Welcome to Pivot Pal - a Python-based toolkit designed to streamline the exploration and analysis of datasets. Whether you're diving into the Titanic's passenger list, analyzing police records, or exploring Airbnb listings, Pivot Pal has got you covered with a suite of powerful tools.
🌐 For detailed documentation and case studies, visit our official website: pythonpivotpal.com
pip install pivot-palTo start using Pivot Pal, simply import the necessary modules:
import pandas as pd
from IPython.display import display, MarkdownGet a snapshot of your dataset.
pp.overview(df)Analyze the distribution of values for a specific column.
pp.distribution(df, "column_name")Determine the minimum and maximum values for each column.
pp.range(df)Count the unique values for each column.
pp.unique(df)Summarise numeric columns with various statistics.
pp.summarise(df)Identify columns with missing data.
pp.missing(df)Highlight columns with zero values.
pp.zeros(df)Understand the data types present in your dataset.
pp.datatypes(df)Dive deep into real-world data exploration with our comprehensive case studies:
Contributions are welcome! Please read our contributing guidelines to get started.
This project is licensed under the MIT License. See the LICENSE file for details.