datatable
pandas_exercises
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datatable | pandas_exercises | |
---|---|---|
9 | 10 | |
1,790 | 10,188 | |
0.8% | - | |
6.1 | 0.0 | |
5 months ago | 30 days ago | |
C++ | Jupyter Notebook | |
Mozilla Public License 2.0 | BSD 3-clause "New" or "Revised" License |
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
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.
datatable
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Cheat Sheets for data.table to Python's pandas syntax?
Aside from that, there is a Python translation of data.table (see documentation here), which might be worth looking into. However, it hasn't had any major updates in a while: the last release 2 years ago ...
- Any advice on using Pandas as a data analyst?
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Alternative to Pandas
There's datatable. I haven't used it much, but the R version (data.table) is phenomenal.
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Need advice on whether to store data set for regression model in SQL database or by using Python modules like Pickle or Parquet
just use HDF5 or Parquet, or CSV + https://github.com/h2oai/datatable to speed up the file reading.
- Massive R analysis of Data Science Language and Job Trends 2022
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Scikit-Learn Version 1.0
> For me I had with pandas the most issues using it's multiindex.
Yessss. I loathe indices, and have never been in a situation where I was better off with them than without them.
> Regarding fast you have something like Vaex on python sid
I've never used Vaex, but I've used datatable (https://github.com/h2oai/datatable) and polars (https://github.com/pola-rs/polars). Polars is my favorite API, but datatable was faster at reading data (Polars was faster in execution). I'll have to give Vaex a try at some point.
- Show HN: Sheet2dict – simple Python XLSX/CSV reader/to dictionary converter
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Hey Reddit, here's my comprehensive course on Python Pandas, for free.
Yep. I think this is the downside to a package being entirely maintained by volunteers. In any case, Pandas is still the leading data wrangling package for Python. (I'm excited to see how datatable evolves.)
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Ditching Excel for Python in a Legacy Industry (Reinsurance)
h2o's data.table clone is fine
https://github.com/h2oai/datatable
pandas_exercises
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Does CS 1301 cover topics like NumPy and pandas?
pandas notebook
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Any advice on using Pandas as a data analyst?
Personally, practiced the exercises present in this github repo, it was very helpful. https://github.com/guipsamora/pandas_exercises
- Pandas Exercises to Learn by Doing
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How to improve machine learning programming skills?
Check this out for practicing Pandas using specific exercises: https://github.com/guipsamora/pandas_exercises
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[NBS Accountancy] Ranking and Tiering every core modules with description)! Hope this will be fun read for the current/past Accountancy students, and helpful for incoming batch of Accountancy students :))
Tips: For quiz 1, I used this whereas for quiz 2, I used this to revise. I cannot conclude whether they really helped in the end since the quiz results aren't released, but managed to nab an A for this mod so there's that.
- Looking for Pandas course in Jupyter Notebook so I can learn both at the same time
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Using mean on numeric columns of a GroupedDataFrame
I am trying to solve the exercises in the excellent guipsamora/pandas_exercises repo using DataFrames.jl and other Julia tools. A question in the repo is something like this
- Associate Data Scientist @ IBM?
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PySpark exercises for practice?
Are there some PySpark exercises available on GitHub for practice? I am looking for something like this pandas exercises collection - https://github.com/guipsamora/pandas_exercises
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Python Intermediate-advanced tests
Pandas Exercises Github
What are some alternatives?
polars - Dataframes powered by a multithreaded, vectorized query engine, written in Rust
100-plus-Python-programming-exercises-extended - The repository is about 100+ python programming exercise problem discussed, explained, and solved in different ways
DataFrame - C++ DataFrame for statistical, Financial, and ML analysis -- in modern C++ using native types and contiguous memory storage
qs_ledger - Quantified Self Personal Data Aggregator and Data Analysis
db-benchmark - reproducible benchmark of database-like ops
pandas-cookbook - Recipes for using Python's pandas library
scientific-visualization-book - An open access book on scientific visualization using python and matplotlib
100-pandas-puzzles - 100 data puzzles for pandas, ranging from short and simple to super tricky (60% complete)
sktime - A unified framework for machine learning with time series
PANDAS-TUTORIAL - Jupyter Notebooks and Data Sets for Pandas Library
vinum - Vinum is a SQL processor for Python, designed for data analysis workflows and in-memory analytics.
github_innovation_graph_analysis