virva


Namevirva JSON
Version 0.1.9 PyPI version JSON
download
home_pagehttps://github.com/charleslf2/virva
SummaryVirva is the simplest fake dataframe generator
upload_time2023-01-04 19:11:40
maintainer
docs_urlNone
authorCharles TCHANAKE
requires_python
licenseMIT
keywords data generator fake data generator csv generator dataframe generator
VCS
bugtrack_url
requirements No requirements were recorded.
Travis-CI No Travis.
coveralls test coverage No coveralls.
            # Virva

Virva is the simplest fake dataframe generator 

# Purpose of the package
+  The purpose of this package is to provide the world simplest fake dataframe generator


# Features
+ Generate fake dataframe of any lenght 
+ Random names generations
+ Random cities generations
+ Random jobs title generations
+ Random contrie generations
+ CSV export
+ Generate custom categorical variables
+ Generate custom numerical variables
+ And much more


# Getting Started
The package can be found on pypi hence you can install it using pip

### Installation

```bash

pip install virva

```
### Usage
```python
# Import Virva generator
>>> from virva.core import Generator

# generate 50 random names
>>> names= Generator.generate_names("Names", number=50)

# generate 50 random age's between 5 and  18 year old
>>> ages =Generator.generate_integers("Ages", number=50, 5, 18)

# generate 50 random  scores between 1.0 and 5.0
>>> scores=Generator.generate_floats("stars", number=50, 1.0, 5.1)

# generate 50 random gender type between Male (M) and Female (F)
>>> gender=Generator.generate_objects("Gender", number=50,  ["M", "F"])

# generate 50 random jobs
>>> jobs= Generator.generate_jobs("Jobs", number=50)

# generate 50 random cities
>>> cities= Generator.generate_cities("Cities", number=50)

# generate 50 random diseases
>>> diseases=Generator.generate_diseases("diseases", number=50)

# generate 50 random foods
>>> foods=Generator.generate_foods("foods", number=50)

# generate 50 random us_states
>>> us_states=Generator.generate_us_states("us_states", number=50)

# generate 50 random contries
>>> countries=Generator.generate_countries("Countries", number=50)


#generate csv file with above dataframe with the name "my_shynthetic_dataframe"
>>> list_of_dataframe=[names, ages, scores, gender, jobs, cities, diseases, foods, us_states, countries]

>>>Generator.assemble("path/to/your/directory", list_of_dataframe, "my_shynthetic_dataframe")
```

### Contribution
Contribution are welcome.
Notice a bug ? let us know. Thanks you

### Author
+ Main Maitainer : Charles TCHANAKE
+ email : datadevfernolf@gmail.com 

            

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    "description": "# Virva\r\n\r\nVirva is the simplest fake dataframe generator \r\n\r\n# Purpose of the package\r\n+  The purpose of this package is to provide the world simplest fake dataframe generator\r\n\r\n\r\n# Features\r\n+ Generate fake dataframe of any lenght \r\n+ Random names generations\r\n+ Random cities generations\r\n+ Random jobs title generations\r\n+ Random contrie generations\r\n+ CSV export\r\n+ Generate custom categorical variables\r\n+ Generate custom numerical variables\r\n+ And much more\r\n\r\n\r\n# Getting Started\r\nThe package can be found on pypi hence you can install it using pip\r\n\r\n### Installation\r\n\r\n```bash\r\n\r\npip install virva\r\n\r\n```\r\n### Usage\r\n```python\r\n# Import Virva generator\r\n>>> from virva.core import Generator\r\n\r\n# generate 50 random names\r\n>>> names= Generator.generate_names(\"Names\", number=50)\r\n\r\n# generate 50 random age's between 5 and  18 year old\r\n>>> ages =Generator.generate_integers(\"Ages\", number=50, 5, 18)\r\n\r\n# generate 50 random  scores between 1.0 and 5.0\r\n>>> scores=Generator.generate_floats(\"stars\", number=50, 1.0, 5.1)\r\n\r\n# generate 50 random gender type between Male (M) and Female (F)\r\n>>> gender=Generator.generate_objects(\"Gender\", number=50,  [\"M\", \"F\"])\r\n\r\n# generate 50 random jobs\r\n>>> jobs= Generator.generate_jobs(\"Jobs\", number=50)\r\n\r\n# generate 50 random cities\r\n>>> cities= Generator.generate_cities(\"Cities\", number=50)\r\n\r\n# generate 50 random diseases\r\n>>> diseases=Generator.generate_diseases(\"diseases\", number=50)\r\n\r\n# generate 50 random foods\r\n>>> foods=Generator.generate_foods(\"foods\", number=50)\r\n\r\n# generate 50 random us_states\r\n>>> us_states=Generator.generate_us_states(\"us_states\", number=50)\r\n\r\n# generate 50 random contries\r\n>>> countries=Generator.generate_countries(\"Countries\", number=50)\r\n\r\n\r\n#generate csv file with above dataframe with the name \"my_shynthetic_dataframe\"\r\n>>> list_of_dataframe=[names, ages, scores, gender, jobs, cities, diseases, foods, us_states, countries]\r\n\r\n>>>Generator.assemble(\"path/to/your/directory\", list_of_dataframe, \"my_shynthetic_dataframe\")\r\n```\r\n\r\n### Contribution\r\nContribution are welcome.\r\nNotice a bug ? let us know. Thanks you\r\n\r\n### Author\r\n+ Main Maitainer : Charles TCHANAKE\r\n+ email : datadevfernolf@gmail.com \r\n",
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