Videos#
Below are the assigned videos for this week. The videos are collapsible so once you’re done with one, you can move to the next one. In the sidebar on the right, you can use the checklists to keep track of what’s done.
Required Videos#
Below are the assigned videos for this week.
Videos before Tuesday’s class#
1. Data, Internet, and Billboard 100
2. Beautiful Soup
Videos before Thursday’s class#
3. Dataframe Filtering
4. Pandas and Dates
5. Plotting with Pandas
Optional Videos#
Pandas in Data Science Tutorial
Some of you have asked me for advanced Pandas tutorials for your own side-projects and other courses. Though much of this content is beyond the scope of this course, here is a nice video that I assign to students in one of my other data science courses that might be useful for you.
Here is an outline of the timestamps of this video (clickable links in the YouTube Video description)
0:00 - Why Pandas?
1:46 - Installing Pandas
2:03 - Getting the data used in this video
3:50 - Loading the data into Pandas (CSVs, Excel, TXTs, etc.)
8:49 - Reading Data (Getting Rows, Columns, Cells, Headers, etc.)
13:10 - Iterate through each Row
14:11 - Getting rows based on a specific condition
15:47 - High Level description of your data (min, max, mean, std dev, etc.)
16:24 - Sorting Values (Alphabetically, Numerically)
18:19 - Making Changes to the DataFrame
18:56 - Adding a column
21:22 - Deleting a column
22:14 - Summing Multiple Columns to Create new Column.
24:14 - Rearranging columns
28:06 - Saving our Data (CSV, Excel, TXT, etc.)
31:47 - Filtering Data (based on multiple conditions)
35:40 - Reset Index
37:41 - Regex Filtering (filter based on textual patterns)
43:08 - Conditional Changes
47:57 - Aggregate Statistics using Groupby (Sum, Mean, Counting)
54:53 - Working with large amounts of data (setting chunksize)
You can download the pokemon.csv dataset here and this notebook here.
5. Seaborn
You can see the associated Jupyter Notebook here