gooddata-python-sdk
Pandas
gooddata-python-sdk | Pandas | |
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2 | 399 | |
25 | 42,104 | |
- | 0.9% | |
9.6 | 10.0 | |
4 days ago | 5 days ago | |
Python | Python | |
GNU General Public License v3.0 or later | BSD 3-clause "New" or "Revised" License |
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Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
gooddata-python-sdk
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Why You Should Use Python For Your Next Project
Our product contains a Headless BI engine where you can connect any application, data platform, or visualization tool to the engine’s semantic layer and consume the same consistent analytics anywhere. Connecting to a semantic layer with the help of GoodData Python libraries is very straightforward! GoodData Pandas allows creating pandas series and data frames from the computations done against a semantic model in GoodData.CN. As mentioned above, imagine you have a database with many tables, and you want to get a data frame consisting of columns from various joined tables. Usually, you have to do many joins manually in SQL before getting the desired data frame in Pandas. But if you connect the database to GoodData.CN, you can forget joins — with the help of a semantic model and GoodData Pandas, you will get your desired data frame with much less hassle. Just for demonstration, compare the two following code snippets. The first one is just pure pandas:
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Headless BI: Metric Standardization in Action
To follow this article, you can download GoodData Python SDK, which contains a docker-compose file, and run the following command in the root folder:
Pandas
- The Birth of Parquet
- PDEP-13: The Pandas Logical Type System
- PHP Doesn't Suck Anymore
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AWS Serverless Diversity: Multi-Language Strategies for Optimal Solutions
Python is a natural fit for serverless development. It boasts a vast array of libraries, including Powertools for AWS and robust libraries for data engineers. Its versatility and excellent developer experience make it a top choice for serverless projects, offering a seamless and enjoyable development experience.
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Pandas reset_index(): How To Reset Indexes in Pandas
In data analysis, managing the structure and layout of data before analyzing them is crucial. Python offers versatile tools to manipulate data, including the often-used Pandas reset_index() method.
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Deploying a Serverless Dash App with AWS SAM and Lambda
Dash is a Python framework that enables you to build interactive frontend applications without writing a single line of Javascript. Internally and in projects we like to use it in order to build a quick proof of concept for data driven applications because of the nice integration with Plotly and pandas. For this post, I'm going to assume that you're already familiar with Dash and won't explain that part in detail. Instead, we'll focus on what's necessary to make it run serverless.
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Help Us Build Our Roadmap – Pydantic
there is pull request to integrate in both pydantic extra types and into pandas cose [1]
[1]: https://github.com/pandas-dev/pandas/issues/53999
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Stuff I Learned during Hanukkah of Data 2023
Last year I worked through the challenges using VisiData, Datasette, and Pandas. I walked through my thought process and solutions in a series of posts.
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Introducing Flama for Robust Machine Learning APIs
pandas: A library for data analysis in Python
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Exploring Open-Source Alternatives to Landing AI for Robust MLOps
Data analysis involves scrutinizing datasets for class imbalances or protected features and understanding their correlations and representations. A classical tool like pandas would be my obvious choice for most of the analysis, and I would use OpenCV or Scikit-Image for image-related tasks.
What are some alternatives?
Multicorn - Data Access Library
Cubes - [NOT MAINTAINED] Light-weight Python OLAP framework for multi-dimensional data analysis
dbeaver - Free universal database tool and SQL client
tensorflow - An Open Source Machine Learning Framework for Everyone
gooddata-ui-sdk - GoodData.UI SDK
orange - 🍊 :bar_chart: :bulb: Orange: Interactive data analysis
NumPy - The fundamental package for scientific computing with Python.
Airflow - Apache Airflow - A platform to programmatically author, schedule, and monitor workflows
examples - TensorFlow examples
Keras - Deep Learning for humans
fastapi - FastAPI framework, high performance, easy to learn, fast to code, ready for production
Pytorch - Tensors and Dynamic neural networks in Python with strong GPU acceleration