edazer 0.1.1

lightweight library that provides functionalities for common EDA tasks

Edazer

Edazer is a lightweight package that provides functionalities for common EDA tasks. It helps you quickly understand, summarize, and inspect your datasets with minimal code.

---

Features

• Quick DataFrame Summaries: Instantly view info, describe, nulls, duplicates, and shape using summary method
• Unique Value Inspection: Easily display unique values for any or all columns.
• Type-based Column Selection: Find columns by dtype (e.g., numeric, categorical).
• Flexible Subsetting: Use the lookup method to view head, tail, or random samples.
• Custom DataFrame Naming: Track multiple DataFrames with custom names for clarity.

---

Installation

pip install edazer

---

Quick Start with Titanic Dataset

import seaborn as sns
from edazer import Edazer

# Load the Titanic dataset from seaborn
titanic = sns.load_dataset('titanic')

# Create an Edazer instance
titanic_eda = Edazer(titanic, name="titanic") # setting name useful when working with multiple dataframes

#Complete DataFrame summary: info | descriptive statistics | nulls| duplicates | uniques | shape
titanic_eda.summarize_df()

# Show unique values for selected columns
titanic_eda.show_unique_values(column_names=['class', 'embarked'], max_unique=5)

# Get columns with float dtype
print(titanic_eda.cols_with_dtype(['float']))

#Combine multiple methods
titanic_dz.show_unique_values(column_names=titanic_dz.cols_with_dtype(dtypes=["object"]))

# Display the first few rows
print(titanic_eda.lookup("head"))

---

API Reference

Edazer(df: pd.DataFrame, name: str = None)

• df: The pandas DataFrame to analyze.
• name: Optional name for the DataFrame (useful when working with many DataFrames).

Methods

• summarize_df(): Print a summary (info, describe, nulls, duplicates, shape).
• show_unique_values(column_names=None, max_unique=10): Show unique values for specified columns.
• cols_with_dtype(dtypes): Return columns matching the given dtypes.
• lookup(option="head"): Return a subset of the DataFrame (head, tail, or sample).

---

Example Output

titanic_eda.show_unique_values(column_names=titanic_dz.cols_with_dtype(dtypes=["object"]))

# Output:
sex: ['male', 'female']
embarked: ['S', 'C', 'Q', nan]
who: ['man', 'woman', 'child']
embark_town: ['Southampton', 'Cherbourg', 'Queenstown', nan]
alive: ['no', 'yes']

---

Contributing

Contributions are welcome! Please open issues or pull requests on Github

License

MIT License

---

Author

adarsh3690704