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Description:
datahorse 0.0.4
🎉 Do data science and data analysis in plain english 🌟
DataHorse
🚀 DataHorse is an open-source tool and Python library that simplifies data science for everyone. It lets users interact with data in plain English 📝, without needing technical skills or watching tutorials 🎥 to learn how to use it. With DataHorse, you can create graphs 📊, modify data 🛠️, and even create smart systems called machine learning models 🤖 to get answers or make predictions. It’s designed to help businesses and individuals 💼 regardless of knowledge background to quickly understand their data and make smart, data-driven decisions, all with ease. ✨
Quick Installation
pip install datahorse
Examples
Setup and usage examples are available in this Google Colab notebook.
import datahorse
df = datahorse.read('https://raw.githubusercontent.com/plotly/datasets/master/iris-data.csv')
# Data transformation
df = df.chat('convert species names to numeric codes')
df = df.chat('add a new column "petal_area" calculated as petal_length * petal_width')
# Queries
average_measurements = df.chat('what are the average sepal length and petal width for each species?')
species_count = df.chat('how many samples are there for each species?')
largest_petal_length = df.chat('which species has the largest petal length?')
# Plotting
df.chat('scatter plot of sepal length vs petal length by species')
df.chat('histogram of petal width')
df.chat('box plot of sepal length distribution by species')
License
For personal and professional use. You cannot resell or redistribute these repositories in their original state.
Customer Reviews
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