datapad | Fluent API for Exploratory Data Analysis

by huyng Python Version: 0.7.6 License: Apache-2.0

X-Ray Key Features Code Snippets(2)Community Discussions(1)Vulnerabilities Install Support

kandi X-RAY | datapad Summary

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

Datapad is a Python library for processing sequence and stream data using a Fluent style API. Data scientists and researchers use it as a lightweight toolset to efficiently explore datasets and to massage data for modeling tasks. It can be viewed as a combination of syntatic sugar for the Python itertools module and supercharged tooling for working with Structured Sequence data.

Support

Quality

Security

License

Reuse

Support

datapad has a low active ecosystem.

It has 8 star(s) with 0 fork(s). There are 2 watchers for this library.

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

datapad has no issues reported. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of datapad is 0.7.6

Quality

datapad has no bugs reported.

Security

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

License

datapad 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

datapad releases are not available. You will need to build from source code and install.

Deployable package is available in PyPI.

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

Installation instructions are not available. Examples and code snippets are available.

Top functions reviewed by kandi - BETA

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

Groups the elements of the elements in the sequence
Returns an iterator over all records
Collect all entities
Join two sequences
Apply a function to each element of the sequence
Map a function over each element in the sequence
Apply a function to data
Returns the next count elements from the stream
Get the first item from the query
Returns a copy of the sequence
Read JSON data from file
Read files
Generate a sequence of paths from a glob
Return a new Query with drop elements removed
Return a sequence of rows from a csv file
Apply a function to each element in the sequence
Returns the next document
Create a batch of a sliding window
Create a sliding window of the given sequence

Get all kandi verified functions for this library.

datapad Key Features

No Key Features are available at this moment for datapad.

datapad Examples and Code Snippets

Exploratory data analysis with Datapad

Python

Lines of Code : 32

License : Permissive (Apache-2.0)

Copy

>>> import datapad as dp
>>> data = ['a', 'b', 'b', 'c', 'c', 'c']
>>> seq = dp.Sequence(data)
>>> seq.count(distinct=True) \
...    .collect()
[('a', 1),
 ('b', 2),
 ('c', 3)]

>>> import datapad as dp
&g

Install

Python

Lines of Code : 1

License : Permissive (Apache-2.0)

Copy

pip install datapad

Community Discussions

Trending Discussions on datapad

Trouble with scanf command in c ( cant find anywhere else in forums)

QUESTION

Trouble with scanf command in c ( cant find anywhere else in forums)

Asked 2018-Feb-13 at 09:35

FILE *datapad;
char filename[20];
printf("please enter file \n");
scanf(" %s", &filename);
fflush(stdin);
printf("processing");
datapad = fopen(filename,"r");

...

ANSWER

Answered 2018-Feb-13 at 01:04

The format for your scanf() is incorrect

Source https://stackoverflow.com/questions/48757808

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

Vulnerabilities

No vulnerabilities reported

Install datapad

You can install using 'pip install datapad' or download it from GitHub, PyPI.
You can use datapad like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.

Support

For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .

Find more information at: