Age of passenger.
--  SibSp: Indication that passenger have siblings and spouse.
--  Parch: Whether a passenger is alone or have family.
+-  SibSp: Indication that passengers have siblings and spouses.
+-  Parch: Whether a passenger is alone or has a family.
 -  Ticket: Ticket number of passenger.
 -  Fare: Indicating the fare.
 -  Cabin: The cabin of passenger.
@@ -199,7 +199,7 @@ selection brackets ``[]``. Only rows for which the value is ``True``
 will be selected.
 
 We know from before that the original Titanic ``DataFrame`` consists of
-891 rows. Let’s have a look at the amount of rows which satisfy the
+891 rows. Let’s have a look at the number of rows which satisfy the
 condition by checking the ``shape`` attribute of the resulting
 ``DataFrame`` ``above_35``:
 
@@ -398,7 +398,7 @@ See the user guide section on :ref:`different choices for indexing <indexing.cho
     <div class="d-flex flex-row gs-torefguide">
         <span class="badge badge-info">To user guide</span>
 
-A full overview about indexing is provided in the user guide pages on :ref:`indexing and selecting data <indexing>`.
+A full overview of indexing is provided in the user guide pages on :ref:`indexing and selecting data <indexing>`.
 
 .. raw:: html
 
diff --git a/doc/source/getting_started/intro_tutorials/04_plotting.rst b/doc/source/getting_started/intro_tutorials/04_plotting.rst
index f3d99ee56359a..9102de98a6c2a 100644
--- a/doc/source/getting_started/intro_tutorials/04_plotting.rst
+++ b/doc/source/getting_started/intro_tutorials/04_plotting.rst
@@ -167,7 +167,7 @@ I want each of the columns in a separate subplot.
     @savefig 04_airqual_area_subplot.png
     axs = air_quality.plot.area(figsize=(12, 4), subplots=True)
 
-Separate subplots for each of the data columns is supported by the ``subplots`` argument
+Separate subplots for each of the data columns are supported by the ``subplots`` argument
 of the ``plot`` functions. The builtin options available in each of the pandas plot
 functions that are worthwhile to have a look.
 
@@ -213,7 +213,7 @@ I want to further customize, extend or save the resulting plot.
         </li>
     </ul>
 
-Each of the plot objects created by pandas are a
+Each of the plot objects created by pandas is a
 `matplotlib <https://matplotlib.org/>`__ object. As Matplotlib provides
 plenty of options to customize plots, making the link between pandas and
 Matplotlib explicit enables all the power of matplotlib to the plot.