DSQ Reviews

Plotly Reviews

DSQ mentions (11)

• Tracking SQLite Database Changes in Git

  You might want to look at tsv-utils, or a similar project: https://github.com/eBay/tsv-utils (No longer maintained, but has links to lots of other projects). - Source: Hacker News / 8 months ago

• Command-line data analytics made easy

  SPyQL is really cool and its design is very smart, with it being able to leverage normal Python functions! As far as similar tools go, I recommend taking a look at DataFusion[0], dsq[1], and OctoSQL[2]. DataFusion is a very (very very) fast command-line SQL engine but with limited support for data formats. Dsq is based on SQLite which means it has to load data into SQLite first, but then gives you the whole breath... - Source: Hacker News / over 1 year ago

• Jq Internals: Backtracking

  > dsq registers go-sqlite3-stdlib so you get access to numerous statistics, url, math, string, and regexp functions that aren't part of the SQLite base. (https://github.com/multiprocessio/dsq#standard-library) Ah, I wondered if they rolled their own SQL parser, but no, I now see the sqlite.go in the repo and all is made clear. - Source: Hacker News / over 1 year ago

• Run SQL on CSV, Parquet, JSON, Arrow, Unix Pipes and Google Sheet

  I am currently evaluating dsq and its partner desktop app DataStation. AIUI, the developer of DataStation realised that it would be useful to extract the underlying pieces into a standalone CLI, so they both support the same range of sources. Dsq CLI - https://github.com/multiprocessio/dsq. - Source: Hacker News / almost 2 years ago

• Xlite: Query Excel, Open Document spreadsheets (.ods) as SQLite virtual tables

  This is a cool project! But if you query Excel and ODS files with dsq you get the same thing plus a growing standard library of functions that don't come built into SQLite such as best-effort date parsing, URL parsing/extraction, statistical aggregation functions, math functions, string and regex helpers, hashing functions and so on [1]. [0] https://github.com/multiprocessio/dsq [1]... - Source: Hacker News / about 2 years ago

Plotly mentions (30)

• Essential Deep Learning Checklist: Best Practices Unveiled

  How to Accomplish: Utilize visualization libraries like Matplotlib, Seaborn, or Plotly in Python to create histograms, scatter plots, and bar charts. For image data, use tools that visualize images alongside their labels to check for labeling accuracy. For structured data, correlation matrices and pair plots can be highly informative. - Source: dev.to / 11 days ago

• Python equivalent to power bi/power query?

  For dashboards: - https://plotly.com/ is probably my favourite, but there are others like streamlit, voila and others... Source: 7 months ago

• Junior Developer asked to make Saaas in first month.

  If your CEO wants you to solo build an alternative to Tableau, PowerBi, or even Plotly then consider him/her delusional. Source: about 1 year ago

• PSA: You don't need fancy stuff to do good work.

  Python's pandas, NumPy, and SciPy libraries offer powerful functionality for data manipulation, while matplotlib, seaborn, and plotly provide versatile tools for creating visualizations. Similarly, in R, you can use dplyr, tidyverse, and data.table for data manipulation, and ggplot2, lattice, and shiny for visualization. These packages enable you to create insightful visualizations and perform statistical analyses... Source: about 1 year ago

• Wait, but I thought they were the same thing?

  I use plotly and like it a lot. It is slower though. Noticeable if you want to batch-generate a bunch of images and dump them into a folder. But that probably isn't the case most times. Source: over 1 year ago