VerticaPy | Python library that exposes sci

by vertica Python Version: 1.0.4 License: Apache-2.0

X-Ray Key Features Code Snippets(3)Community Discussions(3)Vulnerabilities Install Support

kandi X-RAY | VerticaPy Summary

VerticaPy is a Python library typically used in Big Data, Spark applications. VerticaPy has no vulnerabilities, it has build file available, it has a Permissive License and it has low support. However VerticaPy has 31 bugs. You can install using 'pip install VerticaPy' or download it from GitHub, PyPI.

VerticaPy is a Python library with scikit-like functionality used to conduct data science projects on data stored in Vertica, taking advantage Vertica’s speed and built-in analytics and machine learning features. It supports the entire data science life cycle, uses a ‘pipeline’ mechanism to sequentialize data transformation operations, and offers beautiful graphical options. Nowadays, 'Big Data' is one of the main topics in the data science world, and data scientists are often at the center of any organization. The benefits of becoming more data-driven are undeniable and are often needed to survive in the industry. Vertica was the first real analytic columnar database and is still the fastest in the market. However, SQL alone isn't flexible enough to meet the needs of data scientists. Python has quickly become the most popular tool in this domain, owing much of its flexibility to its high-level of abstraction and impressively large and ever-growing set of libraries. Its accessibility has led to the development of popular and perfomant APIs, like pandas and scikit-learn, and a dedicated community of data scientists. Unfortunately, Python only works in-memory as a single-node process. This problem has led to the rise of distributed programming languages, but they too, are limited as in-memory processes and, as such, will never be able to process all of your data in this era, and moving data for processing is prohobitively expensive. On top of all of this, data scientists must also find convenient ways to deploy their data and models. The whole process is time consuming. VerticaPy aims to solve all of these problems. The idea is simple: instead of moving data around for processing, VerticaPy brings the logic to the data. 3 years in the making, we're proud to bring you VerticaPy. Main Advantages:.

Support

Quality

Security

License

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Support

VerticaPy has a low active ecosystem.

It has 130 star(s) with 41 fork(s). There are 16 watchers for this library.

There were 1 major release(s) in the last 6 months.

There are 23 open issues and 283 have been closed. On average issues are closed in 113 days. There are 3 open pull requests and 0 closed requests.

It has a neutral sentiment in the developer community.

The latest version of VerticaPy is 1.0.4

Quality

VerticaPy has 31 bugs (8 blocker, 0 critical, 22 major, 1 minor) and 1630 code smells.

Security

VerticaPy has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

VerticaPy code analysis shows 0 unresolved vulnerabilities.

There are 17 security hotspots that need review.

License

VerticaPy is licensed under the Apache-2.0 License. This license is Permissive.

Permissive licenses have the least restrictions, and you can use them in most projects.

Reuse

VerticaPy releases are available to install and integrate.

Deployable package is available in PyPI.

Build file is available. You can build the component from source.

Installation instructions, examples and code snippets are available.

It has 44186 lines of code, 1795 functions and 107 files.

It has high code complexity. Code complexity directly impacts maintainability of the code.

Top functions reviewed by kandi - BETA

kandi has reviewed VerticaPy and discovered the below as its top functions. This is intended to give you an instant insight into VerticaPy implemented functionality, and help decide if they suit your requirements.

Normalize the object
Return the category of the expression
Returns the expression where the expression is not None
Format a magic value
Plot the plot
Return the sqrt expression
Return a dictionary with the values of d1
Generate colors
Fill missing values
Perform seasonal decomposition
Fit the model
Calculate the mean value of a given column
Set an option
Calculate Cochru orcutt
Predict probabilities for a given dataset
Compute the het - Friedman statistic
Make a bubble plot
Saves the VDataFrame to a JSON file
Applies a function to a function
Get dummy values from the table
Generate a regression report
Plot a density plot
Plot a scatter plot
Creates a horizontal horizontal plot
Compute the adfuller function for a given statistic
Plot the model

Get all kandi verified functions for this library.

VerticaPy Key Features

No Key Features are available at this moment for VerticaPy.

VerticaPy Examples and Code Snippets

VerticaPy,Quick Start

Python

Lines of Code : 85

License : Permissive (Apache-2.0)

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root@ubuntu:~$ pip3 install verticapy

from verticapy import vertica_conn
cur = vertica_conn("VerticaDSN").cursor()

from verticapy import vDataFrame
vdf = vDataFrame("my_relation", cursor = cur)

from verticapy.learn.datasets import load_titanic
vdf

VerticaPy,Connecting to the Database,JDBC

Python

Lines of Code : 20

License : Permissive (Apache-2.0)

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import jaydebeapi

# Vertica Server Details
database = "testdb"
hostname = "10.211.55.14"
port = "5433"
uid = "dbadmin"
pwd = "XxX"

# Vertica JDBC class name
jdbc_driver_name = "com.vertica.jdbc.Driver"

# Vertica JDBC driver path
jdbc_driver_loc =

VerticaPy,Connecting to the Database,ODBC

Python

Lines of Code : 15

License : Permissive (Apache-2.0)

Copy

import pyodbc

# Connection using all the DSN information
driver = "/Library/Vertica/ODBC/lib/libverticaodbc.dylib"
server = "10.211.55.14"
database = "testdb"
port = "5433"
uid = "dbadmin"
pwd = "XxX"
dsn = ("DRIVER={}; SERVER={}; DATABASE={}; PORT=

Community Discussions

Trending Discussions on VerticaPy

Not seeing all values of list when I create a dataframe from list

Why do I see a table and not only avg value when I call vDataFrame.count

Panda get all data from a column A where they have the same value in the column B

QUESTION

Not seeing all values of list when I create a dataframe from list

Asked 2022-Apr-10 at 13:20

I am using VerticaPy - https://www.vertica.com/python/

I have created two vDataFrame using train.csv and test.csv of kaggle's Titanic problem. the vDataFrames are created correctly

...

ANSWER

Answered 2022-Apr-10 at 13:03

Change to concat

Source https://stackoverflow.com/questions/71816781

QUESTION

Why do I see a table and not only avg value when I call vDataFrame.count

Asked 2022-Apr-08 at 08:29

This is my Jupyter code for a code written for VerticaPy - https://www.vertica.com/python/documentation_last/vdataframe/statistics.php

I have created a vDataFrame for a table and want to find avg of a column

...

ANSWER

Answered 2022-Apr-08 at 08:29

DataFrame.mean is a function, unlike properties like DataFrame.shape. You need to call functions using parentheses, e.g. df.mean()

Source https://stackoverflow.com/questions/71793158

QUESTION

Panda get all data from a column A where they have the same value in the column B

Asked 2022-Feb-16 at 17:30

I have a dataset (df) like that :

...

ANSWER

Answered 2022-Feb-16 at 17:30

First, you need to calculate the mean value per card number. Let's calculate that by grouping same card numbers, getting the average amount, and call that 'card_mean':

Source https://stackoverflow.com/questions/71145811

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install VerticaPy

To install VerticaPy with pip:.
Install the library using the pip command. Create a vertica cursor. Create the Virtual DataFrame of your relation. If you don't have data on hand, you can easily import well-known datasets.