datazets

• datazets is Python package

Star this repo if you like it! ⭐️

bash pip install datazets

Import datazets

```python

Import library

import datazets as dz

Import data set

df = dz.get('titanic')

```

Data sets:

| Dataset Name | Shape Size | Type | Description | |------------------------|----------------------|---------------------|-----------------------------------------------------------------------------------------------| | meta | (1472, 20) | Continuous, time | Stock price of Meta | | bitcoin | (2522, 2) | Continuous, time | Bitcoin price history data for time series and price prediction | | iris | (150, 3) | Continuous | Classic flower classification dataset with iris species measurements with coordinates | | | | | | | gasprices | (6556, 2) | Mixed, time | Historical gas prices by region for trend analysis | | ads | (10000, 10) | Discrete | Data on online ads, covering click-through rates and targeting information | | sprinkler | (1000, 4) | Discrete | Synthetic dataset with binary variables for rain and sprinkler probability illustration | | randomdiscrete | (1000, 5) | Discrete | Synthetic dataset with random discrete variables, useful for probability modeling | | | | | | | maliciousurls | (387588, 2) | Text | URLs labeled as malicious or benign, useful in cybersecurity | | maliciousphish | (651191, 4) | Text | URLs labeled as malicious or benign, defacement, phishing, malware (cybersecurity) | | | | | | | stormofswords | (352, 3) | Network | Character data from A Storm of Swords, with relationships, traits, and alliance info | | bigbang | (9, 3) | Network | Data on The Big Bang Theory episodes and characters | | energy | (68, 3) | Network | Data on building energy consumption | | | | | | | autompg | (392, 8) | Mixed | Data on cars with features for predicting miles per gallon | | breastcancer | (569, 30) | Mixed | Dataset for breast cancer diagnosis prediction using tumor cell features | | cancer | (4674, 9) | Mixed | Cancer patient data for classification and prediction of diagnosis outcome with Coordinates | | censusincome | (32561, 15) | Mixed | US Census data with various demographic and economic factors for income prediction | | electionsrus | (94487, 23) | Mixed | Russian election data with demographic and political attributes | | electionsusa | (24611, 8) | Mixed | US election data with demographic and political attributes | | fifa | (128, 27) | Mixed | FIFA player stats including attributes like skill, position, country, and performance | | marketingretail | (999, 8) | Mixed | Retail customer data for behavior and segmentation analysis | | predictivemaintenance | (10000, 14) | Mixed | Industrial equipment data for predictive maintenance | | student | (649, 33) | Mixed | Data on student performance with socio-demographic and academic factors | | surfspots | (9413, 4) | Mixed, latlon | Information on global surf spots, with details on location and wave characteristics | | tips | (244, 7) | Mixed | Restaurant tipping data with variables on meal size, day, and tip amount | | titanic | (891, 12) | Mixed | Titanic passenger data with demographic, class, and survival information | | waterpump | (59400, 41) | Mixed | Water pump data with features for predicting functionality and maintenance needs | | | | | | | catanddog | None | Image | Images of cats and dogs for classification and object recognition | | digits | (1083, 65) | Image | Handwritten digit images (8x8 pixels) for recognition and classification | | faces | (400, 4097) | Image | Images of faces used in facial recognition and feature analysis | | flowers | None | Image | Various flower images for classification and image recognition | | imgpeaks1 | (930, 930, 3) | Image | Synthetic peak images for image processing and analysis | | imgpeaks2 | (125, 496, 3) | Image | Additional synthetic peak images for image processing | | mnist | (1797, 65) | Image | MNIST handwritten digit images (28x28 pixels) for classification tasks | | scenes | None | Image | Scene images for scene classification tasks | | southernnebula | None | Image | Images of the Southern Nebula, suitable for astronomical analysis | | | | | | | blobs | Custom | Continuous | Synthetic data of datapoints in blob shape | | moons | Custom | Continuous | Synthetic data of datapoints in moon shape | | circles | Custom | Continuous | Synthetic data of datapoints in circle shape | | anisotropic | Custom | Continuous | Synthetic data of datapoints with anisotropic shape | | globular | Custom | Continuous | Synthetic data of datapoints with globular shape | | uniform | Custom | Continuous | Synthetic data with uniform shape | | densities | Custom | Continuous | Synthetic data with different densities | | | | | |

Example:

```python

import datazets as dz df = dz.get(data='titanic')

```

```python

import datazets as dz

Import from url

url='https://archive.ics.uci.edu/ml/machine-learning-databases/adult/adult.data' df = dz.get(url=url, sep=',')

```

Maintainer

• Erdogan Taskesen, github: erdogant

Contribute

• All kinds of contributions are welcome!
• If you wish to buy me a Coffee for this work, it is very appreciated :)

Licence

See LICENSE for details.