From 150e2c108ed1b03e3efe8b95af20ecf64f0434cc Mon Sep 17 00:00:00 2001 From: Christian Fosli Date: Sat, 6 Apr 2024 20:52:55 +0200 Subject: [PATCH] Finish off the Streamlit post --- .../bar_chart_demo.png | Bin 0 -> 675293 bytes .../bike-counter-sykkelstamvegen.jpg | Bin 0 -> 338580 bytes .../dataframe_demo.png | Bin 0 -> 828942 bytes .../2024-data-webapps-with-streamlit/index.md | 79 ++++++++++++++++-- 4 files changed, 73 insertions(+), 6 deletions(-) create mode 100644 content/posts/2024-data-webapps-with-streamlit/bar_chart_demo.png create mode 100644 content/posts/2024-data-webapps-with-streamlit/bike-counter-sykkelstamvegen.jpg create mode 100644 content/posts/2024-data-webapps-with-streamlit/dataframe_demo.png diff --git a/content/posts/2024-data-webapps-with-streamlit/bar_chart_demo.png b/content/posts/2024-data-webapps-with-streamlit/bar_chart_demo.png new file mode 100644 index 0000000000000000000000000000000000000000..1b39fdfeca3de05df56329364976b4d1d421cf90 GIT binary patch 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Photo by me! + I pretty recently switched jobs (from one IT consultancy to another). This also meant switching client project, and subsequently I would be working with another tech stack than what I had been using the last few years. I was going from microservices in csharp/.NET to "data apps" with Python, Pandas and Streamlit. @@ -21,7 +23,10 @@ If you want a deeper understanding, check out the official [streamlit.io/get-sta ### Setup / installation -0. Create and navigate to a new project directory +> Note that I'm on a Fedora Linux computer using the bash shell. +> A few adjustments might be needed to follow along from Windows or Mac OS.. + +0. Create and navigate to a new empty project directory 1. Create and activate a new Python virtual environment within the project directory @@ -30,15 +35,14 @@ If you want a deeper understanding, check out the official [streamlit.io/get-sta . .venv/bin/activate ``` - > Note: - > If you're using Linux and want to use another version of python than what `python` is installed/configured to be, + > Note: If you're using Linux and want to use another version of python than what `python` is installed/configured to be, > I have [some notes](https://notes.christianfosli.com/python.html#managing-multiple-python-versions-and-dependencies) 2. Install dependencies with pip ```bash echo < requirements.txt -streamlit~=1.32 +streamlit~=1.33 pandas~=2.2 numpy~=1.26 EOF @@ -71,6 +75,69 @@ Now we're ready to explore some more features 😄. ### Dataframes +Dataframes are the primary data structure in the pandas library. +It is commonly used to store tabular data, i.e. data which consists of rows and columns, like spreadsheets do. + +Streamlit makes it very simple visualize dataframes. + +After some googling for a sort-of interesting dataset to play with, I found out Stavanger kommune publishes +[data from bike counter sensors publically](https://opencom.no/dataset/sykkeldata), +and the most recent dataset (as of April 2024) is available as [a CSV file here]( +https://opencom.no/dataset/90cef5d5-601e-4412-87e4-3e9e8dc59245/resource/4c71d19a-adc4-42e0-9bed-c990316479be/download/sykkeldata.csv). +Unfortunately it's a bit outdated, data from 2022, but it will do for this demonstration. + +Let's update application.py to demonstrate parsing this CSV to a dataframe and visualizing the results as a table: + +```python +import pandas as pd +import streamlit as st + +BIKE_COUNT_DATA_URL: str = ( + "https://opencom.no/dataset/90cef5d5-601e-4412-87e4-3e9e8dc59245/resource/4c71d19a-adc4-42e0-9bed-c990316479be/download/sykkeldata.csv" +) + + +@st.cache_data(ttl=3600) +def load_count_data() -> pd.DataFrame: + df = pd.read_csv(BIKE_COUNT_DATA_URL) + return df + + +st.title("Streamlit demo") + +df = load_count_data() +st.dataframe(df) +``` + +And that's it! +Go back to your web browser and hit the "Rerun" button in the top right and notice we now have a fully interactive table of the dataset to play with! + +![streamlit app with dataframe](dataframe_demo.png) + ### Plots +For a quick plotting demo, let's visualize bike counts (across all counter locations) by date. +We'll add a line to application.py: + +```patch +@@ -16,3 +16,4 @@ st.title("Streamlit demo") + + df = load_count_data() + st.dataframe(df) ++st.bar_chart(df, x="Date", y="Count") +``` + +And here we go: + +![streamlit app with bar chart](bar_chart_demo.png) + +Streamlit supports several different native chart types, as well as rendering charts from popular libraries from the ecosystem, such as matplotlib and plotly, +so there are lots of options and possibilities! + +We could also use pandas to transform our dataframe in different ways prior to plotting the data, as needed. + ### More + +This was just the tip of the iceberg with regards to data apps on Streamlit. +Hopefully it was useful and/or inspires you to try it out and learn more 😄. +

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