Flexible and powerful data analysis / manipulation library for Python, providing labeled data structures similar to R data.frame objects, statistical functions, and much more

pandas is a Python package that provides fast, flexible, and expressive data structures designed to make working with "relational" or "labeled" data both easy and intuitive. It aims to be the fundamental high-level building block for doing practical, real world data analysis in Python. Additionally, it has the broader goal of becoming the most powerful and flexible open source data analysis / manipulation tool available in any language. It is already well on its way towards this goal. Easy handling of missing data (represented as NaN, NA, or NaT) in floating point as well as non-floating point data Size mutability: columns can be inserted and deleted from DataFrame and higher dimensional objects Automatic and explicit data alignment: objects can be explicitly aligned to a set of labels, or the user can simply ignore the labels and let Series, DataFrame, etc. automatically align the data for you in computations Powerful, flexible group by functionality to perform split-apply-combine operations on data sets, for both aggregating and transforming data Make it easy to convert ragged, differently-indexed data in other Python and NumPy data structures into DataFrame objects Intelligent label-based slicing, fancy indexing, and subsetting of large data sets Intuitive merging and joining data sets Flexible reshaping and pivoting of data sets Hierarchical labeling of axes (possible to have multiple labels per tick) Robust IO tools for loading data from flat files (CSV and delimited), Excel files, databases, and saving/loading data from the ultrafast HDF5 format Time series-specific functionality: date range generation and frequency conversion, moving window statistics, date shifting and lagging 

The fundamental package for scientific computing with Python.

Seaborn is a Python visualization library based on matplotlib. It provides a high-level interface for drawing attractive statistical graphics. 

The open and composable observability and data visualization platform. Visualize metrics, logs, and traces from multiple sources like Prometheus, Loki, Elasticsearch, InfluxDB, Postgres and many more. 

The open-source platform for monitoring and observability. Visualizations: Fast and flexible client side graphs with a multitude of options. Panel plugins offer many different ways to visualize metrics and logs. Dynamic Dashboards: Create dynamic &amp; reusable dashboards with template variables that appear as dropdowns at the top of the dashboard. Explore Metrics: Explore your data through ad-hoc queries and dynamic drilldown. Split view and compare different time ranges, queries and data sources side by side. Explore Logs: Experience the magic of switching from metrics to logs with preserved label filters. Quickly search through all your logs or streaming them live. Alerting: Visually define alert rules for your most important metrics. Grafana will continuously evaluate and send notifications to systems like Slack, PagerDuty, VictorOps, OpsGenie. Mixed Data Sources: Mix different data sources in the same graph! You can specify a data source on a per-query basis. This works for even custom datasources. 

An Open Source Machine Learning Framework for Everyone

TensorFlow is an end-to-end open source platform for machine learning. It has a comprehensive, flexible ecosystem of tools, libraries, and community resources that lets researchers push the state-of-the-art in ML and developers easily build and deploy ML-powered applications. TensorFlow was originally developed by researchers and engineers working on the Google Brain team within Google's Machine Intelligence Research organization to conduct machine learning and deep neural networks research. The system is general enough to be applicable in a wide variety of other domains, as well. TensorFlow provides stable Python and C++ APIs, as well as non-guaranteed backward compatible API for other languages. Keep up-to-date with release announcements and security updates by subscribing to announce@tensorflow.org. See all the mailing lists. 

Cold Storage Prediction

DATA

pandasby pandas-dev

pandasby pandas-dev

numpyby numpy

numpyby numpy

VISUAL ANALYTICS

seabornby mwaskom

seabornby mwaskom

grafanaby grafana

grafanaby grafana

ML

tensorflowby tensorflow

tensorflowby tensorflow

scikit-learnby scikit-learn

scikit-learnby scikit-learn