You signed in with another tab or window. Reload to refresh your session.You signed out in another tab or window. Reload to refresh your session.You switched accounts on another tab or window. Reload to refresh your session.Dismiss alert
Copy file name to clipboardExpand all lines: notebooks/animation.ipynb
+20-15Lines changed: 20 additions & 15 deletions
Original file line number
Diff line number
Diff line change
@@ -7,25 +7,19 @@
7
7
"# Animation"
8
8
]
9
9
},
10
-
{
11
-
"cell_type": "markdown",
12
-
"metadata": {
13
-
"collapsed": false,
14
-
"jupyter": {
15
-
"outputs_hidden": false
16
-
}
17
-
},
18
-
"source": [
19
-
"time stamp at 1:19"
20
-
]
21
-
},
22
10
{
23
11
"cell_type": "markdown",
24
12
"metadata": {},
25
13
"source": [
26
14
"## Overview\n",
27
15
"\n",
28
-
"Summary text here\n"
16
+
"Animations can be a useful and effective tool to visualize data, especially when that data changes over time. In this notebook, we will explore how to create animations using the `matplotlib` library. \n",
17
+
"\n",
18
+
"We will cover the two methods for creating animations in `matplotlib`, how to set up the elements of both types of animation, how to show the animation in jupyter notebooks, and how to save the animation to a file.\n",
19
+
"\n",
20
+
"1. Animation fundamentals with matplotlib\n",
21
+
"2. Artist Animation\n",
22
+
"3. Function Animation\n"
29
23
]
30
24
},
31
25
{
@@ -144838,7 +144832,7 @@
144838
144832
"source": [
144839
144833
"## Summary\n",
144840
144834
"\n",
144841
-
"We learned the two ways to make animations in matplotlib: artist animation and function animation, how to display them in jupyter notebooks, and how to save them to a file.\n",
144835
+
"Creating animations in matplotlib might seem intimidating, but is easier when you know the options and purpose of each method. These visualizations can be a powerful tool to display and understand time-dependent data.\n",
0 commit comments