Python Programming Tutorials
Sometime ago we learnt about how to upload files and process the uploaded files in Streamlit. We dived deeper into the Streamlit UploadedFile Class and how it reads it as a file-like Byte IO type. In this tutorial we will learn about how to save our uploaded file into a directory. This is useful in …
How to Save Uploaded Files to Directory in Streamlit Apps Read More »
Pandas is one of the best libraries for doing data analysis in general. It is so popular and useful that it has become the defactor DataFrames library when doing Data Science in Python. However, there are times that your dataset may be too big for Pandas and too small for PySpark – this is where …
PyPolars – Data Analysis with PyPolars – a Pandas Alternative Read More »
In this tutorial we will explore Waypoint – a tool designed by Hashicorp to build,deploy and release your application with ease and simplicity. Waypoint makes it easier for developers to build,deploy and release most applications using a similar and simple workflow. The main requirement includes Your App requirements.txt : For the app you want to …
Build and Deploy Flask App Using Hashicorp’s Waypoint Read More »
Streamlit is such an awesome framework that allows you to build several cool data science apps. In this tutorial we will see how to embed PDF files in our streamlit app. To be able to do so we will need just 2 main things st.markdown() : this will enable us to use the same format …
Reproducibility and re-usability of your Python projects is an essential aspect of being a software developer or engineer, and one of the ways to do so is to provide means that others can get the same working environments you used for your projects and the same versions of packages and libraries used. This is one …
Pipreqs Tutorial – How to Create Requirements.txt File In Python with Ease Read More »
When working on any python project or data science project it is essential to always work in an environment that makes your project reusable and repeatable without any issues for anyone that picks up your project in the future. This will even help you yourself when you revisit your project in the future. One of …
Streamlit is awesome we several cool and useful features, in this tutorial we will explore yet another additional feature of streamlit – st.beta_columns() and st.beta_expander(). This feature is available from version 0.68 and upwards hence you will need to upgrade your previous version via pip install streamit -U or pip install streamlit –upgrade Let us …
Exploring your dataset is an essential aspect of every data science task or project. As an aspect of the Data Science Life Cycle , it allows you to derive descriptive and practical insight into what your data comprises of. It is essential to know how to derive such insight from your data by creating your …
3 Exploratory Data Analysis Tools In Python For Data Science Read More »
In today’s tutorial we will be exploring another powerful natural language processing library called Flair. We will be seeing how to use Flair for text classification. Specifically we will learn how to build a model to predict or classify text as either offensive or non-offensive. What is Flair? Flair is a state of the art(SOTA) …
Text Classification with Flair – Pytorch NLP Framework Read More »
The simplicity that streamlit offers for building apps is so cool and useful. But sometimes you may be constrained by lack of compute or incompatible working environment on your local computer. In most cases Colab solves that problem. But what if you want to share your streamlit app with others from Colab. In this tutorial …