The conversational way of generating code with ChatGPT works well with the cell structure of Jupyter Notebooks — Is AI the future of data analysis? I’m going to put my head above the parapet, stick my neck out, go out on a limb, and say: “well, maybe”. You can undoubtedly use AI to perform relatively simple code generation and that can save you a lot of time and…

No waffle, just a 10-point SEO checklist that you can quickly scan before publishing generated by ChatGPT — We all want our writing to be read. Obviously. So we’ve all read loads of stuff about SEO. The trouble is, with me, it goes in one ear and out the other. What I want is a simple checklist to look through before hitting the publish button, to make sure…

You can get around Streamlit’s restrictions and use all of the built-in themes for Plotly with a simple Streamlit component — Plotly themes are normally specified when creating a plot (e.g. template=plotly_dark) but unfortunately, in Streamlit, this theme information gets overwritten when the chart is drawn. Streamlit only supports the use of two themes and these are specified as an argument to the st.plotly_chart() function. …

Your Streamlit text no longer has to be boring. Version 1.16 lets you colour markdown text. — You’ve been able to use coloured text in Streamlit Markdown strings for a long time but it has required using HTML embedded in the Markdown text. And that can get a little clumsy: st.markdown("The next word is <span style='color:red'>red</span>", unsafe_allow_html=True) All that just to make one word red.

Streamlit has a set of colours that is consistent throughout the app but Plotly did not conform — with Streamlit 1.16, this has changed. — Streamlit’s standard theming is clear and appealing, but until now when creating Plotly charts, you were stuck with Plotly’s standard theme and its light blue-grey background. And although Plotly provides a mechanism for changing from the standard theme, for some reason this does not work inside a Streamlit app.

Streamlit has simple but effective components for user interaction and layout which let us build effective and attractive data science and dashboard applications — We are going to explore some of the layout and user interface features of Streamlit so we can create a simple but effective data dashboard app. In previous articles in this series, we have seen how to present text, media and data, now we use this knowledge and add layout…

Define your problem, develop a plan, find the data, analyze the data and then communicate your conclusions — that’s PPDAC — Whatever happened to methodologies? When I first started in software development they were all the rage but they seem to have lost their appeal. Maybe developers simply don’t like being told what to do. I suspect that methodologies are not popular when they are prescriptive. But they don’t have to…

Who knew that a book about punctuation could be so entertaining Do I need to tell you the joke? I’ll tell you the joke. A panda walks into a restaurant and orders a meal. He seems to be enjoying it and when he’s finished the waiter approaches. “Would you like…

From text and tables to sophisticated charts. From Pandas dataframes to Matplotlib, Plotly, Altair and other charts. Streamlit provides a comprehensive set of tools for presenting your data — Streamlit was designed for Data Scientists and so data presentation is fundamental to it. Streamlit supports several charting packages, like Pyplot, Plotly, Altair and Bokeh, as well as ways of textually presenting data. We will look at them all, briefly, along with Streamlit’s built-in charts.