23
23
<div class =" card-body" >
24
24
<p class =" card-text" >
25
25
26
- This tutorial uses the titanic data set, stored as CSV. The data
26
+ This tutorial uses the Titanic data set, stored as CSV. The data
27
27
consists of the following data columns:
28
28
29
29
- PassengerId: Id of every passenger.
@@ -72,7 +72,7 @@ How do I select specific columns from a ``DataFrame``?
72
72
<ul class =" task-bullet" >
73
73
<li >
74
74
75
- I’m interested in the age of the titanic passengers.
75
+ I’m interested in the age of the Titanic passengers.
76
76
77
77
.. ipython :: python
78
78
@@ -111,7 +111,7 @@ the number of rows is returned.
111
111
<ul class =" task-bullet" >
112
112
<li >
113
113
114
- I’m interested in the age and sex of the titanic passengers.
114
+ I’m interested in the age and sex of the Titanic passengers.
115
115
116
116
.. ipython :: python
117
117
@@ -198,7 +198,7 @@ can be used to filter the ``DataFrame`` by putting it in between the
198
198
selection brackets ``[] ``. Only rows for which the value is ``True ``
199
199
will be selected.
200
200
201
- We now from before that the original titanic ``DataFrame `` consists of
201
+ We know from before that the original Titanic ``DataFrame `` consists of
202
202
891 rows. Let’s have a look at the amount of rows which satisfy the
203
203
condition by checking the ``shape `` attribute of the resulting
204
204
``DataFrame `` ``above_35 ``:
@@ -212,7 +212,7 @@ condition by checking the ``shape`` attribute of the resulting
212
212
<ul class =" task-bullet" >
213
213
<li >
214
214
215
- I’m interested in the titanic passengers from cabin class 2 and 3.
215
+ I’m interested in the Titanic passengers from cabin class 2 and 3.
216
216
217
217
.. ipython :: python
218
218
0 commit comments