1. Using other built in cell types
Welcome to this video on filtering data and using built-in charts in DataLab! Unlike other notebook environments, DataLab includes special cell types that make data exploration easier. Let's learn how to filter data using Explore cells and create visualizations using Chart cells!
2. Filtering data using Explore cells
Explore cells make filtering data easy. Instead of writing queries, we can apply filters interactively to drill down into the dataset. Whether we're sorting values or searching for specific entries, explore cells help us refine our data quickly.
3. Filtering an Explore cell
To filter an Explore cell, we can right click on a value to filter for it.
Or we can click the filter switch to add a filter.
We can set the column and the operator for the kind of filter we want, both numeric and text.
4. Exploring films
Now, let's walk through an example of filtering data in an explore cell. First, open an explore cell with a dataset, here we're using the films table.
First, we make sure we're looking at the whole dataset.
Let's see if this has any Japanese films, let's look for Akira - that Manga classic.
5. Exploring films
Yes, there are Japanese films. Okay, now we can filter just for Japanese films, and sort by gross to see what's the biggest grossing Japanese film. Ponyo! My kids love that film.
This interactive process allows us to explore the data quickly.
6. Special cell types in DataLab
DataLab extends the traditional notebook experience, which are made up of Code and Text cells,
with special cell types designed for data analysis.
We already learned about explore cells, now we’ll introduce chart cells, which let us create visualizations effortlessly.
7. Introducing Chart Cells
With chart cells, anyone can produce striking and insightful graphs! Instead of writing code for visualizations, we can generate charts with just a few clicks. Select from different chart types and customize how our data is displayed.
8. Creating a chart from an Explore Cell
We can build a full data analysis workflow without any coding! We start by using explore cells to filter and refine our dataset.
Once we have the data we need, we can convert it into a chart cell with this switch.
9. Editing a Chart cell
When creating a chart cell we need a category which is the main breakout you want to plot. This could be dates or a categorical variable.
We then need a series to plot, this is a numeric variable.
Lastly, DataLab makes it easy to perform aggregations on your variables, so you can quickly visualize averages, totals and counts of your data.
10. Let's practice!
You now know how to filter datasets using explore cells and create charts with chart cells. By combining these tools, you can analyze data faster and more efficiently. Let's practice!