README.md

metadata

title: Streamlit Docker
emoji: 🐨
colorFrom: indigo
colorTo: red
sdk: docker
pinned: false
license: apache-2.0
app_port: 8501

Introduction to Data Science with Python

Overview

Location: Accra, Ghana When: July 31 and August 1, 2023

This material focuses on Polars, Parquet files, Plotly Express, and Streamlit to introduce the data science process.

Installing the tools

We will need Visual Studio Code and Python installed for this short course. Each tool has additional packages/extensions that we will need to install as well.

Visual Studio Code Extensions

You can use Managing Extensions in Visual Studio Code to learn about how to install extensions. We will use Python - Visual Studio Marketplace extension heavily. Managing Extensions in Visual Studio Code provides more background on extensions if needed.

VS Code Interactive Python Window

An open-source project called Jupyter is the standard method for interactive Python use for data science or scientific computing. However, there are some issues with its use in a development environment. VS Code provides a way for us to have the best of Python and Jupyter Notebooks with their Python Interactive Window.

VS Code is fairly intelligent in responding to your needs. If you open a .py file it should ask pop up a window asking you if you would like prepare your Python experience. You will need to install the jupyter python package. If VS Code doesn't install it it, you can use pip or pip3 for the interactive Python window to work.

Using the VS Code functionality, you will work with a standard .py file instead of the .ipynb extension typically used with jupyter notebooks. The Python extension in VS Code will recognize # %% as a cell or chunk of python code and add notebook options to ‘Run Cell’ as well as other actions. You can see the code example bellow with the image of the view in VS Code as an example. Microsoft’s documentation goes into more detail (https://code.visualstudio.com/docs/python/jupyter-support-py).

To make the interactive window use more functional you can ctrl + , or cmd + , on a mac to open the settings. From there you can search ‘Send Selection to Interactive Window’ and make sure the box is checked. Now you will be able to use shift + return to send a selected chunk of code or an entire cell.

# %%
msg = "Hello World"
print(msg)

# %%
msg = "Hello again"
print(msg)

Python Packages

pip overview

The standard command - pip install polars[all] plotly streamlit is executed in your Terminal, Command Window, or by using the New Terminal under Terminal in VS Code. If you are using a Mac you most likely will use pip3 install polars[all] plotly streamlit. In your interactive Python environment in VS Code (Jupyter server) you can run !pip install polars[all] plotly streamlit as explained here. Finally, you could use the following Python code snippet.

The two commands that can be used in the interactive python window in VS Code to install packages.

!pip install polars[all] plotly streamlit

or

import sys
!{sys.executable} -m pip install polars[all] plotly streamlit

pip commands

• pip install polars[all] plotly streamlit should install all needed packages.

You could install them individually using the following commands.

• pip install polars[all] for Polars
• pip install streamlit for Streamlit
• pip install plotly for plotly in Python

Repo Navigation

guides folder

The guides folder will allow us to explore these packages if the internet connection is down during our course.

• PDF Files: The pdf files should have most of the commands we will need during the course. The polars_website.pdf is a full pdf build of their website guide as of July 2023.
• streamlit_md folder: This folder has the markdown files used to build their website guide. It is a little harder to navigate.
• polars_site folder: This folder has the fully built website for the polars package as of July 2023. From your OS file explorer open the index.html file to see the full site.

data folder

This folder has the data we will be using for the short course. Read more about the data folder.

Scripts folder

The scripts folder has the starting scripts for each of the activities we will complete during the short course.

Markdown links

• plotly.md: links to the primary functions we will use as we create charts with Plotly Express
• polars.md: links to the key methods we will leverage for data import and munging.
• streamlit.md: links to the dashboard functions and concepts we will use with Streamlit

Slides

The HTML Slides and pdf slides