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10 changes: 5 additions & 5 deletions doc/source/getting_started/intro_tutorials/03_subset_data.rst
Original file line number Diff line number Diff line change
Expand Up @@ -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.
Expand Down Expand Up @@ -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``:

Expand Down Expand Up @@ -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

Expand Down
4 changes: 2 additions & 2 deletions doc/source/getting_started/intro_tutorials/04_plotting.rst
Original file line number Diff line number Diff line change
Expand Up @@ -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.

Expand Down Expand Up @@ -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.
Expand Down