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sleepydatapeek

A quick way to peek at local datafiles.


Welcome to sleepydatapeek!

One often needs to spit out a configurable preview of a data file. It would also be nice if said tool could detect and read several formats automatically.
sleepydatapeek has entered the chat!

Quickly summarize data files of type:

  • csv
  • parquet
  • json
  • pkl
  • xlsx

ℹ️ Note that this tool presumes format by file extension. If you leave out extensions, or give csv data a .json extension for funsies, then you're being silly.


Get Started 🚀


pip install sleepydatapeek
pip install --upgrade sleepydatapeek

python -m sleepydatapeek --help
python -m sleepydatapeek my_data.csv

Usage ⚙


Set a function in your shell environment to run a script like:

alias datapeek='python -m sleepydatapeek'

Presuming you've named said function datapeek, print the help message:

$ datapeek test.xlsx

════════════════════ test.xlsx ════════════════════
      Unnamed: 0    CustomerID  ProductName      Quantity  OrderDate      Price
--  ------------  ------------  -------------  ----------  -----------  -------
 0             0           101  Laptop                  2  2023-10-26      1200
 1             1           102  Mouse                   1  2023-10-26        25
 2             2           103  Keyboard                1  2023-10-27        50
 3             3           104  Monitor                 1  2023-10-27       300
 4             4           105  Headphones              3  2023-10-28        80

═══Summary Stats
╭──────────────┬─────────────────╮
│ Index Column  (no_name):int64 │
├──────────────┼─────────────────┤
│ Row Count     30              │
├──────────────┼─────────────────┤
│ Column Count  6               │
├──────────────┼─────────────────┤
│ Memory Usage  < 0.00 bytes    │
╰──────────────┴─────────────────╯

═══Schema
╭─────────────┬────────╮
│ Unnamed: 0   int64  │
├─────────────┼────────┤
│ CustomerID   int64  │
├─────────────┼────────┤
│ ProductName  object │
├─────────────┼────────┤
│ Quantity     int64  │
├─────────────┼────────┤
│ OrderDate    object │
├─────────────┼────────┤
│ Price        int64  │
╰─────────────┴────────╯
═══════════════════════════════════════════════════

Optionally, you can also get group-by counts for distinct values of a given column:

datapeek test.xlsx --groupby-count-column=ProductName

# typical output (elided)

═══Groupby Counts
  (row counts for distinct values of ProductName)
╭──────────────┬───╮
│ Laptop        3 │
├──────────────┼───┤
│ Mouse         3 │
├──────────────┼───┤
│ Keyboard      3 │
├──────────────┼───┤
│ Monitor       3 │
├──────────────┼───┤
│ Headphones    3 │
├──────────────┼───┤
│ USB Drive     3 │
├──────────────┼───┤
│ Printer       3 │
├──────────────┼───┤
│ Webcam        3 │
├──────────────┼───┤
│ Speakers      3 │
├──────────────┼───┤
│ External HDD  3 │
╰──────────────┴───╯
═══════════════════════════════════════════════════

Technologies 🧰



Contribute 🤝


If you have thoughts on how to make the tool more pragmatic, submit a PR 😊.

To add support for more data/file types:

  1. append extension name to supported_formats in sleepydatapeek_toolchain.params.py
  2. add detection logic branch to the main function in sleepydatapeek_toolchain/command_logic.py
  3. update this readme

License, Stats, Author 📜


example image tag

PyPI - License PyPI - Version GitHub repo size

See License for the full license text.

This package was authored by Isaac Yep.

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