Learn about the fundamentals of the Bokeh library in this course, which will enable you to level up your Python data visualization skills by building interactive plots. You’ll see how to set up configuration tools, including the HoverTool, providing various opportunities for stakeholders to interact with your plots!

Pengantar Bokeh

Kapan menggunakan plot sebar (scatter plot)

Blocks vs. rebounds

Performa Kevin Durant sepanjang musim

Kemampuan tembakan berdasarkan posisi

Alat konfigurasi

Opsi

Alat Pan/Drag

Alat Scroll/Pinch

Alat Click/Tap

Alat terbaik untuk tugasnya

Menetapkan tools

Menambahkan LassoSelectTool

HoverTool

Menambahkan HoverTool

Memformat HoverTool

Introduction to Bokeh

For this chapter, you’ll learn how to customize axes, create and enhance a legend, modify glyph settings, and apply Bokeh's custom themes!

Adding style

Colors, legend, and theme

Customizing glyphs

Customizing axes

Average building size

Sales over time

Subplots

Categorical column subplots

Size, location, and price

Using gridplot

Changing size

Visualizing categorical data

High to low prices by region

Creating nested categories

Visualizing sales by period

Customizing Visualizations

Learn how to use various elements to communicate with stakeholders. You’ll produce grouped bar plots with categorical data, build multiple subplots, add annotations, and modify the text to make your Bokeh visualizations even more striking!

Customizing glyph settings

Shooting guards versus small forwards

Big shooters

Evolution of the point guard

Highlighting and contrasting

Highlighting by glyph size

Steals vs. assists

Adding a color bar

Free throw percentage by position

Communicating with text

Sales by time and type of day

Products sold by the time of day

Adding annotations

Box annotations for sales performance

Setting up a polygon annotation

Annotating Netflix stock price growth

Storytelling with Visualizations

Discover Bokeh's widgets and how they enable users to modify Python visualizations! You’ll learn about Spinners, which allow viewers to change the size of glyphs. We’ll discuss Sliders, which can be used to change axis ranges. Lastly, we’ll introduce the Select widget, which will enable plot updates based on dropdown options.

Introduction to widgets

Adding a Div

Modifying glyph size with a widget

Slider widgets

Automotive stocks analysis

Tech stock performance over time

Select widgets

Travel analysis

Changing line plots with Select

Congratulations!

Introduction to Widgets

Bakery Sales

Stocks

NBA Player Statistics

Australia Property Market

Bokeh adalah paket Python yang andal untuk visualisasi data interaktif, memungkinkan Anda melampaui plot statis dan memberi pemangku kepentingan kendali untuk memodifikasi visualisasi Anda! Dalam kursus visualisasi data interaktif dengan Bokeh ini, Anda akan bekerja dengan beragam himpunan data, termasuk harga saham, statistik pemain bola basket, dan data penjualan real estat Australia. Melalui latihan praktis, Anda akan membangun dan menyesuaikan berbagai plot, termasuk sebar, batang, garis, dan batang berkelompok. Anda juga akan mempelajari alat konfigurasi untuk mengubah cara penonton berinteraksi dengan plot Anda, menjelajahi tema kustom Bokeh, mempelajari cara membuat subplot, dan bahkan menambahkan widget ke plot Anda!

Data Manipulation with pandas

Pelajari cara membuat visualisasi data interaktif dan menghubungkan widget dengan Bokeh!

Visualisasi Data Interaktif dengan Bokeh

Pelajari cara membuat visualisasi data interaktif, termasuk membangun dan menghubungkan widget menggunakan Bokeh!

Alat terbaik untuk tugasnya

Visualisasi Data Interaktif dengan Bokeh

Latihan interaktif langsung