tensor2 1.0.2

Business Analytics lab experiments — import, run, and save ready-to-use Python scripts.

tensor2

Business Analytics lab experiments — import, browse, and generate ready-to-run Python scripts.

Installation

pip install tensor2

# Install ALL optional experiment dependencies at once:
pip install "tensor2[all]"

Quick Start

from tensor2 import index

# ① Interactive menu — pick an experiment number, get a saved .py file
index.main()

# ② Just print the list
index.list_experiments()

# ③ Get source code as a string
code = index.get(3)
print(code)

# ④ Save directly to a file
index.get(5, save_to='data_quality.py')

Available Experiments

#	Title	Key Libraries
1	Data Importing and Exporting using Pandas	pandas, openpyxl
2	Data Cleaning and Preprocessing	pandas, numpy, matplotlib, seaborn
3	Data Integration and Reshaping (Data Wrangling)	pandas, numpy
4	Dealing with Time Series Data	pandas, numpy, matplotlib
5	Data Quality Assurance (DQA)	pandas, numpy, matplotlib, seaborn
6	Exploratory Data Analysis and Visualization	pandas, numpy, matplotlib, seaborn
7	Big Data Analysis — Apache Hive & Neo4j*	(external tools)
8	Forecasting using ARIMA Model	statsmodels, scikit-learn
9	Sentiment Analysis of Social Media Data	textblob, vaderSentiment, nltk
10	Regression Analysis on Stock Data	scikit-learn, yfinance

* Experiment 7 prints the Hive/Cypher commands you need to run in their respective shells.

Dataset Replacement

Every experiment uses a synthetic dataset by default so you can run it immediately. Look for the comment block at the top of each experiment:

# Replace with your own file:
#   df = pd.read_csv('your_file.csv')

Simply swap in your real data source and the rest of the script runs unchanged.

How index.main() Works

1. Prints a numbered list of all experiments.
2. You type the experiment number.
3. You choose a file name (or press Enter for the default).
4. A ready-to-run .py file is saved in your current directory.

License

MIT