dashcamcsv 0.2.5

Helpful utilities for data science workflows.

dashcamcsv

A simple Python package with helpful utilities for data science workflows.

Features

• load_and_describe(url: str): Load a CSV from a URL and print basic statistics.
• missing_report(df): Show missing value counts and percentages.
• info_summary(df): Print DataFrame shape, types, and memory usage.
• clean_data(df, strategies=None): Perform basic data cleaning with customizable strategies.
• quick_plot(df, column, figsize=(10, 6)): Plot a histogram or bar plot for a column with custom figure size.
• plot_advanced(df, x, y=None, kind='pairplot', figsize=(10, 8)): Create advanced visualizations using seaborn with custom figure size.

Installation

pip install dashcamcsv

Usage

from dashcamcsv import load_and_describe, missing_report, info_summary, clean_data, quick_plot, plot_advanced

# Basic example
df = load_and_describe("https://raw.githubusercontent.com/mwaskom/seaborn-data/master/iris.csv")
missing_report(df)
info_summary(df)

# Data cleaning
# Apply different cleaning strategies for different columns
clean_df = clean_data(df, strategies={
    'sepal_length': 'median',  # Fill missing values with median
    'species': 'mode',         # Fill missing values with most common value
    'petal_width': 'drop',     # Drop rows where this column has missing values
    'sepal_width': 'value:5.0' # Fill missing values with a specific value
})

# Visualization
quick_plot(df, "sepal_length", figsize=(12, 6))  # Customize figure size

# Advanced visualizations with seaborn
plot_advanced(df, 'sepal_length', 'sepal_width', kind='scatter', figsize=(10, 8))  # Scatter plot with regression line
plot_advanced(df, 'species', 'sepal_length', kind='box', figsize=(8, 6))  # Box plot
plot_advanced(df, kind='heatmap', figsize=(12, 10))  # Correlation heatmap

Changelog

• v0.2.5: Added clean_data function for flexible data cleaning
• v0.2.4: Fixed plotting bugs and improved error handling
• v0.2.3: Updated documentation and examples
• v0.2.2: Fixed plotting functions to handle categorical data better
• v0.2.1: Added compatibility with Python 3.8+
• v0.2.0: Added figsize parameter to plotting functions
• v0.1.0: Initial release