smartanalytics 1.0.0

A Python library for data cleaning, statistical analysis, and insights.

smartanalytics

A Python library for data cleaning, statistical analysis, and data insights.

Installation

pip install smartanalytics

Modules

1. cleaning — Data Cleaning

Clean and preprocess your DataFrames before analysis.

Function	Description
remove_nulls(df)	Remove rows with missing values
remove_duplicates(df)	Remove duplicate rows
fill_missing(df, value)	Fill NaN values with a given value
normalize_data(df)	Min-Max normalize all numeric columns

2. stats — Statistics

Compute core statistical measures from lists.

Function	Description
mean(data)	Arithmetic mean
median(data)	Middle value
mode(data)	Most frequent value(s)
standard_deviation(data)	Spread of the data

3. insights — Data Insights

Advanced analysis functions for real-world data understanding.

Function	Description
detect_outliers(data)	IQR-based outlier detection
correlation_matrix(df)	Pearson correlation between columns
dataset_summary(df)	Shape, dtypes, nulls, and stats overview
missing_value_report(df)	Column-wise missing value report

Quick Example

import pandas as pd
from smartanalytics import cleaning, stats, insights

# Sample dataset
df = pd.DataFrame({
    'Age':    [25, 30, None, 22, 30],
    'Score':  [88, 92, 95, 88, 92],
    'Salary': [30000, 45000, 50000, 28000, 45000]
})

# Clean the data
df = cleaning.remove_nulls(df)
df = cleaning.remove_duplicates(df)

# Statistical analysis
print(stats.mean(df['Score'].tolist()))
print(stats.standard_deviation(df['Salary'].tolist()))

# Generate insights
print(insights.missing_value_report(df))
print(insights.correlation_matrix(df))

License

MIT