This Pandas Trick Will Blow Your Mind As a Data Scientist! — Part 2

Author(s): Gencay I.

Originally published on Towards AI.

Let’s build a streamlit app in 8 steps!

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Now, you’ve liked Part 1 of this article a lot, where we have created an app in Jupyter Notebook that automates data analysis with Python, like the screenshot below;

Reference

But why don’t we create a streamlit app from this? I know you probably want to share this app with your friends, am I right? And guess what? If you follow all the steps, you can deploy your app to the streamlit cloud for free and share it with your friends!

Check the result from the screenshot below.

SS of the Final Part!

Let’s implement it in under 10 minutes in 8 steps!

Let’s load all libraries.

import streamlit as stimport pandas as pdimport numpy as npimport seaborn as snsimport matplotlib.pyplot as plt

Streamlit is a speedy way of publishing your data apps. If you need to learn what it is, check out this article, where I created a financial dashboard with streamlit.

Here, we will set titles like this.

st.title("Automate Your Data Analysis with Pandas and Streamlit")st.write("Upload a CSV file and explore it with just a few clicks!")

Streamlit provides a file_uploader feature, which will… Read the full blog for free on Medium.

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Published via Towards AI