JetBrains and the Python Software Foundation's latest Python Developer Survey highlights key trends in data science for 2024. pandas remains the top choice for data processing, while Polars is gaining popularity. Popular data visualization tools include Plotly Dash, Streamlit, and the emerging HoloViz Panel. In the realm of machine learning, scikit-learn and PyTorch are prominent players. For MLOps, tools like Docker and TensorBoard are essential, though newer tools like MLflow are on the rise. The article also covers the importance of managing big data using tools like Spark and Databricks. PyCharm offers a range of features to support data science projects, from data processing and visualization to model deployment and integration with Hugging Face models.
Table of contents
Data processing: pandas remains the top choice, but Polars is gaining groundData visualization: Will HoloViz Panel surpass Plotly Dash and Streamlit within the next year?ML models: scikit-learn is still prominent, while PyTorch is the most popular for deep learningMLOps: The future of data science projectsBig data: How much is enough?Communities: Events shifting focus toward data scienceFinal thoughtsEnhance your data science experience with PyCharmSort: